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Climate change projection using statistical downscaling model over Chittagong Division, Bangladesh

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F21%3A43902690" target="_blank" >RIV/60076658:12520/21:43902690 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.1007/s00703-021-00817-x" target="_blank" >https://doi.org/10.1007/s00703-021-00817-x</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s00703-021-00817-x" target="_blank" >10.1007/s00703-021-00817-x</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Climate change projection using statistical downscaling model over Chittagong Division, Bangladesh

  • Popis výsledku v původním jazyce

    Countries around the world have already been experiencing the repercussions of climate change. Bangladesh is cited as one of the most vulnerable countries among them. Due to the utmost contribution to the country&apos;s economy and continuous exposure to climatic extremes, climate change scenarios for the largest division in the country, the Chittagong Division, have a major concern. This study analyzed the potential climatic changes by the downscaling approach for the Chittagong Division under Representative Concentration Pathways (RCPs) i.e., RCP 2.5, RCP 4.5 and RCP 8.5, and Special Report on Emission Scenarios (SRES) i.e., A2, A1B, and B2 scenarios. Statistical Downscaling Model (SDSM) was used for downscaling three General Circulation Models (GCMs) viz. HadCM3, CanESM2, and CGCM3. A quantitative approach was used for both calibration and validation, where the results indicated the suitability of SDSM for downscaling daily mean temperature and precipitation under different scenarios for three future time horizons, i.e., early-twenty-first, mid-twenty-first, and late-twenty-first century. Additionally, bias correction was applied to downscaled climate variables. The downscaled projection showed increasing trends in mean annual temperature and precipitation for all the scenarios by the end of the century. Under CanESM2, the highest increase in temperature and precipitation were projected as 1.1 degrees C and 1.7 mm for the RCP 8.5. On the other hand, the highest increase in temperature and precipitation were projected as 0.5 degrees C and 1.4 mm for the SRES scenario A2 under CGCM3 and HadCM3. The spatial distribution of projections shows that the southern coastal part of the division is marked by remarkable future changes. The downscaled pathways have set a basis for assessing the impacts of future climate change on different sectors for the Chittagong Division and other areas in the country.

  • Název v anglickém jazyce

    Climate change projection using statistical downscaling model over Chittagong Division, Bangladesh

  • Popis výsledku anglicky

    Countries around the world have already been experiencing the repercussions of climate change. Bangladesh is cited as one of the most vulnerable countries among them. Due to the utmost contribution to the country&apos;s economy and continuous exposure to climatic extremes, climate change scenarios for the largest division in the country, the Chittagong Division, have a major concern. This study analyzed the potential climatic changes by the downscaling approach for the Chittagong Division under Representative Concentration Pathways (RCPs) i.e., RCP 2.5, RCP 4.5 and RCP 8.5, and Special Report on Emission Scenarios (SRES) i.e., A2, A1B, and B2 scenarios. Statistical Downscaling Model (SDSM) was used for downscaling three General Circulation Models (GCMs) viz. HadCM3, CanESM2, and CGCM3. A quantitative approach was used for both calibration and validation, where the results indicated the suitability of SDSM for downscaling daily mean temperature and precipitation under different scenarios for three future time horizons, i.e., early-twenty-first, mid-twenty-first, and late-twenty-first century. Additionally, bias correction was applied to downscaled climate variables. The downscaled projection showed increasing trends in mean annual temperature and precipitation for all the scenarios by the end of the century. Under CanESM2, the highest increase in temperature and precipitation were projected as 1.1 degrees C and 1.7 mm for the RCP 8.5. On the other hand, the highest increase in temperature and precipitation were projected as 0.5 degrees C and 1.4 mm for the SRES scenario A2 under CGCM3 and HadCM3. The spatial distribution of projections shows that the southern coastal part of the division is marked by remarkable future changes. The downscaled pathways have set a basis for assessing the impacts of future climate change on different sectors for the Chittagong Division and other areas in the country.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10509 - Meteorology and atmospheric sciences

Návaznosti výsledku

  • Projekt

  • Návaznosti

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Ostatní

  • Rok uplatnění

    2021

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Meteorology and Atmospheric Physics

  • ISSN

    0177-7971

  • e-ISSN

  • Svazek periodika

    133

  • Číslo periodika v rámci svazku

    4

  • Stát vydavatele periodika

    AT - Rakouská republika

  • Počet stran výsledku

    19

  • Strana od-do

    1409-1427

  • Kód UT WoS článku

    000669171000001

  • EID výsledku v databázi Scopus

    2-s2.0-85109254210