scholarly journals Simulation performance of selected global and regional climate models for temperature and rainfall in some locations in India

2021 ◽  
Vol 22 (4) ◽  
pp. 407-418
Author(s):  
SHWETA PANJWANI ◽  
S. NARESH KUMAR ◽  
LAXMI AHUJA
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
India Meteorological Department ◽  
Regional Climate Models ◽  
Climate Data ◽  
Simulation Performance ◽  
Climate Change Assessment ◽  
Better Than

Global and regional climate models are reported to have inherent bias in simulating the observed climatology of a region. This bias of climate models is the major source of uncertainties in climate change impact assessments. Therefore, use of bias corrected simulated climate data is important. In this study, the bias corrected climate data for 30 years’ period (1976-2005) from selected common fourGCMs and RCMs for six Indian locations are compared with the respective observed data of India Meteorological Department. The analysis indicated that the RCMs performance is much better than GCMs after bias correction for minimum and maximum temperatures. Also, RCMs performance is better than GCMs in simulating extreme temperatures. However, the selected RCMs and GCMs are found to either over estimate or under estimate the rainfall despite bias correction and also overestimated the rainfall extremes for selected Indian locations. Based on the overall performance of four models for the six locations, it was found that the GFDL_ESM2M and NORESM1-M RCMs performed comparatively better than CSIRO and IPSL models. After bias correction, the RCMs could represent the observed climatology better than the GCMs. And these RCMs viz., GFDL_ESM2M and NORESM1-M can be usedindividually after bias correction in the climate change assessment studies for the selected regions.

Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

2021 ◽  
Author(s):  
Gaby S. Langendijk ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Data ◽  
Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2°C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.</p>

scholarly journals Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 801 ◽  
Author(s):  
Brian Ayugi ◽  
Guirong Tan ◽  
Niu Ruoyun ◽  
Hassen Babaousmail ◽  
Moses Ojara ◽  
...  
Keyword(s):  
Bias Correction ◽  
Impact Analysis ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Absolute Error ◽  
Intermediate Step ◽  
Climate Data ◽  
Quantile Mapping ◽  
Mapping Bias

This study uses the quantile mapping bias correction (QMBC) method to correct the bias in five regional climate models (RCMs) from the latest output of the Rossby Center Climate Regional Model (RCA4) over Kenya. The outputs were validated using various scalar metrics such as root-mean-square difference (RMSD), mean absolute error (MAE), and mean bias. The study found that the QMBC algorithm demonstrates varying performance among the models in the study domain. The results show that most of the models exhibit reasonable improvement after corrections at seasonal and annual timescales. Specifically, the European Community Earth-System (EC-EARTH) and Commonwealth Scientific and Industrial Research Organization (CSIRO) models depict remarkable improvement as compared to other models. On the contrary, the Institute Pierre Simon Laplace Model CM5A-MR (IPSL-CM5A-MR) model shows little improvement across the rainfall seasons (i.e., March–May (MAM) and October–December (OND)). The projections forced with bias-corrected historical simulations tallied observed values demonstrate satisfactory simulations as compared to the uncorrected RCMs output models. This study has demonstrated that using QMBC on outputs from RCA4 is an important intermediate step to improve climate data before performing any regional impact analysis. The corrected models may be used in projections of drought and flood extreme events over the study area.

scholarly journals CLIMATE CHANGE IMPACTS ON PROJECTED PV POWER POTENTIAL UNDER RCP 8.5 SCENARIO IN BURUNDI

2020 ◽  
Vol 8 (5) ◽  
pp. 1-14
Author(s):  
Marc Niyongendako ◽  
Agnidé Emmanuel Lawin ◽  
Célestin Manirakiza ◽  
Serge Dimitri Yikwé Buri Bazyomo ◽  
Batablinlè Lamboni
Keyword(s):  
Climate Change ◽  
Solar Irradiance ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Potential Change ◽  
Historical Period ◽  
Climate Data ◽  
Future Period ◽  
Near Future

