Sensitivity studies with the regional climate model COSMO-CLM 5.0 over the CORDEX Central Asia Domain

Abstract

Due to its extension, geography and the presence of several underdeveloped or developing economies, the Central Asia domain of the Coordinated Regional Climate Downscaling Experiment (CORDEX) is one of the most vulnerable regions on Earth to the effects of climate changes. Reliable information on potential future changes with high spatial resolution acquire significant importance for the development of effective adaptation and mitigation strategies for the region. In this context, regional climate models (RCMs) play a fundamental role.In this paper, the results of a set of sensitivity experiments with the regional climate model COSMO-CLM version 5.0, for the Central Asia CORDEX domain, are presented. Starting from a reference model setup, general model performance is evaluated for the present day, testing the effects of singular changes in the model physical configuration and their mutual interaction with the simulation of monthly and seasonal values of three variables that are important for impact studies: near-surface temperature, precipitation and diurnal temperature range. The final goal of this study is twofold: having a general overview of model performance and its uncertainties for the considered region and determining at the same time an optimal model configuration.Results show that the model presents remarkable deficiencies over different areas of the domain. The combined change of the albedo, taking into consideration the ratio of forest fractions, and the soil conductivity, taking into account the ratio of liquid water and ice in the soil, allows one to achieve the best improvements in model performance in terms of cli-matological means. Importantly, the model seems to be particularly sensitive to those parameterizations that deal with soil and surface features, and that could positively affect the repartition of incoming radiation. The analyses also show that improvements in model performance are not achievable for all domain subregions and variables, and they are the result of a compensation effect in the different cases. The proposed better performing configuration in terms of mean climate leads to similar positive improvements when considering different observational data sets and boundary data employed to force the simulations. On the other hand, due to the large uncertainties in the variability estimates from observations, the use of different boundaries and the model internal variability, it has not been possible to rank the different simulations according to their representation of the monthly variability.This work is the first ever sensitivity study of an RCM for the CORDEX Central Asia domain and its results are of fundamental importance for further model development and for future climate projections over the area.

A Sensitivity Study of High-Resolution Climate Simulations for Greece

“…This fact could be related to the interaction of the microphysical scheme with the association of PBL (MYJ) scheme, which is in line with other studies with higher precipitation totals and more convective precipitation [89,90]. Additionally, for precipitation over areas of complex topography, wet bias is particularly found to be common to several RCMs [91,92], and is probably caused by an overestimation of orographic precipitation enhancement [93], and/or to an inaccurate PBL simulation [7,11,94]. The Taylor diagrams shown in Figure 3 provide the comparative assessment of the four different model experiments to the choice of the physical parameterizations, to simulate the seasonal spatial pattern of daily precipitation during the examined period.…”

“…This fact could be related to the interaction of the microphysical scheme with the association of PBL (MYJ) scheme, which is in line with other studies with higher precipitation totals and more convective precipitation [88,89]. Additionally, for precipitation over areas of complex topography, wet bias is particularly found to be common to several RCMs [90,91], and is probably caused by an overestimation of orographic precipitation enhancement [92], and/or to an inaccurate PBL simulation [7,11,93].…”

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

“…for the cold biases in the northwest and over the mountain ranges. Similar biases to those of ALARO-0 in summer were found by Russo et al (2019) with the RCM COSMO-CLM 5.0. In spring and summer both RCMs show a pronounced warm bias over Pakistan and the northern part of India and there is also a north-south gradient from cold to warm biases over the Arabian Peninsula.…”

“…Giot et al (2016) suggested this could be due to the strong synoptic scale forcing in winter and stable boundary layer issues. A warm bias during winter in the northeastern part of the domain was found as well by Russo et al (2019) and Ozturk et al (2012 and for the COSMO-CLM 5.0 and RegCM models, respectively. Furthermore, Fig.…”

“…Moreover, this resolution is insufficient for impact modelling and environmental assessment applications and thus higher-resolution climate data over the CAS-CORDEX region is needed (Kotova et al, 2018). Recently, Russo et al (2019) presented model evaluation results of the COSMO-CLM 5.0 model ran at 0.22° or 25 km resolution over the CAS-CORDEX region. The current study significantly extends our knowledge over the CAS-CORDEX domain by validating two different RCMs based on multiple scores for temperature (mean, minimum and maximum) and precipitation over a much longer period In order to fill the knowledge gap over Central Asia two RCMs, ALARO-0 and REMO, were run over this region at 0.22° resolution in line with the CORDEX-CORE protocol (CORDEX Scientific Advisory Team, consulted on 01/03/2019).…”