scholarly journals Assessment of Various Bias Correction Methods on Precipitation of Regional Climate Model and Future Projection

2021 ◽  
Author(s):  
Gunavathi S ◽  
Selvasidhu R
Keyword(s):  
Regional Climate Model ◽  
Bias Correction ◽  
Climate Model ◽  
Rainwater Harvesting ◽  
Regional Climate ◽  
Power Transformation ◽  
Northeast Monsoon ◽  
Correction Technique ◽  
Simulated Precipitation ◽  
The Future

Abstract The application of regional climate model simulations (RCMs) in climate change impact studies is challengeable due to the risk of possible biases. Some sort of correction needs to be done prior to the application of RCM simulations. This study attempts to assess the performance of a simple (linear scaling and Delta Change method) and complex correction technique (Local intensity scaling, Power transformation and Distribution mapping) on CORDEX(Coordinated Regional Climate Downscaling Experiment)simulated precipitation series for the Thanjavur district. The performance at annual resolution is evaluated using various statistical parameters such as Correlation, Root Mean Square Error and Bias against the observed precipitation data. The raw RCM estimates were improved significantly after the bias correction with all methods. However, Power transformation exhibits good agreement with the observed data at the district level than other methods because it corrects both the mean and variance. The future climate was projected from 2021 to 2100 for RCP 4.5 and RCP 8.5 scenarios. The temporal distribution of future precipitation clearly shows that most of the years will receive heavy precipitation; rather, some years will receive low and average precipitation. The spatial distribution pattern indicates that the northeast monsoon will dominate over all the ranges and places. This study has provided clear information on future precipitation to the environmentalist, urban planners, and policymakers to take appropriate mitigation measures towards agriculture and disaster management. Rainwater harvesting, recharging the aquifers, afforestation, and redirecting the excess amount of water to the river through proper channels is the plausible actions suggested overcoming excessive precipitation in the future.

scholarly journals Regionalization of Climate Change Simulations over the Eastern Mediterranean

2009 ◽  
Vol 22 (8) ◽  
pp. 1944-1961 ◽  
Author(s):  
Bariş Önol ◽  
Fredrick H. M. Semazzi
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Temperature Increase ◽  
Climate Model ◽  
Eastern Mediterranean ◽  
Regional Climate ◽  
Future Climate ◽  
Climate Change Projections ◽  
Model Simulations ◽  
The Future

Abstract In this study, the potential role of global warming in modulating the future climate over the eastern Mediterranean (EM) region has been investigated. The primary vehicle of this investigation is the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 (ICTP-RegCM3), which was used to downscale the present and future climate scenario simulations generated by the NASA’s finite-volume GCM (fvGCM). The present-day (1961–90; RF) simulations and the future climate change projections (2071–2100; A2) are based on the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) emissions. During the Northern Hemispheric winter season, the general increase in precipitation over the northern sector of the EM region is present both in the fvGCM and RegCM3 model simulations. The regional model simulations reveal a significant increase (10%–50%) in winter precipitation over the Carpathian Mountains and along the east coast of the Black Sea, over the Kackar Mountains, and over the Caucasus Mountains. The large decrease in precipitation over the southeastern Turkey region that recharges the Euphrates and Tigris River basins could become a major source of concern for the countries downstream of this region. The model results also indicate that the autumn rains, which are primarily confined over Turkey for the current climate, will expand into Syria and Iraq in the future, which is consistent with the corresponding changes in the circulation pattern. The climate change over EM tends to manifest itself in terms of the modulation of North Atlantic Oscillation. During summer, temperature increase is as large as 7°C over the Balkan countries while changes for the rest of the region are in the range of 3°–4°C. Overall the temperature increase in summer is much greater than the corresponding changes during winter. Presentation of the climate change projections in terms of individual country averages is highly advantageous for the practical interpretation of the results. The consistence of the country averages for the RF RegCM3 projections with the corresponding averaged station data is compelling evidence of the added value of regional climate model downscaling.

scholarly journals A new region-aware bias-correction method for simulated precipitation in areas of complex orography

2018 ◽  
Vol 11 (6) ◽  
pp. 2231-2247 ◽  
Author(s):  
Juan José Gómez-Navarro ◽  
Christoph C. Raible ◽  
Denica Bozhinova ◽  
Olivia Martius ◽  
Juan Andrés García Valero ◽  
...  
Keyword(s):  
Bias Correction ◽  
Hydrological Cycle ◽  
Regional Climate ◽  
Simulated Data ◽  
Correction Method ◽  
Climate Impact ◽  
Climate Modelling ◽  
Correction Technique ◽  
Simulated Precipitation ◽  
Systematic Biases

