Impact of lateral boundary conditions on precipitation and temperature extremes over South Korea in the CORDEX regional climate simulation using RegCM4

2013 ◽  
Vol 49 (4) ◽  
pp. 497-509 ◽  
Author(s):  
Seok-Geun Oh ◽  
Myoung-Seok Suh ◽  
Dong-Hyun Cha
2005 ◽  
Vol 18 (7) ◽  
pp. 917-933 ◽  
Author(s):  
Wanli Wu ◽  
Amanda H. Lynch ◽  
Aaron Rivers

Abstract There is a growing demand for regional-scale climate predictions and assessments. Quantifying the impacts of uncertainty in initial conditions and lateral boundary forcing data on regional model simulations can potentially add value to the usefulness of regional climate modeling. Results from a regional model depend on the realism of the driving data from either global model outputs or global analyses; therefore, any biases in the driving data will be carried through to the regional model. This study used four popular global analyses and achieved 16 driving datasets by using different interpolation procedures. The spread of the 16 datasets represents a possible range of driving data based on analyses to the regional model. This spread is smaller than typically associated with global climate model realizations of the Arctic climate. Three groups of 16 realizations were conducted using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) in an Arctic domain, varying both initial and lateral boundary conditions, varying lateral boundary forcing only, and varying initial conditions only. The response of monthly mean atmospheric states to the variations in initial and lateral driving data was investigated. Uncertainty in the regional model is induced by the interaction between biases from different sources. Because of the nonlinearity of the problem, contributions from initial and lateral boundary conditions are not additive. For monthly mean atmospheric states, biases in lateral boundary conditions generally contribute more to the overall uncertainty than biases in the initial conditions. The impact of initial condition variations decreases with the simulation length while the impact of variations in lateral boundary forcing shows no clear trend. This suggests that the representativeness of the lateral boundary forcing plays a critical role in long-term regional climate modeling. The extent of impact of the driving data uncertainties on regional climate modeling is variable dependent. For some sensitive variables (e.g., precipitation, boundary layer height), even the interior of the model may be significantly affected.


2011 ◽  
Vol 5 (1) ◽  
pp. 96-105 ◽  
Author(s):  
Shuyan Liu ◽  
Xin-Zhong Liang ◽  
Wei Gao ◽  
Yuxiang He ◽  
Tiejun Ling

The dependence of the RegCM3 (Regional Climate Model version 3) downscaling skill on initial conditions (ICs) and lateral boundary conditions (LBCs) are investigated for the 1998 summer flood along the Yangtze River Basin in China. The effect of IC uncertainties is depicted by 15 realizations starting on each consecutive day from April 1 to 15 while all ending on September 1, 1998 with identical driving LBCs, analyses are based on June, July and August simulations. The result reveals certain IC effect on precipitation for daily evolution but little for summer mean geographical distribution. In contrast, the effect of LBCs uncertainties as represented by four different reanalyses are notably larger in both daily evolution and summer mean distribution. The ensemble average among either 15 IC realizations or 4 LBC runs does not show important skill improvement over the individuals. None of the RegCM3 simulations (including the ensemble means) captured the observed main rain band along the Yangtze River Basin. This general failure suggests the need for further model physics improvement.


2012 ◽  
Vol 25 (2) ◽  
pp. 638-656 ◽  
Author(s):  
Rebecca L. Gianotti ◽  
Dongfeng Zhang ◽  
Elfatih A. B. Eltahir

Abstract This paper describes an assessment of the Regional Climate Model, version 3 (RegCM3), coupled to two land surface schemes: the Biosphere–Atmosphere Transfer System, version 1e (BATS1e), and the Integrated Biosphere Simulator (IBIS). The model’s performance in simulating precipitation over the Maritime Continent was evaluated against the 3-hourly Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 product. It is found that the model suffers from three major errors in reproducing the observed rainfall histogram: underestimation of the frequency of dry periods, overestimation of the frequency of low-intensity rainfall, and underestimation of the frequency of high-intensity rainfall. Additionally, the model does not accurately reproduce the observed timing of the diurnal rainfall peak, particularly over land. These four errors persisted regardless of the choice of lateral boundary conditions, convective parameterization scheme, or land surface scheme. The magnitude of the wet–dry bias in the simulated volumes of rainfall was, however, strongly dependent on the choice of the convection scheme and lateral boundary conditions. The Grell convection scheme with Fritsch–Chappell closure was the best performing of the convection schemes, having the smallest error magnitudes in both the rainfall histogram and average diurnal cycle, and also having good representation of the land surface energy and evapotranspiration components. The 40-yr ECMWF Re-Analysis (ERA-40) was found to produce better simulations of observed rainfall when used as lateral boundary conditions than did the NCEP–NCAR reanalysis. Discussion of the nature of the major model errors is provided, along with some suggestions for improvement.


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