Best convective parameterization scheme within RegCM4 to downscale CMIP5 multi-model data for the CORDEX-MENA/Arab domain
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A suitable convective parameterization scheme within Regional Climate Model version 4.3.4 (RegCM4) developed by the Abdus Salam International Centre for Theoretical Physics, Trieste, Italy, is investigated through 12 sensitivity runs for the period 2000–2010. RegCM4 is driven with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim 6-hourly boundary condition fields for the CORDEX-MENA/Arab domain. Besides ERA-Interim lateral boundary conditions data, the Climatic Research Unit (CRU) data is also used to assess the performance of RegCM4. Different statistical measures are taken into consideration in assessing model performance for 11 sub-domains throughout the analysis domain, out of which 7 (4) sub-domains give drier (wetter) conditions for the area of interest. There is no common best option for the simulation of both rainfall and temperature (with lowest bias); however, one option each for temperature and rainfall has been found to be superior among the 12 options investigated in this study. These best options for the two variables vary from region to region as well. Overall, RegCM4 simulates large pressure and water vapor values along with lower wind speeds compared to the driving fields, which are the key sources of bias in simulating rainfall and temperature. Based on the climatic characteristics of most of the Arab countries located within the study domain, the drier sub-domains are given priority in the selection of a suitable convective scheme, albeit with a compromise for both rainfall and temperature simulations. The most suitable option Grell over Land and Emanuel over Ocean in wet (GLEO wet) delivers a rainfall wet bias of 2.96 % and a temperature cold bias of 0.26 °C, compared to CRU data. An ensemble derived from all 12 runs provides unsatisfactory results for rainfall (28.92 %) and temperature (−0.54 °C) bias in the drier region because some options highly overestimate rainfall (reaching up to 200 %) and underestimate temperature (reaching up to −1.16 °C). Overall, a suitable option (GLEO wet) is recommended for downscaling the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model database using RegCM4 for the CORDEX-MENA/Arab domain for its use in future climate change impact studies.
The employment of a regional climate model (RCM) is invaluable for its capabilities in capturing the local climate in detail, which is essential in assessing the impacts of climate change at national and regional levels. One such activity in employing different RCMs, in order to produce a multiple member ensemble of downscaled data of Coupled Model Intercomparison Project Phase 5 (CMIP5) archives, was initiated by the World Climate Research Program (WCRP) through a coordinated effort with the international regional downscaling community. The initiative taken by WCRP is named the COordinated Regional climate Downscaling EXperiment (CORDEX) (http://www.meteo.unican.es/en/projects/CORDEX) with the aim to generate regional climate change projections as inputs for impact and adaptation studies. Meanwhile, a joint regional initiative of the Arab League and the United Nations called Regional Initiative for the assessment of climate change impacts on water resources and socioeconomic vulnerability in the Arab Region (RICCAR) was working on recognizing the vulnerability of the Arab region to climate change. Because of the commonality in various goals of both the initiatives, RICCAR joined the regional climate modeling activity of CORDEX. Afterwards, it was decided to conduct further activities in downscaling the CMIP5 database using an RCM as per CORDEX protocols. In this connection, among various others RCMs, the International Centre for Theoretical Physics, Trieste, Italy’s REGional Climate Model version 4.3.4 (RegCM4; Giorgi et al. 2012) was considered as a better option due to its good performance over different domains around the globe. It is worth mentioning here that RegCM4 has been used in climate downscaling over many regions of the world, such as in Africa (Anyah and Semazzi 2007), Asia (Dash et al. 2006; Rahman et al. 2007a, b), Europe (Cossarini et al. 2008; Salon et al. 2008), the Middle East (Almazroui 2012; Islam and Almazroui 2012; Artale et al. 2010), and the USA (O'Brien et al. 2012; Chen et al. 2003).