This work focuses on analysis of climate change effects on Photovoltaic (PV) power output in the Eastern and Northeastern of Burundi. Monthly temperature data from meteorological stations and solar irradiance data provided by SoDa database were considered as observed dataset for the historical period 1981-2010. Projection climate data from eight Regional Climate Models of CORDEX for Africa were used over the near future period 2021-2050. The change in temperature and solar irradiance were analyzed and the effects of these climate changes were assessed to show their impacts on PV power potential. The results indicated increasing trends and change in temperature for about 2°C over this near future period. The solar irradiance change was revealed negative with a high interannual variation for all regions and the mean decrease ranges between 2 and 4 W/m². The findings revealed also a negative change in PV power potential close to zero for all regions with a high change occurred in NLL. Indeed, the contribution of each parameter to PV power potential change was negative all over regions. However, the projected climate change does not predict a huge PV power potential change by 2050. Therefore, Burundi may invest in producing electricity energy from PV systems.

scholarly journals Assessment of potential hydrological climate change impacts in Kastoria basin (Western Macedonia, Greece) using EUROCORDEX regional climate models

2021 ◽  
Keyword(s):  
Climate Change ◽  
Groundwater Level ◽  
Climate Models ◽  
Regional Climate ◽  
Substantial Reduction ◽  
Regional Climate Models ◽  
Water Yield ◽  
Climate Projections ◽  
Climate Data ◽  
Northern Greece

<p>The Mediterranean region is expected to present reduced availability of water resources due to climate change. This study aims to assess the potential hydrological responses to climate change in the Kastoria basin (Western Macedonia, Northern Greece) for the period 2019-2078. Climate projections from eight regional climate models from EURO-CORDEX were bias-adjusted using the linear scaling method. The bias-adjusted climate data were used to force the FeFLOW hydro-logical model to predict the discharge of the Kastoria aquifer towards lake Orestiada along with the projected groundwater level distribution. Precipitation (temperature) shows a tendency to decrease (increase) mainly in late spring to early autumn while increase (decrease) in the other sea-sons. Moreover, results indicate a significant increase in temperature and a slight decrease in precipitation towards 2078, while the predicted groundwater level of Kastoria aquifer will reduce slightly. However, the future hydrological behavior of the basin indicates a substantial reduction by approximately 15% of total water yield towards the end of the century.</p>

Assessment of climate change impacts in a semi-arid watershed in Iran using regional climate models

2014 ◽  
Vol 6 (1) ◽  
pp. 161-180 ◽  
Author(s):  
Hamid R. Solaymani ◽  
A. K. Gosain
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Assessment Tool ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Models ◽  
Water Yield ◽  
Climate Data ◽  
Water Shortages ◽  
Semi Arid

This paper aims to summarize in detail the results of the climate models under various scenarios by temporal and spatial analysis in the semi-arid Karkheh Basin (KB) in Iran, which is likely to experience water shortages. The PRECIS and REMO models, under A2, B2 and A1B scenarios, have been chosen as regional climate models (RCMs). These regional climate models indicate an overall warming in future in KB under various scenarios. The increase in temperature in the dry months (June, July and August) is greater than the increase in the wet months (January, February, March and April). In order to perform climate change impact assessment on water resources, the Arc-SWAT 9.3 model was used in the study area. SWAT (Soil and Water Assessment Tool) model results have been obtained using present and future climate data. There is an overall reduction in the water yield (WYLD) over the whole of the KB. The deficit of WYLD is considerable over the months of April to September throughout KB due to the increase in average temperature and decrease in precipitation under various emission scenarios. Statistical properties in box-and-whisker plots have been used to gain further understanding relevant to uncertainty analysis in climate change impacts. Evaluation of uncertainty has shown the highest uncertain condition under B2.

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 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 ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 1046 ◽  
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.

Temperature Trends in the NARCCAP Regional Climate Models

2012 ◽  
Vol 25 (11) ◽  
pp. 3985-3991 ◽  
Author(s):  
Melissa S. Bukovsky
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
Near Surface ◽  
The North ◽  
Temperature Trends ◽  
Scale Temperature ◽  
Climate Change Assessment

The skill of six regional climate models (RCMs) in reproducing short-term (24-yr), observed, near-surface temperature trends when driven by reanalysis is examined. The RCMs are part of the North American Regional Climate Change Assessment Program (NARCCAP). If RCMs can reproduce observed temperature trends, then they are, in a way, demonstrating their ability to capture a type of climate change, which may be relevant to their ability to credibly simulate anthropogenic climate changes under future emission scenarios. This study finds that the NARCCAP RCMs can simulate some resolved-scale temperature trends, especially those seen recently in spring and, by and large, in winter. However, results in other seasons suggest that RCM performance in this measure may be dependent on the type and strength of the forcing behind the observed trends.

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