Supplementary Material
Cloud cover climatologies in the Mediterranean obtained from
satellites, surface observations, reanalyses, and CMIP5 simulations:
validation and future scenarios
Aaron Enriquez-Alonso1, Arturo Sanchez-Lorenzo2, Josep Calbó1, Josep-Abel
González1, Joel R. Norris3
1
2
Department of Physics, University of Girona, Girona, Spain
Instituto Pirenaico de Ecología, Consejo Superior de Investigaciones Científicas
(IPE-CSIC), Zaragoza, Spain
3Scripps
Institution of Oceanography, University of California, San Diego, La Jolla, CA,
USA
Climate Dynamics
Corresponding author: aaron.enriquez@udg.edu
Tables
Table S1. Description of Physical Parameterization Schemes in the GCMs (updated from
Zhang et al., 2005). Models highlighted with (*) provide results with the ISCCP simulator.
Models highlighted with (--) do not provide future projections for the scenarios considered at
the end of our paper.
GCM
Stratiform Clouds
Convective Clouds
Convection
Cloud Microphysics
ACCESS 1.0
Uses HadGEM2 atmospheric physics.
ACCESS 1.3
Uses atmospheric physics similar to that of the Met Office GA1.0 model configuration (Hewitt et al. 2011),
including the PC2 prognostic cloud scheme (Wilson et al. 2008)
BCC-CSM 1.1
Atmospheric module is BCC-AGCM2.1. Convection: Mass flux (Wu 2012)
BCC-CSM 1.1(m)
Atmospheric module is BCC-AGCM2.2. Convection: Mass flux (Wu 2012)
BNU-ESM
CanESM2 (*)
Diagnostic (Klein and
Hartmann 1993; Kiehl et al.
1996; Collins et al. 2006)
The atmospheric module is CAM 3.5:
(Zhang and McFarlane 1995)
(Xu and Krueger
and convective momentum
1991; Hack 1994)
transport (Richter and Rasch
2008)
(Rasch and
Kristjánsson 1998;
Zhang et al. 2003)
Fractional cloud cover is evaluated from the prognostic moisture and temperature fields through relative
humidity (McFarlane et al. 1992)
The atmospheric module is CAM 4:
CCSM4
As CAM 3.5, modified for
polar clouds (Vavrus and
Waliser 2008)
As CAM 3.5
As CAM 3.5
As CAM 3.5
CESM1-BGC
The atmospheric module is CAM 5:
CESM1-CAM5
CESM1-FASTCHEM (--)
(Park and Bretherton
2009)
As CAM 4
CESM1-WACCM (--)
(Morrison and
Gettelman 2008)
As CAM 3.5
CMCC-CESM (--)
CMCC-CM
Uses atmospheric module ECHAM5 (as MPI models)
CMCC-CMS
CNRM-CM5
CSIRO-Mk 3.6.0.
FGOALS-g2.0
Diagnostic (Ricard and
Royer 1993)
(Bougeault 1985)
Sub-grid condensation
parameterization from
(Bougeault 1981;
Bougeault 1982)
Uses atmospheric physics very similar to HadCM/HadGEM models
Diagnostic (Rasch
and Kristjánsson
1998)
Mass flux (Zhang and
McFarlane 1995)
(Rasch and
Kristjánsson 1998)
FGOALS-s2.0 (--)
Diagnostic RH based (Liu
and Wu 1997)
FIO-ESM
GFDL-CM3
GFDL-ESM2G
GFDL-ESM2M
Mass flux (Tiedtke 1989)
The atmospheric module is CAM 3.5 (see BNU-ESM)
Prognostic (Tiedtke 1993;
Geophysical Fluid
Dynamics Laboratory
Global Atmospheric Model
Development Team (GFDL
GAMDT) 2004)
Prognostic; (Tiedtke
1993; GFDL
GAMDT 2004)
RAS (Moorthi and Suarez
1992)
(Rotstayn 1997; GFDL
GAMDT 2004)
RH based, Sundqvist type
(Del Genio et al. 2005)
Diagnostic (Del
Genio et al. 2005)
Mass flux (Del Genio and
Yao 1993)
(Del Genio et al. 2005)
Statistical (Smith 1990)
Diagnostic (Gregory
and Rowntree 1990)
Mass flux (Gregory and
Rowntree 1990; Gregory and
Allen 1991)
(Smith 1990)
Statistical (Smith 1990)
with modifications (Cusack
et al. 1999; Webb et al.