For the application of a RCM over a new region, along with the selection of an appropriate domain, the key challenge is the selection of suitable set of parameterization schemes. In RegCM4, there are multiple options for convective and land surface schemes available; hence, it becomes a matter of extremely importance to select best suite among them. Recently, Almazroui (2015) assessed the suitability of the CORDEX domains for climate simulation using RegCM4 for the Arab countries. He discussed the limitations of the different CORDEX domains because none of them covers the large-scale circulation patterns from the Mediterranean Sea to Indian Ocean particularly well which control the climate of the Arab countries. Accordingly, he suggested a new CORDEX-MENA/Arab domain (27°W–76°E, 7°S–45°N) with the BATS land scheme within RegCM4. He also emphasized for a detail analysis in selection of suitable convective parameterization scheme available in RegCM4. Therefore, for the application of a model in the new CORDEX-MENA/Arab domain, the selection of best convective parameterization scheme within RegCM4 becomes a high-priority issue, one that is vital for downscaling the climate scenarios.
The key question is why we need to downscale CMIP5 datasets. In general, downscaling is the process of translating climate projections from coarse resolutions (typical of GCMs) to finer resolutions, i.e., those that are suitable for assessing impacts using various methods (Brown et al. 2008). It is well known that the skill of GCM projections (in terms of rainfall and temperature) generally decreases along with the spatial and temporal scales under consideration. However, GCMs have more skill over the continental scale. In any given area, the climate response pattern generally depends substantially on the atmospheric circulation patterns, and the distribution of rainfall and temperature depends on this local climate (Islam et al. 2007). In elaborating this local climate, downscaling the GCM outputs is essential for delivering finer detail vis-à-vis the patterns of the climatic variables; this is particularly useful in application-oriented tasks.
Resolution in the CMIP5 GCMs is typically of the order of 1–2° (lat/long). However, GCMs cannot be considered reliable on the scale of individual grid boxes, which constrains the utility of these model outputs in climate change impact studies. Therefore, we need to downscale to finer-scale climate scenarios, which are applicable in vulnerability and adaptation studies at the national level. This can be done by dynamical downscaling using an RCM that transforms the GCM outputs into a finer resolution; this is an accepted procedure (Giorgi and Hewitson 2001; Jones et al. 2004; Pal et al. 2007). Importantly, downscaling is partly dependent on the ability of GCMs to successfully project the climate change signal; therefore, any downscaling performance by an RCM is influenced by the GCM signals (Almazroui 2011).
Prior to downscaling the CMIP5 projections, the level of realism as well as understanding the biases in the present climate is important. The biases among the convective parameterization schemes within RegCM4 must be investigated and validated against reference datasets. Once confidence in the present datasets is gained, particularly in terms of climate mean and the variability of rainfall and temperature, the same criteria in RegCM4 can be applied for downscaling the future climate. As mentioned earlier, Almazroui (2015) suggested the new domain and mentioned the best land surface scheme within RegCM4 in the simulation of rainfall and temperature for the Arab countries. This paper identifies the best convective parameterization scheme within RegCM4 to downscale CMIP5 data for the present climate in the CORDEX-MENA/Arab domain as preparation for downscaling the projections.
2 Data and methodology
2.1 Model description and experiment setup
In RegCM4, there are four options for representing cumulus convection, which are (i) the simplified version of the Kuo-type scheme of Anthes (1977), as described by Anthes et al. (1987); (ii) the most used scheme called Grell (1993) in the implementation of Giorgi et al. (1993); (iii) the MIT scheme (EMAN; Emanuel 1991; Emanuel and Živković-Rothman 1999); and (iv) a mixed convection scheme that has the capability of running different convection schemes over land and ocean (Giorgi et al. 2012). The Grell scheme has two different closures, viz: an Arakawa and Schubert (1974) type closure (GAS) and a Fritsch and Chappell (1980) type closure (GFC). The mixed convection preliminary tests conducted over the CORDEX framework suggested that the Grell scheme over land and the EMAN scheme over the oceans (GLEO) might be the most suitable option to pursue (Giorgi et al. 2012).
In RegCM4, the radiative transfer scheme follows the global model CCM3 (Kiehl et al. 1996), the planetary boundary layer (PBL) processes follow the modified Holtslag et al. (1990) and the University of Washington’s scheme (Grenier and Bretherton 2001; Bretherton et al. 2004), the land surface process follows the biosphere-atmosphere transfer scheme (BATS) of Dickinson et al. (1993) and the Community Land Model version CLM3.5 (Tawfik and Steiner 2011), and the prognostic sea surface temperatures (SST) scheme is as described by Zeng et al. (1998). Details of the RegCM4 model physics can be seen in Giorgi et al. (2012).
