Climate change projections in the Awash River Basin of Ethiopia using Global and Regional Climate Models

2019 ◽  
Vol 40 (8) ◽  
pp. 3649-3666
Author(s):  
Mahtsente T. Tadese ◽  
Lalit Kumar ◽  
Richard Koech
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
Awash River Basin

scholarly journals Uncertainties in climate change projections and regional downscaling in the tropical Andes: implications for water resources management

2010 ◽  
Vol 14 (7) ◽  
pp. 1247-1258 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Tropical Andes ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

Climate Change Projections in Latin America and the Caribbean: Review of Existing Regional Climate Models' Outputs

2016 ◽  
Author(s):  
Ramiro Alberto Ríos Flores ◽  
Alejandro Pablo Taddia ◽  
Alfred Grunwaldt ◽  
Russel Jones ◽  
Richard Streeter
Keyword(s):  
Climate Change ◽  
Latin America ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
The Caribbean

scholarly journals Uncertainties in climate change projections and regional downscaling: implications for water resources management

2010 ◽  
Vol 7 (2) ◽  
pp. 1821-1848 ◽  
Author(s):  
W. Buytaert ◽  
M. Vuille ◽  
A. Dewulf ◽  
R. Urrutia ◽  
A. Karmalkar ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Regional Climate Model ◽  
Water Resources Management ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Projections ◽  
Resources Management

Abstract. Climate change is expected to have a large impact on water resources worldwide. A major problem in assessing the potential impact of a changing climate on these resources is the difference in spatial scale between available climate change projections and water resources management. Regional climate models (RCMs) are often used for the spatial disaggregation of the outputs of global circulation models. However, RCMs are time-intensive to run and typically only a small number of model runs is available for a certain region of interest. This paper investigates the value of the improved representation of local climate processes by a regional climate model for water resources management in the tropical Andes of Ecuador. This region has a complex hydrology and its water resources are under pressure. Compared to the IPCC AR4 model ensemble, the regional climate model PRECIS does indeed capture local gradients better than global models, but locally the model is prone to large discrepancies between observed and modelled precipitation. It is concluded that a further increase in resolution is necessary to represent local gradients properly. Furthermore, to assess the uncertainty in downscaling, an ensemble of regional climate models should be implemented. Finally, translating the climate variables to streamflow using a hydrological model constitutes a smaller but not negligible source of uncertainty.

Climate change projections of medicanes with a large multi-model ensemble of regional climate models

2017 ◽  
Vol 151 ◽  
pp. 134-143 ◽  
Author(s):  
Raquel Romera ◽  
Miguel Ángel Gaertner ◽  
Enrique Sánchez ◽  
Marta Domínguez ◽  
Juan Jesús González-Alemán ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Model Ensemble ◽  
Climate Change Projections

scholarly journals Using a Hydrologic Model to Assess the Performance of Regional Climate Models in a Semi-Arid Watershed in Brazil

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 170 ◽  
Author(s):  
Carlos Santos ◽  
Felizardo. Rocha ◽  
Tiago Ramos ◽  
Lincoln Alves ◽  
Marcos Mateus ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Northeastern Brazil ◽  
Impact Of Climate Change ◽  
Monthly Streamflow ◽  
The Impact

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.

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

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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