►
Description
2020 CESM Workshop Day 3 - Wednesday, 17 June 2020 - 13:00-16:30 - Climate Variability and Change
The 25th Annual CESM Workshop will be a virtual workshop with a modified schedule on its already scheduled date. Specifically, the virtual Workshop will begin with a full-day schedule on 15 June 2020 with presentations on the state of the CESM. On 16-17 June 2020, working groups and cross working groups have half-day sessions, some with presentations and some that are discussion only.
More information about the CESM Climate Variability and Change Working Group:
http://www.cesm.ucar.edu/working_groups/CVC/
More information about the workshop:
http://www.cesm.ucar.edu/events/workshops/2020/
Talks included:
EL Nino Southern Oscillation (ENSO) in the NCAR Community Earth System Model version 2
Evaluation of Leading Modes of Climate Variability in the CMIP Archives
The Impact of the Observed Arctic Sea-ice Variability on the Cold Season Atmospheric Circulation in Large-ensemble AGCM Experiments
Impacts of Arctic climate change on synoptic cyclones
Role of AMOC in transient climate response to greenhouse gas forcing in two coupled models
Indian Ocean warming as a driver of the North Atlantic warming hole: atmospheric versus oceanic mechanisms
Competing anthropogenic effects cause distinct regional impacts on extreme wildfire risk
Regional drivers of the response of Sahel precipitation to anthropogenic aerosols
The North Atlantic Climate Response to Stratospheric Sulfate Geoengineering
Pushing the Limits of Pattern Scaling to Separate Tropical and Polar Climate Change Signals
Was the Great Salinity Anomaly of the 1970s induced by an extreme Fram Strait Sea-Ice Export?
Amplified Madden-Julian oscillation impacts in California due to eastward-extended teleconnection pattern
Role of tropical variability in driving decadal shifts in the SH summertime eddy-driven jet
A
A
A
C
A
I
was
just
gonna
say
so
like
if
something
really
weird
happened,
like
one
of
our
computers
crashed,
our
Internet's
crashed
the
co-host
with,
because
there's
some
co-host,
it
would
still
stay
up,
live
right.
It
should
we
haven't
really
encountered
yesterday
afternoon
when
I
was
watching
a
mwg
or
whenever
that
was
my.
A
Just
stopped
doing
zoom,
it
all
went
away
and
then
a
few
seconds
later
it
came
back
on
they
said
it
was
reconnecting
and
Elizabeth
thought
that
was
just
some
kind
of
internet.
You
know
temporary
glitch
thing:
okay,
well,
yeah,
seeing
how
we
have
multiple
co-hosts
and
I'm
at
the
yeah
I'm
at
the
Mesa
with
the
good
internet.
We
should
be
good
to
go,
but
okay,
I'll
keep
an
eye
out
just
in
case.
Okay
and
I'll
start
the
record
at
right
at
when
they
start.
F
F
I
had
I
didn't
want
to
get
people
confused
with
Google
Docs,
so
I
just
had
the
one
about
the
CSL
and
I
had
pretty
here
that
people
could
voice
their
views.
Din.
The
chat
on
these
other
things,
but
I
was
in
two
minds
about
egg
I,
actually
did
prepare
a
Google,
Doc
and
then
I
thought.
Maybe
people
gonna
get
confused
by
which
Google
Docs,
to
put
there,
maybe
I
guess
I
could
put
sections
in
the
CSL.
Google
talked
about
yeah.
E
F
E
G
F
E
A
E
E
E
G
G
A
E
G
F
A
H
E
F
F
E
F
E
E
J
E
F
F
F
E
A
E
E
A
A
F
F
Yeah
everyone,
if
you
could
meet
mute
your
microphones
unless
you're
talking
good,
so
just
a
quick
couple
of
things
before
we
get
started
with
the
talks.
Just
to
remember
the
code
of
conduct
conduct,
constructive
and
considerate
of
everyone.
We
have
a
few
things
that
we'd,
like
your
input
on
and
since
we
don't
actually
have
a
time
for
discussion,
we're
gonna
try
and
do
this
to
a
Google
Doc.
So
the
link
is
here
and
I
also
shared
it
in
the
chat
so
yeah.
F
Let
me
know
if
you
have
any
troubles
getting
on
there,
and
so
one
of
the
things
is
we'd,
like
some
input
on
the
tutorials.
So
if
you
have
any
views
on
that,
please
I've
made
three
sections
in
the
Google
Doc,
so
try
and
put
them
in
the
right
section:
we'd,
also
like
you're
in
good
on
the
next
proposal
for
the
CSL
for
the
computing
time,
so
that
that
we
use
to
run
the
simulation.
F
So
if
you
have
any
suggestions
of
simulations
you
like
to
see
done,
please
either
add
them
in
the
Google
Doc
or
get
in
touch
with
me
or
one
of
the
other
co-chairs,
and
then
one
of
the
things
that
came
up
in
the
mwg
yesterday
they
like
to
also
hear
views
on
is
whether
there's
any
interest
in
a
high
resolution
version
of
CES
mt.
I
mean
the
question
here
is
really
do
we
do
we
put
the
effort
in
now
or
do
we
kind
of
wait
for
the
next
generation?
F
That
would
have
a
higher
vertical
resolution
and
put
the
effort
in
then
and
kind
of
continue
to
use
CSM
one
for
high
resolution
at
this
point.
So
if
you
have
any
views
on
any
of
these
things,
please
put
them
in
the
Google
Doc
and
then
we're
going
to
start
with
the
questions
again.
So
we
have
a
10-minute
warning
when
you're
at
ten
minutes
and
then
we'll
try
to
take
finish
by
12
minutes
and
have
a
couple
of
minutes
for
questions.
F
G
A
A
F
F
A
G
And
it's
part
of
the
special
issue
on
CSM,
so
this
that
paper
was
really
meant
to
assess
the
model
fidelity
in
reproducing
this
mode,
so
variability
in
in
CSM
to
weather
models,
especially
this
long
control
simulation
like
the
one.
We
use
that
also
very
useful
for
trying
to
assess
the
robustness
of
aspect
of
n
so
that
we
may
determine
too
much
shorter
observational
record.
G
G
They
make
care
sometimes
seem
to
work
an
X,
okay,
yeah,
okay,
so
here
this
is
a
figure
from
the
paper.
The
special
issue
paper,
where
I'm
showing
on
the
left,
the
Manta
standard,
deviation
auto
correlations
in
the
central
column
and
the
power
spectra
for
both
CSM
two
windows.
So
we
compare
it
with
its
predecessors,
model,
CS,
m1
and
CSM
for
the
observations.
Our
estimates
are
shown
in
red
and
they
are
from.
G
And
they
are
from
the
ers
sis,
TV
5,
over
1900,
2000
and
I.
Think
I
cannot
see
actually
the
my
first
slider
you
have
them
so
and
in
order
to
account
for
the
four
possible
low
frequency
variation
in
n.
So
in
in
this
long
model
simulation,
we
actually
divide
the
1000
year
model
run
in
eighteen,
119
segments.
G
So
that's
the
same
duration
as
the
observations
and
so
the
shading,
the
blue
light
blue
shading
shows
the
spread
of
this
spectral
estimate
and
while
the
black
lines
represent
the
mean
values,
so
we
can
see
that
the
Manta
standard
deviation.
It
shows
a
reasonable
variation
with
the
seasonal
cycle.
Although
we
can
see
already
that
this
Manta
standard
deviation
are
larger,
then
the
observations
and
also
both
autocorrelation
function
and
power
spectra
show
that
the
dominant
timescale
of
answer
in
CSM
to
as
a
realistic,
compares
well
with
observation.
In
terms
of
time
scales.
G
G
So
what
about
spatial
patterns
I'm
going
to
examine
the
special
pattern?
In
the
context
of
n,
so
the
density
and
for
that
I'm
using
the
definition
of
Takashi
a
tile
which
is
based
on
the
two
leading
OFS
of
sea
surface
temperature
in
the
equatorial
Pacific
than
South
10
north.
This
is
a
domain
where
the
two
leading
UF
explained
a
large
fraction
of
the
variance
the
pattern
of
the
these
two
EDF
s
is
obtained
by
the
grass
seeing
the
corresponding
by
regressing.
The
sea.
G
G
So
the
e
mode
shows
like
largest
anomaly
in
the
far
western
Pacific
against
the
South
American
coast,
while
the
sea
mode,
as
this
is
this
largest
anomaly,
and
also
the
largest
thermocline
depth
anomaly
at
also
displaced
from
the
West.
So
this
is
based
on
the
ECMWF
aura
s4
the
analysis
from
1958
to
2015
and
will
offer
confirm,
refer
to
it
as
observation
and,
of
course,
is
just
an
ocean
of
analysis,
and
so
how
does
CSM
to
compare
with
the
reanalysis?
G
So
the
e
and
c
mode
for
CSM
two
are
shown
in
the
right
column
here,
and
so
we
can
see
that
qualitatively.
The
comparison
is
reasonable.
Reasonably
good,
although
it's
obvious,
is
evident
that
the
anomalies
in
the
model
are
displaced
further
west,
the
e
modes
as
the
largest
anomaly,
that
don't
touch
the
South
American
coast
and
even
in
the
case
of
the
seam
of
the
largest
anomaly,
really
extending
to
the
Dateline
and
much
beyond
it.
G
So
to
determine
the
answer,
precursors,
I'm,
going
to
use
a
methodology
known
as
linear,
inverse
modeling,
and
just
very
briefly,
this.
The
in
within
this
methodology,
the
tropical
Pacific
system
is
described
by
a
state
vector
s
which
includes
information
of
sea,
surface
temperature
and
sea
surface
height.
The
evolution
of
this
state,
vector
as
shown
in
this
equation,
is
due
to
two
terms.
The
first
term
is
the
deterministic
part
of
the
evolution
which
is
encapsulated
by
in
this
dynamical
operator.
G
L,
and
the
second
term
is
a
stochastic
term,
which
we
assumed
to
be
white
in
time
with
the
spatial
pattern
kind
of
described
by
s
and
the
in
this
methodology.
The
state
vector
time,
T
plus
tau,
can
be
related
to
the
state
vector
a
time
at
time.
T
through
this
operator
and
this
approaches
allow
us
to
determine
the
initial
condition
that
produce
the
largest
growth
given
final
state.
G
So
the
initial
and
final
condition
that
are
are
called
the
optimal
initial
and
final
structures,
and
this
is
what
they
look
like
for
order
as
force
on
the
left.
We
see
the
initial
condition
at
time.
T
equals
zero,
which
so
the
shading
is
for
sea.
Surface
temperature
contours
are
for
sea
surface
height,
so
we
see
here
this
positive
anomaly
in
the
subtropics
extending
from
the
northeast
toward
the
equator,
with
some
anomaly
also
at
the
equator,
which
are
typical
of
the
North
Pacific
Mariana
mode.
G
There
are
also
anomaly
in
the
southeastern
Pacific,
which
also
extend
all
the
way
to
the
equator.
This
again
is
a
similar
to
what
is
described
in
the
literature
at
the
South
Pacific
Meridian
and
modes
thermocline
that
jog
deeper
in
the
central
equatorial
Pacific,
indicating
a
recharge
higher
heat
content
there
and
eight
month
later.
So
that
was
the
leg
chosen.
We
find
a
full
answer
event
a
canonical
incident
with
dislodges
anomaly
in
around
Nino
3
region.
G
G
So
what
about
tensile
diversity
also-
and
we
can
also
use
the
same
time
series
then
also
to
find
the
larger
scale
patterns
of
sea,
surface
temperature,
LCC
level
pressure
and
winds
associated
to
these
initial
conditions
and,
in
both
cases,
both
models
and
the
analysis.
We
have
meridional
dipole
patterns
which
are
well
known
in
the
literature,
is
the
North
Pacific
oscillation
and
in
the
South
in
the
South
Pacific.
G
This
has
been
recently
defined
and
this
is
the
South
Pacific
oscillation
and
they
are
kind
of
well
known
and
so
precursors,
so
let's
terminan
Hey,
oops,
okay,
so
the
the
classical
the
standard
leme
approach
on
the
device,
those
optimal
routes
toward
the
canonical
mode.
So
here
we
are
using
multiple
linear
regression
to
find
the
initial
condition
that
actually
would
maximize
the
growth
toward
the
index
and
the
C
index.
And
how
do
they
look
like
so
here
you
have
orders
for
in
CSM
side
by
side,
so
in
the
initial
state,
this
is
for
the
emotes.
G
We
find
this
again,
not
Pacific
and
South
Pacific
Mariana
mode.
In
this
case
the
thermocline
is
deeper
more
in
the
eastern
Pacific.
We
can
actually
use
our
lim
that
lim
model
to
evolve
this
condition.
So
as
we
progress
in
time,
we
see
this
anomaly
in
the
eastern
pacific
extend
westward
as
well
as
the
deepening
of
the
thermocline.
We
also
see
that
the
negative
anomaly
is
the
surface.
I
tendon
organs
of
thought,
which
is
also
propagate
westward.
Those
are
the
upwelling
Rossby
waves
and
again
this
evolution
leads
to
this.
G
G
The
correlation
are
larger,
but
significantly
larger
for
the
SI
indices
and
and
so
and
again-
and
this
is
if
we
then
look
at
the
sea
level
pressure
and
winds
structures
associated
with
this
initial
conditions.
They
look
similar,
but
they
are
much
much
more
pronounced
in
the
case
of
the
sea
mode,
so
in
conclusions,
I
think
I
only
have
shown
the
temporal
and
spectral
characteristics
of
answers
we
have
described
in
the
special
issue
paper,
but
there
are
several
aspects
of
answer
in
CSM
to
that.
G
Compare
well
with
observation
and
whether
the
anomalies
are
too
large
and
they
tend
to
be
displaced
too
far
west,
which
is
a
limitation
of
the
model
that
seemed
to
hinder
the
ability
to
represent
the
food
range
of
ENSO
diversity.
Nevertheless,
the
precursor
events
of
the
density
changes
at
very
similar
in
this
very
long
one
tower
thousand
year
simulation
in
relative
to
only
558
years
or
longer,
reanalysis,
and
they
have
the
evolution
of
this
event
is
also
very
similar.
G
But
there
are
difference
in
the
sea
surface
height
in
with
possible
implication
for
the
role
of
the
subsurface
in
determining
which
event
will
evolve,
and
also
the
indication
from
what
CSM
to
analysis
is
that
Central,
Pacific
and
lynnie
events
seem
to
be
more
predictable
than
eastern
Pacific
events,
and
this
seem
to
be
actually
in
disagreement
with
what
operational
forecasting
system
are
finding
that
they
don't
seem
to
have
good
prediction
for
Central
Pacific
in
linear,
and
so
this
is
definitely
something
that
need
to
be
examined
further
in
the
future.
Thank
you.
Thank.
F
You
do
you
have
one
quick
question
for
Antonia:
please
raise
your
hand
or
put
it
in
the
chat,
if
not
well,
we're
already
a
little
behind.
So
if
you
have,
if
you
have
any
questions
you
can,
you
can
put
them
in
the
chat
and
Antonia
take
it
answer
them
in
the
chat
all
right.
Thank
you.
So
we'll
move
on
to
John,
pezzulo
and
I'm
who's.
Looking
at
evaluating
leading
modes
of
climate
variability
in
the
cement
archives.
H
All
right
so
that
talk
was
a
nice
actually
segue
into
what
I'm
looking
at,
which
is
more
of
an
effort
to
look
across
the
steam
of
archives
and
evaluate
many
modes
of
variability,
but
several
the
results
that
we
showed
are
actually
consistently
what
we
find
with
with
em.
So,
and
so
this
is
work
that
began
about
a
year
ago,
but
actually
extends
from
an
effort
about
six
years
ago
to
develop
the
climate,
variability
diagnostics
package,
and
so
with
the
release
of
seemeth
six.
H
We
now
have
three
generations
of
steam
of
archives
to
apply
this
package
across
and
address
some
very
basic
questions
about
how
the
fidelity
of
models
has
changed
over
time,
as
well
as
some
second-order
questions.
This
work
is
published.
It
came
out
in
journal
climate
last
month,
and
this
is
kind
of
a
summary
of
part
of
that
paper.
I
don't
have
time
to
go
through
all
the
modes
covered
in
that
paper,
but
I
will
touch
on
really
the
main
findings.
H
Okay,
so
the
question
we're
asking
this:
how
have
models
improved
over
time
and
if
they
have
improved
in
what
ways?
What
model
biases
persist
and
how
did
those
improvements
across
generations
actually
compare
to
differences
across
models
within
a
given
generation,
and
so
to
do
that,
we
need
to
really
develop
a
method
for
quantifying
the
temporal
and
spatial
characteristics
of
model
bias
and
summarize
it
in
a
in
a
digestible
fashion.
We
have
dozens
of
models
and
they
all
differ
from
each
other
in
some
ways.
H
So
how
can
we
kind
of
distill
that
into
a
simple
understanding
and
before
we
do
any
of
this,
we
actually
have
to
address
the
question
as
to
what
modes
are
well
constrained
by
the
observational
record
relative
to
the
magnitude
of
model
era
that
we're
looking
at
so
I
hope
to
address
all
three
of
these
during
the
course
of
presentation
just
quickly
for
people
who
aren't
familiar
with
it.
We
have
the
climate
variability
Diagnostics
package
tool
that
we're
using
in
this
work
and
we're
focusing
on
a
few
of
the
modes
in
that
package.
H
We're
not
going
to
focus
on
all
of
the
modes
today,
but
just
the
modes
I
show
you
here
and
so
we're
looking
at
metrics
of
ENSO
that
were
documented
and
deaths
at
all.
2012.
We're
looking
at
the
PDO
is
defined
if
I
meant,
with
all
97
kinds
of
Northern
Hemisphere
I
should
topical
modes
from
rel
and
dr.
2009
and
the
southern
angular
modes
from
Thompson
of
Wallace
in
2000,
and
so
we
have
kind
of
these
patterns
and
spatial
and
temporal
characteristics
of
these
modes
from
the
CV
BP.
H
We're
looking
at
a
period
of
1920
to
2018
as
it's
available.
Not
all
awesome
models
extend
that
far
more
than
the
observations
we
can
extend
that
far,
except
for
Sam,
so
Sam
because
of
poor
observational
sampling,
the
southern
hemisphere
before
1950,
it's
really
best
to
work
with
data
from
1950
to
the
present.