2001)
Diagnostic (Gregory
and Rowntree 1990)
with modifications
(Gregory 1999)
Mass flux (Gregory and
Rowntree 1990; Gregory and
Allen 1991)
(Wilson and Ballard
1999)
Diagnostic based on RH,
temperature and vertical
temperature gradient
(Betts 1986)
(Betts 1986)
Statistical (Le Trent and Li
1991)
Statistical (Bony and
Emanuel 2001)
(Emanuel 1991)
GISS-E2-H
GISS-E2-H-CC
GISS-E2-R
GISS-E2-R-CC
HadCM3 (--)
HadGEM2-AO
HadGEM2-CC
HadGEM2-ES (*)
INM-CM4
IPSL-CM5A-LR (*)
IPSL-CM5A-MR (*)
(Le Trent and Li 1991)
IPSL-CM5B-LR
MIROC-ESM (*)
MIROC-ESM-CHEM (*)
(Le Trent and Li 1991)
MIROC4h (--)
MIROC5 (*)
(Watanabe et al. 2009). Convective clouds (Chikira and Sugiyama 2010)
MPI-ESM-LR (*)
MPI-ESM-MR
Prognostic (Tompkins
2002)
Diagnostic;
(Roeckner et al.
1996)
Mass flux (Tiedtke 1989;
Nordeng 1994)
(Lohmann and
Roeckner 1996)
MPI-ESM-P (--)
MRI-CGCM3 (*)
New two-moment bulk cloud scheme (Tiedtke 1993; Jakob 2000). Convective clouds: mass-flux (Tiedtke 1989;
Yoshimura et al. 2014)
NorESM1-M
The atmospheric module is CAM 4 (see CCSM4)
NorESM1-ME
Table S2. Values of the different metrics used to compare the TCC from the CMIP5 models
and multi-model mean (MMM) against PATMOS-x. The metrics are the Mean Difference
(MD), the Mean Absolute Difference (MAD), the Skill Score (SS), the Annual Range (AR)
difference, this latter being defined as the AR (i.e. mean winter TCC minus mean summer
TCC) for a particular GCM minus the AR for the PATMOS-x, and the coefficient of spatial
and temporal correlation (R). Units are % of sky cover for MD, MAD and AR difference,
while SS and R are dimensionless values between 0 and 1. In parentheses, the ordinal
position of each model for each metric.
Models
ACCESS1.0
ACCESS1.3
BCC-CSM1.1
BCC-CSM-1.1(m)
BNU-ESM
CanESM2
CCSM4
CESM1-BGC
CESM1-CAM5
CESM1-FASTCHEM
CESM1-WACCM
CMCC-CESM
CMCC-CM
CMCC-CMS
CNRM-CM5
CSIRO-Mk3.6.0.
FGOALS-g20
FGOALS-s20
FIO-ESM
GFDL-CM3
GFDL-ESM2G
GFDL-ESM2M
GISS-E2-H
GISS-E2-H-CC
GISS-E2-R
GISS-E2-R-CC
HadCM3
HadGEM2-AO
HadGEM2-CC
HadGEM2-ES
INM-CM4
IPSL-CM5A-LR
IPSL-CM5A-MR
IPSL-CM5B-LR
MIROC4h
MIROC5
MIROC-ESM
MIROC-ESM-CHEM
MPI-ESM-LR
MPI-ESM-MR
MPI-ESM-P
MRI-CGCM3
NorESM1-M
NorESM1-ME
Multimodel Annual
Multimodel DJF
Multimodel MAM
Multimodel JJA
Multimodel SON
MD
-8.9
-0.2
-4.8
-12.1
-10.0
-8.9
-18.5
-18.5
-5.1
-19.0
-14.4
-2.3
-3.3
0.1
-11.8
-0.2
3.5
-14.1
-9.1
7.2
2.3
3.1
5.5
4.5
4.9
4.9
-7.6
-9.7
-8.4
-9.1
-5.9
-12.1
-11.3
-3.2
-13.8
-11.7
-12.0
-11.6
-3.0
-3.3
-3.6
-6.9
-12.1
-11.9
-6.4
-6.6
-9.4
-3.6
-6.0
(24)
(2)
(14)
(36)
(29)
(24)
(42)
(42)
(16)
(44)
(41)
(4)
(9)
(1)
(33)
(2)
(11)
(40)
(26)
(21)
(4)
(7)
(18)
(13)
(15)
(15)
(22)
(28)
(23)
(26)
(19)
(36)
(30)
(8)
(39)
(32)
(35)
(31)
(6)
