Sensitivity of Southeast Asia rainfall simulations to cumulus and air-sea flux parameterizations in RegCM4

Abstract

We investigated the performance of RegCM4 in simulating rainfall over Southeast Asia with different combinations of deep-convection and air−sea flux parameterization schemes. Four different gridded rainfall datasets were used for the model assessment. In general, the simulations produced dry biases over the equatorial region and slightly wet biases over mainland Indo-China, except those experiments with the MIT Emanuel cumulus schemes, in which large positive rainfall biases were simulated. However, simulations with the MIT schemes were generally better at reproducing annual rainfall variations. The simulations were not sensitive to the treatment of air−sea fluxes. While the simulations generally produced the rainfall climatology well, all simulations showed stronger inter-annual variability compared to observations. Nevertheless, the time evolution of the inter-annual variations was well reproduced, particularly over the eastern Maritime Continent. Over mainland Southeast Asia, all simulations produced unrealistic rainfall anomaly responses to surface temperature. The lack of summer air−sea interactions in the model resulted in enhanced oceanic forcing over the regions, leading to positive rainfall anomalies during years with warm ocean temperature anomalies. This shortcoming in turn caused much stronger atmospheric forcing on the land surface processes compared to that of the observation. A robust score-ranking system was designed to rank the simulations according to their performance in reproducing different aspects of rainfall characteristics. The results suggest that the simulation with the MIT Emanuel convective scheme and the BATS1e air−sea flux scheme performs better overall compared to the rest of the simulations.

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

“…3b). Compared with ERA-Interim, rainfall patterns can also be more correlated in NHRCM over the Maritime Continent, such as in Peninsular Malaysia (R13), but may also be less correlated in other regions, similar with Juneng et al (2016). However, APH-RODITE is noted to have lower precipitation values over high terrain (e.g., Vietnam, as noted in Kieu-Thi et al (2016)) and the equatorial area, which may be due to differences involved in data processing (Yatagai et al 2012;Juneng et al 2016).…”

“…A regional analysis is also conducted over 20 subregions in the domain (see Fig. 1) defined by Juneng et al (2016), which was based on precipitation climatology in the literature. Figure 2 shows the ability of NHRCM to represent seasonal patterns in rainfall and winds over Southeast Asia, consistent with the findings of Cruz et al (2016) and Kieu-Thi et al (2016).…”

“…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.…”

Validation of the WRF regional climate model over the subregions of Southeast Asia: climatology and interannual variability

“…In recent years, many attempts have been made to understand regional climate variability over SE Asia using regional climate models (e.g. Aldrian et al 2004, Francisco et al 2006, Im et al 2008, Phan et al 2009, Takahashi et al 2009, 2010, Chotamonsak et al 2011, Raktham et al 2015, Raghavan et al 2016, Juneng et al 2016. To the authors' knowledge, there are no comprehensive studies available evaluating the performance of an RCM over SE Asia and its subregions for different seasons of the year.…”

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.…”