future temperature in southwest asia projected to exceed a...

Future Temperature in Southwest Asia Projected to Exceed a Threshold for Human Adaptability

Supplementary Information

Jeremy S Pal1, 2 and Elfatih A B Eltahir2

1. Department of Civil Engineering and Environmental Science, Loyola Marymount

University, Los Angeles, CA 90045

2. Ralph M. Parsons Laboratory, Massachusetts Institute of Technology, Cambridge, MA

02139.

Methods In this study, the Massachusetts Institute of Technology Regional Climate Model

(MRCM) is used1, which is based on the ICTP Regional Climate Model version 3

(RegCM3)2 with several significant enhancements3-‐6. The MRCM grid, centered at 24°N

and 47°E on a Lambert Conformal projection, consists of 144 points in the x-‐direction

and 130 points in the y-‐direction (Figure SI1). The grid cells are separated by 25-‐km in

the horizontal, and 18 sigma levels are prescribed in vertical. Output from three global

climate models (GCMs) from the Coupled model Intercomparison Project Phase 5

(CMIP5) database is used as atmospheric boundary conditions for the MRCM

integrations7. Present-‐day conditions are represented with historical greenhouse gas

(GHG) concentrations for the period 1975 through 20058. To consider the impacts of

climate change, two future GHG scenarios are considered based on the IPCC

Representative Concentration Pathway (RCP) trajectories for the period 2070 through

2100: RCP 8.5 and RCP 4.5. RCP 8.5, which represents 8.5 W/m2 of radiative forcing

values in the year 2100 relative to pre-‐industrial values, is considered a high (or

business as usual) GHG concentration scenario that does not consider any mitigation

target9. RCP 4.5, which represents 4.5 W/m2 of radiative forcing, is considered a

mitigation scenario10.

Recently, work has been carried out focusing on improving understanding of the

regional climate of Southwest Asia and on improving the skill of MRCM in simulating the

key processes in this arid region11-‐15. As much of the land surface in Southwest Asia is

characterized as desert and semi-‐desert, it is essential that the soil albedo and

Future temperature in southwest Asia projected to exceed a threshold for human adaptability

SUPPLEMENTARY INFORMATIONDOI: 10.1038/NCLIMATE2833

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emissivity be accurately characterized. To correct the high soil albedo bias (0.06 over

land) present in the default version of MRCM, albedo is prescribed based on the

NASA/GEWEX Surface Radiation Budget (SRB) Project (Figure SI2)16. In addition,

emissivities over desert and semi-‐desert are reduced from 0.95 to 0.91 and 0.93,

respectively, according to the NASA MODIS surface emissivity data17. These two

improvements significantly reduce an overall T and TW cold biases of approximately

1.5°C to less than 0.5°C over Southwest Asia when compared to the European Centre for Medium-‐Range Weather Forecasts Interim Reanalysis18 (ERA-‐Interim) data, except in

areas of complex topography (Figure SI3). The model includes a representation for the

emission, transport and deposition of mineral aerosols and their direct radiative

effects11,14. Lastly, irrigated crop and marshland land cover types are included to better

represent the surface conditions in southern Iraq.

In order to objectively compare and select GCMs for use as boundary conditions for

MRCM, we apply the following criteria:

1. The GCM provide representations of the Red Sea and Persian Gulf by use of an ocean

model of adequate resolution. Each of the GCMs selected represents ocean processes

between 0.4° and 1.11° horizontal resolution (Table SI1 and Figure SI4). While these

resolutions are less than optimal to simulate some of the key processes in the

Red Sea and Persian Gulf, they represent the best available from the CMIP5

archive.

2. The GCM accurately simulate surface T, TW and relative humidity over the Red

Sea and Persian Gulf surrounding coastal regions, as well as over all of Southwest

Asia. Output from more than 30 GCMs used in CMIP5 are objectively analyzed

and compared to both the ERA-‐Interim18 and Climate Research Unit19 datasets.

To assess the performance of each GCM, the normalized root mean square error

for each variable (T, TW, and relative humidity) is averaged separately over each

region (Persian Gulf, Red Sea, and Arabian Peninsula).

