{"id":3597,"date":"2019-08-13T16:39:55","date_gmt":"2019-08-13T10:39:55","guid":{"rendered":"https:\/\/www.isrt.ac.bd\/?post_type=tribe_events&#038;p=3597"},"modified":"2019-08-13T16:43:43","modified_gmt":"2019-08-13T10:43:43","slug":"3597","status":"publish","type":"tribe_events","link":"https:\/\/isrt.ac.bd\/event\/3597\/","title":{"rendered":"PhD seminar talk on August 27 at 2pm"},"content":{"rendered":"<div><strong>Title:<\/strong> Improved Statistical Approach for Climate Projection over Bangladesh using Downscaling of Global Climate Model (GCM) Outputs<\/div>\n<div><\/div>\n<div><strong>Speaker:<\/strong> Md. Bazlur Rashid<\/div>\n<div><\/div>\n<div><strong>Abstract:<\/strong><\/div>\n<div>Global Climate Model (GCM) has evolved from the Atmospheric General Circulation Models<br \/>\n(AGCMs) widely used for daily, seasonal and long term weather prediction. The most widely<br \/>\nrecognized application is the projection of future climate states under various scenarios of<br \/>\nincreasing atmospheric elements. Over the last few decades, GCMs have been developed to<br \/>\nemulate the present climate system and to project future climate scenarios. Despite notable<br \/>\ndevelopment, GCMs do not provide perfect simulations of reality and cannot provide the details<br \/>\non very small spatial scales due to incomplete scientific understanding and limitations of<br \/>\navailable observations in our country. For bridging the gap between the scale of GCMs and<br \/>\nrequired resolution for practical applications, downscaling provides climate change information<br \/>\nat a suitable spatial and temporal scale from the GCM data. No downscaling for Bangladesh of<br \/>\ndetail temperature, precipitation, wind speed, pressure and humidity has been undertaken.<br \/>\nCurrent research in Bangladesh has not addressed thermal comfort under climate change. In<br \/>\naddition, current studies for Bangladesh do not look at seasonality clearly. Extreme events<br \/>\n(rainfall and temperature), thermal comfort, humidity and wind characteristics, along with<br \/>\nseasonality, under future climate in Bangladesh represent a further research gap and opportunity<br \/>\nfor this research. The main object of study will attempt to find and\/or develop efficient statistical<br \/>\nmethods\/tools for climate projection. The specific objectives are (i) to identify suitable model<br \/>\nwith bias corrections for climate projection using climate model outputs; (ii) to explore the<br \/>\neffectiveness of the bias correction statistical downscaling method in addressing the model-<br \/>\nrelated uncertainties involved in future climate predictions; (iii) to identify a suitable<br \/>\ndownscaling approach for climate model data to allow daily\/ monthly or seasonal meteorological<br \/>\nclimate impact studies; (iv) to develop modify algorithms for quantifying the time-variant<br \/>\nuncertainty associated with meteorological extreme weather systems and persistent events under<br \/>\nfuture climate scenarios and (v) to cross check between available statistical downscaling<br \/>\ntechniques for future climate projections and scenarios generation over Bangladesh. So, GCM<br \/>\ninformation can be enhanced for better representation of the conditions in specific places by<\/div>\n<div>using historically observed local climate information from weather stations. Statistical<br \/>\nDownscaling of climate model can include independent components of climatic signals like El<br \/>\nNino-Southern Oscillations (ENSO), Indian Ocean Dipole (IOD) and Pacific Decadal<br \/>\nOscillations (PDO) for a long-lead weather forecast. So, this information can also be used to<br \/>\nimprove the future climate projections to assess potential impacts and guide climate-smart<br \/>\ndecisions about climate resilience in Bangladesh.<\/div>\n<div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Title: Improved Statistical Approach for Climate Projection over Bangladesh using Downscaling of Global Climate Model (GCM) Outputs Speaker: Md. Bazlur Rashid Abstract: Global Climate Model (GCM) has evolved from the &#8230; <a class=\"\" href=\"https:\/\/isrt.ac.bd\/event\/3597\/\">[ Read More ]<\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"template":"","meta":{"_acf_changed":false,"nf_dc_page":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[15],"class_list":["post-3597","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-seminar","cat_seminar"],"acf":[],"_links":{"self":[{"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/tribe_events\/3597","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/tribe_events"}],"about":[{"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/types\/tribe_events"}],"author":[{"embeddable":true,"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/users\/3"}],"version-history":[{"count":5,"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/tribe_events\/3597\/revisions"}],"predecessor-version":[{"id":3602,"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/tribe_events\/3597\/revisions\/3602"}],"wp:attachment":[{"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/media?parent=3597"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/tags?post=3597"},{"taxonomy":"tribe_events_cat","embeddable":true,"href":"https:\/\/isrt.ac.bd\/wp-json\/wp\/v2\/tribe_events_cat?post=3597"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}