In order to find the best convective parameterization scheme within RegCM4, we have conducted 12 sensitivity experiments in the CORDEX-MENA/Arab domain (27°W–76°E and 7°S–45°N) with 50-km domain resolution. RegCM4 was driven with 0.75° resolution ERA-Interim (hereafter referred to ERA-Int) boundary conditions (Simmons et al. 2006) obtained from the European Centre for Medium-range Weather Forecasting (ECMWF) website for the period 2000–2010 (2000 is the spin-up year). A 10-year simulation is acceptable because for many climatic parameters, shorter averaging periods such as 10 years often perform as adequately as 30-year averaging periods (WMO 2007). The GLEO convective scheme is used to drive RegCM4 in the normal, wet, and dry options. These three options are the threshold-based options within RegCM4 in tuning precipitation simulation for a region. Therefore, three runs are completed for the GLEO scheme. Likewise, the EMAN, GFC, and GAS schemes are employed to complete another nine runs (normal, wet, and dry for each scheme) to fulfill 12 sensitivity experiments.
2.2 Data analysis
RegCM4 outputs are transferred to daily, monthly, seasonal, annual, and decadal scales. The ERA-Int driving field is also used to assess the model’s performance. To fully comprehend the reliability of the RegCM4 outputs, CRU data (CRU TS3.21; New et al. 2000; Mitchell and Jones 2005) are considered as a reference. The main climatic parameters (rainfall and temperature) are analyzed in detail. Moreover, other meteorological elements, such as pressure, wind, specific humidity, and evaporation, are also analyzed. Runoff and soil water are also taken into account in assessing the model’s performance. Statistical measures, such as correlation coefficient, bias, root mean square difference, and standard deviation, are employed. Box-whisker plots and Taylor diagrams are also employed in summarizing the statistical measures for the selection of a suitable convective scheme. For easy reference in understanding the rainfall and temperature of the study domain, analyses are performed separately for the wetter region, the drier region, and the entire domain. Among the studied 12-run options and for simplicity in deciding upon the most suitable scheme, priority is given to the rainfall and temperature biases of the drier region because most of the Arab countries in the CORDEX-MENA/Arab domain are situated in this area.
3.1 Rainfall climatology
Figure 3 displays the distribution of RegCM4-simulated annual rainfall bias with respect to the CRU data. The patterns are similar to the bias of the ERA-Int driving forcings (see Fig. 2). However, variations among the data sources (simulated and driving) are observed in different sub-domains (I to XI, Fig. 1) throughout the domain. Scheme to scheme variations in rainfall simulation by RegCM4 with reference to the CRU data are also noticed. The options in each group of convective schemes (i.e., normal, wet, and dry) for GLEO, EMAN, GFC, and GAS do indeed have similarities, but the scheme to scheme variations are large. The EMAN scheme has a large wet bias over almost the whole of the domain for the normal, wet, and dry options, whereas the other schemes (GLEO, GFC, and GAS) show (overall) a little wet bias, except for a few southern sub-domains of dry bias. Thus, the question arises, which convective scheme, and particularly which option within RegCM4, is better for downscaling coarse-resolution GCM data. To answer this question, the best convective parameterization scheme within RegCM4 is identified through objective analyses in order to recommend it for use in downscaling CMIP5 multi-model data for the CORDEX-MENA/Arab domain is discussed in Section 3.3.
3.2 Temperature climatology
3.3 Selection of convective scheme for CORDEX-MENA/Arab domain
In the case of temperature simulation by RegCM4, almost all the options follow the annual cycle; however, underestimations are observed in December–February and June–August for many of the options (Fig. 6b). Careful inspection reveals that the EMAN dry option overestimates temperature in July–September. Hence, time series of interannual monthly rainfall and temperature data cannot assist in deciding upon the best convective scheme option within RegCM4, although it clearly indicates the patterns of interannual variation, which follow the CRU observations relatively well.
