Recent changes in temperature and rainfall trends and variability over Bangladesh Authors: Dewan Abdul Quadir; Catharien Terwisscha van Scheltinga; Fulco Ludwig Bangladesh Delta Plan Project & Toma Rani Saha Christian Commission for Development of Bangladesh
1. Background Wide acceptance that Bangladesh is one of the most vulnerable countries of the world due to climate change: Facts and dimensions of climate change parameters are needed in order to act. Bangladesh Delta Plan 2100 Formulation Project is working on a longer term (50 to 100 year) time frame plan for the country. A climate change study has been done, collecting existing knowledge on trends and changes in climate parameters (Terwisscha van Scheltinga et al, 2015). This presentation shows the results of additional study
2. Objectives Considering the need of incorporating the climate change knowledge in the processes of short, medium and long term planning and implementation BDP-2100 has undertaken study on Baseline Climate Change of Bangladesh. The presentation is an additional part of the BDP Climate change study. We present some results of trend analysis of minimum, maximum and mean temperature and rainfall. DATA USED The daily and monthly Minimum, Maximum and Mean Temperature and rainfall for 32 meteorological stations belonging to Bangladesh Meteorological Department have been used.
3. Methodology Data preparation Data quality checking. Erroneous data are deleted The gaps are filled using interpolation with neighboring stations Climatology has been analyzed For trend analysis least square regression technique has been used The results are presented in tables, figures, graphs and maps
Temperature ( o C) Standard deviation ( o C) 4. Results & Discussions 4.1. General Climatic Condition of Bangladesh Av. Tmax: Peak in April (33.5 0 C) Secondary peak in September (31.6 0 C) Tmin: Lowest in January (12.5 0 C).= Annual rainfall: 2425 mm Monsoon: 1750 mm(72 % of the annual). Pre-monsoon 17 % Post-monsoon: 9 % Winter: 1.5% 500 400 Rainfall(mm) S.D. CV% 45 40 35 30 25 20 15 10 5 0 Mean Tmax Mean Tmin SD Tmax SD Tmin J F M A M J J A S O N D 3 2 1 0 300 200 100 0 J F M A M J J A S O N D
4.2 Climate change (Temperature) Temperature ( C) 1948 1953 1958 1963 1968 1973 1978 1983 1988 1993 1998 2003 2008 26.5 26 25.5 25 24.5 Annual Trend of Mean Temperature y = 0.0103x + 4.9261 R² = 0.3582 Season Year Trend ( o C/year)and R 2 values Tmin p Tmax p Tmean p Annual 0.014 <0.001 0.008 <0.001 0.010 <0.001 Winter 0.021 <0.001 0.000 n.s. 0.013 <0.002 0 C/year 0.03 0.025 0.02 0.015 0.01 0.005 Tmin Premonsoo n Monsoo n Postmonsoo n 0.014 <0.002-0.004 n.s. -0.001 n.s. 0.008 <0.001 0.015 <0.001 0.011 <0.001 0.016 <0.001 0.024 0.528 0.016 <0.001 0-0.005-0.01 Annual Winter Pre-mon Monsoon Post-mon
4.3 Spatial distribution of Trends of Annual min and max temperature (T min and T max ) Annual T min Annual T max
Winter Pre-monsoon 4.3.1 Seasonal Trends of Minimum Temperature Monsoon Post-monsoon
Winter Pre-monsoon 4.3.2 Seasonal Trends of Maximum Temperature Monsoon Post-monsoon
Precipitation (mm) Precipitation (mm) 4.4 Trends of annual and seasonal rainfall Precipitation (mm) Precipitation (mm) 2900 Annual y = 3.96x - 5545. R² = 0.070 2400 1900 1400 150 100 50 0 700 500 300 100 1948 1958 1968 1978 1988 1998 2008 (a) Winter 1948 1958 1968 1978 1988 1998 2008 (b) Pre-monsoon 1948 1958 1968 1978 1988 1998 2008 2000 (c) Monsoon 1800 1600 1400 1200 400 300 200 100 0 1948 1958 1968 1978 1988 1998 2008 (d)post-monsoon 1948 1958 1968 1978 1988 1998 2008
4.4.1 Annual and Seasonal Trends Season Trend value (mm/year) % increase of precipitation in 50 years Probability p Winter 0.2 29.2 n.s. Pre- monsoon 1.3 12.2 <0.01 Monsoon 2.1 6.3 <0.01 Post-monsoon 0.5 11.4 <0.05 Annual 4.0 8.6 <0.001
4.5 Map of Annual Rainfall Trend (mm/year) The trend maps are useful for regional level and local level adaptation formulation and planning
Winter Monsoon Pre-monsoon Post-monsoon 4.5.1 Maps of seasonal rainfall trends (mm/year)
1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 Rainfall (mm) 1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 1948 1951 1954 1957 1960 1963 1966 1969 1972 1975 1978 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008 2011 Rainfall days RAinfall days 35 30 25 20 15 10 5 0 Dry Period (a) y = 0.050x + 13.21 R² = 0.034 120 115 110 105 100 95 90 85 80 75 70 Wet period (b) y = 0.175x + 92.75 R² = 0.182 Year Year 150 140 130 120 110 100 90 80 Annual (c) y = 0.244x + 105.2 R² = 0.208 4.6 The analysis of the number of rain days for : Dry period (November-January), Wet Period (May-October) The increasing trends of number of trends of rain days infers that the increasing of rainfall is mainly associated with the increase of the number of rain days. Year
4. CONCLUSSIONS: The study has the following conclusions: The temperature of Bangladesh has increasing trends. Minimum temperature of winter and Pre-monsoon seasons are increasing faster than maximum temperature. But in Monsoon and Post monsoon seasons the Maximum Temperature increases faster. The annual mean temperature has increased by around 0.64 C during the past 64 years (1948-2011) The annual and seasonal rainfall is found to increase. The increasing trends are significant for Pre-monsoon and Monsoon seasons and show 6% and 11% increase respectively over the last 50 years. The significant increasing trends of number of rain days depicts that the increase of rainfall is caused mainly by the increase of the number of rain days
4. CONCLUSSIONS (cont The spatial distribution of trends of temperature shows that the climate change is not uniform and causes of such variations are related to land-use change (urbanization, Land-use change and deforestation ) The spatial distribution of trends of temperature and rainfall shows that the trends are not uniform neither for temperature nor for rainfall over the space or over the seasons. Thus, there no unique solution for adaptation for the whole country and the local level climate change and variability are needed to be considered. These maps would be very useful as they provide local level information of climate change.