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Mediterranean precipitation climatology, seasonal
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cycle, and trend as simulated by CMIP5
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Colin Kelley, Mingfang Ting, Richard Seager, Yochanan Kushnir
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Supplementary Material (Appendix)
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1. Precipitation Climatology Taylor Diagram
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The precipitation patterns shown in Fig. 1 in the main text are further compared here
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(Fig. S1) using the Taylor diagram [Taylor, 2001] for each individual models (see Table
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S1 for a list of CMIP5 models used) and between the two observed datasets, using the
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GPCC as a reference. During the six-month winter (shown in blue) the GPCC and CRU
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observations share a spatial pattern correlation of nearly .95, very similar standard
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deviations and a root mean squared difference of less than 10mm/month. For those with
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similar spatial patterns, the spread in standard deviation indicates a difference in the
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domain averaged amplitude. Thus the GPCC gridded shows a slightly higher
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precipitation amplitude than in the CRU gridded data.
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The pattern correlations between CMIP5 model simulated and observed
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precipitation in winter (solid blue dots) range from .75 to .9, while the spread in standard
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deviations is 23 to 32 mm/month. The observed standard deviation lies nearly in the
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center of the CMIP5 model spread. The CMIP5 model spread is reduced compared to the
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CMIP3 models (shown as blue open circles), and the correlations improved, which can be
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seen from the multi-model means (the blue asterisks). For the summer, the CMIP5 model
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spread (solid red dots) in the standard deviation is larger than for winter, ranging from 15
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to 32 mm/month, but the pattern correlations are slightly higher. As with winter the
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CMIP5 correlations have improved over CMIP3, however there is little improvements in
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reducing the summer model spread in CMIP5 compared to CMIP3. While the
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multimodel mean CMIP5 has reduced RMSD and higher pattern correlation compared to
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that of CMIP3 in both summer and winter, the models substantially underestimate the
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standard deviation of the observed precipitation in summer due largely to the
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underestimate of the precipitation amplitude. This underestimation is likely due to
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precipitation patterns north of 45N, as Fig. 2 indicates that CMIP5 models slighly
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overestimate the Mediterranean region precipitation. Figure S1 indicates a modest but
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significant improvement of the precipitation spatial patterns and amplitude simulated in
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CMIP5 models over that in CMIP3.
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2. Externally forced trend
To better compare the externally forced portion of the total trends between models
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and observations, we apply signal-to-noise (S/N) maximization EOF to obtain a winter
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and summer signal representing the forced precipitation response. The S/N maximizing
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EOF analysis is used to remove any residual “noise” left in the multimodel mean. We
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use the preindustrial control runs, for the same models that were used to compose the
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multimodel mean, to represent the noise. The time mean for each preindustrial model run
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is removed first, and a pooled covariance matrix is created with each model’s time series
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connected end to end. We use the first 104 years of the preindustrial run for each model
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(see Kelley et al., 2011 for a more thorough discussion of the S/N maximizing EOF
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technique). The analysis is applied to Mediterranean precipitation for the six-month
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winter and summer over the domain shown in Fig. 1 from 1900-2004. A 10-year low
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pass Butterworth filter was applied to the model output prior to any analysis for the
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purpose of focusing on decadal and longer time scale variability. The S/N EOF for
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winter and summer are shown in Figure S2 in spatial patterns (EOFs) and time series
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(PCs) of the leading mode. For winter the signal indicates a zonal band of drying with
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wetting poleward, for positive values of the time series, with the zero lines near 45
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degrees north. A robust center of winter drying occurs in the eastern Mediterranean
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basin, along the Mediterranean Sea coastline of Turkey, and the multimodel mean trend
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pattern (Fig. 3), agrees quite well. The time series indicates little change before 1970,
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after which the signal begins to steadily increase. In summer the band of drying shifts
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poleward, with the strongest centers over land, particularly Portugal and northern Turkey,
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which again agrees with the multimodel mean trend in Fig.3. In this case however, there
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is a difference in sign over the Alps between the signal and multimodel mean trend
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patterns. The signal pattern indicates much stronger precipitation change over southern
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Europe relative to northern Europe. The pattern is also less zonally symmetric than for
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winter, notably so north of the Black Sea. Unlike the winter time series the summer
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signal increases linearly throughout the century.
