2019
DOI: 10.1002/joc.6394
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Changes in future rainfall extremes over Northeast Bangladesh: A Bayesian model averaging approach

Abstract: In this paper, we used a Bayesian model averaging (BMA) approach to analyse the changes in rainfall extremes in the periods 2041-2070 and 2071-2099 over northeast Bangladesh as a consequence of climate change. Climate change over this region could potentially impact agricultural production, water resources management, and the overall economy of the country. We used six regional climate models (RCMs) over the Coordinated Regional Downscaling Experiment South Asia domain. We used one medium stabilization scenari… Show more

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Cited by 11 publications
(3 citation statements)
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References 70 publications
(113 reference statements)
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“…Bayesian Model Average (BMA) is a probabilistic post-processing technique that generates probability predictions by quantifying prediction uncertainty [46]. The Bayesian formula was used to combine the prior distribution with the likelihood function in the BMA method, which aims to obtain the posterior distribution of the predicted object.…”
Section: Construction Of the Bma Modelmentioning
confidence: 99%
“…Bayesian Model Average (BMA) is a probabilistic post-processing technique that generates probability predictions by quantifying prediction uncertainty [46]. The Bayesian formula was used to combine the prior distribution with the likelihood function in the BMA method, which aims to obtain the posterior distribution of the predicted object.…”
Section: Construction Of the Bma Modelmentioning
confidence: 99%
“…The mean BMA unifies the posterior distribution of all the final trained models. The purpose of BMA is to combine uncertain models to get the best model [9]. EMOS used a single normal distribution, where the mean is an affine function of the ensemble members, and the variance is an affine function of the ensemble variable [10].…”
Section: Introductionmentioning
confidence: 99%
“…Although the AEM simulation reduces the model bias compared to a single climate model, the systematic bias cannot be neglected and would hinder reliable projections of future droughts. An alternative approach of the AEM approach is Bayesian model averaging 4 (BMA), which has been proven to be a promising tool for improving multi-model hydroclimate simulations (Duan and Phillips 2010;Yang et al 2011;Olson et al 2016Olson et al , 2018Zhang et al 2016;Ahmadalipour et al 2018;Shin et al 2019;Basher et al 2020). However, little effort has been directed towards applying BMA to project future drought characteristics (Ahmadalipour et al 2018;Miao et al 2020).…”
Section: Introductionmentioning
confidence: 99%