H
H
The
theme
of
simulations
were
looking
at
include
16cm
at
three
simulations.
There
16
models
rather
77
different
members
pursuing
a
5.
We
have
29
models
and
a
number
of
members
that
were
run
increased
and
then
it
seemed
f6,
and
this
is
actually
some
without
a
date.
At
the
time
we
did
the
analysis.
We
had
22
models,
an
order
of
400
simulations
and
of
note.
We
are
just
using
one
model
from
each
modeling.
H
Center
I
will
describe
an
EO
f
analysis
method
in
a
bit
and
we're
trying
not
to
over
weight
to
the
theme
of
tix,
just
because
the
lipsticks
has
more
simulations
were
trying
to
evenly
weight
across
the
limits
and
then
Shasta
mate,
the
intrinsic
noise
of
the
modes,
we're
looking
at
the
CSM,
large
ensemble
and
also
the
MPI
grand
ensemble.
It
turns
out
there
they're
consistent
in
some
of
the
most
but
actually
have
some
some
fairly
large
differences
that
are
noteworthy.
H
So
the
first
step
is
to
ask
what
Mo's
can
we
make
a
meaningful
assessment
with
the
observational
record?
And
so
what
you
see
here
are
two
basic
constraints
that
you
have
to
satisfy.
The
first
is
your
observations
have
to
agree
with
one
another,
and
so,
if
you
look
at
the
red
dot,
that
is
the
correlation
between
the
patterns
for
an
n,
so
sea
level,
pressure
tell
a
connection
for
djf
that
you
get
to
knowledge
between
our
two
sea
level.
H
H
So
for
this
mode
we
have
a
very
wide
variation
with
Seema,
five
relative
to
the
intrinsic
variability
of
the
modes,
and
so
that
gives
us
a
fairly
robust
constraint
from
the
observations.
But
now,
of
course,
we
look
at
many
more
modes
in
our
paper.
I
don't
want
to
go
through
this
paper,
and
but
is
this
figure
in
gory
detail,
but
what
you
will
find
is
that
there
are
some
measures,
for
example,
of
low
frequency
variability
that
are
very
well
very
poorly
constrained
by
the
observational
record.
H
And
so,
if
you
look
at
the
PDO,
the
size
of
those
whiskers
at
the
top
of
those
bars
and
black
is
small
comparison
to
seem
of
five
range.
But
that's
not
the
case
for
the
IPO
so
to
the
right
of
that
through
the
IPO
and
the
green
human
5
range
is
actually
not
that
much
greater
and
you
get
just
from
internal
variability
alone.
And
on
top
of
that,
the
correlation
that
you
get
between
the
different
observational
data
sets
is
not
that
strong.
H
And
so
these
are
relatively
poorly
constrained
and
we
try
to
avoid
these
modes,
and
the
same
can
be
said
of
the
amo
that
you
don't
have
a
very
good
signal
to
noise
ratio
and
for
low-pass
version
of
the
amo.
We
actually
have
some
observational
uncertainty,
so
we
avoid
those
modes
today,
I'm
just
focusing
on
the
PDO
and
ENSO,
but
first
I
want
to
describe
the
method
that
we're
using
for
diagnosing
components
of
the
bias
and
that
consists
of
taking
these
AOS
principal
component
analysis
in
bias
space.
H
So,
instead
of
Latin
long
and
time
what
I'm
doing
is
taking
the
bias
patterns
in
this
case
for
the
PDO
and
I'm
ordering
those
by
model.
So
this
is
the
case
where
we're
only
using
a
subset
of
the
available
simulations
to
avoid
over
waiting
and
in
one
model,
but
what
you
get
from
that
and
I
wasn't
sure
what
I
get
from
this
when
I
first
did
it,
whether
it
would
just
be
statistical
noise,
whether
the
EOS
would
be
separable,
but
what
we
do
get
from.
H
That
is
actually
some
some
leading
patterns
that
are
both
large
scale
and
indicative
of
coherent
large-scale
patterns,
but
also
separable
us.
So
we're
not
just
looking
at
noise
here
we're
looking
at
really
fundamental
ways
in
which
models
disagree
with
each
other
and
that's
at
the
core
of
the
science
questions
that
we're
posing.
We
don't
want
to
just
look
at
mean
bias.
We
want
to
look
at
spread
across
models
and
so
for
the
PDO.
In
this
case,
for
example,
you
have
to
your
left
now.
H
Looking
at
the
bottom
of
the
figure
you
have
eaten,
the
leading
to
us
explains
32
percent
of
the
variance
robust
us,
and
it
has
this
kind
of
global
pattern
to
it.
And,
interestingly,
ef-2
is
much
more
focused
in
the
in
the
North
Pacific
Ocean,
and
so
you
can
look
at
the
principal
component
values
across
terse
aisles
of
the
ensemble
and
that's
what
you
see
for
these
two
principal
components
in
the
bottom
panel.
Dark
blue
is
team
of
six
light.
H
Blue,
a
seam
of
five
and
green
is
team
of
three
and
those
are
averages
in
each
tercile
for
each
seam
up
in
each
principal
component,
and
so
you
can
add
observations
to
this
uf
analysis
and
they
lie
to
the
right
by
ordering
them
on
the
right,
their
bottom
right
part
of
the
panel.
You
have
basically
the
two
to
leave
us
representing
biases
in
that
mode.
H
The
bias
patterns
from
that
mode,
so
there's
systematic
bias
in
this
case
for
pc1,
and
you
can
look
at
this
in
a
little
more
detail,
looking
more
generally
at
the
PDO
across
the
seam
of
archive.
So
let
me
take
a
moment
to
really
describe
all
the
panels
here.
Top
left.
You
see
the
observations
from
your
SST
and
then
below
that
you
can
see
the
standard
deviation
of
the
bias
across
the
model
that
highlights
the
areas
in
which
the
models
really
disagree.
With
how
strong
their
PDO
pattern
is.
H
You
can
look
at
a
mean
bias,
for
example,
from
schema
3
to
the
right
of
that
seam
of
5
down
one
to
the
last
and
team
of
six
to
the
right,
and
in
general,
you
get
this
sense
with
a
decrease
in
bias
across
the
archives,
but
really
on
some
modes.
Taking
the
mean
like
this
is
very
misleading,
especially
where
the
biases
aren't
systematic,
in
this
case,
they're
fairly
systematic,
and
you
can
see
that
your
magnitude
of
bias
increases
in
two-seam
of
six
and
those
are
the
two
leading
AOS
that
we
just
discussed
at
the
bottom.
H
You
have
this
profitable
expression.
Gof
were
very
strong
weightings
in
the
tropics.
It's
positively
correlated
to
the
mean
pattern,
and
overall
this
relates
to
how
strongly
the
PDO
gets
expressed
at
low
latitudes
across
model
some
models.
Do
it
very
differently
than
others,
and
increasingly
they
do
it
well.
H
This
relates
more
to
the
structure
that
in
the
North
Pacific
Ocean
doesn't
correlate
that
strongly
with
the
observed
pattern
or
with
the
bias.
It
just
represents
a
fundamental
distinction
across
models
and
it's
more
scattered
around
the
observational
estimate,
but
there
is
a
systematic
component
to
it.
So
now,
if
you
look
for.
H
Right
so
CES
m1
has
improved
into
c
es
m2,
and
this
shows
roughly
where
these
guys
are
on
the
pc
plot.
So
within
so,
and
this
relates
to
a
lot
of
what
pants
and
yet
I
just
showed,
you
can
see
a
you
know,
some
of
the
fundamental
features
of
the
space-time
bias
and
then
so
represented
by
models.
So
the
observed,
composites
and
so
with
longitude
and
time
is
upper
left
the
areas
where
they
disagree.
The
most
is
below
that
and
then
you
have
this
canonical
bias
that
I
think
I'd
alluded
to.
H
Event
so
from
the
bottom
left
and
ef-2
on
the
bottom
right
to
duration.
Now
the
leading
component.
Is
you
look
at
the
principal
components?
You
can
see
a
scattered
more
about
the
observations,
and
so
there
are
two
models
in
particular
in
theme
of
three
that
have
this
huge
by
any
ality
and
those
show
up
on
the
far
left
side
of
the
PC
plot.
But
in
general,
what
you
see,
most
importantly,
going
from
symmetries
to
mystics
is
a
of
the
spread.
H
You
have
this
very
wide
range
of
behavior,
in
symmetry,
from
models
with
very
weekend,
so
stood
overly
strong
and
so
collapsing
along
the
PC
one
axis,
and
then
there's
also
error
in
the
PC
2
axis.
That
has
collapsed
somewhat.
So
both
of
these
things
are
improving.
The
second
PC
relates
the
duration
event.
So
and,
as
you
get
a
lude,
that's
actually
improved
in
CES
M,
and
so
you
can
see
how
these
things
have
changed
from
CES
m13
sm
we're
almost
right
on
top
of
observations,
at
least
in
these
metrics
with
CES
M.
H
You
can
see
that
over
on
the
right
hand,
side
that
same
improvements
of
some
real
disagreement
as
to
how
wide
that
spread
should
be
between
the
GSM
and
the
MPI
large
ensembles,
but
it's
a
persistent
improvement
nonetheless,
and
characterized
to
first
order
by
getting
rid
of
the
worst
model.
So
in
Sima
3,
both
the
PDO
for
ENSO
and
the
overall
score,
we
had
some
very
poorly
performing
models.
Let
me
just
jump
this
conclusion
to
this
point.
H
We
have
a
very
clear
answer
to
our
question
as
to
whether
models
have
progressed
the
reputation
of
internal
variability,
they
have
C
VDP
scores
have
generally
increased
across
the
model
generations
for
many
of
the
modes.
I
didn't
touch
on
this
much,
but
the
extra-tropical
modes
are
difficult
to
deal
with
the
mean
scores
tend
to
be
higher
and
the
intrinsic
noise
tend
to
be
larger,
and
so
it's
difficult
to
really
resolve
the
signal-to-noise.
H
I
didn't
I,
mention
it,
but
we've
done
the
same
thing
for
La
Nina
and
you
get
more
to
your
money,
Nia's
and
then
the
PDO
connections,
so
the
tropics
have
become
stronger,
and
so
many
of
these
canonical
biases
remain
through
the
theme
of
archives
but
they're
reduced
in
magnitude
and
we're
able
to
resolve
that
with
our
package,
so
I'll
just
end
there.
Thank
you.
F
H
Think
that
has
to
do
with
the
coherence
between
the
Northern,
Hemisphere
and
southern
hemisphere,
nodes
of
the
PDI
IPO
and
how
coherent
they
are
I
think
is
somewhat
of
an
open
question
and
and
whether
you
know
we
don't
look
at
the
IPO
extensively
in
this
manuscript
but
I
think
there's
a
fair
amount
of
intrinsic
variability
that
arises
from
that.
Perhaps
lack
of
coherence
between
the
hemispheres
in
the
IPO.
F
H
F
A
H
H
F
Antonieta
I
don't
know
if
you
saw
there's
a
question
in
the
chat
for
you,
so
if
all
the
speakers
could
keep
an
eye
on
the
chat
as
people
think
of
their
questions,
so
we'll
move
on
to
the
next
speaker.
You
chow
line
Liang
who's.
Talking
about
the
impact
of
Arctic
sea
ice
variability
on
the
atmospheric
circulation.
B
K
B
Of
Arctic,
sea
and
reliability
on
atmospheric
circulation-
and
this
work
is
many
working
with
Claude,
Frankie,
Knoll
and
Yong
Quan,
and
and
also
called
handi,
Steve
and
other
European
partners.
So
I
especially
want
to
thank
eight
European
groups.
They
contribute
their
agc
and
experiments.
So
there
is
a
clear
up
linkage
between
Arctic
sea
ice
and
atmospheric
circulation
in
real
analysis.
B
Theta
said
here,
for
example,
from
naio
structure,
so
you
can
see
that
in
December
in
the
January
the
negative,
the
way
all
atmospheric
circulation
structure
is
statistically
related
to
a
preceding
November
Arctic
sea
ice
variability,
which
is
characterized
by
large
bearing
heresy
sea
ice
decline.
However,
this
observational
energy
is
not
simulated
consistently
in
current
ages
global
climate
models,
so,
for
example,
some
model
shows
positive
in
Leo
structure
in
rebounds
to
response
with
Arctic
sea
ice
retreat.
B
However,
other
a
other
simulation
shows
negative,
a
meal
structure,
so
such
inconsistency
make
this
harder
to
anything
and
the
makers
also
the
interpretation
of
a
causality.
So,
under
the
you
founded
reaction
project,
we
confronted
a
large
coordinated,
a
large
ensemble
AGC,
an
experiment
to
address
these
issues.
So
in
total
we
have
nine
participating
models
and
each
model
produced
from
ten
to
thirty
ensemble
members,
so
total
we
have
160
65
members
and
our
who
in
her
group,
will
be
UCS
until
welcome
six
with
specified
chemistry,
and
then
we
generated
30
ensemble
members.
B
So
then
for
the
experiment,
the
first
set
of
experiment.
We
call
it
experiment,
one
or
forcing
experiment.
So
we
prescribe
time-varying
arctic
sea
ice
and
the
global
SST,
a
new
greenhouse
gas,
forcing
from
1979
to
2014
in
contrasting
experiment,
to
or
recalls
Arctic
sea
ice
climatology
wrong.
We
replace
the
time
varying
Arctic
sea
ice
by
its
climatological
value,
but
we
still
keep
global
SST
and
greenhouse
gas
in
force
in
time.
Very
so,
the
only
difference
between
these
two
sets
of
two
sets
of
experiments
is
the
Arctic
sea
ice,
forcing
the
science.
B
Its
scientific
questions
we
want
to
answer
is
the
can
a
GCM
simulate
the
Arctic
sea
ice
impact
on
large-scale
atmospheric
circulation?
Well,
especially,
those
identified
in
reanalysis
data
set,
and
we
especially
focus
on
October
November
December
in
the
January
February
March
in
the
following
analysis
and
the
second
one
to
answer:
what
is
the
role
of
Internet
and
most
recoverability?
B
As
many
study
has
shown,
large
internal
variability
may
affect
a
forced
variability
and
third,
can
we
use
this
a
GCM
to
quantify
the
Arctic
sea
ice
forced
atmospheric
circulation,
and
in
this
study
we
mainly
focus
on
two
component-wise
Longtin
train
and
the
internal
variability.
But
today,
because
of
the
time,
many
showing
you
the
trend,
the
analysis,
so
we
made
two
basic
assumption.
The
first
one
used
forced
component
can
be
separated
from
internal
variability
by
using
a
multi-model
ensemble
mean
over
165
members.
B
So
in
here
we
I
I
treated
each
member
equally,
so
without
performing
any
waiting.
When
we
take
more
time
at
ensemble
me
and
the
second,
the
headmaster,
atmospheric
circulation
response
to
Arctic
sea
ice
variability
is
assuming
to
be
sufficiently
linear
and
implying
their
activity
so
based
on
these
assumptions.
So
if
we
take
a
multi-model,
ensemble
mean
overall
force
in
wrong.
We
can
get
the
force
the
component
by
all
the
force,
including
sea
ice.
B
It
says
t
crayons
guessing
and
the
radiative
forcing
and
similarly,
if
we
take
a
multimode
ensemble
mean
over
sea
ice
climatology
wrong,
we
can
again
get
the
forcing
component
a
force,
the
component
except
the
Arctic
sea
ice,
forcing
and
by
taking
their
T
difference.
We
can
further
concept
by
the
Arctic
sea
ice
force.
The
component
and
we
and
I
will
use
a
sigh
in
the
following
presentation.
So
first
we
look
at
the
spatial
pattern
and
of
their
surfaces.
Air
temperature
trend
in
all
multi-model
ensemble
me
in
the
ER
8
5.
B
So
here
we
can
see
within
the
Arctic
Circle
there's
a
large
or
Arctic
warming
trend
appears
and
there,
and
they
are
very
similar
in
ER,
f5
and
all
multi-model
ensemble
mean
impulse
oh
and
D
integer
M.
So
this
similar
special
currency
in
area,
5
and
all
Matamata
ensemble
mean
indicates
that
this
temperature
trying
to
incinerate
5,
are
possibly
forced
by
sea
ice
as
SST
or
global
rail
radiative.
Forcing.
However,
this
wooden
train
is
now
consistent
is,
for
example,
outside
the
Arctic
Circle.
For
example.
B
So,
for
example,
the
black
shading
indicates
the
95%
inter
competence
interval
of
the
er,
a
five
trend
and
in
order
we
are
trying
to
inform
the
range
of
variation
and
the
it
is
generally
reasonable
to
think
about
this
spread.
The
this
interval
is
large,
contributed
from
internal
atmospheric
of
variability.
So
first,
if
we
look
at
the
range
of
the
of
the
of
each
member
is
largely
comparable
to
the
estimate
of
ER
f5
so
indicating
that
it
is
likely
the
large
internal
variability
contributed
to
the
spread
in
the
model
and
the
second.
B
If
we
compare
the
difference
between
black
and
magenta
shading
and
I
forgot,
to
mention
the
much
initiating
is
similar.
95%
interval
estimate,
based
on
all
multi-model
ensemble,
mean
surface
air
temperature
trend,
so
compare
their
difference.
We
can
see
how
the
reduction
in
indicates
us
that
how
much
the
effect
of
internal
variability
so,
for
example,
if
we
compare
this
shading
to
magenta
in
the
black,
we
can
see
the
reduction,
and
this
gives
us
some
idea
about
the
effect
of
internal
variability.
And
finally,
despite
the
effects
of
internal
variability,
we
can
see
all
the
trend
on
others.
B
Turn
signs
are
all
positive,
indicating
that
the
warming
trend
is
robust
and
the
possible
reforest
component.
However,
this
is
not
the
case
for
sativa
pressure,
as
we
can
see
in
terms
of
spatial
pattern.
They're,
so
diverse,
burning,
er,
f5
and
all
multi-model
ensemble
mean
imposed
Ont
in
the
chair
again.
So
this
the
different
special
panel
indicates
that
the
pattern
we
see
in
our
f5
our
passport
not
forced,
but
just
a
one
realization
or
representation
of
internal
variability,
and
it
is
indeed
a
case
if
we
look
at
the
distributions,
so
we
can
see
that
now.
B
If
we
focus
on
the
Arctic
averaged
a
suitable
pressure
trend,
you
can
see
its
sign
some
of
the
science
negative
some
of
the
signs
positive
and
that
this
is
highly
affected
by
the
internal
variability.