Best convective scheme option within RegCM4 at different sub-domains and regions in the CORDEX-MENA/Arab domain
For simplicity in searching for the suitable convective option (common for both rainfall and temperature), four sub-domains (III, V, VI, and IX) having rainfalls above the average for all 11 sub-domains are designated as a wetter region, and the other seven sub-domains (I, III, IV, VII, VIII, X, and XI) having rainfalls below the average are designated as a drier region. It is worth mentioning that most of the Arab countries are situated under the drier region of the study domain. In determining the most suitable option, some statistical measures, namely, bias, correlation coefficient, root mean square difference (RMSD), and standard deviation, for the wetter and drier regions are presented here.
Rainfall and temperature biases corresponding to each convective parameterization scheme options within RegCM4 with respect to CRU data for the CORDEX-MENA/Arab domain (All), wetter, and drier regions
Rainfall bias (%)
Temperature bias (°C)
Various convective parameterization schemes within RegCM4 show that many of them are not suitable in the simulation of rainfall and temperature climatology for a particular region as well as for the entire CORDEX-MENA/Arab domain. However, a few of them are found suitable in constructing a high resolution climate database to use in application-oriented tasks. Among the 12 options investigated in this study, GFC is found suitable in rainfall simulation, and GLEO dry is suitable in temperature simulation for the entire domain, although these options vary from region to region (sub-domain to sub-domain, see Table 1). However, giving priority to the drier region, where most of the Arab countries are located, GLEO wet comes up as the best option, i.e., common for both rainfall and temperature simulations. To investigate the reason for the better performance of a specific convective scheme option, the available climatic parameters are analyzed and compared with the ERA-Int driving data.
Through 12 sensitivity experiments for various convective parameterization scheme options within RegCM4, the selection of the best option for downscaling CMIP5 global datasets for the CORDEX-MENA/Arab domain is suggested. A suitable convective scheme option for wetter region, drier region, and each of 11 sub-domains (8° × 8° boxes) is also suggested throughout the analysis domain.
The most suitable convective scheme option within RegCM4 varies from region to region. However, for the entire CORDEX-MENA/Arab domain, the Grell convective scheme with Fritsch-Chappell closure (GFC) is found to be better for rainfall simulation, as it has the lowest bias (0.37 %) compared to the CRU data. For temperature, Grell over land and Emanuel over water with the dry option (GLEO dry) is found to be better, as it has the lowest bias (−0.05 °C). Among the all options, Emanuel (EMAN) is found to have the highest overestimation (183.64 %) in rainfall simulation, while GFC wet shows the largest cold bias (−0.95 °C) in temperature simulation. Ensemble (from the 12 convective scheme options) is found to have large rainfall (22.35 %) and temperature (−0.48) bias. The sources of these biases seem to emanate from the differences in surface pressure, water vapor, and low level wind speeds in RegCM4 simulations as compared to the driving fields. Giving priority to the drier region, where most of the Arab countries are located, the GLEO wet option is found to be suitable for both rainfall (2.96 %) and temperature (0.26 °C) simulations when using RegCM4. Therefore, the single option GLEO wet in downscaling CMIP5 data using RegCM4 is suggested for the CORDEX-MENA/Arab domain; this is cost effective and convenient for many climate research centers where computational facilities are not quite adequate. However, for the application of RegCM4 on specific region, especially at national level within the CORDEX-MENA/Arab domain, the model should be driven with its own individual most suitable option, as discussed in this paper and presented in Table 1.
The authors would like to acknowledge the grant by the NSTIP strategic technologies program in the Kingdom of Saudi Arabia– Project No. 12-ENV3197-03 to complete this work– and the Science and Technology Unit, King Abdulaziz University for technical support. The ICTP, Trieste, Italy, is acknowledged for providing RegCM4 and CRU data wete acquired from their website. The League of Arab States (LAS) and the United Nations Economic and Social Commission for Western Asia (UN-ESCWA) are also acknowledged for leading and facilitating the “Regional Initiative for the Assessment of Climate Change Impacts on Water Resources and Socio-economic Vulnerability in the Arab Region (RICCAR)”.
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