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After regressing the GPCC observations since 1900 onto the signal timeseries, we
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reconstruct the externally forced field by multiplying the regression coefficients by the
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signal timeseries [Kelley et al., 2011),
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Pr*(x,y,t) = a(x,y) * PC1(t),
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where Pr*(x,y,t) is the reconstructed precipitation from S/N PC1 and a(x,y) is the
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regression coefficients between observed precipitation Pr(x,y,t) and PC1(t) at each grid
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point. The externally forced trend is then obtained by least-square fit on the
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reconstructed precipitation time series at each grid point, Pr*(x,y,t) from 1950-2004, and
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is shown in the middle panels of Fig.3.
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References:
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Kelley, C., M. Ting, R. Seager and Y. Kushnir (2011), The relative contributions of
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radiative forcing and internal climate variability to the late 20th Century winter drying of
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the Mediterranean region. Climate Dyn., 38(9-10): 2001-2015. doi: 10.1007/s00382-011-
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1221-z
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Taylor, Karl E. (2001), Summarizing multiple aspects of model performance in single
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diagram, J. Geophys. Res., 106, D7, 7183--7192, 2001.
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Supplemental Table S1: CMIP5 models used in this study, horizontal resolution, number of
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runs and modeling groups.
Horizontal
# historical runs
resolution
used
MODEL
(lon x lat)
Modeling center
bcc-csm1-1
2.81x2.81
3
Beijing Climate Center
CanESM2
2.81x2.81
5
Canadian Centre for Climate Modeling
and Analysis
CCSM4
1.25x.94
6
National Center for Atmospheric Research
CNRM-CM5
1.41x1.41
8
Centre National de Recherches
Meteorologiques
CSIRO-Mk3-6-0
1.88x1.88
10
Commonwealth Scientific and Industrial
Research Organisation
GFDL-CM3
2.5x2
3
Geophysical Fluid Dynamics Laboratory
GFDL-ESM2G
2.5x2
3
Geophysical Fluid Dynamics Laboratory
GFDL-ESM2M
2x2.5
1
Geophysical Fluid Dynamics Laboratory
GISS-E2-H
2.5x2
5/5 (two phys)
Goddard Institute for Space Studies
GISS-E2-R
2.5x2
6/5/5 (three phys) Goddard Institute for Space Studies
HadCM3
3.75x2.5
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Met Office Hadley Centre
HadGEM2-CC
1.88x1.25
1
Met Office Hadley Centre
HadGEM2-ES
1.88x1.25
4
Met Office Hadley Centre
inmcm4
2x1.5
1
Institute for Numerical Mathematics
IPSL-CM5A-LR
3.75x1.89
5
Institut Pierre-Simon Laplace
IPSL-CM5A-MR
2.5x1.27
1
Institut Pierre-Simon Laplace
MIROC-ESM
2.81x2.81
3
Model for Interdisciplinary Research on
Climate, Univ. of Tokyo
MIROC-ESM-CHEM 2.81x2.81
1
Model for Interdisciplinary Research on
Climate, Univ. of Tokyo
MIROC-4h
.56x.56
3
Model for Interdisciplinary Research on
Climate, Univ. of Tokyo
MIROC-5
1.41x1.41
4
Model for Interdisciplinary Research on
Climate, Univ. of Tokyo
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MPI-ESM-LR
1.88x1.88
3
Max Planck Institut
MRI-CGCM3
1.13x1.13
3/2 (two phys)
Meteorological Research Institute, Japan
NorESM1-M
2.5x1.89
3
Norwegian Climate Centre
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Fig. S1: Winter (Nov-Apr) and summer (May-Oct) Mediterranean (-10 to 50, 20 to 60)
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precipitation climatology intercomparison, 1950-2004, in a Taylor Diagram. GPCC gridded
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precipitation is used as a reference state. Blue dots are for the six-month winter (Nov-Apr) and
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red for summer (May-Oct). Open circles are for CMIP3 and solid for CMIP5 models. The
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asterisks are for observed and multi-model mean precipitation, as indicated on the plot.
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Fig. S2: Signal-to-Noise Maximizing EOF spatial pattern (top) and PC1 time series (bottom) for
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GPCC six-month winter (Nov-Apr) and summer (May-Oct) precipitation over the Great-
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Mediterranean region as shown in Fig. 1.
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