So
in
other
words,
the
internal
variability
can
determine
the
sign
of
the
sea
level
pressure
trend.
B
So
so
the
effect
of
internal
probability
determines
the
sign
of
C
the
pressure
trend
or
these
dynamical
variables.
So
in
next
we
want
to
further
understand
or
quantify.
Arctic
sea
has
forced
a
trend
in
service
and
meet
the
tropospheric
field.
So
we
now
we
consider
the
difference
of
the
motor
model.
Ensemble
minnow,
two
sets
of
experiment,
so
here
I'm,
showing
you
jfm
surface
air
temperature
trend
and
the
cederberg
pressure
500
minute
about
you,
but
potential
high
and
there's
all
no
way.
So.
First,
we
look
at
the
city
of
surface
air
temperature
trend.
B
We
can
see
large
localized
the
warming
trend
just
sitting
right
above
where
large
Arctic
sea
ice
retreat
and
if
we
compare
this
to
the
all,
forcing
ultimate
ensemble
mean
this
woman
trend
accounts
about
50
percent
of
the
warming
trend,
indicating
that
50
percent
of
the
warming
trend
related
to
Arctic
sea
ice
decline
and
for
the
sea
level
pressure
trend.
We
see
some
localized,
a
lousy
double
pressure
sitting
right
on
top
of
this
warming
hotspot.
B
So
this
is
reflect
so
called
heat,
low
feature,
atmospheric
circulation
features
which
has
been
seeing
in
many
model
studies
and
outside
this
warming
hotspot.
You
can
see
some
positive
sea
level
pressure,
train
and
especially
in
the
North
Atlantic
sector.
We
see
these
currencies
resembling
a
negative
and
mayo
like
structure.
Okay,
and
this
negative
angle
structure
becomes
more
clear
when
we
located
500
mini
budget
potential,
high
field
and
hemispherical
speaking.
This
pattern
is
more
resemble
like
the
negative
AVO
structure
and
a
correspondingly.
B
We
have
a
weekend
amid
already
featured
with
slightly
soft
worship,
but
is
not
a
parent,
so
we
further
provide
some
quantification.
So,
for
example,
if
we
took
area
averaged
over
northern
europe,
where
the
trend
is
significant,
we
can
get
a
value
about
point
two,
one
hip-hop
syllable
pressure
increase
per
decade.
However,
we
also
provide
the
quantification
based
on
the
observational
estimates
from
Samoa
all
2020
and
that
they
found
much
larger
syllable
pressure
change
increase
in
roughly
similar
similar
regions.
So
this
means
our
a
GCM.
We
underestimate
the
Arctic
forest
trend
in
this.
F
F
A
F
A
F
F
Well,
maybe
maybe
the
easiest
thing
is
for
you
to
answer
the
questions
in
the
chat
and
we
proceed
to
the
next
speaker.
Hopefully
he's
hearing
that
I'll
message
him
in
the
chat
just
in
case
not
so
the
next
speaker
is
Ming
Hong
Jang
talking
about
sticking
with
the
Arctic
in
impacts,
the
Arctic
climate
changes
on
synoptic,
cyclones,
so
Ming
Hong.
If
you're
there.
L
Just
a
moment
like
there
are
some
securities
18,
sorry,
okay,
let
me
try.
Okay,
okay,
yeah
I
can
also
get
I
like
how
you
see
my
screen
all
yep.
Okay
mm
yep.
It
is
a
good.
Okay,
looks
good,
okay,
hello,
everyone.
My
name
is
Amin
Hong
Kong.
My
talk
is
the
impact
of
active
climate
change.
Also
optical
cyclones
and
I
prefer
hi.
This
this
guide
is
work,
the
way
that
we
are
peri
and
the
trends
are
known
at
the
paid
for
Institute
of
Oceanography.
L
In
this
talk,
sorry
yeah
you
just
talk.
First
I
will
do
background
introduction,
then
I
will
show
Apollo
off
set
up
an
orientation
insert
a
part.
I
will
show,
don't
see
any
result.
A
psycho
response
in
wind
hana
summer
at
last,
I
really
was
summary.
The
act
iike
had
experienced
dramatic
or
climate
change,
acting
as
a
ice
Repton
decline
and
they
are
more
open.
Water
areas,
arctic
sea
ice
become
a
younger
and
the
sinner
there's
increase
the
ice
motion.
L
L
Both
the
opposition
at
the
model
results
suggest
that
in
the
warming
active
notice,
strong
air
sea
ice
interaction,
younger
and
the
synergy
I
see,
the
mall
will
are
about
to
atmospheric.
First,
especially,
it
was
the
optical
weather
system.
So
this
logical
why
the
system
is
becoming
increasingly
important
in
the
ice
motion
and
the
fresh
water
redistribution.
This
motivator,
our
this
study.
L
Here
we
use
the
power
wash
3.26
special
Aleutian
to
25
kilometres,
that
the
plot
shows
the
motor
domain
power
of
it,
driven
by
output
from
Hollis
our
system
model.
Sweden
skinning
simulation
have
been
conducted
over
the
period
from
1970
to
2099,
including
historical
experiment,
and
the
two
scenarios
are
CP
8.5
and
a
4.5.
L
The
zucchini
result
has
been
validated
away:
the
real
estate
higher
in
her
room
and
the
holidays.
The
model
results
University
of
Americans
automatically
cycle.
Trainees
gave
me
the
user
to
track
cyclone.
Our
result
has
shown
that
the
polar
worth
improves
the
simulation
of
active
cyclone
more
details
for
the
model
configuration
at
the
meditation.
Please
refer
to
our
paper
on
atmosphere
and
the
ocean,
so
you
next
to
slide
in
next
to
slide.
The
area
briefly
shows
the
performance
of
the
polar
Polar
Wharf
in
the
current
climate.
First,
we
look
at
the
winters
cyclones
yesterday,
I
made.
L
The
upper
panel
shows
the
probability
density
function
of
a
cyclone
track
number
here:
proper
power
curve
data
from
a
file
read
out
politely,
it's
the
yaw
in
terrain
right,
it's
the
polar
world
and
blue
is
address
our
system
model.
From
this
plot
we
can
say
both
model
and
estimate,
the
frequency
of
winter
cyclone
and
the
polar
wolf
had
the
comparable
cyclone
members
are
seeing
TCM.
It
is
because
the
harvest
and
her
assistant
model
overestimated
the
cyclone
cyclone
see
central,
Arctic
and
girlfriend
street
areas.
L
We
can
see
this
from
this
difference
plot
between
Moto's
Malorie
I
in
her
reign
as
for
intensity.
The
bottom
panel
shows
the
PDFs
of
cyclones
and
her
pressure.
We
can
clearly
see
a
sickness
in
the
pole.
Award
shows
comparable
intensity
are
seeing
realizes
dataset
why
the
holiday,
Sandra's
moto,
underestimated
the
intensity
of
the
wing,
her
cyclone
and
then
we
look
at
the
SHA.
Then
we
look
at
the
summer
cycle
or
a
historic
climate.
L
The
first
we
look
at
the
PDF
PDF
plot
of
the
cyclone
I
clamber.
We
can
see
both
model
also
an
estimated
frequency
of
summer.
Cyclone.
However,
polar
warm
stimulate,
more
cyclone
members,
the
show
in
TCM.
It
also
can
see
very
clearly
from
this
different
difference:
plot
between
Moto's
manners,
the
yari
in
her
reign.
As
for
the
intensity.
First,
let's
look
at
the
histogram
of
the
cyclone
central
pressure.
We
can
see.
L
Polar
war
has
more
intense
signal
and
the
last
few
were
moderate
cyclone,
the
yah-yah-yah
interim
and
the
holidays
model
and
the
hardest
model
had
a
distant
n
cycle
in
the
current
climate.
Therefore,
the
pdfs
plot
is
clearly
show
that
the
intensity
also
active.
Secondly,
in
polar
world,
it's
generally
stronger
the
Ranas,
theta
and
holidays
TCM,
so
in
next
part,
I
will
show
the
future
change
or
active
cycle,
or
in
winter
and
the
summer
fossil
is
located
or
sorry.
Let's
look
at
a
winter
cyclone
in
the
future.
L
The
right
the
left
column
shows
a
side
note
remember
in
historic
climate
and
our
CPA
Doyle
file,
the
dry.
The
two
column
shows
the
difference
plot
between
our
CP
miners,
historical,
a
mentor.
Let's
just
look
at
the
difference
plot
we
can
see
they
are
to
increase
the
cyclone
embers
in
the
central
west
active
and
the
decrease.
The
cyclone
name
in
the
east
active
in
post
Solaria
in
post
model.
L
Next,
we
just
look
at
the
sorry.
Let's
learn
we
does
not
have
the
PDFs
plot.
The
upper
panel
shows
the
PDFs
of
the
second
node
check
number
in
polar
were
found
in
TCM.
We
can
see,
there's
no
significant
change
in
cycle
of
lampur,
seeing
the
future
climate,
our
CPI
25
0.05,
compared
with
the
historical
climate.
This
is
due
to
the
increase
the
cycling
in
Central
West
active,
a
compensated
by
decra
cycling
in
Easter
active.
L
Then
we
look
at
the
intensity.
The
bottom
of
plant
shows
the
PDFs
of
cyclones
central
pressure
in
polar
180
cm.
We
can
see
there's
a
significant
increase
in
the
intensity
of
a
winter
cyclone
in
our
CP
8.5
14.5.
Compared
with
the
historical
climate
1
compare
that
ISM
result
with
the
polar
water
result.
We
can
see
the
overall
intensity
over
the
winter
cyclone
in
polar
water.
It's
stronger
than
the
in
TCM
in
the
future
climate
due
to
increase
the
frequency
and
intensity.
L
Also
active
the
cyclone,
the
sea
level
pressure
a
system
prefer
high,
become
weakening
the
future
climate.
The
bottom
applaud
compared
with
the
current
climate,
the
upper
upper
plot
so
index
to
slide
I,
discuss
the
possible
reasons.
The
for
such
chips,
you
bring
her
cyclone
a
fossil
is
located
a
cycle
on
Genesis
the
left
or
to
column
shows
a
cyclogenesis
historical
climate.
An
RCP
8.5,
the
graphical
column
shows
the
difference.
L
We
eater
suggest
that
cyclogenesis,
don't
it's
a
Polaroid
extended
compared
with
the
historical
kilometer,
and
this
is
due
to
the
polar
where
the
displaced
found
to
them
with
the
icy
retreat
in
winter,
then
we
located
a
cyclone
Isis.
We
just
let's
just
look
at
the
difference
plotted
in
the
writer
to
Colin.
We
can
see
there
are
the
similar
increase
that
in
Isis
event
in
the
Canada
archipelago
raging
and
the
decrease
the
nicest
event
in
western
yeast
active
impulses,
ilaria
and
an
impulse
model.
L
This
could
be
caused
by
the
chance
in
the
upper
levels,
the
stirring
flaw.
So,
let's
look
at
the
five
hundred
zero
potential
high
in
the
historical
climate
under
the
RCP
8.5,
compared
with
the
current
kilometer
in
our
CP,
a
25
polar
vortex
becomes
warmer
and
awakening,
and
the
euro
trolls
becomes
porous
channel
in
the
future,
such
as
here
in
this
result
in
most
diagnosed
moving
into
the
central
active
and
the
last
icon,
or
moving
through
east
active.
So
next
I
will
talk
about
the
summer
psychologist
in
future
kilometer.
L
This
slide
shows
the
second
try
clamber
enough
in
the
current
climate
and
the
future
kilometer.
Also,
we
just
focus
on
a
difference
plot
between
the
RCP
mister
kilometer.
We
can
see
that
also
increased
summer
cycle
member
in
the
central
and
the
west
act.
Iike
decrease
the
cycle
member
in
the
east,
active
in
postal
area
and
the
impulse
model.
L
Next,
we
just
look
at
the
pdfs
plot
over
the
summer.
Cyclone
sorry,
I
reminisce.
Okay,
I
just
precisely
the
read
occurrence
in
his/her
climate,
blanket
RCP
and
qualifier
blue
is
our
CP.
Sorry,
black,
hey,
the
4.5
blue,
is
our
CP
Edwin
file.
So
the
upper
panel
shows
a
PDF
of
a
side
note
right
number,
because
there's
no
significant
urgency
in
the
frequency
of
summer
cyclone,
the
reader.
It
is
similar
because
the
compensation
effect,
then
we
look
at
the
intensity
and
the
battle
palace
justice
PDFs
over
sent
cyclone
central
pressure
in
war,
philatelist
ECM.
L
We
can
see
there
they're,
just
increasing
difficulty,
increase
in
more
intense
cyclone
in
our
CP
8.5
4.25,
compared
with
the
character
kilometer
imposed
the
polar
world
and
180
cm.
Please
allow
this
is
just
more
intense
cycle.
They
lost
significantly,
there's
no
secret
for
the
change
in
the
overall
overall
intensity
change
and
comparative
same
result
with
the
polar
of
a
result.
There
are
the
more
intense
the
cyclone
in
power
worth
the
unit
is
them
in
the
future
climate.
We
also
try
to
look
at
with
so
delta
link.
L
Is
the
frequency
the
intensity
of
a
summer
cycle
on
the
silica
pressure
system
over
high
is
also
a
weekend
in
the
future
climate
and
the
surface
law
over
the
central
Arctic
is
enhanced
in
the
future
climate.
We
also
not
have
the
cycle
of
Genesis
to
investigate
the
possible
reasons
for
such
chains.
In
stammers
I
:,
let's
just
look
at
the
difference
plot
the
rider
two
columns
we
can
see.
There
are
two
clearly
significant
increase,
cyclogenesis
in
central
active
and
the
decrease,
the
cyclogenesis
in
Eurasia,
active
in
post
scenario
and
the
impulse
model.
L
This
is
this
also
could
be
caused
by
the
polar
oddities.
Please,
the
polar
photo
dome
with
ice
retreat
again
summer.
There's
other
possible
reason
that
it's
not
included
in
this
study.
So
we
just
go
to
the
summary
to
the
end
over
the
21
century,
when
her
before
I
becomes
weakening
and
in
ice
free
summer
buffer
height
also
weekend
under
the
surface
noisy
in
highest
listened
to
do
to
increase
the
frequency
and
intensity
of
activist
acronym.
L
There
are
the
several
reasons
for
the
changes
in
this
optic:
cyclone
we're
into
the
polar
water
displaced,
the
polar
fun
to
do
with
the
accident
sheet
in
the
update,
the
Sigma
is
a
weakening
polar
what
x6
toward
Canada
archipelago
such
a
chance
in
the
stirring
floor
without
the
most
like
not
moving
into
central
a
critical
unless
I
go
into
Easter
active.
Let's
all
follow.
Thank
you
for
attention.
F
L
The
changes
in
the
in
the,
for
example,
middle
levels-
502
opponents
are
high.
It's
significant
awakened
the
poor
for
high
and
no
sorry
it's
a
weaken
the
polar
vortex.
We
also
look
at
the
we
also
look
at
the
CSS
I'm
for
without
it
is
shows
a
similar
response
in
winter
and
a
summer
also
the
GCM
and
the
polymers.
F
J
J
This
is
figure
shows
on
Monday
by
marca
de
Lincoln,
from
his
research
we
found
out
is
the
equivalent
emissions
15
see,
increase
in
him,
see
know
of
six
model
banks
in
m6,
but
his
updated.
The
data
shows
that
the
equipment,
if
he
is
about
0.5
degree,
cave
in
14
out
of
the
40
symmetries
models,
but
only
two
models
in
cs5-
and
here
we
particularly
increased
in-
is
the
CSM
and
the
EPS
and
back
because
these
two
models
are
both
have
the
same
equivalent
and
Mississippi
way.
But
I
said
Mark
said
they
are
further.
J
We
see
that
the
a
mark
is
the
quite
different.
Very
much
for
the
easier
Sam
is
a
lowering
and
see.
Csm
is
red
in
the
middle.
Actually,
the
CSM.
The
vertical
structure
is
very
close
to
the
record
on
tuition
to
about
2
2
meter
depth
and
after
you
can
start
with
their
work
from
the
revisions.
Now,
one
unfocused
is
whether
this
difference,
with
the
mean
stating
a
mark,
will
affect
the
climate
response
as
happier
to
this
uncertainty.
J
So
the
model,
as
we
say
we
use
CSM
to
responsive
evolution
and
EPS
and
one
Miss
22.
The
submission
we
analyzed
is
the
1850
pediatric
on
children
see
asymptotes
five
years.
If
you
have
some
banks
welcome,
you
will
also
analyze
the
historical
situation
from
1850
to
2014
TSM
what
to
have
German
and
some
numbers
meteors,
and
we
have
thousands
of
members.
We
also
included
the
future
projections
before
CSM
to
or
Nazi
nucleus,
and
one.
J
This
is
the
image
index
which
we
defined
is
the
maximum
of
the
Atlantean,
where
you
from
below
parameter
that
can
print
equipment
or
run.
We
can
clear
say
the
remark
is
stronger.
Insidious
and
to
time
is
fearsome
one.
This
is
the
mean
number
and
in
a
20-cent
reservation
you
can
say
started
it.
We
ask
them
to
CSM
to
there's
a
rising
claim
of
the
image
in
here,
and
then
it
is
awkward.
J
This
picture
is
similar
to
many
other
domestic
models,
but
he
nucleus
and
one
we
see-
can
do
small
alpha
twin,
but
with
a
filter
protection.
It
is
interesting
that
TSM
to
show
a
deep
level,
a
bug
is
similar
from
different
scenarios.
This
is
a
bit
different
from
what
it
happened
in
sin:
M
PI.
Actually,
this
is
also
similar
picture
in
many
others
in
m6
moments
to
do
affair.
In
the
comparison
with
afterwards,
we
are
going
to
focus
on
one
from
sue
program,
because
in
this
world
only
14
change
is
the
real
effects.
J
So,
for
this
one
person,
super
rare
consider
for
CSM
to
the
email
will
be
planned,
a
lot
which
the
deep
ties
much
larger
than
that
in
serious
and
one,
but
in
the
simulation
the
into
the
email
is
still
stronger
in
CS
and
2001
Pacific
lies.
We
say
that
that's
easier,
Sam,
the
diplom
a
map
is
roughly
is
about
30
percent
by
the
time
of
a
simple
Kentucky,
but
all
seniors,
and
to
this
is
over
50%.
