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ABSTRACT Stability indices provide simple metrics to characterize tropospheric states favouring convection. Not only for regions where precipitation is mainly related to convective processes, important aspects of the climate comprising information from different levels and variables can therefore be summarized in scalar metrics. Although the linkage between tropospheric stability and convective precipitation is blurred by additional prerequisites often not resolved in atmospheric models, analysis of stability indices from global climate models (GCMs) provides a more process-orientated assessment than the separate analysis of the individual climate variables. This paper presents an assessment of GCM capabilities to simulate tropospheric stability on the Arabian Peninsula. Therefore, six stability indices (K-Index, Total Totals Index, Vertical Totals Index, Showalter Index, SWEAT and Cross Totals Index) were calculated for several GCMs from the Climate Model Intercomparison Project 3 archive for three locations. GCM indices were compared with reanalysis data from the National Centers for Environmental Prediction in collaboration with the National Center for Atmospheric Research as well as radiosoundings from the Integrated Global Radiosounding Archive. Comparison was done by means of a classification approach based on quantile values of the index distribution. Input parameters of the indices were also analysed and biases for indices as well as input parameters were identified. There are biases found for the different indices which can be attributed to some extent to biases of the input parameters. There is no input parameter which is biased in the same direction for all indices and locations. Due to the variability of the results, rankings of the models are characterized by large rank differences so that there is no overall best performing model. Nevertheless, this study provides some insight in the performance of the GCMs to simulate tropospheric stability at individual locations and so presents an alternative method of model performance assessment. [ABSTRACT FROM AUTHOR]

In this article, the climatological state and the seasonal variability of the Arabian heat low (AHL) and the intertropical discontinuity (ITD) are investigated over the Arabian Peninsula using the 1979–2019 ERA‐5 reanalysis data. The AHL is a summertime feature, mostly at 15°–35°N and 40°–60°E, exhibiting a clear strengthening over the last four decades in line with the observed increase in surface temperature. However, no clear shift in its position is detected. The AHL, driven by both thermodynamic and dynamic forcing, is broader and stronger during daytime and exhibits considerable variability on day‐to‐day timescales, likely due to the convection associated with the Asian summer monsoon. The ITD is the boundary between the hot and dry desert air and the cooler and more moist air from the Arabian Sea. It lies along the Arabian Peninsula's southern coastline in the cold season but reaches up to 28°N between 50° and 60°E in the summer months. While in the former it has a rather small diurnal variability; in the latter it shows daily fluctuations of up to 10° in latitude. The presence of the Sarawat Mountains over southwestern Saudi Arabia precludes a northward migration of the ITD in this area. The ITD exhibited a weak northward migration in the 41‐year period, likely due to the increased sea surface temperatures in the Arabian Sea. On inter‐annual timescales, the El Niño‐Southern Oscillation, the Indian Ocean Dipole, and solar‐geomagnetic effects play an important role in the AHL's and ITD's variability. [ABSTRACT FROM AUTHOR]

Climate change is known as one of the key challenges of the 21st century for sustainable agricultural development over Southwest Asia. However, not much is known about the way that climate changes might affect precipitation, temperature, and climate zones as their consequence over Southwest Asia. Here we have analysed probable changes in modified Thornthwaite climate zones by using monthly temperature and precipitation data from 320 meteorological stations during the historical period of 1971–2015, as well as the future projections of 17 GCMs (General Circulation Models) outputs under the RCP4.5 and RCP8.5 scenarios in two future periods, 2041–2070 and 2071–2100. The CMIP5 climate projections were bias corrected using the correction factors derived in the historical period and applied to simulate future climatic conditions over Southwest Asia. Results derived from multi model ensemble projections of precipitation and temperature indicated that the regional mean annual temperature by the future period of 2071–2100 is expected to increase by 2.4 and 3.8°C, under RCP4.5 and RCP8.5, respectively. Also, except for the southern and eastern parts of the Arabian Peninsula, by 2071–2100, the mean annual precipitation would significantly decrease by on average 6.2 and 7.5%, under RCP4.5 and RCP8.5, respectively. Computing climate types based on averages from three climatic periods (1971–2015, 2041–2070, and 2071–2100) showed that Southwest Asia tends to become warmer and dryer. For example, by the end of the 21st century, the percentage of the area occupied by the torrid‐arid climate type (which already covers 13.8% of the total area) would be 29.3 and 36.4% under RCP4.5 and RCP8.5, respectively. These changes are important because they would definitely have profound ecological, hydrologic, and social consequences and may affect the basic components of sustainable agricultural systems like crop and livestock productions. [ABSTRACT FROM AUTHOR]

ABSTRACT The interannual rainfall variability derived from the 22 Global Climate Model ( GCM) simulations of the Intergovernmental Panel on Climate Change ( IPCC) Fourth Assessment Report ( AR4) for the duration 1979-2000 is analysed and compared with the gridded observed dataset over the Arabian Peninsula. The annual cycle of the rainfall derived from these models is validated for the entire Arabian Peninsula, and separately for its two sub-regions, named northern and southern Arabian Peninsula. The spatial patterns of the rainfall and the mean sea level pressure are analysed to judge the ability of the models to simulate the mean climatology of the Peninsula. This analysis reveals that out of the 22 IPCC AR4 GCM multi-model datasets, only one group (composed of 5 models) is relatively better than all the others in simulating the interannual variability of the wet season rainfall for the northern sub-region, and another group (also composed of 5 models) is likewise for the dry season rainfall climatology of the southern sub-region, compared with the gridded dataset. The above two groups of models tend to fall within one-sigma standard deviation of the mean seasonal rainfall derived from the gridded dataset. Moreover, only one model [ CCCMA-CGCM3 ( T47) from Canada] is found to be relatively better in simulating the rainfall climatology for both the wet and the dry seasons (i.e. for the northern and the southern sub-regions) simultaneously, compared with the observed data. [ABSTRACT FROM AUTHOR]