Exploring the parameter space of the COSMO-CLM v5.0 regional climate model for the Central Asia CORDEX domain

Abstract

Abstract. The parameter uncertainty of a climate model represents the spectrum of the results obtained by perturbing its empirical and unconfined parameters used to represent subgrid-scale processes. In order to assess a model's reliability and to better understand its limitations and sensitivity to different physical processes, the spread of model parameters needs to be carefully investigated. This is particularly true for regional climate models (RCMs), whose performance is domain dependent. In this study, the parameter space of the Consortium for Small-scale Modeling CLimate Mode (COSMO-CLM) RCM is investigated for the Central Asia Coordinated Regional Climate Downscaling Experiment (CORDEX) domain, using a perturbed physics ensemble (PPE) obtained by performing 1-year simulations with different parameter values. The main goal is to characterize the parameter uncertainty of the model and to determine the most sensitive parameters for the region. Moreover, the presented experiments are used to study the effect of several parameters on the simulation of selected variables for subregions characterized by different climate conditions, assessing by which degree it is possible to improve model performance by properly selecting parameter inputs in each case. Finally, the paper explores the model parameter sensitivity over different domains, tackling the question of transferability of an RCM model setup to different regions of study. Results show that only a subset of model parameters present relevant changes in model performance for different parameter values. Importantly, for almost all parameter inputs, the model shows an opposite behaviour among different clusters and regions. This indicates that conducting a calibration of the model against observations to determine optimal parameter values for the Central Asia domain is particularly challenging: in this case, the use of objective calibration methods is highly necessary. Finally, the sensitivity of the model to parameter perturbation for Central Asia is different than the one observed for Europe, suggesting that an RCM should be retuned, and its parameter uncertainty properly investigated, when setting up model experiments for different domains of study.

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

“…COSMO-crCLIM (Convection-resolving climate modeling on future supercomputing platforms) is an accelerated version of the COSMO model (based on version 4) that has been developed to run on heterogeneous hardware architectures including multicore central processing units (CPUs) and graphics processing units (GPUs) (Fuhrer et al, 2014;Schär et al, 2020). COSMO-crCLIM was adapted for climate applications (Leutwyler et al, 2017), and the current configuration includes a new groundwater formulation (Schlemmer et al, 2018).…”

The long-standing dilemma of European summer temperatures at the Mid-Holocene and other considerations on learning from the past for the future using a regional climate model

“…The atmospheric component ECHAM6 (Stevens et al, 2013) is run at T63 horizontal resolution (1.875°on a Gaussian grid) with 47 levels in the vertical. to be most sensitive for Europe (Bellprat et al, 2012a(Bellprat et al, , 2016Russo et al, 2020), and include at least one member for each of the main model schemes (i.e. turbulence, land-surface, convection, soil and radiation).…”

“…Even though climate models are deterministic, changes in their unconstrained model parameter values may lead to different results, assuming a large spectrum of outcomes. The best compromise when applying climate models to study future or past climate is to calibrate them against observations for the present and determine an optimal model configuration that can be assumed to be the best for other time periods as well (Bellprat et al, 2012a, b;Russo et al, 2019Russo et al, , 2020. However, this is just an assumption, since there is no guarantee on whether the best model configuration for the present will be the same for other periods of time characterized by different forcing.…”

Sensitivity of precipitation and temperature over the Mount Kenya area to physics parameterization options in a high-resolution model simulation performed with WRFV3.8.1

“…This circulation has also an impact on the short rains in East Africa Nicholson, 2016b). In general, moisture convergence and increased convective activity over East Africa are associated with positive sea surface temperature anomalies over the western equatorial Indian Ocean (Saji et al, 1999;Ummenhofer et al, 2009). Additionally, the Madden-Julian oscillation can impact precipitation on inter-seasonal timescales and is able to strengthen or weaken the climatological convective and dynamic zonal gradients between Southeast Asia and East Africa .…”