J
This
is
a
global
mean
temperature
in
the
control
room,
instantly,
RSS
feed
and
the
conference
in
here
in
the
controller
is
there
is
a
small
apple
tree
in
CVS
and,
and
this
Apple
twin
is
about
twice
as
large
in
see
TSM
to
plan
B
3,
as
my
the
mean
state
in
general,
the
Year
Sam
is
a
be
the
bomber
than
Ethier.
Sam
is
about
how
equal
difference,
income
of
the
country
response
to
the
20th
century
and
say
the
timer
can
be
struck
row
a
very
similar,
but
it
was
after
that.
J
You
see
nineteen
sixties,
the
tanker
right
acquaintance
easy
CSM,
the
larger
than
that.
If
the
answer
can
say
this
difference
here,
it's
lighter
than
the
different
entity
in
a
one-person
suit
who
simulation
which
say
something
just
hops
it,
although
the
CEO
easier,
say
I'm
starting
at
a
lower
temperature,
but
he
did
ransom
faster
by
the
end
at
the
end
of
the
140
years.
Actually,
the
temperature
is
about
one
point,
five
degree
difference
for
the
duration
of
the
campaign
is
about
one
point:
five
degree
height.
J
J
J
Lee
is
very
similar
in
this
mode,
but
the
difference
it
shows
that
another
half
year
in
January
summer
in
East,
fierce
and
cool
than
if
you
have
some
of
the
Sun
engines,
put
this
part
of
the
hangar
differences
between
samples,
the
difference
due
to
the
change
of
luck,
which
is
from
very
much-
we
generally
see
a
warmer
northern
hemisphere
than
the
solar
energy.
So
we
think
that
the
difference
between
the
two
model
in
many
caused
by
the
different
students
of
a
map
in
the
new
state
in
response
to
seal,
to
oppose
him
or
CSM
cool.
J
Dear
sir
warming,
almost
everywhere,
instead
of
support,
not
spending
which
the
technically
is
slightly
cooler
than
will
not
be
conclusive
climate,
this
feature
is,
has
been
seen
from
many
cement
pile
models.
The
immediate
M
is
the
same
thing
is
everywhere
is
warming,
but
the
subpolar
cooling
is
absent
in
this
model
in
comparison
to
the
alcohol
amplify,
the
Romney
based
and
firebombing
museum
is
much
larger
than
CSM.
J
A
A
J
Now,
there's
full
look
at
about
the
physical
processes
of
housing,
the
difference
of
a
mean
state,
and
if
you
can
change
the
image
here,
we
showed
is
the
difference
between
CSM
ii
and
III
sm1
this
for
the
controller.
This
is
the
the
change
in
a
civil
topic
of
aluminum
pan
between
these
two
models,
the
control
of
acidity.
This
is
the
whimper.
Mixer
attempts
is
machi
non-heme
here
and
the
september
in
southern
india.
In
turn,
we
see
is
the
mix
theories
of
people
almost
everywhere
in
two
years
and
to
that
is
yes
mark.
J
That
means
the
our
loss
specification
in
CSF,
who
is
a
bigger
than
say,
Ethier
sambar
for
darker
ocean
in
the
stop
collar,
not
lanky,
we
say
here
is
significant,
a
deeper
mix,
we're
in
CSM
truth
that
is
recent
month.
Actually,
if
you
look
at
the
absolute
value,
we
series,
there
is
nearly
no
deep
immersion
in
the
lacrosse
team
will
be
disability
or
serious
issue,
XM
one,
but
all
the
people,
you
see
osama
happen
even
since
a
weekend.
That
is
why
the
image
is
much
bigger
in
their
mid
stage.
Iii
accent
one.
J
If
you
look
at
the
temperature.
Actually
mr.
Grassi
Obama
in
another
hand
here
serving
or
in
some
symbolize
the
circle
thing,
and
this
deep
exactly
does
not
copy
the
two
of
the
deeper
mixer
in
CSM.
But
the
is
these
people,
mcdeere,
is
caused
by
the
sea.
Surface
salinity,
deep
integrity,
stop
:.
Hustling
me
dsm2
is
Marcus
saltier
than
he
s.
My
this
is
Sophia
our
over
to
make
the
water
much
happier
and
making
smart
phone
here.
J
Let's
look
at
the
change
of
the
mixed
layer
in
the
Houston
super
potent.
We
can
clearly
see
the
reduction
of
the
mix
here
in
CSM
to
the
processor.
You
can
is
much
stronger.
That
means
the
beginning
of
a
motley.
Many
happened
in
this
video
for
peanuts
and
to
and
the
reason
for
this,
larger
Whitney
is
because
of
the
sing
it
changes
lager
in
CSM,
two
of
them
III
sm
1.
That
means
the
best
freak'n
in
fact
is
much
larger.
I
was
in
stronger
with
me
baby.
J
If
we
look
at
the
absolute
value
with
and
still
sitting
in
this
region,
the
EMA,
the
the
service
of
India
is
still
stuck
here
in
CSM
to
with
myself
last.
Let's
look
at
how
this
will
affect
them:
the
ocean,
a
big
uptick
order
in
his
beauty
in
the
ocean.
This
is
the
global
tsunami
in
temperature,
and
this
is
our
normally.
So
we
can
see
that
with
the
stronger,
a
values
years
and
two
in
general,
the
deeper
or
change
the
bummer
is
including
effects
and
one
in
response
to
the
co2
boxing,
and
that
was
plenty.
J
We
can
clear
series
for
a
proportion.
The
bombing
is
stronger
in
easier
sentencing
self,
but
other
water
deeper
than
pepper,
meter,
depth
for
bombing
actually
in
CES
and
who
is
stronger
than
evening
Sam.
This
is
because
the
stronger
stratification
material
Sam
is
a
weaker
in
life.
It
prevented
is
a
further
downward
can
follow
the
observed
in
the
field.
That's
why,
because
in
this
market
and
stayed
in
our
ocean
and
they're
stronger,
ramen
UCSF,
but
in
see,
thank
you
mrs.
from
very
much
there's
more
heat
appropriate
downward
into
the
deeper
ocean
which
reduces
the
surface
moment.
J
So
in
some
way,
although
the
easiest
is
force
it
even
for
serious
and
who
and
us
among
the
I
mean
state-
is
quite
different,
it
is
model
the
way
very
much.
You
see
easier
sand.
One
is
authority
to
a
regular
so
colonoscopy,
including
absent
of
D
production.
Mr.
polar
here
is
one
whose
breaks
the
co2
concentration
remark:
weekends
more
in
CS
and
cool
than
December.
J
F
J
Summarizes,
but
here,
while
it
didn't
seem
much
such
as
the
mix
near
change,
is
it's
less
likely
in
CSM
to
calm
down,
then
the
mix
there
is
a
becomes
a
deeper.
You
see
smq
in
southern
ocean,
then
you
see
XM
bank
and
also
on
deeper
than
in
productive
controller.
This
is
to
displease
me
of
the
voiceless
in
the
sun
ocean,
which
calcium,
a
deeper
big,
fair,
around
unhappy,
a
costly.
F
J
Stan
study
he
says,
and
from
now
announcing
the
biggest
show
is
and
the
trend
economic
results
may
be
different
from
the
equipment.
Kind
of
response,
or
we
can
say,
is
although
the
distribution
of
the
heat
ocean,
even
in
constant
time,
but
when
the
thermal,
which
I
include
mistake,
the
ocean
filled
up
may
be
the
same.
That
is
why,
eventually,
this
email
difference
and
may
not
change
the
improve
intensity,
but
he
does.
F
F
C
A
C
Great
Thank,
You,
Ella
and
global
ocean
warming
has
rich
regional
features
and
in
today's
talk,
I
would
like
to
talk
about
two
of
them.
In
has
the
Indian
Ocean
warming
and
the
suppressed
the
North
Atlantic.
A
warming
and
I
will
argue
that
they
are
actually
closely
connected
through
both
atmospheric
and
oceanic
pathways.
C
Here
is
the
observed
long-term
trend
in
annual
mean
SST
and
the
regardless
of
which
observational
data
center
you
use
or
which
appear
that
you
used
to
calculate
the
long-term
trend.
I
won't
robust.
The
feature
is
that
this
opponent,
North
Atlantic,
has
experienced
a
suppressed
warming
or
even
slight
cooling
and
in
contrast
with
the
warming
of
the
Cerrone
oceans.
C
So-
and
this
is
sometimes
called
the
North
Atlantic
alarming
ho
and
to
quantify
that
I
proposed
a
North
Atlantic
of
warming
ho
index
as
the
SST
difference
between
the
small
blue
box
and
the
bigger
blue
box
here
just
to
highlight
the
regional
deviation
of
SST
change
over
the
Cipolla
North
Atlantic
and
this
warming
hole
feature
has
also
been
seen
in
global
warming.
Simulations
and
many
studies
have
tried
to
understand
the
cause
of
the
warming
hole
and
among
them,
when
most
popular
theory
is
the
slowdown
of
a
mark
and
the
physics
behind
it
is
quite
straightforward.
C
C
So
basically,
we
don't
have
evidence
from
either
observations
or
kinda
models
that
can
support
the
idea
that
the
a
mock
slowdown
has
caused
the
North
Atlantic
warming
hole
for
the
historical
period.
So
in
today's
talk,
I
want
to
propose
an
alternative
mechanism
for
the
warming
hole
and
that
is
related
to
atmosphere.
Exchanges
here
on
the
Left
I'm,
showing
the
climatology
Coast
sea
level
pressure
and
the
service
weights
and
the
south
of
Greenland.
C
Pressure
and
in
between
there
are
westerly
wind
induced
article,
and
so
this
kind
of
pattern
might
remind
you
of
the
positive
phase
of
North,
Atlantic,
Oscillation
and
indeed,
over
the
same
period
on
there
was
an
upward
trend
in
the
NAO
index
and
that
has
significant
crime
impacts,
especially
on
North,
America
and
Europe,
and
you
can
refer
to
this
really
nice
with
your
paper
for
many
details
about
that.
So
the
service
of
huayna
strengthening
can
potentially
call
the
surface
ocean
through
two
effects
and
one
is
the
increase.
C
The
wind
speed
will
enhance
service
turbulent
heat
flux,
and
so
this
is
a
thermodynamic
cooling
effect
and
in
the
meanwhile,
on
the
surface
of
western
wind
anomalies
can
drive
an
anomalous
soft
water,
Ekman
transport
which
bring
colder
high
latitude
water
to
the
south.
So
that's
a
dynamical
cooling
effect,
so
both
the
thermodynamic
and
the
dynamic
effects
of
service
west
wind,
strengthening
and
act
together
and
can
potentially
give
rise
to
a
North
Atlantic
of
warming
hole
and
to
test
this
idea.
C
The
first
thing
I
did
is
to
simply
average
the
surface
westerly
wind
surfaces-
oh
no
wind
over
this
green
box
and
brought
together
with
the
North
Atlantic,
a
woman
who
interacts
we
previously
defined
so
I
was
doing
that.
You
can
immediately
see
a
really
nice
negative
correlation
between
those
two
indices
and
the
long-term
development
of
the
North
Atlantic
warming.
Hole
over
the
past
century
is
accompanied
by
a
long-term
strengthening
of
surface
West
wing's
by
about
30
percent
over
this
period.
C
So,
and-
and
we
also
noticed
that
this
negative
covariation
is
not
owning
for
our
long-term
trend
but
also
exists
for
multi-decade
or
variations
as
well,
and
the
correlation
is
as
high
as
point
9.
So
this
observational
hint
really
motivated
me
to
propose
the
hypothesis
that
the
observed
long-term
North
North
Atlantic,
a
woman
who
was
probably
constant
by
the
service,
the
west
and
wind,
strengthening
over
the
sub
:
North
Atlantic,
and
this
is
in
turn
constant
by
the
Indian
Ocean
for
me,
and
I
will
explain
that
just
in
a
second.
So
this
is
again.
C
This
enhance
the
indian
ocean.
Warming
can
cause
global
scale,
climate
impacts
through
atmospheric
interconnections,
and
that
includes
a
positive
nao.
So
this
indian
ocean
warming
and
the
positive
old
link
has
been
identified
about
two
decades
ago
by
holding
at
all
in
the
following
studies
as
well,
using
a
GCM
simulations,
and
today's
talk
is
kind
of
revisited.
This
problem,
but
more
folks
on
the
link
between
in
the
ocean
warming
and
the
support
of
North,
Atlantic
warming,
hope
and
in
a
couple
of
context.
So
the
model
I
will
use
is
CSM.
C
It's
ocean
on
a
sphere
free,
coupled
and
I'm,
using
a
relatively
low
resolution,
configuration
by
manually,
adding
a
surface
heat
flux,
I
restored
the
tropical
Indian
Ocean
SSD
to
a
one
degree
warmer
climatology
and
after
doing
that,
an
Indian
ocean
gets
warmer
by
about
1
degree,
as
is
shown
on
the
right
and
the
rest
of
global
ocean
is
fully
coupled
with
the
atmosphere
and
that
they
respond
to
the
ocean
warming.
And
this
relation
is
integrated
for
200
years
and
as
in
the
ocean,
gets
warmer.
C
So
let's
not
take
a
look
at
how
the
SST
respond
so
right
beneath
the
West,
the
wind
anomalies,
we
indeed
see
a
development
of
a
North
Atlantic.
A
warming
whole
feature
that
looks
very
similar
with
the
observations,
but
I
should
mention
that
this
is
not
the
only
pathway
for
the
Indian
Ocean
to
a
factory
support
North,
Atlantic
SST,
and
it
can
also
be
affected
as
through
the
a
mark
changes.
So
here
is
the
response
of
a
Mach
intensity
anomaly
to
one
degree
in
the
ocean
warming
and
over
the
initial
period.
C
A
period
the
a
market
doesn't
change
much
their
inter
starts
to
strengthen
and
then
in
about
a
century,
or
so
it
reaches
a
quasi
equilibrium
state.
And
finally,
the
market
gets
stronger
by
about
five
severe
drops
prevent
equal
India
ocean
warming.
So
here
I
don't
have
time
to
talk
about
the
detail
of
detailed
mechanisms
for
the
a
mock
strengthening,
and
you
can
refer
to
this
paper.
We
published
last
year
for
more
details,
but
the
most
important.
C
We
cannot
really
see
the
warming
hole
and
instead
we
see
a
basin-wide
warming
and
what
interesting
feature
is
that,
even
though
the
SST
changes
a
lot
from
initial
to
final,
but
the
surface
wind
pattern
doesn't
change.
Much
so
it
tells
us
that
the
local
SST
change
over
the
Sapporo
North
Atlantic
is
relatively
insufficient
enforcing
the
local
wing
changes
as
compared
to
the
remote
forcing
from
the
trucker
oceans.
So
now
you
can
subtract
the
initial
from
the
final
and
get
the
net
impact
of
Enochs
traveling.
C
So
here
you
can
see
a
much
more
spatially,
coherent
structure
with
a
warming
Center,
the
south
of
Greenland,
and
that
is
due
to
the
a
Mach
strengthened
and
here
I
termed
them
as
the
fast
versus
the
slow
response,
maturity,
Indian,
Ocean
warming
and
they
operate
on
different
timescales
and
in
reality,
I'm.
The
since
Indian
Ocean
is
gradually
warming
and
the
slow
response
takes
about
multiple
decades
to
a
century
to
respond,
and
we
think
the
faster
response
to
Indian
Ocean
warm
is
probably
more
relevant
on
to
the
historical
period.
C
So
now,
let's
put
together
the
faster
response
with
observed
climate
trends
and
even
though
on
the
observe,
the
trends
are
much
noisier
due
to
internal
climate
variability.
But
the
most
important
features
like
the
service
weather
window,
strengthening
and
in
the
North
Atlantic
warming
hole
all
very
well
representation
warming,
and,
given
this
on
the
spatial
similarity,
it
motivates
us
to
take
a
further
look
and
to
quantify
how
much
of
the
observed
the
North,
Atlantic
warming
whole
can
be
explained
by
the
concurrently.
The
ocean,
warm
you're.
C
And
so
to
do
that
we
conducted
a
suite
of
sensitivity,
experiments
and
in
some
of
them
we
increase
the
warming
magnitude
over
in
the
ocean
to
two
degree,
and
then
we
could
in
the
ocean,
by
one
degree
and
in
some
experiments
we
impose
the
observed
temperature
anomalies
over
Indian
Ocean
and
also
over
the
tropical
Pacific
and
Atlantic
just
to
be
more
realistic.
And
after
doing
that,
you
will
see
a
really
tight
correlation
between
and
there's
not
a
trench
for
warming
hole
index
and
the
relative
Indian
Ocean
SST.
C
So
now
we
can
overlay
the
observe
the
values
and
on
top
of
that,
and
you
will
find
that
the
observed
the
reality
of
Indian
Ocean
warming
can
actually
explain
about
a
90
percent
of
the
historical
north
of
tragical
warming.
Hoax,
so
that's
basically
a
majority
of
the
historical
women
who
can
be
explained
by
in
the
ocean.
Warming
actually
is
the
based
on
Holland
model
as
faint,
so,
okay,
so
just
to
quickly
summarize,
we
find
out
in
here
ocean
warming
can
influence
the
South
Pole
and
North
Atlantic
SST
through
two
pathways
and
a
floor.
C
The
faster
response
it
can
enhance
and
surface
westerly
winds
in
the
South,
Pole
and
North
Atlantic
and
loud
will
give
rise
to
a
local
cooling,
looks
looking
very
similar
with
the
North
Atlantic
of
warming.
How
that's
observed
and
for
longer
times
goes
on
from
multi-decade
o
to
the
century.
The
Indian
Ocean
woman
can
straighten
the
a
mark
and
therefore
warmly
support
North,
Atlantic,
SST
and
I.
C
Think
in
the
ocean,
woman
is
a
really
nice
example
that
the
atmospheric
mechanism
and
the
oceanic
mechanism
for
the
North
Atlantic
warming
hole
are
not
necessarily
exclusive
of
each
other
and
that
they
can
operate.
At
the
same
time,
the
relative
importance
depends
on
which
time
period
at
which
time
scale
you're
looking
at
and
here
we
also
argued
that
the
observed
North
Atlantic,
a
warming
ho
the
majority
of
it
can
be
explained
by
the
and
the
spherical
changes
related
to
the
Indian
Ocean
warming
and
with
that
I
will
be
happy
to
take
any
questions.
