Geophysical Research Letter
Supporting Information for
Inter-model variations in projected precipitation change over the North
Atlantic: Sea surface temperature effect
Shang-Min LONG1, 2 and Shang-Ping XIE1, 2
1
Physical Oceanography Laboratory/Qingdao Collaborative Innovation Center of
Marine Science and Technology, Ocean-Atmosphere Interaction and Climate Laboratory,
Ocean University of China, Qingdao, China
2
Scripps Institution of Oceanography, University of California at San Diego, La Jolla,
California, USA
Contents of this file
Text S1
Figure S1
Tables S1 to S2
Introduction
The support information contains a text and a figure illustrating the importance of
model certainty in developing reliable rainfall projection, a table describing the 23
CMIP5 models, and a table showing the results from the first 10 modes of the intermodel SVD analysis.
Text S1
The CMIP5 multi-model ensemble-mean precipitation change and the signal-to-noise
ratio are shown in Fig. S1. The ensemble-mean change is generally smaller than the
model uncertainty in most regions but relatively high on midlatitude lands and in
coastal regions. Furthermore, the signal-to-noise ratio is very small over regions where
the agreement in the sign of rainfall change among models is low (unstippled grid
points). The domain mean (80°W-0°, 20°N-60°N, ocean only) signal-to-noise ratio is
0.63, 0.68 and 0.65 for annual, DJF and JJA means, respectively.
Fig. S1 (Left panels) The CMIP5 multi-model ensemble mean precipitation change
(color shaded) and inter-model standard deviations (black contours). (Right panels)
Signal-to-noise ratio, defined as the absolute value of the ensemble mean
precipitation change (Em) divided by the inter-model standard deviation (Std),
black contours indicate value at 1. In (d-f) grid-points where at least 15 models
agree on the sign of the ensemble mean change are marked with dots. Results are
based on annual-mean in (a and d), DJF-mean in (b and e) and JJA-mean in (c and f).
All results are normalized by the domain mean (80°W-0°, 20°N-60°N) SST warming.
Table. S1. List of 23 models from CMIP5 analyzed in this study. * and x denote nearsurface humidity and wind speed outputs are not available in the model, respectively.
Model Name
Modeling Center (or Group)
ACCESS1.0
ACCESS1.3
BCC-CSM1.1
BCC-CSM1.1(m)
BNU-ESM
CanESM2
CCSM4
CESM1-BGC
CESM1-CAM5
CMCC-CM
x
x
*
CNRM-CM5
GFDL-CM3
HadGEM2-ES
IPSL-CM5A-LR
IPSL-CM5A-MR
IPSL-CM5B-LR
MIROC-ESM
Commonwealth Scientific and Industrial Research
Organization (CSIRO) and Bureau of Meteorology
(BOM), Australia
Beijing Climate Center, China Meteorological
Administration
College of Global Change and Earth System Science,
Beijing Normal University
Canadian Centre for Climate Modelling and Analysis
National Center for Atmospheric Research
Community Earth System Model Contributions
Centro Euro-Mediterraneo per I Cambiamenti Climatici
Centre National de Recherches Météorologiques / Centre
Européen de Recherche et Formation Avancée en Calcul
Scientifique
NOAA Geophysical Fluid Dynamics Laboratory
Met Office Hadley Centre (additional HadGEM2-ES
realizations contributed by Instituto Nacional de
Pesquisas Espaciais)
Institut Pierre-Simon Laplace
MIROC-ESM-CHEM
MIROC5
MPI-ESM-MR
*
MRI-CGCM3
NorESM1-M
x
NorESM1-ME
x
Japan Agency for Marine-Earth Science and Technology,
Atmosphere and Ocean Research Institute (The
University of Tokyo), and National Institute for
Environmental Studies
Atmosphere and Ocean Research Institute (The
University of Tokyo), National Institute for
Environmental Studies, and Japan Agency for MarineEarth Science and Technology
Max-Planck-Institut für Meteorologie (Max Planck
Institute for Meteorology)
Meteorological Research Institute
Norwegian Climate Centre
Table. S2. Spatial correlation and explain variance in the first 10 inter-model SVD
modes.
Annual-mean
Spatial correlation
(ΔP, ΔSST) (ΔP, RegΔE)
DJF mean JJA mean
Explained variance
(ΔP, ΔSST)
ΔP
ΔSST
SVD1
0.79
0.89
27.7%
30.8%
0.82
0.22
SVD2
0.65
0.72
20.9%
26.7%
0.68
0.35
SVD3
0.64
0.78
12.5%
13.4%
0.74
0.11
SVD4
0.63
0.64
6.3%
5.3%
0.75
0.30
SVD5
0.64
0.73
5.6%
3.6%
0.52
-0.09
SVD6
0.52
0.65
5.1%
3.4%
0.72
0.53
SVD7
0.69
0.73
2.9%
4.8%
0.13
0.38
SVD8
0.65
0.80
2.7%
2.7%
0.41
0.30
SVD9
0.32
0.31
3.4%
2.1%
0.31
0.02
SVD10
0.50
0.61
2.0%
1.2%
0.68
0.18