Bias Correction for RCM Predictions of Precipitation and Temperature in the Chaliyar River Basin

Ky, Raneesh; Sg, Thampi

doi:10.4172/2332-2594.1000105

Cited by 6 publications

(2 citation statements)

References 21 publications

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“…However, the closer the R-value is to one means a good correlation between the simulated and observed data. Most previous studies assessed the performance of bias correction methods and hydrological models using these statistical analyses (Nohara et al, 2006;Raneesh and Thampi, 2013;Fang et al, 2015;Xue et al, 2017;Geleta and Gobosho, 2018).…”

Section: Statistical Analysis Of Bias Correction Methodsmentioning

confidence: 99%

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

Tadese

Kumar

Koech

2019

Intl Journal of Climatology

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Understanding the long‐term variability and change in climate variables is critical for the sustainable management of water resources. This research aimed to project and analyse climate change in the Awash River Basin (ARB) using bias‐corrected Global and Regional Climate Model simulations. The analysis included a baseline period from 1986 to 2005 and two future scenarios (2050s and 2070s) under two representative concentration pathways (RCP4.5 and RCP8.5). Following the evaluation of bias correction methods, the distribution mapping and power transformation were used for temperature and precipitation projection, respectively. The 2050s and 2070s RCP4 simulations showed an increase in precipitation during half of the months with 32 and 10%, respectively. Moreover, the 2050s and 2070s RCP8.5 simulation indicated a decrease in precipitation with 18 and 26%, respectively. The 2050s and 2070s RCP8.5 simulation indicated a significant decrease in precipitation in four of the months (February/March to May) with the highest decreasing rate of 34.7%. The 2050s and 2070s RCP4.5 simulation showed an increase of 0.48–2.6°C in maximum temperature. In the case of RCP8.5, the simulated maximum temperature increase reached 3.4 and 4.1°C in the 2050s and 2070s, respectively. The future precipitation and temperature change projected in ARB might worsen the water stress and incidence of dry spells in the basin, and hence mitigation strategies and management options to reduce this negative impact should be developed.

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Section: Statistical Analysis Of Bias Correction Methodsmentioning

confidence: 99%

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

Tadese

Kumar

Koech

2019

Intl Journal of Climatology

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“…March and April are the hottest months, and December and January are the coolest months. Average annual precipitation is 3012.61 mm, and the maximum and minimum temperatures are 34 °C and 24 °C, respectively (Raneesh and Thampi 2013). Digital elevation model (DEM) of the river basin, locations (Table 1) of the gauging stations viz, Kottamparamba, Manjeri and Nilambur and locations of grids of the downscaling RCMs over the river basin are presented in Fig.…”

Section: Study Areamentioning

confidence: 99%

Analysis of extreme precipitation and its variability under climate change in a river basin

2019

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This study investigated the variation of extreme precipitation on a catchment under climate change. Extreme value analysis using generalized extreme value distribution was used to characterize the extreme precipitation. Reliability ensemble average of annual maximum precipitation projections of five global climate model-regional climate model (GCM-RCM) combinations was used to analyse the precipitation extremes under the representative concentration pathways, RCPs 4.5 and 8.5. In order to tackle the nonstationarity present in the bias-corrected ensemble-averaged annual maximum precipitation series under RCPs 4.5 and 8.5, it was split in such a way that the resulting blocks were stationary. Here the analysis was performed for three blocks 2010-2039, 2040-2069 and 2070-2099, each of which were individually stationary. Uncertainty analysis was done to estimate the ranges of extreme precipitation corresponding to return periods of 10, 25 and 50 years. Results of the study indicate that the extreme precipitation corresponding to these return periods in the three time blocks under the RCPs 4.5 and 8.5 exhibit an increasing trend. Extreme precipitation for these return periods are obtained as higher for the RCP scenarios compared to that obtained using observations. Also the extreme precipitation under RCP8.5 is higher compared to that under RCP4.5 scenario.

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Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

2017

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Bias Correction for RCM Predictions of Precipitation and Temperature in the Chaliyar River Basin

Cited by 6 publications

References 21 publications

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

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

Analysis of extreme precipitation and its variability under climate change in a river basin

Climate projections and extremes in dynamically downscaled CMIP5 model outputs over the Bengal delta: a quartile based bias-correction approach with new gridded data

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