Introduction to climate change work in Bangladesh A.K.M. Saiful Islam Institute of Water and Flood Management (IWFM) Bangladesh University of Engineer and Technology (BUET) Training workshop on Regional Climate Modeling using PRECIS February 14-18, 2010, Dhaka, Bangladesh

Outline  Introduction to Climate Change Study Cell at BUET  Climate Change Conditions of Bangladesh  Regional Climate Change Modeling using PRECIS for Bangladesh

Climate Change Study Cell at BUET

Climate Change Study Cell  IWFM has established a climate change study cell in  The vision of the Cell is to establish itself as the premier knowledge center on climate change risk and adaptation for Bangladesh. Launching Ceremony On March 08, 2009 Chief Guest was Minister of Disaster Management

Institution Frameworks Syndicate BOG Director Coordinator Advisory committee Liaison Committee Research Teams IWFMCCSC

Activities in 2008 Short courses  Two short courses on "Climate Change Training for Water Professionals”, were held on November and October of 2008 at DCE, BUET.  Short Course on "Climate Change Risks and Adaptation in Water Sector" held on February, 2008 at DCE, BUET.

Activities in 2009 M.Sc. Course in Climate Change Risk Management offered at IWFM Course web site- climatecourse2009.html In future Certificate course will be offered for professionals

Activities in 2009 Total 20 participants will attend this workshop from various Gov. and Non-Gov. organizations. This workshop will be organized in collaboration with Met Office, UK and funded by DFID, UK.

Upcoming – Capacity Building Program In response to the call for project proposals for “Climate Change Trust Fund” from Ministry of Environment and Forestry (MoEF), CCSC has submitted a project proposal which include-  Fifteen Research Proposals on climate change  Computational Facility Development for Regional Climate Change Modeling  Student Fellowship  International Conference Organizations  Institutional Strengthen of the Cell

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Changing Climate of Bangladesh

Temperature Data Analysis ( ) Mean daily temperature of Bangladesh has increased with a rate of C per 100 years

Trends of Temperature of Bangladesh ( ) Max. Temp. = C/100 year Min. Temp. = C/100 year

Meteorological Observational Stations in Bangladesh

IDStationLatitudeLongitudeAltitudeMax. Temp. ( 0 C per yr.) Min. Temp. ( 0 C per yr.) 11704Barisal m Bhola m Bogra m Chandpur m Chittagong m Chuadanga m Comilla m Cox's Bazar m Dhaka m Dinajpur m Faridpur m Feni m Hatiya m Ishardi m Jessore m Khepupara m Khulna m Kutubdia m Madaripur m Maijdicourt m Mongla m Mymensing m Patuakhali m Rajshahi m Rangamati m Rangpur m Sandwip m Satkhira m Sayedpur m Sitakunda m Srimangal m Sylhet m Tangail m Teknaf m Trends of Temperature For 34 ground measuring Stations of BMD

Monthly temperature over Bangladesh ( )

Month-wise Trends MonthMax. Temp. ( 0 C per yr.) Min. Temp. (0C per yr.) January February March April May June July August September October November December

Change of mean Temperature( 0 C/year)

Average Temperature in January ( ) Daily Maximum Daily Minimum

Maximum Temperature Maximum increase: at Shitakunda Minimum increase: at Rangpur Minimum Temperature Maximum increase: at Bogra Minimum increase: at Tangail Spatial Distribution of Trends of Temperature ( )

Climate Change Impact for Bangladesh  Increase of intensity and duration of natural disasters such as floods, Cyclones and Storm Surges.  Increase of moisture stress (droughts) due to erratic precipitation  Salinity intrusion due to Sea Level Rise  Inundation due to sea level rise leading towards “Climate Refugees”  Effect on health and livelihood of coastal people.  Effect on Bio-diversity, Ecology & Sundarbans.  Hampered Food Security & Social Security.

The Sundarbans..Mangrove forest?

Facing Climate Change National Awareness building –Capacity Building through Training –Innovative Research for knowledge generations Mitigation –Reduce Co 2 emission, Use Green technology –Use of Alternative Energy sources – Solar, Wind etc. Adaptation – –Build Shelters, Rise Embankments & Polders, Roads, Houses –Salinity tolerant crops, Forestation, alternative livelihood, improve warning system, migrations Global Awareness & Justice –– Kyoto Protocol, COP15, COP16…. Raise our voice !

Regional Climate Change Modeling for Bangladesh

Regional Climate change modeling in Bangladesh PRECIS regional climate modeling is now running in Climate change study cell at IWFM,BUET. Uses LBC data from GCM (e.g. HadCM3). LBC data available for baseline, A2, B2, A1B scenarios up to Predictions for every hour. Needs more than 100 GB free space.

Domain used in PRECIS experiment

Topography of Experiment Domain Zoom over Bangladesh Simulation Domain = 88 x 88 Resolution = 0.44 degree

Predicted Change of Mean Temperature ( 0 C) using A1B Baseline = 2000

Predicting Maximum Temperature using A2 Scenarios [Output of PRECIS model using SRES A2 scenario]

Predicting Minimum Temperature using A2 Scenarios

Change of Mean Rainfall (mm/d) using A1B Scenarios Baseline = 2000

Predicting Rainfall using A2 Scenarios [Output of PRECIS model using SRES A2 scenario]

Change of mean climatic variables of Bangladesh using A1B Scenarios Temperate ( 0 C) Rainfall (mm/d)

Monthly Average Rainfall (mm/d) Month January February March April May June July August September October November December

Monthly Average Temperature ( 0 C) Month January February March April May June July August September October November December

Summary  Analysis of the historic data ( ) shows that daily maximum and minimum temperature has been increased with a rate of C and C per 100 years respectively.  PRECIS simulation for Bangladesh using A1B climate change scenarios showed that mean temperature will be increased at a constant rate 4 0 C per 100 year from the base line year  On the other hand, mean rainfall will be increased by 4mm/d in 2050 and then decreased by 2.5mm/d in 2100 from base line year 2000.

Recommendations In future, Climate change predictions will be generated in more finer spatial scale(~25km). PRECIS model will be simulated with other Boundary condition data such as ECHAM5 using A1B scenarios. Results will be compared with other regional climate models such as RegCM3 etc.