Abstract. Regional climate modelling is used to simulate the hydrological cycle, which is fundamental for climate impact investigations. However, the output of these models is affected by biases that hamper its direct use in impact modelling. Here, we present two high-resolution (2 km) climate simulations of precipitation in the Alpine region, evaluate their performance over Switzerland and develop a new bias-correction technique for precipitation suitable for complex topography. The latter is based on quantile mapping, which is applied separately across a number of non-overlapping regions defined through cluster analysis. This technique allows removing prominent biases while it aims at minimising the disturbances to the physical consistency inherent in all statistical corrections of simulated data. The simulations span the period 1979–2005 and are carried out with the Weather Research and Forecasting model (WRF), driven by the ERA-Interim reanalysis (hereafter WRF-ERA), and the Community Earth System Model (hereafter WRF-CESM). The simulated precipitation is in both cases validated against observations in Switzerland. In a first step, the area is classified into regions of similar temporal variability of precipitation. Similar spatial patterns emerge in all datasets, with a clear northwest–southeast separation following the main orographic features of this region. The daily evolution and the annual cycle of precipitation in WRF-ERA closely reproduces the observations. Conversely, WRF-CESM shows a different seasonality with peak precipitation in winter and not in summer as in the observations or in WRF-ERA. The application of the new bias-correction technique minimises systematic biases in the WRF-CESM simulation and substantially improves the seasonality, while the temporal and physical consistency of simulated precipitation is greatly preserved.

scholarly journals Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue

2013 ◽  
Vol 26 (6) ◽  
pp. 2137-2143 ◽  
Author(s):  
Douglas Maraun
Keyword(s):  
Regional Climate Model ◽  
Bias Correction ◽  
Climate Model ◽  
Daily Precipitation ◽  
Temporal Structure ◽  
Regional Climate ◽  
Quantile Mapping ◽  
Model Simulations ◽  
Scale Mismatch ◽  
Climate Model Simulations

Abstract Quantile mapping is routinely applied to correct biases of regional climate model simulations compared to observational data. If the observations are of similar resolution as the regional climate model, quantile mapping is a feasible approach. However, if the observations are of much higher resolution, quantile mapping also attempts to bridge this scale mismatch. Here, it is shown for daily precipitation that such quantile mapping–based downscaling is not feasible but introduces similar problems as inflation of perfect prognosis (“prog”) downscaling: the spatial and temporal structure of the corrected time series is misrepresented, the drizzle effect for area means is overcorrected, area-mean extremes are overestimated, and trends are affected. To overcome these problems, stochastic bias correction is required.

scholarly journals High-resolution Med-CORDEX regional climate model simulations for hydrological impact studies: a first evaluation in Morocco

2013 ◽  
Vol 10 (5) ◽  
pp. 5687-5737 ◽  
Author(s):  
Y. Tramblay ◽  
D. Ruelland ◽  
S. Somot ◽  
R. Bouaicha ◽  
E. Servat
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Regional Climate Model ◽  
Bias Correction ◽  
Hydrological Model ◽  
Climate Model ◽  
Regional Climate ◽  
Impact Studies ◽  
Hydrological Impact ◽  
Split Sample

Abstract. In the framework of the international CORDEX program, new regional climate model (RCM) simulations at high spatial resolutions are becoming available for the Mediterranean region (Med-CORDEX initiative). This study provides the first evaluation for hydrological impact studies of these high-resolution simulations. Different approaches are compared to analyze the climate change impacts on the hydrology of a catchment located in North Morocco, using a high-resolution RCM (ALADIN-Climate) from the Med-CORDEX initiative at two different spatial resolutions (50 km and 12 km) and for two different Radiative Concentration Pathway scenarios (RCP4.5 and RCP8.5). The main issues addressed in the present study are: (i) what is the impact of increased RCM resolution on present-climate hydrological simulations and on future projections? (ii) Are the bias-correction of the RCM model and the parameters of the hydrological model stationary and transferable to different climatic conditions? (iii) What is the climate and hydrological change signal based on the new Radiative Concentration Pathways scenarios (RCP4.5 and RCP8.5)? Results indicate that high resolution simulations at 12 km better reproduce the seasonal patterns, the seasonal distributions and the extreme events of precipitation. The parameters of the hydrological model, calibrated to reproduce runoff at the monthly time step over the 1984–2010 period, do not show a strong variability between dry and wet calibration periods in a differential split-sample test. However the bias correction of precipitation by quantile-matching does not give satisfactory results in validation using the same differential split-sample testing method. Therefore a quantile-perturbation method that does not rely on any stationarity assumption and produces ensembles of perturbed series of precipitation was introduced. The climate change signal under scenarios 4.5 and 8.5 indicates a decrease of respectively −30% to −57% in surface runoff for the mid-term (2041–2062), when for the same period the projections for precipitation are ranging between −15% and −19% and for temperature between +1.28°C and +1.87°C.

scholarly journals Bias Correction of High‐Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments

2019 ◽  
Vol 124 (24) ◽  
pp. 14220-14239 ◽  
Author(s):  
Daniel Bannister ◽  
Andrew Orr ◽  
Sanjay K. Jain ◽  
Ian P. Holman ◽  
Andrea Momblanch ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Model Precipitation ◽  
Best Estimates
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