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Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22° resolution over the CORDEX Central Asia domain

Evaluation of regional climate models ALARO-0 and REMO2015 at 0.22° resolution over the CORDEX Central Asia domain
Abstract. To allow for climate impact studies on human and natural systems, high-resolution climate information is needed. Over some parts of the world plenty of regional climate simulations have been carried out, while in other regions hardly any high-resolution climate information is available. The CORDEX Central Asia domain is one of these regions, and this article describes the evaluation for two regional climate models (RCMs), REMO and ALARO-0, that were run for the first time at a horizontal resolution of 0.22∘ (25 km) over this region. The output of the ERA-Interim-driven RCMs is compared with different observational datasets over the 1980–2017 period. REMO scores better for temperature, whereas the ALARO-0 model prevails for precipitation. Studying specific subregions provides deeper insight into the strengths and weaknesses of both RCMs over the CAS-CORDEX domain. For example, ALARO-0 has difficulties in simulating the temperature over the northern part of the domain, particularly when snow cover is present, while REMO poorly simulates the annual cycle of precipitation over the Tibetan Plateau. The evaluation of minimum and maximum temperature demonstrates that both models underestimate the daily temperature range. This study aims to evaluate whether REMO and ALARO-0 provide reliable climate information over the CAS-CORDEX domain for impact modeling and environmental assessment applications. Depending on the evaluated season and variable, it is demonstrated that the produced climate data can be used in several subregions, e.g., temperature and precipitation over western Central Asia in autumn. At the same time, a bias adjustment is required for regions where significant biases have been identified.
PARAMETERIZATION, Regional climate, China, COSMO-CLM, Performance, Seasonal variation, Qinghai-Xizang Plateau, ENSEMBLE, Parameterization, Air temperature, CHANGE PROJECTIONS, Annual cycle, Downscaling, Precipitation assessment, TEMPERATURE, Snow cover, Historical climate, QE1-996.5, Multidisciplinary, Change projections, Atmosphere, Environmental assessment, HISTORICAL CLIMATE, Temperature, Euro-cordex, Precipitation climatology, Climate effect, Geology, Cosmo-clm, Seasonality, PERFORMANCE, CMIP, ATMOSPHERE, PRECIPITATION CLIMATOLOGY, Physics and Astronomy, Earth and Environmental Sciences, EURO-CORDEX, Ensemble, Geosciences
PARAMETERIZATION, Regional climate, China, COSMO-CLM, Performance, Seasonal variation, Qinghai-Xizang Plateau, ENSEMBLE, Parameterization, Air temperature, CHANGE PROJECTIONS, Annual cycle, Downscaling, Precipitation assessment, TEMPERATURE, Snow cover, Historical climate, QE1-996.5, Multidisciplinary, Change projections, Atmosphere, Environmental assessment, HISTORICAL CLIMATE, Temperature, Euro-cordex, Precipitation climatology, Climate effect, Geology, Cosmo-clm, Seasonality, PERFORMANCE, CMIP, ATMOSPHERE, PRECIPITATION CLIMATOLOGY, Physics and Astronomy, Earth and Environmental Sciences, EURO-CORDEX, Ensemble, Geosciences
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