Thank
you.
C
F
You
so
there
are
a
large
number
of
questions
in
the
chat.
Maybe
we'll
just
take
the
first
one,
and
then
you
could
try
and
answer
them
in
the
chat
after
that,
so
from
Paul
Kushner,
very
nice
talk
and
observations
has
an
increase
in
precipitation
over
the
Indian
Ocean,
accompanied
the
indian
ocean
warming.
I
asking
if
the
atmospheric
diabetic
heating
response
matches
your
picture
of
cause
and
effect.
C
Yes,
so
this
is
a
great
question
and
since
the
idea
that
indian
ocean
warming
can
induce
a
positive
nao,
there
has
been
a
lot
of
a
debate
on
whether
the
indian
ocean
has
really
been
warming
so
much
to
give
rise
to
the
latin
heat
release
over
that
region
and
I.
Think
it's
still
under
debate
and
the
president
are
also
looking
into
the
ICO
as
data,
and
we
need
to
see
a
increase
of
a
cloud
amount
but
just
qualitatively
and
we're
averaging
over
the
whole
tropical
ocean
basin.
But
that's
that
has
a
high
uncertainty,
so
yeah.
F
F
Yeah
yeah,
okay,
so
we'll
just
take
a
quick
five-minute
break
and
then
we'll
come
back
for
the
next
set
of
talks
at
the
same
time
as
planned,
originally
at
2:45
and
remember
to
voice
your
views
on
all
the
things
I
mentioned
at
the
beginning.
I'll
put
that
slide
up
again
and
repost
the
link
to
the
Google
Doc,
so
you
can
think
about
it
in
the
coffee
break,
Thanks.
F
E
E
E
E
E
E
E
E
E
Okay,
welcome
back
everybody
and
we're
ready
to
start
up
again
for
the
session
here
after
the
break
the
same
ground
rules
as
before.
Let
the
speakers
know
at
the
ten
minute
mark
that
they
just
have
a
few
minutes
left
so
for
our
first
speaker
is
Daniel
Toma,
and
so
you
can
share
your
screen.
That'd
be
great
and
also
unmute
yourself.
M
M
Cool,
so
thanks
for
the
session
so
far
has
been
great,
even
though
it's
virtual,
it's
so
exciting,
to
see
everyone
science.
So
today,
I'm
going
to
be
talking
to
you
about
my
recent
research
that
can
get
how
computing
anthropogenic
effects
caused,
distinct,
regional
impacts
on
extreme
wildfire
risk.
This
is
work
that
I've
been
doing
at
UC
Santa
Barbara,
with
Sam
Stevenson
and
Flavio
leaner
and
slow
cuts
who
are
at
NCAR
in
university
of
hawaii.
M
Erika
escaped
so
we've
seen
some
recent
unprecedented
global
wildfire
events
globally.
These
are
just
a
few
examples
of
these
events.
California
experienced
to
really
large
fires
in
2017
and
2018
and,
as
we
all
heard
about
probably
Amazon,
has
some
really
large
fires
in
2019
and
Australia
as
well
had
some
really
large
fires
in
the
past
year,
and
all
of
these
fires
have
some
devastating
effects,
especially
through
fatalities
and
economic
and
environmental
damages.
M
So
recent
studies
have
shown
that
increases
in
fuel
aridity
can
cause
larger
and
more
severe
fires.
So
the
study
from
abatzoglou
and
Williams
in
2016
showed
the
strong
relationship
between
forest
fire
area
and
fuel
aridity
in
the
western
US,
and
you
can
also
see
that
in
more
recent
years
there
have
been
larger
fire
as
well
as
much
dryer
fuels
in
this
region.
M
But
we
know
that
anthropogenic
forcings
can
have
competing
effects
over
the
globe,
so
greenhouse
gases
have
an
overwhelming
warming
effect
over
the
globe,
and
this
is
over
the
past
two
centuries,
while
aerosols
and
land-use
change
have
a
slight
cooling
effect,
and
we
also
know
that
these
effects
can
I
change
in
time
and
over
over
the
globe.
So
you
can
see
that
at
the
beginning
of
the
20th,
from
the
beginning
of
the
20th
century
to
the
end
of
the
20th
century,
aerosol
the
aerosol
effect
became
much
larger
in
magnitude,
but
also
the
space
show.
M
Set
of
simulations
twenty
member
greenhouse
gas,
fixed
greenhouse
gas,
ensemble
and
then
fifteen
members
for
a
fixed
biomass,
burning,
ensemble
and
five
members
for
LEDs
change,
fixed
land-use
change,
Ensemble-
and
you
can
read
more
about
these
in
these
publications,
I
believe,
there's
a
paper
describing
the
single
forcing
simulations
that
that's
in
a
revision
right
now.
So
hopefully
that
will
come
out
soon
so
to
quantify.
M
To
quantify
the
conditions
that
allow
for
fire
risk
and
spread,
we
use
the
fire
weather
index
and
this
fire
weather
index
accounts
for
daily
to
seasonal
variations
and
temperature
rainfall
relative
humidity
and
wind,
and
we
are
interested
in
when
these
when
the
fire
weather
index
is
extreme.
So
and
the
way
we
quantify.
This
is
using
the
90th
percentile
of
this
daily
fire
weather
index
for
every
location
across
the
globe.
M
So
to
quantify
the
impact
of
anthropogenic
forcing
on
the
risk
of
extreme
fire
could
extreme
fire
weather
conditions.
We
calculate
the
risk
ratio,
which
is
the
probability
of
extreme
fire
weather
with
a
given
forcing
divided
by
the
probability
of
extreme
fire
weather
without
that
forcing
so
when
the
risk
ratio
is
greater
than
1.
That
means
that
that
forcing
increases
the
risk
of
extreme
fire
weather
and
it's
when
it's
less
than
1.
It
means
that
that
for
singing
decreases
the
risk
so
for
the
current
period
that
we're
in
right
now,
2006
to
2029.
M
We
see
that
greenhouse
gases
have
a
generally
increasing
impact
on
extreme
fire
weather
risk.
In
some
regions,
such
as
the
Mediterranean
region
in
Southeast,
Asia
and
the
Amazon,
we
see
that
the
risk
the
risk
of
extreme
fire
weather
has
doubled,
Jiji
greenhouse
gases
alone,
and
we
see
that
whoops.
We
see
that
aerosols
have
an
opposing
effect
of
during
this
period,
so
in
many
regions
over
the
amazon
and
the
mediterranean
region
and
parts
of
africa,
we
see
that
air
assaults
actually
reduce
the
risk
of
extreme
fire
weather,
though
the
magnitude
is
not
as
high.
M
Yeah
and
here
the
shading
represents
the
ensemble
spread
across
the
CSM
large
ensemble,
so
you
can
see
that
greenhouse
gases
have
increased
extreme
fire
weather
risk
through
much
of
the
through
much
of
the
20th
century
and
continue
to
do
so.
I
till
the
end
of
the
21st
century.
On
the
other
hand,
aerosols
reduce
extreme
fire
weather
risk
through
much
of
the
20
20th
century,
but
more
recently
have
started
to
that
effect
has
started
to
become
much
smaller
and
has
also
aerosols
have
started
to
also
increase
extreme
fire.
M
So
I'll
show
you
here
in
a
little
insect.
If
what
happens
at
that
end
of
the
21st
century
is
that
greenhouse
gases
actually
cause
around
150
cause
extreme
fire
weather
risks.
You
actually
become
150
times
more
likely,
which
is
quite
a
startling
result
that
we
saw
so
we
wanted
to
dive
in
a
little
bit
and
ask
why
do
greenhouse
gases
cause
these
large
increases
in
extreme
fire
weather
risk?
M
So
we
isolated
the
impact
of
greenhouse
gases
on
each
variable
that
we
use
in
the
fire
weather
index,
so
here
I'm
showing
the
impact
of
greenhouse
gases
on
temperature.
At
the
end
of
the
21st
century,
you
can
see
that
greenhouse
gases
caused
an
increase
in
an
increase
in
temperature
I'm
during
this
period,
as
we
expect
Danielle.
M
M
So
we
can
look
to
see
how
the
anthropogenic
forcings
impact
this
time
of
emergence
and
we
find
that
aerosols,
aerosols
mostly
delay
this
time
of
emergence.
So
you
can
see
over
the
Amazon
parts
of
the
Mediterranean
and
parts
of
Africa.
You
see
that
the
sum
of
emergence
is
delayed
between
around
10
to
20
years.
M
So
what
I'm,
showing
here
are
all
these
regions
that
are
stippled
show
that
the
time
of
emergence
only
occurs
when
you
have
that
forcing
and
would
not
occur
if
we
fixed
greenhouse
gases
at
19:20
levels,
so
I'll
stop
there
and
I'll
leave
my
confusion
side
up
here
and
I'll.
Take
any
questions.
Thank
you.
Ok,.
M
I'm,
not
really
sure
I
was
actually
hoping.
You
know
if
you
were
all
in
person,
someone
would
kind
of
know.
What's
going
on
I'm
over
the
Amazon,
with
the
changes
in
wind
and
relative
humidity,
it
seems
to
really
pop
up
there
and
we
were
thinking
of
trying
to
dig
in
a
little
bit
and
see
what's
happening
over
the
Amazon,
because
that's
really
the
only
region
that
occurs
in
you
all
other
regions,
kind
of
stay
below
around
like
well
sure,
like
a
three
times
increase
or
four
times
increase
at
a
maximum
okay.
M
M
M
E
M
N
Right,
sorry,
okay,
so
yeah,
my
name
is
Haruki
and
I'm,
and
so
today,
I'm
gonna
be
discussing
some
work.
I've
been
doing
at
the
University
of
Toronto,
along
with
collaborators
at
the
Grand
in
Canada,
and
incur
looking
at
the
regional
drivers
of
Sahel,
precipitation
response
to
anthropogenic
aerosols
and
so
in
particular,
we're
looking
at
the
20th
century,
drought
and
recovery
of
Sahel
precipitation
that
occurred
in
observations
and
so
on.
N
The
left
here
you
can
see
four
different
gridded
precipitation
data
sets
where
you
see
this
large
multi
dakedo
swing,
going
from
a
wet
period
in
the
50s
descending
into
a
drought
in
the
80s
and
a
recovery
thereafter,
and
so
this
obviously
had
pretty
severe
impacts
on
the
local
population.
As
noted
in
this
1984
New
York
Times
article,
which
is
titled
in
Africa,
a
natural
disaster
made
worse
by
man
and
so
in
this
case,
they're
talking
about
various
political
mismanagement
that
exasperated
the
famine.
N
But
we
can
also
wonder
if
that's
if
that
headline
is
true
from
the
climatological
perspective
as
well,
and
so
in
order
to
look
at
this,
what
we've
done
is
where
we've
analyzed
two
large
ensembles
in
CS,
m1
and
Kenya,
some
two,
and
so
these.
As
mentioned
previously.
These
large
ensembles
include
subsets
of
simulations
which
can
be
used
to
isolate
the
effect
of
at
the
bo
genic
aerosols.
N
You
know
in
or
in
terms
of
looking
at
why
these
models
underestimate
the
multidecadal
variability.
You
can.
We've
looked
at
some
emmab
simulations
where
observed,
SS
T's
are
applied,
and
it
seems
as
though,
in
the
case
of
chem
5,
when
you
impose
observed
SS
T's
the
match
between
the
models
and
the
observations
improves
substantially
following
the
case
of
Ken
m4,
which
is
the
atmosphere
model
for
Kenya,
sim
and
imposing
observed.
Ssds
actually
doesn't
really
change
the
variability
or
on
a
multi-decade
timescale
of
much
at
all.
N
So
clearly,
the
reason
for
the
underestimation
or
the
model
errors
is
different
between
these
two
models,
but
going
back
to
the
main
point
of
this
talk,
so
in
order
to
understand
how
aerosols
or
any
external,
forcing
effect
Sahel
climate,
you
can
and
divide
the
total
coupled
climate
response
into
two
components
that
conceptually
the
first
is
the.
What
we're
calling
the
direct
atmospheric
response,
which
is
the
atmosphere
and
lands
response
that
is
directly
due
to
the
radiative,
forcing
as
well
as
any
rapid
cloud
changes.
N
This
is
also
referred
to
as
the
fast
response,
but
clearly
this
well.
What
what
you
call
fast
and
slow
depends
a
lot
on
what
you're
looking
at
and
the
second
is
the
ocean
mediated
response,
which
is
the
response
of
the
atmosphere
and
land
to
forced
changes
and
assess
ease
and
sea
ice,
and
so
many
past
proposed
mechanisms
for
precipitation
change
in
the
Sahel.
It
can
sort
of
fall
in
these
two
categories.
N
For
example,
in
the
case
of
the
direct
atmospheric
effect
or
the
early
hypothesis
of
Shani
posited
that
increased
local
reflectance
caused
downwelling
and
drying
in
his
case,
he
was
talking
about
surface
albedo
due
to
land
use
change,
but
a
similar
mechanic
might
also
apply
for
a
reflectance
due
to
air
assaults.
There's
also
recent
work.
N
We
also
did
instead
of
Kenan
fort,
but
we're
focusing
on
Kenneth
cam
5
here,
for
obvious
reasons,
and
so
in
order
to
obtain
the
direct
atmospheric
response,
we
change
aerosol
emissions
while
keeping
SST
and
sea
ice
fixed
and
in
order
to
obtain
the
ocean
mediated
response.
We've
perturb,
the
a
GCM
SST,
is
using
the
large
ensemble
aerosol
force
anomalies
and
keeping
emissions
fixed,
and
we
do
this
for
in
order
to
look
at
two
periods,
so
the
drying
period,
the
70s
50s
and
the
recovery
period
mm
70s.
N
And
so
you
can
see
the
results
here
for
camp
fight
where
we
have
going
from
left
to
right.
The
total
direct,
atmospheric
and
ocean
mediated
responses
for
the
two
periods,
with
the
early
drying
period
on
top
and
the
recovery
period
on
bottom,
and
so
you
can
see
that
the
total
drying
signal
for
the
early
period
appears
to
be
mostly
due
to
the
direct
atmospheric
response.
N
While
the
later
period
recovery
is
mostly
ocean,
mediated
and
so
there's
a
couple
puzzling
aspects
of
this
response
or
unexpected
ice,
and
so
the
first
is
that
there's
a
notably
weak,
70s,
50s
ocean
mediated
response
and
spied
a
pretty
substantial
SST
change.
And
so
we
hypothesized
that
this
is
due
to
cancelling
castling
effects
from
anomalies
in
different
ocean
basins.
And
so
in
order
to
check
that
we've
run
an
additional
set
of
shorter,
a
GCM
simulations
where
we
determined
the
ocean
mediated
response
to
SST
anomalies
in
different
basins.
And
so
here
we
have
the
Atlantic.
N
And
so
here
we're
looking
at
the
Atlantic
Indian
Ocean
and
the
rest
of
the
world
oceans.
And
we
just
mostly
do
the
Pacific.
And
so
you
can
see
here
the
SST
anomalies
for
the
two
periods
we're
in
the
early
period.
You
have
northern
hemisphere
dominated
cooling
as
well
as
you
can
see
a
bit
of
a
cooling
hole
and
the
North
Atlantic
and
then,
in
the
later
period.
N
We
indeed
see
that
there's
a
increase
due
to
the
Pacific
SSTs
and
a
decrease
in
precipitation
due
to
Atlantic
SS
T's,
which
is
sort
of
that
cancellation
that
we
hypothesized
previously
and
then
in
the
later
period
that
mm
70s.
We
then
find
that
the
recovery
is
mainly
due
to
Pacific
SST
anomalies
rather
than
warming
in
the
North
Atlantic,
for
example.
Although
that
does
have
a
small
effect
and
then
a
second
puzzling
campfire
result
is
that
there
is
a
direct
atmospheric
drying
in
the
later
period
mm
70s.
N
In
spite
of
large
decreases
in
European
and
North
American
emissions
here
in
the
bottom
middle
panel,
and
so
again,
we've
taken
a
similar
approach
and
we
next
isolate
the
direct
atmospheric
response
into
the
response
to
regional
emissions
from
Asia
and
Europe
and
Europe,
which
we
presume
are
the
main
emission
sources
that
drive
climate
change
in
Africa.
And
so
you
can
see
the
sulphate
burden
anomalies
for
the
full,
direct
atmospheric
experiments
and
the
new
vision
and
European
emission
simulations
and
I
guess.
N
One
notable
thing
is
that
it
appears
that
most
of
the
sulphate
burden
anomaly
over
northern
Africa
is
actually
is
due
to
European
emissions
rather
than
local
emissions
over
Africa
as
well.
In
the
case
of
Asian
emissions,
the
burdens
appear
to
be
much
more
localized
and
there's
not
much
of
a
change
locally
over
Africa.
N
And
so
when
we
look
at
the
results
here,
we
have
the
full
direct
atmospheric
response
on
the
left
and
in
the
middle
we
have
the
Asian
emissions
and
the
right
European
emissions,
and
so
as
we
as
a
previous
work
might
have,
as
the
previous
workgroup
I
mentioned
showed.
We
do
indeed
see
that
rising
Asian
emissions
causes
drying
in
the
coastal,
West
African
region
and
the
mm
mm
70s,
in
spite
of
relatively
little
direct
I
guess
forcing
over
the
region,
and
so
it
will
be
interesting
to
see
if
we
see
similar
circulation
responses.
N
Right
awesome
and
so
and
I
guess
rather
puzzlingly
again,
there's
a
lack
of
response
to
the
either
emission
region
for
the
seven
east
50s
either,
and
so
this
could
be
just
a
matter
of
a
lack
of
sample
size.
Maybe
we
need
to
run
the
simulations
out
longer
or
it
could
be,
because
the
drying
is
due
to
local
African
emissions,
perhaps
black
carbon
or
even
North
American
emissions,
which
we
haven't
looked
at
yet
okay.
N
Although
I
guess
attribution
is
pretty
difficult
in
this
case
and
for
the
drying
period,
the
drying
is
primarily
a
direct
atmospheric
response,
but
based
on
our
regional
regional
emissions
simulations
the
source
is
as
yet
unclear
and
the
lack
of
ocean
immediate
effect
is
due
to
cancellation
from
Atlantic
and
Pacific
SST
anomalies
and
then
in
the
later
period,
there's
a
recovery
in
precipitation
that
is
primarily
driven
by
the
ocean
mediated
response,
and
this
continued
direct
atmospheric
drying
that
is
due
to
Asian
emission
increases
yeah.
