Performance evaluation of RegCM4 in simulating extreme rainfall and temperature indices over the CORDEX‐Southeast Asia region

Abstract

In this study, simulations over Southeast Asia (15°S–40°N, 80°–145°E) at 36 km resolution were conducted for the period 1989–2007 using the Regional Climate Model version 4.3 (RegCM4.3) under the framework of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment – Southeast Asia (or SEACLID/CORDEX‐SEA) project. Forced by the European Centre for Medium‐Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA‐Interim), 18 experiments were carried out using different combinations of cumulus parameterization and ocean flux schemes. Twelve extreme indices for both rainfall and temperature were estimated from the model output. A statistical omega index was used to measure the degree of similarity among the 18 experiments in phase and shape. The results showed relatively high similarities among the experiments over mainland Asia compared to those over the Maritime Continent for both seasonal and inter‐annual variability. The extreme rainfall indices had a lower omega compared to that of temperature. Observed daily rainfall and temperature data at 52 meteorological stations over the SEA region were used to validate the simulated extreme indices. The results showed that extreme temperature indices were generally underestimated across the region. Systematic biases for each simulated rainfall index were also identified. A score ranking system was established to compare the relative performance of the 18 experiments over the 52 selected stations objectively. It was shown that the experiments with the Massachusetts Institute of Technology (MIT)‐Emanuel scheme performed relatively better than the other convective schemes. The combination of the MIT‐Emanuel convective scheme with the Biosphere–Atmosphere Transfer scheme (BATS1e) ocean flux scheme produced the best performance.

Simulation of Present Climate over Southeast Asia Using the Non-Hydrostatic Regional Climate Model

“…In June to August (JJA), the southwest monsoon from the Indian Ocean brings high rainfall, particularly over Indochina and the Philippines while relatively dry southeast winds flow over Indonesia (Figs. 2b and 2c) as observed (e.g., Wang and LinHo 2002;Aldrian and Susanto 2003;Nguyen-Le et al 2015). Rainfall over the wet areas, e.g., along the windward side of the coastal regions and mountains in the Philippines, Indochina, Borneo and West Papua, tends to be higher in NHRCM compared with ERA-Interim, interval with 24 and 12 mode numbers in the x-and y-directions, respectively, and a weighting factor set to 1.…”

“…While this area includes the western section of the Pacific Ocean, the analysis in this paper will focus on Southeast Asia. Boundary conditions have been obtained from the 0.75° resolution ECMWF ERA-Interim reanalysis (Dee et al 2011), following the framework for model evaluation of the CORDEX project, which allows some comparison with other RCMs (Giorgi et al 2009;Juneng et al 2016;Ngo-Duc et al 2016). The model is run for 20 years, starting from April 1988 to May 2009.…”

“…In December to February (DJF), the northeasterly winds over the Philippines and Indochina, and the wet northwesterly-westerly winds over Indonesia are represented (Figs. 2e and 2f ), as well as the precipitation along the east coasts of the Philippines and Central Vietnam (e.g., Aldrian and Susanto 2003;Nguyen-Le et al 2015;Cruz et al 2016). The topographic effect on rainfall over Borneo and West Papua is captured in the model albeit overestimated (Fig.…”

“…It is an initial step in contributing to the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-SEA) Project Ngo-Duc et al 2016; see http://www.ukm.edu.my/seaclid-cordex), which aims to understand the impacts of climate change in Southeast Asia, and to provide a comprehensive range of high-resolution climate change scenarios for the region from multiple representative concentration pathway (RCP) scenarios, GCMs and RCMs. The additional use of this RCM can help address the potential source of uncertainty related to the RCM used in downscaling (e.g., Giorgi et al 2009) by comparison and consolidation with other RCM output, e.g., from the Abdus Salam International Centre for Theoretical Physics (ICTP) regional climate model (RegCM4.3), to increase the robustness in climate projection information in the region.…”

Providing future climate projections using multiple models and methods: insights from the Philippines

“…A regional downscaling activity is being conducted as part of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-SEA) project 2 (Juneng et al 2016;Ngo-Duc et al 2017;Cruz et al 2017;Chung et al 2018). With participating members from 20 institutions and 14 countries, including the Manila Observatory in the Philippines, the project aims to generate high-resolution climate change scenarios for the Southeast Asia region at 25 km resolution based on multiple RCP scenarios, GCMs and RCMs.…”