Climate Change Signals Over Senegal River Basin Using Regional Climate Models of the CORDEX Africa Simulations

This study assessed the impact of climate change on the hydrological regime of the Paraguaçu river basin, northeastern Brazil. Hydrological impact simulations were conducted using the Soil and Water Assessment Tool (SWAT) for 2020–2040. Precipitation and surface air temperature projections from two Regional Climate Models (Eta-HadGEM2-ES and Eta-MIROC5) based on IPCC5—RCP 4.5 and 8.5 scenarios were used as inputs after first applying two bias correction methods (linear scaling—LS and distribution mapping—DM). The analysis of the impact of climate change on streamflow was done by comparing the maximum, average and reference (Q90) flows of the simulated and observed streamflow records. This study found that both methods were able to correct the climate projection bias, but the DM method showed larger distortion when applied to future scenarios. Climate projections from the Eta-HadGEM2-ES (LS) model showed significant reductions of mean monthly streamflow for all time periods under both RCP 4.5 and 8.5. The Eta-MIROC5 (LS) model showed a lower reduction of the simulated mean monthly streamflow under RCP 4.5 and a decrease of streamflow under RCP 8.5, similar to the Eta-HadGEM2-ES model results. The results of this study provide information for guiding future water resource management in the Paraguaçu River Basin and show that the bias correction algorithm also plays a significant role when assessing climate model estimates and their applicability to hydrological modelling.

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Multi-Criteria Decision Framework to Evaluate Bias Corrected Climate Change Projections in the Piracicaba River Basin

Revista Brasileira de Meteorologia ◽

10.1590/0102-77863630068 ◽

2021 ◽

Author(s):

Camila Billerbeck ◽

Ligia Monteiro da Silva ◽

Silvana Susko Marcellini ◽

Arisvaldo Méllo Junior

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Models ◽

Regional Climate ◽

Climate Change Impacts ◽

Regional Climate Models ◽

Annual Rainfall ◽

Monthly Precipitation ◽

Climate Change Effects ◽

Piracicaba River

Abstract Regional climate models (RCM) are the main tools for climate change impacts assessment in hydrological studies. These models, however, often show biases when compared to historical observations. Bias Correction (BC) are useful techniques to improve climate projection outputs. This study presents a multi-criteria decision analysis (MCDA) framework to compare combinations of RCM with selected BC methods. The comparison was based on the modified Kling-Gupta efficiency (KGE’). The criteria evaluated the general capability of models in reproducing the observed data main statistics. Other criteria evaluated were the relevant aspects for hydrological studies, such as seasonality, dry and wet periods. We applied four BC methods in four RCM monthly rainfall outputs from 1961 to 2005 in the Piracicaba river basin. The Linear Scaling (LS) method showed higher improvements in the general performance of the models. The RCM Eta-HadGEM2-ES, corrected with Standardized Reconstruction (SdRc) method, achieved the best results when compared to the observed precipitation. The bias corrected projected monthly precipitation (2006-2098) preserved the main signal of climate change effects when compared to the original outputs regarding annual rainfall. However, SdRc produced significant decrease in monthly average rainfall, higher than 45% for July, August and September for RCP4.5 and RCP8.5 scenarios.

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Comparing Bias Correction Methods Used in Downscaling Precipitation and Temperature from Regional Climate Models: A Case Study from the Kaidu River Basin in Western China

Water ◽

10.3390/w10081046 ◽

2018 ◽

Vol 10 (8) ◽

pp. 1046 ◽

Cited By ~ 23

Author(s):

Min Luo ◽

Tie Liu ◽

Fanhao Meng ◽

Yongchao Duan ◽

Amaury Frankl ◽

...

Keyword(s):

Climate Change ◽

River Basin ◽

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Hydrological Modelling ◽

Western China ◽

Kaidu River ◽

Precipitation And Temperature

The systemic biases of Regional Climate Models (RCMs) impede their application in regional hydrological climate-change effects analysis and lead to errors. As a consequence, bias correction has become a necessary prerequisite for the study of climate change. This paper compares the performance of available bias correction methods that focus on the performance of precipitation and temperature projections. The hydrological effects of these correction methods are evaluated by the modelled discharges of the Kaidu River Basin. The results show that all used methods improve the performance of the original RCM precipitation and temperature simulations across a number of levels. The corrected results obtained by precipitation correction methods demonstrate larger diversities than those produced by the temperature correction methods. The performance of hydrological modelling is highly influenced by the choice of precipitation correction methods. Furthermore, no substantial differences can be identified from the results of the temperature-corrected methods. The biases from input data are often greater from the works of hydrological modelling. The suitability of these approaches depends upon the regional context and the RCM model, while their application procedure and a number of results can be adapted from region to region.

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Observed and simulated climate and climate change in the lower Neretva river basin

Journal of Water and Climate Change ◽

10.2166/wcc.2017.034 ◽

2017 ◽

Vol 9 (1) ◽

pp. 124-136 ◽

Cited By ~ 1

Author(s):

Marjana Gajić-Čapka ◽

Ivan Güttler ◽

Ksenija Cindrić ◽

Čedo Branković

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Models ◽

Regional Climate ◽

Ghg Emissions ◽

Regional Climate Models ◽

Seasonal Temperature ◽

Yield Production ◽

Drinking Water Resources ◽

The Mean

Abstract The lower Neretva river basin includes a fertile valley at the estuary into the Adriatic Sea, where intense agricultural production occurs, and the higher terrain where drinking water resources exist. To provide input for the further assessment of crop-yield production and hydrological risks, climate and climate change were analysed using the Opuzen station air temperature and total precipitation data for the 1961–2015 period. Both historical and future climates (2021–2050) were assessed based on simulations of three regional climate models (RCMs). The RCMs were forced by the observed concentrations of greenhouse gases (GHGs) from 1951 to 2000, and the IPCC A1B scenario of the GHG emissions was applied from 2001 onwards. The models were compared with the observations, and two bias adjustment methods were evaluated. The results generally showed a significant increase in the mean annual and seasonal temperature and a weak decreasing trend in annual and seasonal precipitation. Projections revealed a predominant increase in the mean temperature by the mid-21st century for all three RCMs (between 0.5 and 3.5 °C). The precipitation changed by between −60 and +60% throughout the year for the different models, although the changes generally were not statistically significant.

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