So
that's
it.
Thank
you
and.
E
E
N
Yeah
I
guess
it's
so
well,
so
I
guess
for
one
I'd
expect
there
to
be
more
of
a
response
to
European
emissions
in
both
periods,
because,
as
you
might
remember,
there
is
this-
you
know
pretty
strong
change
in
sf4
burdens,
that's
linked
to
European
emissions
over
the
region.
So
it's
not
really
clear.
Why
are
at
least
at
first
glance,
to
me
it's
not
really
clear
why
there
isn't
much
of
a
precipitation
change
being
caused
by
these
emission
changes.
N
It
could
yeah,
and
so
perhaps
it's
a
matter
of
looking
at
different
emissions
from
different
regions
or
I
mean
these
are
relatively
weak
signals
over.
You
know
these
are
pretty
small
periods
as
well
short
periods
as
well.
So
perhaps
it's
just
a
matter
of
extending
the
time
size
simulations
to
get
more
sample
size,
yeah.
O
Hopefully,
you
can
now
see
my
screen
yeah
there
we
go
and
so
appreciate
the
opportunity
to
talk
about
some
work
that
I've
been
doing
recently
in
collaboration
with
my
colleague
up
at
CSU,
that
is
lantau
son
and
also
with
Katie
Dagon
at
NCAR.
There's
a
number
of
other
names
on
this
opening
slide.
I
want
to
thank
all
of
these
individuals.
O
This
work
is
really
benefiting
from
discussions
with
with
all
of
them
and
I'm,
going
to
start
to
kind
of
frame
this
topic
and
provide
some
background
with
with
a
curve
that
needs
no
introduction
to
this
particular
audience.
But
I
have
it
up
here,
because
it's
a
reminder
to
all
of
us
that
atmospheric
concentrations
of
co2
are
continuing
to
increase
at
an
alarming
rate,
and
just
last
month
it
reached
a
seasonal
peak
of
in
excess
of
417
parts
per
million
by
volume
at
maan
Aloha.
O
This
is
not
only
the
the
highest
peak
recorded
in
62
years
of
direct
observations
and
higher
by
about
two
and
a
half
ppm
than
last
year
at
this
time,
but
of
course
it's
the
highest
level
recorded
in
human
history.
In
fact,
the
last
time
that
co2
was
at
this
level
in
the
atmosphere,
the
global
mean
temperature
was
somewhere
between
about
2
and
3
degrees
warmer
than
pre-industrial
times
and
global
mean
sea
level.
Pressures
were
15
to
25
meters
higher.
O
These
these
basic
aspects
of
climate
change
this
this
really
led
to
a
positive
step
forward
about
five
years
ago
or
four
and
a
half
years
ago,
at
the
United
Nations
Climate,
Change
Conference,
and
that
led
to
the
Paris
agreement,
where
there
was
an
overall
agreement
to
try
to
limit
the
warming,
to
quote
well
below
unquote,
two
degrees
relative
to
pre-industrial
temperatures.
To
avoid
some
of
these
worst
impacts
and,
as
I
said,
it's
a
very
positive
step.
O
O
The
warming
would
be
three
or
maybe
four
degrees
by
the
end
of
the
21st
century,
and
it's
in
this
context
that
I
like
to
think
about
geoengineering
or
if
you
prefer,
the
term
climate
intervention
research,
because
I
think
it's
incredibly
important
that
we
understand
if
we
do
have
viable
additional
measures
too.
If
the
world
would
decide
to
to
try
to
reduce
climate
change
impacts
through
these
other
measures.
Now
there
has
been
a
lot
of
climate
intervention
techniques
proposed.
This
is
from
an
older
study
from
the
Royal
Met
Society.
O
If
you
follow
this
kind
of
literature,
you
can
see
that
it
falls
into
two
categories:
carbon
dioxide
removal,
as
well
as
solar
radiation
management.
The
axes
on
this
plot
show
a
measure
of
effectiveness
versus
affordability,
and
so
you'd
want
to
be
somewhere
up
here
in
the
upper
right,
and
so
indeed,
one
of
the
approaches
that
has
received
considerable
attention
is
the
ability
to
increase
the
albedo
of
the
planet
through
the
injection
of
aerosols
into
the
stratosphere,
and
that's
very
much.
O
The
topic
of
what
we're
looking
at
here
today,
so
our
objective,
is
to
try
to
look
at
a
scenario
of
stratospheric,
aerosol
geoengineering
and
look
comprehensively
at
the
climate
impacts.
We're
focusing
on
the
North
Atlantic
sector.
I
don't
have
time
to
go
into
too
much
detail
today,
but
that's
the
basic
premise
of
our
work
and
the
tool
that
we're
using
is
a
very,
very
useful,
large
ensemble
of
geoengineering
simulations
that
were
performed
at
in
car
a
couple
of
years
ago
and
are
available
for
community
analysis.
They're
called
the
blends
ensemble
again.
O
This
is
with
CSM
version.
One
utilizing
wacom
the
whole
atmosphere.
Community
climate
model
was
the
atmospheric
component.
I
can't
go
into
the
details,
but
the
strategy
is
called
a
feedback.
Control
strategy
is
adjusting
the
optimal
injections
to
meet
several
climate
goals
and
those
climate
goals
are
not
only
maintaining
global,
mean
surface
temperatures
at
20:20
levels,
but
also
preserving
the
inner
hemispheric
in
the
equator
to
pole,
service
temperature
gradient.
O
So
there's
a
20
member
ensemble
of
these
geoengineering
simulations
and
in
this
talk
to
look
at
the
impact
of
this
geoengineering
approach
over
the
North
Atlantic
we're
comparing
this.
This
ensemble
average
of
these
20
runs
with
simulations
with
the
exact
same
configuration
of
the
model,
capturing
so-called
present-day
climate,
from
2010
through
2029.
O
This
leads
to
a
warming,
as
you
can
see
in
the
left
diagram
here
of
lower
stratosphere
temperatures
by
about
6
to
10
degrees
by
the
end
of
the
21st
century
compared
to
present-day
climate,
and
this
in
turn
increases
the
equator
to
pole,
temperature
gradient,
which
causes
a
strengthening
of
the
polar
Jets
over
both
the
northern
and
the
southern
hemispheres,
and
you
can
see
that
on
the
right
now.
These
changes,
in
so
no
mean
winds,
are
of
most
relevance
to
northern
hemisphere,
storm
tracks
and
stratosphere
troposphere.
O
Coupling
and
they're
reflected
in
the
stratosphere,
at
least
by
a
trend
toward
the
positive
phase
of
the
northern
annular
mode,
and
you
can
see
that
very
clearly.
You
can
also
see
there's
a
vertical
structure
to
the
trend
in
the
NAMM
or
the
change
in
the
dam
by
the
end
of
the
century,
whereas
if
you
look
at
the
index
of
the
NAMM
at
the
surface
is
suddenly
very
weakly
positive
and
the
main
thing
I
want
to
look
at
in
today's
talk
is
try
to
explain
why.
That
is
the
case.
O
If
you
look
at
how
this
is
manifested
in
terms
of
surface
climate,
here
we're
looking
at
the
change
in
1,000
Ekta
Pascal
height
by
the
end
of
the
century
and
the
geoengineering
runs
compared
to
the
control
of
the
present-day
climate
simulations.
You
see
consistent
with
a
stronger
stratospheric,
polar
vortex.
You
have
lower
than
average
pressures
over
the
Arctic
and
over
the
sub
polar
North
Atlantic.
O
But
if
you're
familiar
with
this
kind
of
a
fingerprint
of
a
stronger
stratospheric
dam,
you
might
expect
to
see
higher
than
average
or
a
positive
change
in
thousand
hectopascal
height
over
the
subtropical
North
Atlantic
and
extending
across
parts
of
Europe.
You
see
some
hint
of
that,
but
it's
not
very
strong
and
I'll
come
back
to
that
later.
In
the
talk
to
show
you
kind
of
how
robust
this
is
in
terms
of
the
seasonal
cycle.
O
Again,
this
is
comparing
the
20
member
ensemble
means
you
can
see
if
you
focus
on
the
sub
:
North
Atlantic,
and
look
at
daily
sea-level
pressure
in
the
in
the
Glen
simulation.
You
have
lower
sea
level
pressures
from
about
mid
October
through
the
end
of
the
spring
season.
So
that
is
why,
in
this
presentation,
we
focus
on
the
extended
extended
boreal
winter
season
of
November
through
April.
O
So
if
you
think
about
these
changes
in
circulation,
that
has
impacts
on
the
on
the
wind
fields
on
the
storm
tracks,
that's
reflected
by
changes
in
surface
temperature
and
precipitation
that
are
shown
here,
changes
in
surface
temperature
that
are
dynamically
consistent
with
the
changes
in
subpolar
pressure
that
I
showed
earlier.
You
see
a
clear
indication
again
consistent
with
kind
of
a
positive
name
or
a
positive
nao
of
a
dipole
and
precipitation
over
Europe
to
just
show
you
very
quickly
how
robust
of
a
signature
this
is
across
all
the
ensemble
members.
O
These
are
histograms,
there's
400
values
here,
plotting
all
possible
combinations
between
the
20
member
Glen's
ensemble
and
the
20
member
control
ensemble,
and
you
can
see
in
Amman.
Almost
all
of
these
simulations
Northern
Europe
tends
to
get
wetter
in
the
in
the
geoengineering
runs,
and
southern
Europe
tends
to
get
drier.
Katie
Dagon
is
doing
some
very
interesting
work,
expanding
beyond
just
looking
at
physical
climate
and
looking
at
terrestrial
ecosystem
impacts
as
well.
I'm
only
going
to
show
this
very
quickly.
O
This
is
the
change
in
the
end
of
the
century,
just
looking
at
the
early
spring
season
march,
through
April
and
looking
at
NPP
or
net
primary
production
in
general.
The
pattern
on
the
left
is
consistent
with
what
you
might
expect
as
a
result
of
the
circulation
changes.
But
if
you
linearly
remove
those
circulation
changes
and
look
at
the
residual
you'll
see
that
indeed
the
total
signal
is
indeed
dominated
by
the
so
called
residual
term.
O
This
is
just
another
way
of
saying
that
co2
fertilization,
that's
the
primary
effect
because
remember
in
the
G
no
engineering
runs
there
run
still
under
an
RCP
eight-point-five
scenario,
so
co2
is
still
increasing
in
the
atmosphere,
so
it
began
to
wrap
up
the
talk.
I
want
to
spend
just
a
couple
of
more
minutes,
then
trying
to
diagnose
in
more
detail
trying
to
kind
of
understand
the
details
of
this
surface
signature
in
the
Atlantic
sector,
because
this
is
very
important
for
understanding
what
the
regional
impacts
of
geoengineering
might
be.
O
If,
if
you
think
about
the
change
in
sea
level,
pressure
or
a
thousand
hectopascal
height
that
you
would
expect
to
be
associated
with
a
more
positive
nao
or
a
more
positive
BAM,
it
would
look
so
thing
like
this
and
so
we're
trying
to
understand
the
the
differences
between
the
plot
on
the
left
and
the
plot
on
the
right,
especially
in
terms
of
the
absence
of
the
higher
sea
level
pressures
or
heights
over
the
Iberian
Peninsula
and
the
middle
latitudes
of
the
Atlantic.
So
there'd
about
twelve
minutes.
O
Great
I
think
I'll
finish
up
on
time,
Jerry,
no,
no
virtual
hook.
Hopefully
so
we
took
advantage
of
these
very
nice
experiments
that
Isla
Simpson
did.
These
are
idealized
stratospheric
heating
experiments.
Just
think
of
this
that
if
stratospheric
heating,
because
of
the
aerosol
injection,
was
the
only
game
in
town,
what
would
the
response
be?
And
this
is
what
the
results
show.
So,
if
you
look
at
the
diagram
on
the
right,
you
can
see
that
indeed,
you
get
a
stronger
middle
latitude,
height
signal,
height,
increased
signal.
O
Then
you
get
and
then
in
the
Glen
simulation,
and
that
is
because
other
things
are
going
on.
If
you
look
at
the
sea,
surface
temperature
and
the
sea
ice
fields
by
the
end
of
the
century,
in
Glens,
you
see
that
there's
a
very
pronounced
warming
of
the
North
Atlantic,
a
very
significant
reduction
in
sea
ice.
O
This
is
largely
due
to
a
very
strong
upward
trend
in
the
strength
of
the
a
Mach
that
we
think
it's
very
strongly
related
to
the
initial
state
of
the
model
when
these
simulations
were
kicked
off
so
I
think
these
results
are
probably
pretty
sensitive
to
the
state
of
a
Mach.
So
lantau
has
done
some
nice
experiments,
then
to
say:
okay,
what
is
the
influence
of
these
SSD
and
sea
ice
changes?
O
So
if
you
conduct
these
experiments
that
are
outlined
in
the
top
and
look
at
the
atmospheric
response
to
this
warming
of
the
North
Atlantic,
that's
this
third
panel.
Now,
while
the
signals
are
relatively
small,
the
key
thing
is,
if
you
add
together
the
heating
and
the
SST
response,
you
indeed
get
a
response.
That's
much
more
similar
to
the
Glen's.
So
with
that
I
will
stop.
O
I
have
some
general
conclusions
at
the
top
that
have
kind
of
grayed
out
the
key
things
that
I've
shown
here
are
in
black
at
the
bottom
and
I
just
want
to
point
out:
it's
not
just
the
stratospheric
heating,
but
it's
this
coupled
response,
and
in
this
case
in
particular,
the
warming
of
the
North
Atlantic,
is
really
affecting
the
details
of
the
overall
response.
So
thank
you
very
much
for
your
attention.
All.
E
Right
thanks
Jim
have
a
question
from
Kevin.
He
asks
about
the
big
issue
with
respect
to
solar
radiation
management
as
effects
on
the
water
cycle,
and
is
that
it's
I'm
interpreting
this
to
mean
that
he
says:
does
this
go
beyond
circulation,
changes
or
I?
Think
that
means
are
these
more
important
than
circulation
changes.
O
Well
so
Iowa's
paper
that
you
can
kind
of
see
in
gray,
there
really
looks
it's
very
nice
paper
documenting
the
overall
hydrological
response
in
these
Glynn
simulations.
You
know,
overall
it's
at
as
sort
of
a
global
average.
You
see
the
changes
in
rainfall,
sort
of
decrease
changes
in
rainfall
compared
to
something
like
an
RCP
8.5
simulation,
but
the
regional
changes
indeed
are
very,
very
dependent
on
the
changes
in
atmospheric
circulation
and
that's
what
we're
trying
to
focus
on
on
this
relatively
small
part
of
the
globe,
but
significant
part
of
globe.
O
E
O
Know
I
haven't
I,
haven't
looked
at
the
interactive
chemistry
in
these
simulations,
so
I'm
going
to
defer
to
climb
to
yoga
or
I'll,
or
someone
like
that
who
may
have
looked
at
that,
but
I
mean
that
that
is
a
concern.
Of
course.
That
is
one
of
the
negative
consequences.
If
you
will
of
this
kind
of
stratospheric,
aerosol
injection
is
a
loss
in
ozone,
but
we
have
not
looked
at
the
interactive
chemistry
in
these
particular
simulations.
O
E
D
D
E
E
J
D
D
Allow
us
to
look
across
models
that
aren't
quite
consistent
and
enforcing
protocols
that
aren't
quite
consistent
and
what
I
want
to
do
is
kind
of
go
to
the
limits
of
how
a
pattern
scaling
works
or
take
a
naive
approach,
see
see
how
that
sort
of
a
strawman
approach
and
see
how
far
we
can
go.
So,
let's,
let's
just
sort
of
start
with
a
key
point
here-
that
when
we
look
at
various
couple
models
that
have
been
run
to
stimulate
sea
ice
laws.
D
So
when
you
impose
the
ice
loss
on
a
couple,
doujin
atmosphere
model,
you
tend
to
see
what
clarinha
desert
is
called
a
mini
global
warming,
and
this
is
a
figure
from
James
greens
review
on
this
topic,
looking
at
various
coupled
models,
and
but
most
of
these
models
exhibit
in
response
to
sea
ice
loss
in
isolation.
A
certain
amount
of
whoops
just
see
if
I
can
get
a
laser
pointer
here:
okay,
good,
a
certain
amount
of
polar
amplification,
a
lot
of
polar
amplification,
but
also
typically,
a
certain
amount
of
tropical
warming.
D
And
so
as
many
global
warming
is
a
cross
coupling
between
the
response
in
temperature
and
in
various
other
fields.
I'll
show-
and
so
there's
you
can
see
here.
There's
several
simulations
and
what
we've
been
doing
in
this
work
is
trying
to
gather
as
many
of
these
types
of
simulations
together
and
the
concept
I
want
to
introduce
is
something
called
model
experiments
alright.
So
we
have
different
models
of
different
experiments
and
the
idea
is
that
we
have
to
consider
the
inconsistencies
in
both
models
and
the
way
they've
driven
to
look
at
the
available
data.
D
These
models
are
very
expensive
to
run,
so
we
thought
we'd
try
to
squeeze
as
much
value
as
we
could
out
of
them.
The
CSM
series
shown
here
this
is
showing
sea
ice
area
in
the
CSM
large
ensemble
forced
through
to
2100
additional
simulations
that
Russell
blackboard
carried
out
for
his
thesis
work
where
we
change
the
albedo
and
by
reducing
the
albedo
of
sea
ice,
actually
induced
sea
ice
melt.
D
We
see
that
they
have
certain
like--that's
features
in
common
and
typically,
what
we
have
are
experiments
in
which
this
sort
of
traditional
global
warming,
greenhouse
warming,
that
warms
the
earth
and
also
the
ocean,
and
also
reduces
sea
ice
loss
and
then
we're
comparing
that
to
simulations
in
which
we
induced
sea
ice
loss.
Okay,
so
there's
a
lot
of
Arctic
sea
ice
loss
here
and
not
a
little
bit
of
low
latitude
warming
and
then
warming
with
a
bit
of
sea
ice
loss
all
right.
D
What
we
have
are
the
outputs.
The
responses
from
different
models
or
response
is
the
difference
between
two
of
these
model
experiments.
So
one
response
that
kind
of
classical
one
would
be.
The
response
in
atmospheric
so
mean
temperature
to
our
CP
8.5,
forcing
projected
from
the
large
ensemble
right
another
would
another
experiment
would
be
from
CS
m
again.
