scholarly journals Addressing the Issue of Systematic Errors in a Regional Climate Model

2007 ◽  
Vol 20 (5) ◽  
pp. 801-818 ◽  
Author(s):  
Vasubandhu Misra
Keyword(s):  
Regional Climate Model ◽  
Bias Correction ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Systematic Errors ◽  
Driver Model ◽  
South American ◽  
Driving Model

Abstract A methodology is proposed in which a few prognostic variables of a regional climate model (RCM) are strongly constrained at certain wavelengths to what is prescribed from the bias-corrected atmospheric general circulation model (AGCM; driver model) integrations. The goal of this strategy is to reduce the systematic errors in a RCM that mainly arise from two sources: the lateral boundary conditions and the RCM errors. Bias correction (which essentially corrects the climatology) of the forcing from the driving model addresses the former source while constraining the solution of the RCM beyond certain relatively large wavelengths in the regional domain [also termed as scale-selective bias correction (SSBC)] addresses the latter source of systematic errors in RCM. This methodology is applied to experiments over the South American monsoon region. It is found that the combination of bias correction and SSBC on the nested variables of divergence, vorticity, and the log of surface pressure of an RCM yields a major improvement in the simulation of the regional climate variability over South America from interannual to intraseasonal time scales. The basis for such a strategy is derived from a systematic empirical approach that involved over 100 regional seasonal climate integrations.

scholarly journals Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa
Keyword(s):  
Regional Climate Model ◽  
Air Temperature ◽  
General Circulation ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Horizontal Resolution ◽  
Temperature And Precipitation ◽  
Current Climate

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.

scholarly journals Evaluating the representation of Australian East Coast Lows in a regional climate model ensemble

2016 ◽  
Vol 66 (2) ◽  
pp. 108
Author(s):  
Alejandro Di Luca ◽  
Jason P. Evans ◽  
Acacia S. Pepler ◽  
Lisa V. Alexander ◽  
Daniel Argüeso
Keyword(s):  
Regional Climate Model ◽  
General Circulation ◽  
East Coast ◽  
Climate Model ◽  
Spatial Scales ◽  
Regional Climate ◽  
Circulation Model ◽  
Future Projections ◽  
Model Simulations ◽  
Observational Uncertainty

Due to their large influence on both severe weather and water security along the east coast of Australia, it is increasingly important to understand how East Coast Lows (ECLs) may change over coming decades. Changes in ECLs may occur for a number of reasons including changes in the general atmospheric circulation (e.g. poleward shift of storm tracks) and/or changes in local conditions (e.g. changes in sea surface temperatures). Numerical climate models are the best available tool for studying these changes however, in order to assess future projections, climate model simulations need to be evaluated on how well they represent the historical climatology of ECLs. In this paper, we evaluate the performance of a 15-member ensemble of regional climate model (RCM) simulations to reproduce the climatology of cyclones obtained using three high-resolution reanalysis datasets (ERA-Interim, NASA-MERRA and JRA55). The performance of the RCM ensemble is also compared to results obtained from the global datasets that are used to drive the RCM ensemble (four general circulation model simulations and a low resolution reanalysis), to identify whether they offer additional value beyond the driving data. An existing cyclone detection and tracking algorithm is applied to derive a number of ECL characteristics and assess results at a variety of spatial scales. The RCM ensemble offers substantial improvement on the coarse-resolution driving data for most ECL characteristics, with results typically falling within the range of observational uncertainty, instilling confidence for studies of future projections. The study clearly highlights the need to use an ensemble of simulations to obtain reliable projections and a range of possible future changes.

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