As a result of applying the above objective criteria, the three GCMs with the lowest total

sum of root mean square errors for each variable and region are selected: Community

Climate System Model version 4 (CCSM4)20, Max-‐Planck-‐Institute Earth System Model

(MPI-‐ESM)21 and Norwegian community Earth System Model (NorESM)22.



The accuracy of the simulations of future T and TW conditions by MRCM in Southwest

Asia reflects to a significant degree the accuracy of the SSTs projected by the coupled

GCMs used as boundary conditions. This is particularly true for SSTs in the Persian Gulf

and Red Sea. Although the CMIP5 GCMs used in this study are screened to resolve the

Persian Gulf and Red Sea, their representations are nevertheless spatially limited,

especially CCSM4 and NorESM1 (Table SI1 and Figure SI4). The associated limited

representation of the SSTs in the Persian Gulf and Red Sea may pose shortcomings that

should be evaluated and addressed in future studies.

TW is computed by the formulation developed by Davies-‐Jones 23. The ERA-‐Interim

reanalysis data are considered the best available combined spatial and temporal

representation of observations for the region, and are therefore used for the following

bias correction procedure:

1. The maximum 6-hour average TW and T for each day are computed for both the

MRCM hourly output and the ERA-Interim Reanalysis 3-hourly 0.75° x 0.75° data,

denoted by TWmax and Tmax, respectively.

2. The ERA-Interim Tmax and TWmax data are interpolated from the 0.75° x 0.75° horizontal grid to the 25-km MRCM grid.

3. Consistent MRCM and ERA-Interim climatologies of Tmax and TWmax are computed

for each day of the year on the MRCM 25-km grid.

4. The magnitude of the bias for each day of the year is estimated by the difference

between 30-day running means of the two climatologies.

5. The daily bias is finally applied to the MRCM daily values of Tmax and TWmax for the

present-day and future climates.

The corrections are on the order of 1-‐2°C for TWmax (Figure SI3 and Figure SI5). It

assumed that the bias in the present day is the same as the bias in the future, which is

commonly done in impacts studies24,25.

The adjusted values are in turn used to compute annual maxima and histograms at each

grid point. Since maximum values of TW in the region occur in July, August, and

September (JAS), histograms of TWmax and Tmax are computed for this period. The JAS

TWmax and Tmax values are additionally sorted to determine the 50th (median) and 95th

percentile values. The 50th percentile value is on average exceeded half of the days and



provides a measure of the mean TWmax, while the 95th percentile is exceeded on average

every 4.6 days of the three-‐month period suggestive of a typical hot TWmax summer

event.

To verify the quality of the ERA-‐Interim Reanalysis data, the observed annual maximum

TWmax is estimated for six stations from the region: two stations adjacent to the Persian

Gulf; two adjacent to the Red Sea; and two in the desert interior (Figure SI6). Present-‐

day TWmax values exceeding 31°C are observed adjacent to the Persian Gulf and the Red

Sea, and lower values are observed in the desert interior, both of which are consistent

with our simulation results (Figures 1 and 2). Furthermore, an increasing trend

significant at the 95% level is observed for each of the stations, also consistent with the

simulations. It is important to note that the station data represent point values, while

the ERA-‐Interim reanalysis data represent spatial averages over a large area (1,000s

km2). As a result, there may be some inconsistencies between the station data and ERA-‐

Interim data. The latter is the dataset used in the bias correction procedure.

Extreme Temperature

Annual Tmax increases monotonically in the different locations in the Southwest Asia

region (Figure SI8). The severest values of annual Tmax occur in Kuwait and Al Ain,

where the 60°C threshold is frequently exceeded several times by the end of the

century. In these locations, 50°C events become normal days during JAS as indicated by

the 50th percentile Tmax (Figure SI9). While Kuwait is protected from extreme TW

conditions due to is geographic position, the annual Tmax approaches 60°C in several

years, with 50th and 95th percentile summer events of 50 and 56°C, respectively

(Figure SI9). In Doha, where the trends in the annual TWmax values are also substantial,

the annual Tmax exceeds 60°C in many years, with respective 50th and 95th percentile

summer events of 45 and 50°C. On the coast of the Red Sea and in the interior regions

of Southwest Asia, Tmax conditions are projected to be less severe but still extreme. For

example, in Jeddah and nearby Mecca, annual Tmax in many years exceeds 50 and 55°C,

respectively, while maintaining annual TWmax values approaching 33 and 32°C,

respectively.