This
changed
now
Vito
inducing
some
polar,
a
lot
of
polar
warming
and
a
little
bit
of
tropical
warming.
D
So
the
idea
of
the
pattern
scaling
is
to
extract
those
parts
of
the
responses
that
are
coherent
with
sea
ice
loss,
as
if
the
tropics
didn't
change
and,
conversely,
can
coherent
with
tropical
change
as
if
the
sea
ice
didn't
it
didn't
change,
and
so
what
you
see
here
is
by
this
decomposition.
We
wipe
out
the
signature
of
ice
loss
in
simulations
and
we
can
get
as
a
pattern
of
warming.
That's
mainly
confined
to
the
tropical
upper
tropospheric,
also
extends
into
the
Arctic
mid
troposphere.
D
And
this
what
we
see
here,
the
lower
right
is
the
sensitivity
to
sea
ice
loss
really
confined
to
a
pure
polar
amplification
signal.
So
we've
repeated
these
this
analysis
and
what
we're
trying
to
do
is
understand,
what's
robust
in
both
the
atmosphere
and
ocean
and
how
far
we
can
take
it.
So
those
that
that's
the
kind
of
research
question
for
this
particular
paper,
so
I'll
just
kind
of
skip
to
the
main
results.
D
So
what
I'm,
showing
you
here
are
the
results
of
this
pattern,
scaling
for
all
the
models
that
we
looked
at
and
the
we're
starting
with
zooming
temperature
and
the
left.
So
that's
it
for
the
ensemble
mean
our
multi
model
mean
of
the
five
model
experiment
sets
we
looked
at
and
the
top
shows
the
sensitivity
to
ice
loss
and
the
bottom
shows
the
sensitive
little
attitude.
Warming.
Ok,
the
hatching
indicates
that
four
of
the
five
models
at
least
agree
in
sign,
and
so
what
we
see
when
we
do
this
kind.
D
B
composition
are
some
well-known
features
of
the
response
of
the
tug-of-war,
the
opposition
between
tropical
warming
and
polar
amplification.
So
here,
for
example,
we
see
that
in
response
to
the
ice
loss,
as
if
the
tropical
warming
didn't
happen,
we
have
an
equatorward
intensification
of
the
Jetstream
weakening
here
and
we
get
kind
of
the
opposite
response
from
from
low
latitude
warming
as
well
as
this
struck
tropical
westerly
response
that
we're
familiar
with.
We
look
at
surface
temperature.
D
We
see
a
pattern
of
response
here,
including
stronger
warming
in
the
eastern
of
East
of
North
America,
a
little
bit
of
cooling
in
in
earlier
Asia,
and
then
this
isn't
to
some
extent.
The
pattern
is
is
similar,
but
also
counteracted
to
some
extent,
by
the
response
to
a
little
latitude
warming,
where
we
have
a
stronger
warming
over
Eurasia,
okay
and
even
a
hint
of
cooling.
Although
this
isn't
robust
across
the
models
in
sea
level
pressure,
we
can
see
that
there's
an
effective
response,
something
like
Jim
just
described.
D
That's
consistent
with
this
pattern
of
cooling,
so
anti
cyclonic,
a
typically
response
over
the
northern
Siberia
and
a
bit
of
an
intensification
of
the
Aleutian
low,
although
it's
not
robust
across
the
models
and
kind
of
an
opposite
response.
Consistent
what
we
see
here
in
the
Eastern
sorry
over
Siberia,
and
even
when
we
look
at
the
precipitation
response,
we
see
really
interesting
complementarity
in
the
different
patterns:
okay,
so,
for
example,
to
response
to
sea
ice
loss.
D
D
So
that's
in
the
atmosphere
now
what
I'm
going
to
show
you
next
is
the
ocean
response
and
I'm
going
to
show
you
in
a
different
way,
I'll
be
showing
you
individual
models
to
give
a
sense
of
how
similar
and
different
so
we'll
start
with
the
response
and
SS
T's
across
the
model
set.
So
we
have
five
models
we
looked
at
and
what
you
can
see
in
response
to
the
sensitivity
sea
ice
loss
consists,
of
course,
of
course,
Arctic
warming
and
warming.
D
That
extends
well
beyond
the
ice
margin
to
the
mid
latitude
oceans
as
well
as
some
anomalous
cooling.
That's
that's
consistent
with
the
kind
of
circulation
patterns
we're
seeing
and
that's
shared
across
the
models.
Alright,
so
we
a
lot
of
all
the
models,
see
a
similar
pattern
except
in
the
North
Atlantic,
and
you
can
scan
here
and
look
at
the
similarities
and
differences
in
response
to
the
latitude,
the
sensitivity.
There
is,
of
course,
a
broad
warming
powder
with
intensified
warming
in
the
West
Pacific
and
the
West
Atlantic.
When
you
look
it's
the
sea
surface,
salinity
response.
D
D
Sets
here
are
regions
that
were
defined
by
previous
work,
Labrador,
sea
and
south
of
Iceland,
the
Nordic
seas,
and
you
can
see
that
in
each
of
these
different
simulations,
this
is
just
under
control,
simulations
they're,
very
different
pictures
of
where
convection
is
occurring
and
how
deep
it
is.
So
we
control
simulations
are
quite
inconsistent
and
also
these
models.
We
made
no
attempt
to
sort
of
unify
the
models.
D
D
Yeah
I'm
just
about
done
all
right
and
then,
if
we
move
over
to
the
a
mock
the
response
and
aim
up
across
these
simulations,
all
different
they're
all
done
differently.
All
these
pictures
are
scaled
by
the
same
amount
of
sea
ice
loss,
but
otherwise
they're,
quite
you
they're
quite
similar,
and
the
main
point
here
is
that
each
model
features
its
own
distinctive,
a
mock
response
and
each
protocol
is
different
as
well
and
the
role
of
sea
ice.
The
correspondence
between
these
different
pictures
is
is
quite
different.
D
So,
for
example,
here's
two
versions
of
the
N
car
model
at
CSM,
one
with
cam
5
physics
and
welcome
with
camphor
physics
and
it's
the
same
ocean
component
and
and
what
we're
seeing
is
that
the
there's,
a
similar
reduction
in
the
strength
of
the
a
lock,
but
the
role
of
sea
ice
in
that
is
at
least
as
diagnosed
here-
is
quite
different.
Alright,
so
sea
ice
loss
is
playing
kind
of
Ally,
a
leading
role
in
the
amok
in
this
in
this
particular
simulation,
whereas.
I
D
The
previous
plot,
it
seemed
to
play
less
of
a
role,
so
that
brings
me
to
the
end
just
to
talk
about
where
we
are
with
this.
So
the
main
point
is
that
pattern
scaling
gives
us
a
way
of
thinking
about
both
the
tropics
and
the
Arctic
at
the
same
time,
and
what
we
see
is
the
you
know.
Primary
message
of
this
analysis
is
a
way
of
quantifying
this
tug-of-war,
the
negative
feedback
of
sea
ice
loss
on
the
circulation
response.
D
We
see
precipitation
signals
that
extend
from
the
tropics
into
the
Arctic
and
that
we
think
are
really
important
to
pull
out
of
greenhouse
warming
process
and
also
a
salinity
salinity
changes
in
the
in
the
ocean
that
are
less
kind
of
that
are
quite
non-local
and
complicated,
but
seem
to
become
in
response
to
tropical
warming.
I
think
I've
said
this
already,
and
hopefully
I've
convinced
you,
and
so
where
we
are
now
is
to
say
that
we
can't
really
proceed
to
understand
these
other
persistent
problems.
D
The
deep
ocean
responds
in
the
North
Atlantic
subpolar
oceans
without
doing
more
coordinated
and
model
experiments,
so
the
polar
amplification
map
which
was
discussed
at
the
PCW
today
is
is
one
mechanism
for
bringing
together
groups
to
do
coordinating
experiments,
and
I,
the
most
of
the
experiments
in
pmf,
are
focused
on
shorter
term
responses,
but
I
think
what
we
do
need
to
think
about
doing
more
coupled
to
longer
term
responses.
Experiments
as
well.
Thank
you
all
right.
D
What
we
used
as
a
proxy
for
convection
was
the
output
from
each
models.
So
actually
the
labels
are
bit
covered
up
here
by
so
I
can't
see
everything,
but
it's
the
maximum
depth
of
deep
convection
as
output
defined
by
each
model,
so
there's
a
there.
So
this
was
the
this
is
the
way
we
diagnosed
it,
and
it's
pretty
common
to
do.
One
of
the
issues
that
we're
still
trying
to
make
sure
we
understand
is
how
each
model
group
diagnosis,
this
particular
convection
depth
quantity.
So
it's
tied
in
with
convection
steam
question
yeah.
F
K
Okay,
I'm
switching
gear
and
talk
about
fresh
water
event
in
the
North
Atlantic
back
in
1970s
I'm,
who
came
Steve,
Yeager
and
Golconda
nervous
chuckle
ooh
are
my
co-author
of
the
study.
This
is
part
of
a
highlight
resin
project
funded
by
goe.
I
would
like
to
thank
our
parents,
artists
for
running
high-resolution
motion
simulation
used
in
the
study.
K
There
they
were
Decatur
scale,
low,
salinity
events
in
that
cause,
Oakland
Dorset
clinic
they
generally.
First
immersion
tests
of
Arctic
seas
entered
the
North
Atlantic
through
the
boundary
currents
of
Greenland
and
moved
along.
The
cyclonic
soulful
desire,
the
most
most
pronounced
event
was
one
during
the
late
60s
and
70s,
often
cold
gray,
salinity,
anomaly
or
CSA.
K
It
is
generally
considered
that
GSA
was
initiated
by
in
as
the
French
rate
ci6
port
in
the
late
1960s,
and
this
freshwater
anomaly
was
expected
to
lever
the
sea
along
the
animation
and
shutting
down
to
the
convection
in
the
laboratory
during
1969
to
1971,
and
then
this
fresh
water
continued
to
move
following
the
solar
dryer
and
return
back
to
subarctic
seas.
About
a
decade,
the
GSA
has
received
attention
attention
because
of
potential
war
of
Arctic
origin,
fresh
water
in
shutting
down
deep
convection.
K
Several
modeling
study
having
conduct
to
test
this
idea
and
most
of
the
results
support
this
convention
of
view,
for
example,
left
shows
results
from
Kenan
in
this
study.
She
artificially
enhanced
from
straight
Isaac
sport
in
ocean
CX,
morrow,
and
she
found
weekend
overturning
circulation
with
substantial
decrease
in
laboratory
compaction,
and
the
right
shows
the
results
from
Coney
ghetto.
They
used
cop
Amaro
and
conductor
conductor,
the
composite
analysis,
using
old
version
of
API
cop
of
simulation
and
consistent
with
her
Keenen
study.
K
K
And
air
index
it
has
been
Y.
Extensive,
is
extensively
demonstrated
that
the
NAO
related
surface
boy
is
forcing
predominantly
controls
the
strength
of
the
compaction
thermohaline
circulation,
which
is
the
bonus
stream
and
a
mark,
and
so
polish
air
circulation,
and
thereby
a
nurse
where
transfer
of
he
deserved
from
the
subtropics.
K
But
surprisingly,
there
has
been
no
modeling
story:
studies
systematically
comparing
the
relative
country,
vision
of
french
fries
gi6
board
and
any
related
boy
acid,
forcing
to
GSA,
although
there
is
an
attempt
using
observation
and
1dmx
of
their
motto
by
Geritol
Lucero,
who
founded
lovely,
lovely,
equal
contributions,
also,
the
models
using
previous
studies
are
almost
two
decades
old.
So
maybe
it's
time
to
revisit
this
issue
here.
So
with
this
motivation,
we
revisited
the
mechanism
of
grey
salinity
anomaly
in
the
1970s.
K
K
Which
will
be
referred
to
as
the
CL
+
+
H
respectively?
We
also
used
other
CSM
one
couple
simulation
in
this
study.
I,
don't
think
I
have
enough
time
to
show
the
results
from
the
letter,
but
I'm
going
to
introduce
the
the
former
CSM
Ennio
surface
to
he
flux,
experiments
when
I
get
to
that
point.
So
first
take
a
look
at
the
how
Fosse
simulate
the
GSA
so
left
plot
shows
the
time
series
of
France
Tracy
I
export
from
the
top
left
see.
K
K
N
K
C
K
You
can
see
some
similarities
between
high
resolution
and
low
resolution
freshening
after
the
event,
freshening
see
I-64
event,
east
of
Greenland
freshening,
deep
convection
suppress
the
convection
in
the
lavender
sea
in
6970,
with
some
freshening
at
the
level
to
see
so
here
the
contour
interval
is
300
meter.
Red
means
negative.
K
Next,
we
try
to
disentangle
two
factors
through
composite
analysis
using
c
sm
p.
I
control
we
try
and
match
the
events
in
the
FASTA
l.
Lo
as
close
as
possible,
the
blue
bars
in
the
top
right
shows
the
monthly
anomalies
of
fresh
red
sea
ice
export
from
the
CL
we
can
see.
Ice
exporter
is
instituting
oli
half
of
1968
and
to
some
extent
in
1967.
So
we
identified
from
Pierre
control
years
when
Gen
2,
June
CI
6
bar,
is
greater
than
one
point.
K
A
standard
deviation
from
those
we
serve
selected
when
the
previous
year,
January,
2
and
CSX
pour,
is
greater
than
average.
Thanks
to
the
long
legs
we
identify
identified
3
939
samples,
despite
this
very
strong
threshold-
and
this
is
the
salinity
and
mr.
devs
pattern
from
this
I-64
composite.
We
can
see
some
similarities
between
this
flaw,
CL
and
dis
composite
anomalies
of
some.
K
K
Identified
from
P
I
control,
January
March,
average
heat
flux,
anomalous,
heat
flux
is
greater
than
1.8
standard
deviation
and
subsample
when
the
next
winter
is
greater
than
long-term
average,
and
this
is
the
same
composite
as
you
can
see
clear,
suppress
suppression
of
the
convection
in
this
composite
in
1969
and
70.
We
can
also
see
some
freshening
and
delever
to
see
in
this
composite,
which
is
also
seen
in
the
passive
yellow
here.
K
This
is
because,
because
of
suppress
mixing
of
relative
refresher
upper
ocean
with
certain
deeper
ocean,
in
the
mean
state,
strong,
helos
over-delivered,
the
sea
coastal
erosion,
so
the
temperature
drives
destabilization
of
the
water
column.
So
when
convection
takes
place,
relatively
fresh
ocean
is
mixed
with
certainty
deeper
ocean,
but
when
the
key
loss
is
weak
enough
to
stop
this
process,
just
fresh
water
stays
there.
So
we
have
anomalous
fresh
upper
layer.
In
this
case
the
right
fig
plus
shows
the
left
see
average
salinity
profiles
in
1969
winter
or
the
corresponding
winter.
K
In
the
surface
he
looks
calm
busy,
as
you
can
see,
they
all
show
is
kind
of
gradual
freshening,
starting
from
the
member
blue
through
January,
yellow
March
red.
In
duffel
layer
and
pressure
certainiy
in
the
deeper
layer
so
for
based
on
this
results,
we
argue
that
this
freshening
and
the
lever
to
see
is
due
to
local
suppressed
mixing
rather
than
the
propagation
of
ice
export
induced
fresh
anomaly.
K
K
As
expected,
we
don't
see
much
propagation
of
fresh
water
at
the
France
Tracy
Isaac
Isaac's
port
composite,
although
there's
some
propagation
of
the
lever
of
the
coast,
but
cinemas,
we
quickly
dissipate
the
low-frequency
magnetic
anomalies
bear
we
can
see
sm1.
So
it's
hard
to
isolate
statistically.
So
we
employ
this
left,
see.
I
know
he
flux,
forcing
experiments
which
she
was
conducted
by
us
to
study
amb
mechanism.
So
we
have
we
imposed
his
winter
surface
heat
flux,
anomaly
associate
and
a
negative
nao
in
CSF
one.
K
We
can
see
kind
of
northward
propagation
of
this
fresh
water
signal
in
response
this
forcing
very
similar
to
this
force
against
regulations
by
design
this.
This
fresh
water
is
due
to
weakened
thermohaline
circulation
in
this
nao
experiment.
As
you
showing
here,
the
a
mock
anomalous,
a
forty
five
nodes.
As
you
can
see,
the
a
mock
was
negative
throughout
the
years.
I
K
K
He
came
rather
than
this
fresh
water
from
France
trade,
Isaac's
port,
the
fresh
water,
the
fresh
water
nominally
propagated
along
the
boundary
currents
to
the
gyre
boundary,
but
disbelief
there
named
desire
boundary
and
the
fresh
water
fresh,
fresh
anomaly
propagating
along
the
so
village,
are
coming
from
the
subtropics
due
to
bigger
thermal
and
circulations.
Ok,
I'll!
Stop
here.
Ok,.
E
P
P
So
it's
a
man
into
racing
is
dominating
subsea
mode
in
the
tropics.
It's
distinct
from
typical
Kotori
waves,
but
because
of
its
panda
skill
and
it's
slow
is
multiplication,
it
can
excite
laws,
be
wave
technicians
that
motivate
ectopic
weathers
and
because
of
that
it
is
an
important
predictor
for
external
weather
forecasts.
So,
in
this
study
we
were
investigate
how
where
the
m0x
tropical
calculation
and
impacts
change
under
future
warming.
So
we
are
focused
on
the
pre
winter
winds
MgO
telling
is
most
pronounced
in
the
northern
hemisphere.
P
The
results
based
on
selected
GCM
that
cooperation
with
Amy
Jo.
We
estimate
respond
to
future
warming
from
differences
in
his
historic
and
ICP
80.5
simulation.
So
we
identify
him
Germans
and
face
based
on
the
real-time
Marty
Faribault
in
Texas,
under
the
delicate
and
pattern
obtained
as
the
as
the
NGO
face
composited
fields.
P
So
this
figure
shows
the
Matt
modem
in
summation
of
the
tropical
state
and
telecare
pattern
associated
with
MgO
Phase
three
under
current
climate
or
under
historical
climatology.
So
the
shading
is
anomalous,
treasure
ferocity
and
the
bracken
tors
anomalous
job
in
height
and
the
cross
symbol
indicates
the
significant
participation
response
over
threshold.
We
also
denote
the
C&O
subtropical
jet
by
the
purple
controls.
