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1 Presented by: Ms. Fatou SIMA Meteorologist Dept. of Water Resources 7, Marina Parade, Banjul Tel: 4377098/7990855 Email: sima_fatou@yahoo.com
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2 Introduction Objective Methodology & Tools Climate Change Scenarios Observed Impacts of C_Change Conclusions & Recommendations
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3 There is increasing concern over climate change phenomena all over the world. Both developing and developed countries have accepted that urgent and definite actions need to be taken to reverse the effects of mans misuse of the natural resources. There is also substantial evidence from the IPCC assessment of climate from the pre- industrial period to the present that the climate is changing over most of the regions. Source; Nigeria climate review bulletin, 2007
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4 What is Climate Change? C_Change is a statistically significant variation in either the meant state of the climate or its variability, persisting for an extended period of decades or longer. What causes Climate Change? natural internal processes/, by persistent anthropogenic (man-made) changes in the composition of the atmosphere or in landuse. Figure 1 Figure 2 Figure 3
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5 The objective of this presentation is to provide climate scenario information advice to decision makers and to ensure that the resulting impacts can be used to provide Gambians with a meaningful national assessment of the impacts of C_Change and how it can contribute to future assessments.
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6 The main steps were: Method; Collection of Meteorological data; Statistical calculation of the long-term data for the Baseline climate scenarios of The Gambia; Comparison of model performance with the current data. Tools; Magic (Scengen); develop the model performance, INSTAT+; calculate the key factors of the growing season, Surfer is used for mapping, Excel for some agro- climatic analysis.
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7 The climate community uses 2 types of scenarios for the study of climate variability and change. Baseline scenarios estimate how the world would change without climate change. Climate change scenarios, on the other hand, estimate likely changes in the climate system that are caused by a certain forcing agent such as increase in concentration of CO 2 in the atmosphere.
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9 Figure 4. Model Projections for monthly mean temperatures (0C) for The Gambia to 2100 Except for the BMRC Model other models show that warming of the atmosphere will be almost the same as current climate. The BMRC model shows that temperatures will increase by about 5 o C above current climate.
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10 Figure 5. Model Projections for annual mean temperatures (0C) for The Gambia to 2100 All the 3 models used in the Study show increase in temperature of about 0.5 in 2010 to about 3.0 to 4.0 o C by 2100. The BMRC Model shows the largest increase of about 4 0 C.
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11 Figure 6. Model Projections for annual mean Rainfall (mm) for The Gambia to 2100 Again the BMRC shows the largest increase in rainfall varying from about 1% increase in 2010 to about 12% increase by 2100. The other models show increase of about 0% in 2010 to about 2.2% by 2100.
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13 E.g ; Interannual Variability of Rainfall Unseasonal rainfall Flooding Key factors of the rainy season (onsets, cessations & S_lengths)
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14 Interannual Variations of the Annual total rainfall (mm)
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15 Interannual Variations of the Annual total rainfall (mm)
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16 Figure 14. Annual total unseasonal rainfall (mm) for the period 1951- 2007 (57yrs) for The Gambia Figure 13. Monthly average unseasonal rainfall (mm) for the period 1951 –2007 (57yrs.) for The Gambia
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17 Figure 16. Flood victims Figure 15. Effects of flood at Ebo Town in 2007 Flooding is one of the most damaging natural disasters; victims were subjected to food insecurity, decline in crop productivity, and pollution of water supply, favorable conditions for breeding mosquitoes. In 2007, residents of parts of Ebo Town are in tears crying out for immediate assistance due to the flood that has wreaked havoc on poor inhabitants recently.
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18 Figure 17. Houses destroyed by heavy intensity of rain at the NBR for the period 2004
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19 Climatic events based on long-term meteorological data show discernible evidence of C_Change in the country. This statement is supported by the analysis of variability’s of long- term (1961-1990) & (1971-2000) on dates of onset, cessation, & season lengths of rainfall occurrence for selected stations in The Gambia using criteria; - After 1 st May, rainfall amounting 20mm in 1 or 2 consecutive days not followed by a dry spell of 10 days in next 30 days of sowing (Alimi et al., 1992).
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20 Normal onset Early onset Late onset 1961-1990 1971-2000 Early onset Normal onset Late onset Fig. 18 a. 1961 – 1990, only the Western sector of the country experiences late onsets Fig. 18 b: However, as the years progressed (1971 – 2000) the late onset had spread to more areas Onsets:
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21 Fig. 19 a : 1961 – 1990, few areas of the country experienced early cessation of the rains Fig. 19 b : However, 1971 – 2000, early cessation (red) has spread to more areas of the country Normal Cessation Late Cessation 1961-1990 1971-2000 Cessation:
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22 Longer S_L Shorter S_L Normal S_L Shorter S_L Normal S_L 1961-1990 1971-2000 Fig. 20a: 1961-1990, Western & CRR north experiences shorter season lengths. Fig. 20 b : 1971-2000, decreased has spread to more places S_Lengths:
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23 Comments; Based from this analysis; for 1961 – 1990, most parts of The Gambia had normal onsets and normal cessation dates of rainy season. As the years progressed (1971 – 2000) the late onset and early cessation had spread to more areas the results of the analysis produces mean season lengths which can be used for choice of crop variety; Mean Season Length (days) 1961-1990 1971-2000 Banjul 114 111 Yundum 116 114 Janjanbureh 126 119 Basse 134 128 Jenoi 119 118 Kerewan 117 117 Kuntaur 115 120 Advises; Crops with cycle of 120 days should be sown in Basse and environs in the eastern sector. Crops with cycle of about 119 days or less should be sown in areas around Banjul, Yundum, Kerewan, Jenoi, Kuntaur and Janjanbureh.
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24 Little or no research has been done in The Gambia on the linkages btw climate and biophysical processes, adverse effects operating indirectly through soil (salinisation, erosion) and water quality degradation (pollution/sediment load, salinity & etc), (NAPA on Climate Change, Banjul November, 2007).
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25 Need to strengthen weather, climate & water monitoring & prediction institutions in order to generate the required data, processed into use-able information, responsive (national development process) to the concerns of various stakeholders, Therefore, in order to produce quality data, maximum support is needed so that our Meteorological stations can be well equipped with standard equipments. Establish partnerships between national weather service and operators in various socio-economic sectors sensitive to variations in the climate system.
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