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Table SI1: Horizontal resolutions of the atmospheric and ocean components of the

three GCMs used in this study.

GCM Atmosphere Ocean

CCSM4 0.9°x1.25° 1.11°x0.27° – 0.54°

MPI-‐ESM T63/1.875° 0.4°x0.4°

NorESM 1.875°x2.5° 1°x1°



Figure SI1: Map of the 25-‐km MRCM domain including land cover (colors) and

topography (contour lines). The MRCM grid, centered at 24°N and 47°E on a Lambert

Conformal projection, consists of 144 points in the x-‐direction and 130 points in the y-‐

direction.



Figure SI2: Map of annual surface albedo for the period 1984-‐2007: (a) NASA/GEWEX

SRB and (b) MRCM with albedo improvements (land only). Averages for land excluding

the buffer zone (LND) and the Arabian Peninsula (AP) are indicated in the bottom right

corner of each plot.



Figure SI3: JAS 30-‐year climatology of mean TW for: ERA-‐Interim (left column), MRCM

forced by ERA-‐Interim data (middle column) and their difference (right column). Data

for the difference plots are interpolated to the coarser ERA-‐Interim grid. Averages for

the domain excluding the buffer zone (DOM), land excluding the buffer zone (LND) and

the Arabian Peninsula (AP) are indicated in the bottom right corner of each plot.



Figure SI4: Map of JAS SST for each of the three GCMs interpolated onto the MRCM grid

for each GHG scenario. The name of the GCM is indicated in the top left of each panel

and the GHG concentrations in the top right.



Figure SI5: Simulated bias of the average annual maximum of TWmax for each GCM

compared to the ERA-‐Interim Reanalysis data. The GCM being compared is indicated in

the top right for each panel. Average biases for the domain excluding the buffer zone

(DOM), land excluding the buffer zone (LND) and the Arabian Peninsula (AP) are

indicated in the bottom right corner of each plot. TWmax is the maximum daily value

averaged over a 6-‐hour window.



Figure SI6: Time series of the annual maximum of TWmax for six meteorological stations

in the Southwest Asia region: two stations adjacent to the Persian Gulf (Dhahran and

Abu Dhabi); two adjacent to the Red Sea (Jeddah and Jazan); and two in the desert

interior (Riyadh and Tabuk). Trends for each of the times series are significant at the

95% level according to the Mann-‐Kendall test (not shown). TWmax is the maximum daily

value averaged over a 6-‐hour window.

16#

18#

20#

22#

24#

26#

28#

30#

32#

34#

36#

1980# 1985# 1990# 1995# 2000# 2005# 2010#

Annu

al&M

axim

um&TW

max&(oC)&

Year&

Dhahran# Abu#Dhabi#

Jeddah# Jazan#

Tabuk# Riyadh#



Figure SI7: Ensemble average of the JAS 6-‐hour 30-‐year mean TW (top row) and T

(bottom row) temperatures for each GHG scenario: historical (left column), RCP 4.5

(middle column) and RCP 8.5 (right column). Averages for the domain excluding the

buffer zone (DOM), land excluding the buffer zone (LND) and the Arabian Peninsula

(AP) are indicated in the bottom right corner of each plot.



Figure SI8: Time series of the annual maximum of Tmax for each ensemble member and

GHG scenario. Blue, green and red lines represent historical (1976-‐2005), RCP 4.5

(2071-‐2100) and RCP 8.5 (2071-‐2100), respectively. Tmax is the maximum daily value

averaged over a 6-‐hour window. The background image is obtained from NASA Visible

Earth.



Figure SI9: Histogram of the summer (JAS) of Tmax for each GHG scenario’s ensemble:

historical (blue), RCP 4.5 (green) and RCP 8.5 (red). The histogram bin interval is 1.0°C

and the values on the y-‐axis indicate the number of exceedances. Values indicated

within each plot represent the 50th and 95th percentile event thresholds. Tmax is the

maximum daily value averaged over a 6-‐hour window. The background image is

obtained from NASA Visible Earth.


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