Here
we
can
see
in
phase
reads
a
material
features,
enhanced
convection
of
the
Indian
Ocean
and
it
suppress
convection
over
West
Pacific
and
in
the
extra
tropics.
A
classic
Peary
pattern
emerges.
P
That
is
the
most
significant
signal
found
in
years
or
exit
region.
So
the
decreasing
is
on
a
wing
the
regime
of
the
subtopic.
Yet
this
is
no
other
without
of
the
batch
of
energy
conversion
which
allow
the
waves
to
extract
energy
from
kramatorsk
ozone
or
asymmetry,
so
we
can
see
increased
with
a
positive
jopen,
height
you're
associated
with
descending
and
a
drying
near
the
west
coast
of
the
North
America.
So
we
now
show
the
Future
response
to
the
response
to
a
future.
Warming
are
dominated
by
arms
or
by
an
eastward
extension
of
the
rim.
P
Geo-Tagging
pattern-
or
we
just
can
see
that
indicated
by
both
the
east,
were
shift
in
the
center
of
this
job
in
high
anomaly
and
also
the
East
Worship
in
its
eastern
boundaries.
I
will
play
it
one
more
time,
so
you
can
see
just
eastward
extent.
Erica
pattern
needs
to
amplified
the
spouse
being
amplified
and
driving
near
the
west
coast.
She
said
for
phase
3.
P
But
we
can
see
the
MgO
impact
external
eastward
and
with
a
larger,
downstream
impacts
and
the
PA
regime
and
over
the
california
are
specifically
same.
Do
induced
variation
in
crustacean
is
amplified
by
almost
50%,
and
we
can
see
because
of
this
eastward
extension
of
the
integrand
pattern.
The
majority
no
impact
actually
arrives.
The
california
I
included
by
the
yellow,
light
here
earlier.
So
so
there
is
a
forward
phase
shift
in
the
image
or
impacts
are
in
california.
P
So,
given
these
massive
impacts,
we
would
like
to
understand
what
causes
this
is
where
external
image
authentication
so
immediate.
Having
patent
depends
on
post
topic
forcing
and
the
extra
optical
means
state
which
moderate
the
source
and
the
appropriation
of
the
roads
we
will
train,
we
can
see,
are
those
both
facto
significant
changes
are
projected
in
those
factors.
So
in
the
in
the
tropics,
we
see
that
the
MGO
activity
extends
eastward.
On
a
future
mean
this
is
singing
boast
of
the
face.
P
The
face
computed
pressure,
ski
and
it's
interface
to
standard
deviation
across
the
faces
so
from
hist
to
ac15.
We
can
see
the
embryo
extends
eastward
another
reason
would
be
I
in
indirect
topics.
The
exit
region
of
the
subtropical
jet
also
shift
eastward
and
as
as
the
peony
as
in
MgO
PA
pattern
is
anchored
to
just
yet
exit.
It
may
are
also
shift
eastward
correspondingly
to
so
to
confirm
these
hypotheses
and
also
exam
the
relative
importance.
P
So
when
we
force
the
model
with
a
mean
state
and
I'm
Jo
heating
dialogue
from
the
his
condition
indeed
seems
the
IBM
can
reproduce
reasonably
reproduce
the
image
opium
pattern,
and
if
we
change
the
mean
state
and
you're
heating
to
a
cp82
that
in
a
CP
we
can
see
the
MGO
telegin
pattern
shift
eastward
now
also
in
just
appear
model,
there's
a
slight
weakening
in
the
embryo
tag
attend
but
awards.
Eastward
extension
change
dominates,
so
there's
amplified
amplified
ascend
near
the
west
coast.
P
Now
we
have
conduct
additional
nation
with
mean
station
only
under
MgO
heat
engine
only
to
further
to
control
the
causes,
or
we
can
see
the
it's
worth
shift
in.
The
geotag
pattern
is
mainly
driven
by
the
eastward
extended
least
were
shifted
yet
exit
and
the
additional
contributed
by
the
east
were
extended.
Mgo
heating,
under
the
slight
weakening
this
appear
model
or
use
a
net
without
of
the
above
of
the
opposing
effect
from
increased
static
stability
that
weekend
immediate
ignition
and
the
amplified
MgO
heating
under
future
warming.
That
enhances
my
authentication.
P
So
we
further
move
on
to
illustrate
the
failure
mechanisms
underlying
the
eastward
extension
of
the
MgO
and
the
easter
shift
of
the
jet
exit.
So
this
figure
here
shows
mg
o
propagation.
So
the
image
of
its
computed
pressure
velocity
equatorial
me
as
a
function
of
longitude
and
faced
so
the
shading,
is
for
the
historical
cram
cravat
and
as
a
contour
is
for
the
ICP
80.5.
We
can
see
confirm
our
previous
figure
that
the
Emidio
extend
eastward
and
the
future
warming.
P
We
can
see
just
eastward
extension
of
the
mg
or
itself
in
kappahd
models
are
used
in
sleep
residue,
stin,
ami
acceleration
with
which
force
to
whisk
pattern.
Warming
party
is
absent.
I
when,
when
we
only
consider
when
you
only
impose
a
uniform
one,
woman
just
indicates
that
the
cojac
pattern
warming
is
critical
for
driving
just
eastward
extension
of
the
imager
and
in
particularly
the
the
projected
warming
officials,
enhanced
warming
to
the
east
of
the
lavatory
woman
poor.
P
This,
where
further
shift,
where
we
extended
a
deep
convective
heap
and
the
moist
region
to
the
Central,
Pacific
and
I'll,
extend
the
MgO
activity.
Eastward
furthermore
amounts
a
projection
of
a
couple
models,
as
shown
in
this
figure,
are
the
Moors
or
Central
Pacific
is
warmed
compared
to
the
West
Pacific.
So
we
measure
that
the
warming
gradient
along
the
long
curve
in
this
box
and
the
Moors
MgO
activity
extends
eastward
and
for
the
jet
exit
it
is
I'll.
Show
you
this
figure.
It
is.
P
It
is
a
integral
tied
to
the
stationary
pattern,
so
we
can
see
that
the
station
pattern
here
is
shown
here
by
the
departure
in
the
job
cutting
height
from
the
gentleman
in
shading,
so
the
strongest
jet
nice
also
the
hello
Joplin
job
in
highly
no
and
as
a
exit.
Yes,
look
you're
located
and
near
the
note
of
the
stationary
pattern.
It
is
started
in
previous
studies,
Simpson
at
all
Ultron
16,
that
the
stationary
pattern
were
shifted
eastward
on
the
future
warming,
because
the
station
is
on
agreeing
the
way
increased.
P
P
Okay,
so
so
so
we
can
see
the
the
my
models.
The
temperature
projected
East
were
shift
in
the
jet
exit
is
corrected
wisdom.
We
zero
similarities
were
shift
in
a
stationary
at
a
pattern
and
the
the
the
number
here
shows
the
selected
models
with
good
MgO,
and
the
green
dots
here
shows
the
models
that
are
not
selected.
P
Furthermore,
we
show
that
the
eastward
extension
of
the
a
metallic
nation-
yes,
it's
correlated
with
the
East-
were
shift
of
the
jet
exit
for
the
selected
models
and
we
show
that
nine
of
the
tech
models
and
the
Torf
out
of
the
14
on
select
models
predict
East
were
shift
of
the
jet
exit
just
indicates.
East
were
extension
in
geotechnical.
She
needs
to
be
will
be
very
likely
to
occur
in
the
future
and
and
also
the
amplified
imager
impacts
in
California,
yes,
created
with
East
were
shift
in
the
jet
exit.
P
So
the
the
black
black
number
here
shows
response
in
the
pressure
velocity
and
the
red
number
here
shows
the
responsive,
a
presentation
both
are
also
suppose
of
ribose
tribals
amplified.
A
major
impacts
that
are
correlated
with
the
east
were
shift
over
the
jet
exit
and
and,
roughly
speaking,
a
one
degree.
East
were
shift
in
the
jet
exit
implies
a
sixty
six
percent
increase
in
the
MGO
induced
a
precipitation
friability
and
for
the
matmata
mean
it
predicts
a
fifty
four
percent
increase
in
the
MgO
induced
preps
agent
liability
by
the
end
of
the
century.
P
P
So
to
summarize,
we
show
that
a
majority
in
the
brain
winter
Pacific
extent
eastward
on
the
future
warming
meaning
amplified
enjoy
impacts
not
seen
in
the
PMI
regions,
and
this
is
what
extended
the
telekinetic
pattern
gets.
Prime
radio,
any
super
shift
in
the
axilla
gene
or
the
sub
job
yet,
and
the
additional
contribute
the
fact
either
extension
of
the
image
itself
so
I'm
the
implication
would
be.
P
P
Subsea
no
I
mean
to
annual
variability
in
California
and
where
we
oppose
acute
challenges
on
regional
resource
management,
an
extreme
weather
prepared,
prepare
ation
so
also
the
East
were
extended.
Php
intelligent
pattern
may
I
indicate
increased
brick
predict
ability
of
beyond
week
to
over
winter
North
America.
P
I
think
the
pressure
velocity
here,
the
Omega
1500-
should
measure
the
dynamic
response,
so
I
would
say
so
you
can
see.
The
preceding
amplification
is
larger
than
just
dynamic.
One
so
I
would
say
dynamic
will
be
v
5%
and
there's
a
dynamic
class.
The
same
economy
increase
in
moisture
away.
This
explains
so
maybe
20%
of
the
application
will
come
from
the
increase
in
moisture.
E
P
Remember
a
talk
from
alum
note,
I
think
yesterday
they
show
that
at
Manila
frequency
and
the
future,
the
landfalling,
the
ninety-four,
the
atmosphere,
the
frequency
we
increased.
But
she
says
even
so.
Overall
frequency
of
the
atmosphere
decreases
and
I
suspect
that
may
be
related
to
the
pattern
shift.
The
MDO,
Terra
Cotta,
but
I'm
not
sure,
okay,.
E
A
P
E
I
Thanks
Barry,
but
they
are
the
one
I'm
young,
I'm
sure
the
year,
PhD
from
one
nation
or
state
in
Australia
myself,
a
library's
professor
Judy,
a
blaster.
Today
I
would
like
to
talk
about
the
role
of
photographer
variability
in
driving
the
back
of
the
ships
in
the
sudden
times
of
year,
sometime
early
June
Jed,
our
paper
has
been
published
in
the
journal
climate
on
the
Assyrian
April.
So
if
you
are
interested
after
my
talk
and
please,
however,
aid
you're
welcome
for
any
further
discussions.
I
Okay
and
as
we
know,
the
southern
hemisphere,
auditor
and
jet
in
the
DTM
season
has
shifted
powered
over
the
Senate
era
and,
in
previous
studies,
explanations
have
mainly
stressed
the
influence
of
external,
forcing
especially
the
ozone
depletion
and
the
greenhouse
gases.
But
here
we
are
also
interesting.
I
Osteo
three
well,
for
example,
pacific
pacemaker,
the
associate
normally
anomalies
in
the
eastern
Pacific
and
largely
in
two
observations.
So
the
pacific
pacemaker
in
thermo
mean
contains
two
signals:
whiny
six
enforcing
and
the
other
is
the
internal
variability
generated
by
these
tropical
pacific
basin
and
the
way
do
the
same
thing
for
the
tropical
indian
pacemaker
as
the
mouse
atlantic
pacemaker.
I
So
we
first
look
into
the
packet
of
difference
of
a
disease
in
the
model.
The
techno
difference
means
we
separate.
I
said
that
enjoy
into
to
curate,
based
on
the
IPO
face
and
a
way
used.
The
second
period
average,
which
is
99
2013,
the
first
appeared
average,
which
is
eighty
to
ninety
eight,
so
panel.
I
A
is
observation,
and
the
model
results
panel
say
here:
either
lenz
enzyme
Bamiyan,
showing
the
external
force
and
influence,
and
the
bottom
three
are
the
union
of
our
abilities
by
subtracting
lines
from
the
Pacemakers
and
the
panel
B
here
is
the
model
summation
so
that
panel
c
d,
e
f
and
from
the
reservation
in
the
Pacific
Basin
we
can
see
there
is
great
cooling
in
the
Chubbuck
or
eastern
Pacific
and
significant
warming
in
the
subtropics.
So
this
is
a
typical
neck.
I
You
IPO
pattern-
and
this
is
Sigma-
is
largely
captured
by
the
Pacific
pacemaker
management's,
showing
the
IPO
is
mainly
an
internal
process
and
the
lens
involves
embalming
showing
by
external
force
and
influence
warms
up
the
surface
nearly
everywhere
and
the
other
logic
on
the
indian
pacemakers,
showing
there
are
less
signals
compared
to
the
pacific
pacemaker
and
the
model.
Summation
is
all
these
four
factors
combined
and
we
can
see
the
model
can
reproduce.
The
observation
in
generally
well,
except
that
in
the
southern
hemisphere,
highlighted
hues.
There
are
some
warm
baths.
I
So
the
key
message
here
is
that,
through
our
methodology
using
lens
and
the
Pacemakers,
we
can
separate-
and
I
dab
ii
of
external,
forcing
and
you
know
our
beauties-
and
this
is
the
macro
difference
of
the
zone
orient
at
850
hectopascal
still.
The
tablet
is
observation
and
the
rest
are
the
northern
results.
So
the
contours
at
the
clare,
metallurgy,
kozo,
no
beans
and
the
shadings
at
the
technical
difference
on
the
top
here
is
a
ceramic
basin
and
the
right
it
is
south
indian
basin
and
on
the
bottom
and
left
and
in
South
Pacific
Basin.
I
So
in
observation
and
the
the
warm
color
is
showing
the
being
the
increase
and
the
blue
colors,
showing
the
window
decrease,
and
this
and
this
overall
type
of
structure
showing
there
is
a
it's-
almost
symmetric,
polar
shift
of
the
editor
in
jet
new
observation,
but
in
the
South
Pacific
Basin,
the
jet
experienced
more
like
an
intensification
instead
of
leaded
here,
the
position
shift
and
from
the
model
results.
We
can
tell
the
main
two
drivers,
the
external,
forcing
as
well
as
the
tropical
Pacific
SSD
for
the
tropical
Pacific
as
he
anomaly.
I
He
drives
the
South
Indian
basin
jet
moved
forward
as
the
intensification
or
the
South
Pacific
Basin,
and
for
the
external,
forcing
his
main
influence
is
restrained.
It's
a
solid
intubation
driving
the
jet
movie
empowered,
and
we
also
did
the
analysis
for
the
sea-level
pressure
field,
which
is
not
shown
here,
but
for
the
slab
pressure
field,
along
with
the
sorceress
shift
of
the
jet.
There
is
a
positive
IPO
phase.
I
So
what's
the
mechanism
behind
the
external
forcing
and
the
tropical
Pacific
as
as
the
influence
under
generation
since
the
atom
inflow,
is
more
important
for
the
original
jet.
Here
we
started
from
the
eddy
montant
allows
convergence,
so
this
plus
the
co
spectra
of
the
atom
Tony
Falasca
rodents
I,
had
to
100
hectare
paska
as
a
function
of
added
wave
phase,
speed
and
latitude.
I
So
the
summer
means
oh,
no
wind
shows
the
jet
moves
powered
by
nearly
one
degree,
and
this
is
the
this-
is
the
result
of
the
power
migration
of
this
at
the
momentum,
class
convergence
pout
and
as
shown
in
this
type
of
structure
here
so
convergence
anomaly,
evidence
anomaly
and
showing
the
original
convergence
that
is
moving
forward.
Now
from
the
model
results
on,
we
can
see
the
this
dipole
structure
and
is
contributing
the
biposto
external
forcing
and
the
tropical
Pacific
as
icy
anomalies.
I
But
why?
The
at
the
momentum,
flux,
convergence,
moves
forward
in
the
middle
latitudes,
we're
looking
to
the
vertical
distribution
of
the
temperature.
So
they
said
the
Tecmo
difference
of
the
tsunami
and
temperature
named
observation.
We
can
see
around
the
30
to
45
degree.
There
are
significant
warming
and
the
source
of
that
there
are
large
cooling
and,
from
the
model
results
external
forcing
showing.
There
is
large
warming
in
the
middle
and
the
low
latitudes
and
cooling
in
the
South
Pole.
And
these
you
notice
the
temperature
contrast
in
the
middle
added
hues.
I
I
I
However,
there
are
some
cavities
of
our
paper
like,
for
example,
due
to
the
tropical
as
a
state
in
her
base
and
connections.
One
might
have
double
pant
of
the
Pacific
as
the
anomaly
influence
and
the
jet
variation,
and
this
means
the
tropical
Pacific
SS.
The
anomaly
can
influence
the
jet
by
direct
atmospheric
teleconnections
are
by
changing
the
SSDs
in
other
basins,
were
first
and
then
imposing
a
secondary
effect
and
under
certain
times
fear.
Yet
and.
E
I
E
E
I
Yes,
when
we
initially
include
the
recipe
of
a
patent
in
the
paper
by
the
original
suggesting
that
you
know
whale
noises
focus
if
we
discuss
pasta
trends
in
at
the
moment
and
classic
emergence
and
the
teleconnections
of
Rossby
waves.
But
we
do
by
the
way
only
looking
to
the
pacific
pacemaker.
So
as
shown
here
and
the
left
is
observation
and
in
the
middle
is
the
pacemaker
in
Sonoma
management's.
I
So
from
the
stream
function,
you
can
see
him
in
observation.
There
is
a
and
teleconnections
propagating
from
the
tropical
Pacific,
but
in
the
model
like
in
the
highlighted
hues
and
Maggie's
life
significant
and
compared
to
the
observation,
so
that's
part
of
the
reason
we
didn't
include
the
guide
in
the
paper.
All.
E
E
E
The
computer
time
allocation
that
we
have
to
write
a
proposal
for
to
get
the
working
group
resources
input
on
the
CSM
tutorial
and
also
any
opinions
may
have
about
having
a
high
resolution
version
of
the
CSM
to
our
resolution,
meaning
or
degree
atmosphere
and
probably
something
like
10
two
degree
ocean,
so
I
think
that's
the
end
of
the
session,
so
I
think
I
can
just
say
on
behalf
of
the
other
co-chairs:
CBC
W
co-chairs,
that's
I,
love,
Qiang
ping,
che
Peter,
Collor
and
myself.
I
want
to
thank
everybody
for
participating.
I
live.