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Tony Del GenioNASA/GISS
What do we need to know about convection?
−20 −16 −12 −8 −4 0 4 8 12 16 20 −20
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20 2xCO2−1xCO2 A30 QFLUX NINT ANN
Low Cloud Cover Change (%)
SW
Clo
ud
Forc
ing
Ch
an
ge
(W/m
**2
)
−20 −16 −12 −8 −4 0 4 8 12 16 20 −20
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20 Conditional 2xCO2−1xCO2 A30 QFLUX NINT ANN
Low Cloud Cover Change (%)
SW
Clo
ud
Forc
ing
Ch
an
ge
(W/m
**2
)34% 5%
43% 18%
63% 3%
17% 18%
GISS GCM: 2.6-2.9°C climate sensitivity…but Δ low cloud cover ~ -2%
Why? Masking by high cloud increases
ARM SGP SCMsimulations:
Good place to look for convection errors is in
weak dynamical forcing conditions
(entrainment?)
Song et al. (2013)
DayNight
YOTC MJO 20-day hindcasts (2009 Event E)Hovmöller composite of all W-H phase 1 rain anomalies
TRMM TMI CMIP5
+ strongerentrainment,rain evaporation,downdrafts
+ Cold pool
SCM, AMIE-DYNAMO forcing, 3 hr relaxationConvective cloud top height vs. column water vapor
KAZR and SCM Forcing Data
40 44 48 52 56 60 64 68 72 COLUMN WATER VAPOR (mm)
0
2
4
6
8
10
12
14
16 18
CL
OU
D T
OP
HE
IGH
T (
km
)
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
log10(%)
KAZR
GAN AR5 W/Relaxation of Forcings Tot=763 (nint)
40 44 48 52 56 60 64 68 72 COLUMN WATER VAPOR (mm)
0
2
4
6
8
10
12
14
16
CL
OU
D T
OP
HE
IGH
T (
km
)
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
log10(%)
GAN AR5 07 W/Relaxation of Forcings Tot=858 (nint)
40 44 48 52 56 60 64 68 72 COLUMN WATER VAPOR (mm)
0
2
4
6
8
10
12
14
16
CL
OU
D T
OP
HE
IGH
T (
km
)
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
log10(%) GAN AR5 66 W/Relaxation of Forcings Tot=931 (nint)
40 44 48 52 56 60 64 68 72 COLUMN WATER VAPOR (mm)
0
2
4
6
8
10
12
14
16
CL
OU
D T
OP
HE
IGH
T (
km
)
-1.6
-1.4
-1.2
-1.0
-0.8
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
log10(%)
CMIP5
+ strongerentrainment,etc.
+ cold pool
If radiative heating drives the MJO,
(a) Maybe it is a nice test of the GCM clouds we form from convection
(b) Since the relevant heating anomalies are largely due to organized convection, maybe we are getting the right answers in GCMs for the wrong reasonCloudSat-CALIPSO FLXHR-LIDAR MJO composite
![GISS-E2.1: Configurations and Climatologyoceans.mit.edu/JohnMarshall/wp-content/uploads/2020/01/GISS_Kell… · 86 R and GISS-E2-H in CMIP5 [Schmidt et al., 2014], and GISS-E2.1-G](https://img.pdfslide.us/doc/110x75/5f165c6a8b5d166c5d052b56/giss-e21-conigurations-and-86-r-and-giss-e2-h-in-cmip5-schmidt-et-al-2014.jpg)
