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

Hasan, Mohammad Alfi; Islam, A. K. M. Saiful; Akanda, A. S.

doi:10.1007/s00382-017-4006-1

Cited by 26 publications

(25 citation statements)

References 80 publications

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“…The highest CWD increase occurred at the end of the century (2070) under the RCP8.5 scenario, while the lowest rise occurred in the middle of the century (the 2040s) under the RCP4.5 scenario. Previously, Hasan et al [37] also projected that heavy rainfall is expected to increase in the future.…”

Section: Changes In Precipitationmentioning

confidence: 99%

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Future Changes in Precipitation and Drought Characteristics over Bangladesh under CMIP5 Climatological Projections

Kamruzzaman

Jang

Cho

et al. 2019

Water

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The impacts of climate change on precipitation and drought characteristics over Bangladesh were examined by using the daily precipitation outputs from 29 bias-corrected general circulation models (GCMs) under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. A precipitation-based drought estimator, namely, the Effective Drought Index (EDI), was applied to quantify the characteristics of drought events in terms of the severity and duration. The changes in drought characteristics were assessed for the beginning (2010-2039), middle , and end of this century relative to the 1976-2005 baseline. The GCMs were limited in regard to forecasting the occurrence of future extreme droughts. Overall, the findings showed that the annual precipitation will increase in the 21st century over Bangladesh; the increasing rate was comparatively higher under the RCP8.5 scenario. The highest increase in rainfall is expected to happen over the drought-prone northern region. The general trends of drought frequency, duration, and intensity are likely to decrease in the 21st century over Bangladesh under both RCP scenarios, except for the maximum drought intensity during the beginning of the century, which is projected to increase over the country. The extreme and medium-term drought events did not show any significant changes in the future under both scenarios except for the medium-term droughts, which decreased by 55% compared to the base period during the 2070s under RCP8.5. However, extreme drought days will likely increase in most of the cropping seasons for the different future periods under both scenarios. The spatial distribution of changes in drought characteristics indicates that the drought-vulnerable areas are expected to shift from the northwestern region to the central and the southern region in the future under both scenarios due to the effects of climate change.

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Section: Changes In Precipitationmentioning

confidence: 99%

“…Recently, Hasan et al [37] projected the future climate and associated extremes while considering the new RCP4.5 and RCP8.5 scenarios by using RCM results driven by the GCMs over Bangladesh within the new CMIP5. The study revealed that overall precipitation and temperature trends are likely to increase in the future over this region.…”

Section: Introductionmentioning

confidence: 99%

Future Changes in Precipitation and Drought Characteristics over Bangladesh under CMIP5 Climatological Projections

Kamruzzaman

Jang

Cho

et al. 2019

Water

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“…We either applied or adopted the climate indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) Peterson (2005). These indices were used in various climate studies to analyze the extremity of the climatic phenomenon (Alexander, 2015;Hasan et al, 2017;Keggenhoff et al, 2015). The selections of the indices in those studies were conducted based on particular objectives of individual studies.…”

Section: Methodsmentioning

confidence: 99%

Quantification of Rotavirus Diarrheal Risk Due to Hydroclimatic Extremes Over South Asia: Prospects of Satellite‐Based Observations in Detecting Outbreaks

et al. 2018

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Rotavirus is the most common cause of diarrheal disease among children under 5. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of 34 climate indices calculated from ground and satellite Earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement and temperature data from the Moderate Resolution Imaging Spectroradiometer sensors to validate the analyses and explore the potential of a satellite‐based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks 1 to 2 months in advance. The satellite data‐driven forecasts also effectively captured the increased vulnerability of dry‐cold regions of the country, compared to the wet‐warm regions.

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“…The literature on statistical downscaling has concentrated on different countries, although there are some publications with a North American focus (Lapp et al, 2002;Benestad et al, 2015;, as well as for Australia/New Zealand (Kidson and Thompson, 1998), Africa (Reason et al, 2006;Penlap et al, 2004), Asia (Oshima et al, 2002;Das and Lohar, 2005) and Bangladesh (Alamgir et al, 2019;Hasan et al, 2017;Nury et al, 2014;Rahaman, et al 2015;Shourav et al, 2016). Rahaman et al (2015) found that statistical downscaling model (SDSM) showed good agreement between observed and simulated maximum and minimum temperature so that it is able to predict future scenarios over Bangladesh with confidence.…”

Section: Introductionmentioning

confidence: 99%

“…Statistical downscaling of modeled temperature and rainfall by GCM can easily be understood and adopted in order to minimize climate changes and its relevant impacts in Bangladesh (Nury et al, 2014). Hasan et al, (2017) found that the severity of summer-day temperatures would be alarming, especially over hilly regions, where winters would be relatively warm. Shourav et al (2016) used SDSM to downscale future climate projections over the city of Dhaka, Bangladesh.…”

Section: Introductionmentioning

confidence: 99%

Future Projection of Mean Temperature of Post-Monsoon Season Over Bangladesh Using Statistical Downscaling of Global Climate Models

Rashid¹,

Hossain

2020

J. of Eng. Sci.

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In statistical downscaling technique, regional or local information are derived by determining a statistical model which relates large-scale climate variables or predictors generated by Global Climate Models (GCMs) to regional and local variables or predictands. In this paper, the results of GCMs were statistically downscaled to produce future climate projections of mean temperature in the post-monsoon season (October and November), for the time periods 2021-2050 and 2071-2100 for Bangladesh. The future climate projections are based on the three emission scenarios RCP2.6, RCP4.5 and RCP8.5 provided by the fifth Coupled Model Intercomparison Project (CMIP5). This paper established a method to analyze GCMs for use in statistical downscaling and utilized fifteen GCMs. The GCMs were assessed based upon their performance in simulated past climate in Bangladesh and adjoining areas. Downscaling was undertaken by linking large scale climate variables, taken from the ERA-Interim (resolution 79 km) reanalysis temperature, a gridded data set incorporating observations and climate models, to local scale observations. Overall, all fifteen GCMs, via statistical downscaling, show that mean temperature of the post-monsoon season in Bangladesh will increase under future climate scenarios. Comparing the ensemble of future projections with the reference period (1981- 2010), the mean post-monsoon temperature in Bangladesh is projected for RCP8.5 showing warming by 0.310C in near future and 1.790C in far future. On the other hand, estimated warming is 0.390C in near future and 1.140C is far future for RCP4.5. Low emission scenarios RCP2.6, near future temperature is nearly same the far future temperature. Journal of Engineering Science 11(2), 2020, 27-35

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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

Cited by 26 publications

References 80 publications

Future Changes in Precipitation and Drought Characteristics over Bangladesh under CMIP5 Climatological Projections

Future Changes in Precipitation and Drought Characteristics over Bangladesh under CMIP5 Climatological Projections

Quantification of Rotavirus Diarrheal Risk Due to Hydroclimatic Extremes Over South Asia: Prospects of Satellite‐Based Observations in Detecting Outbreaks

Future Projection of Mean Temperature of Post-Monsoon Season Over Bangladesh Using Statistical Downscaling of Global Climate Models

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