(9)
(12)
(20)
(36)
(34)
MAD
14.3
(18)
13.8
(15)
13.2
(8)
17.8
(40)
14.8
(21)
15.2
(25)
21.7
(42)
21.8
(43)
13.0
(4)
21.9
(44)
18.2
(41)
13.7
(13)
12.5
(1)
12.5
(1)
16.4
(34)
13.0
(4)
13.1
(7)
17.4
(39)
14.6
(20)
13.7
(13)
12.9
(3)
13.3
(10)
15.7
(29)
15.3
(26)
15.7
(29)
15.5
(27)
15.5
(27)
14.9
(22)
14.2
(17)
14.4
(19)
13.4
(11)
16.4
(34)
16.6
(36)
13.9
(16)
16.8
(38)
15.1
(24)
16.1
(32)
15.8
(31)
13.0
(4)
13.4
(11)
13.2
(8)
15.0
(23)
16.7
(37)
16.3
(33)
11.2
12.4
12.3
9.3
10.7
PATMOS-x
SS
0.69
(17)
0.72
(13)
0.72
(13)
0.56
(40)
0.65
(25)
0.69
(17)
0.44
(42)
0.43
(44)
0.78
(1)
0.44
(42)
0.53
(41)
0.75
(8)
0.76
(5)
0.78
(1)
0.64
(30)
0.71
(15)
0.65
(25)
0.66
(23)
0.64
(30)
0.73
(12)
0.77
(3)
0.76
(5)
0.60
(34)
0.61
(33)
0.60
(34)
0.60
(34)
0.65
(25)
0.67
(21)
0.69
(17)
0.68
(20)
0.75
(8)
0.66
(23)
0.67
(21)
0.75
(8)
0.60
(34)
0.64
(30)
0.65
(25)
0.65
(25)
0.77
(3)
0.75
(8)
0.76
(5)
0.70
(16)
0.59
(39)
0.60
(34)
0.56
-
AR difference
2.1
(11)
1.4
(8)
-2.0
(10)
-5.4
(23)
-0.8
(5)
0.0
(1)
-17.4
(39)
-18.5
(43)
2.9
(16)
-17.7
(41)
-13.1
(34)
4.5
(20)
-3.9
(17)
-1.1
(7)
-6.2
(24)
16.9
(37)
-10.9
(33)
9.2
(30)
-9.1
(29)
-0.1
(2)
6.5
(25)
5.1
(22)
-17.5
(40)
-18.2
(42)
-18.6
(44)
-17.0
(38)
-13.7
(35)
2.4
(14)
2.2
(12)
2.2
(12)
10.4
(32)
9.5
(31)
8.1
(27)
2.6
(15)
-4.5
(20)
-1.0
(6)
4.3
(19)
3.9
(17)
0.1
(2)
-1.9
(9)
0.3
(4)
-13.8
(36)
-8.4
(28)
-7.2
(26)
-3.0
-
R
0.72
(10)
0.68
(26)
0.69
(23)
0.60
(35)
0.72
(10)
0.68
(26)
0.55
(39)
0.55
(39)
0.74
(2)
0.56
(38)
0.64
(34)
0.70
(22)
0.71
(16)
0.71
(16)
0.66
(31)
0.77
(1)
0.66
(31)
0.73
(6)
0.68
(26)
0.74
(2)
0.74
(2)
0.72
(10)
0.50
(43)
0.52
(41)
0.49
(44)
0.51
(42)
0.59
(37)
0.71
(16)
0.72
(10)
0.72
(10)
0.74
(2)
0.72
(10)
0.69
(23)
0.68
(26)
0.71
(16)
0.73
(6)
0.73
(6)
0.73
(6)
0.71
(16)
0.69
(23)
0.71
(16)
0.60
(35)
0.65
(33)
0.67
(30)
0.81
0.67
0.71
0.81
0.78
Figures
Figure S1. Annual Mean Absolute Difference (MAD, %) of the CMIP5 models and multimodel mean (bottom row, fifth column) with respect to ISCCP.
Figure S2. Annual Mean Difference (MD, %) of the CMIP5 models and multi-model mean
(bottom row, fifth column) with respect to PATMOS-x.
Figure S3. Annual Mean Absolute Difference (MAD, %) of the CMIP5 models and multimodel mean (bottom row, fifth column) with respect to PATMOS-x.
Figure S4. Annual Skill Score (SS) of the CMIP5 models and multi-model mean (bottom
row, fifth column) with respect PATMOS-x. The best SS correspond to whitish colors. By
contrast, warmer colors show the worst agreements according to the SS.
Figure S5. Annual and seasonal (left) MD (%) and (right) MAD (%) between of the multimodel mean with respect to PATMOS-x.
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