Downscaling rainfall in the upper Blue Nile basin for use in

Transcription

1 Downscaling rainfall in the upper Blue Nile basin for use in hydrological modelling Michael Menker Girma 1, Brigita Schuett 1, Seleshi B. Awulachew 2, Matthew Mccartney 2, & Solomon S. Demissie 2 1 Department of Earth Sciences, Freie university of Berlin 2 International Water Management Institute, Regional office for Nile Basin and East Africa, Addis Ababa

2 Upper Blue Nile basin (UBN) The Ethiopian portion contribute 86% of Nile flows at Aswan Largest tributary of the main Nile Abay is largest basin in volume of discharge in Ethiopia Mean annual discharge of 48.5 cubic kilometers

3 Trends in temperature Mean annual temperature has increased by 1.3 C between 1960 and 2006, an average rate of 0.28 C per decade. d The increase in temperature in Ethiopia has been most rapid in JAS at a rate of 0.32 C per decade. Daily temperature observations show significantly increasing trends in the frequency of hot days, and much large increasing trends in the frequency of hot nights. Source: UNDP National Communication Support Programme (NSCP) and the UK government Department for International Development (DfiD)

4 Trends in precipitation The strong inter annual and inter decadal variability in Ethiopia's rainfall makes it difficult to detect long term trends. There is not a statistically significant trend in observed mean rainfall in any season in Ethiopia between 1960 and Decreases in JAS rainfall observed in the 1980s have shown recovery in the 1990s and 2000s.

5 Statistical ti ti downscaling Preparation of observed data Preparation of reanalysis data Selection of domains Combining domains Calibration and validation of SDMs Simulation using future Scenarios

6 Statistical ti ti downscaling Empirical relationships b/n circulation patterns with regional climate Strong ocean atmosphere coupling in Tropics Strong variation b/n large scale predictors & local variables Lack of long years and high resolution climate data

7 Preparation a of observed ed data a Five stations selected Gondar, Assosa, Debre Markos, Addis Ababa and Combolcha Data Different climate zones considered

8 Preparation of predictors Predictors are atmospheric & ocean fields. From NCEP-NCER NCER [ / GCM generated through assimilation with observation 25d 2.5 degrees x 25d 2.5 degrees

9 Preparation of predictors Sr. No. Predictors Unit Abbreviation Levels (hp) 1 Geopotential height m 500, Relative humidity % Rh 500, Zonal wind speed m/s U 100, 850,500,700 4 Meridional wind speed m/s V 500, Mean sea level pressure P Mslp surface 6 Sea surface temperature k SST Surface 7 Precipitable water kg/m^2 entire atmospheric column

10 Jun Jul Selection of Domains Aug DJFM Apr Monthly correlation between mean sea level pressure and observed rainfall at Debre Markos for a period of at 10% significant level

11 AP, NAO, STAO, IO and MNA were selected Selection of Domain Correlation analysis (Significant at 10%) Visual inspection Climatology of the basin

12 Combining i domains Monthly correlation b/n area averaged NCEP and observed data showed mixed results No single domain was better than the others A new combined domain was synthesized from the five by extracting the months with the highest correlation from each domain

13 Monthly correlation between observed data & large scale predictors at Addis Ababa after combining domains and screening of candidate predictors on monthly basis

14 Calibration and validation of SDMs Multiple regression analysis base line climatology l Split year approach calibration validation

15 Validation of SDMs

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17 Validation of SDMs Station Addis Ababa 11 Assosa 25 Combolcha 17 Debre Markos 10 Gondar 12 MAE in Mean Annual rainfall ifll( (mm)

18 Simulating using future Scenarios Climate change scenario ECHAM5 A1B scenario from Max-Plank institute of meteorology [ Spatial resolution of 1.9 degree by 1.9 degree Regridding using the cdo operators Gaussian grid to regular lat-long long

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20 The result of future climate change simulation using ECHAM5-A1B outputs as input to SDMs developed for the basin showed: i) a decrease in rainfall by 6-12% during the small rainy period and ii) mixed results for the ) main rainy season.

21 Conclusions The use of more than one testing climate stations to determine the location of downscaling domains is found to be essential. Due to significant ifi variation in monthly correlation between predictors (atmospheric and ocean variables) and predictand d (rainfall) within the annual cycle in different domains, rainfall downscaling in UBN should consider combining predictors from different domains rather than using a particular domain to obtain better SDMs.

22 Acknowledgment This research was supported by the Deutscher Akademischer Austauschdienst (DAAD) through a study grant for the first author. The field work was sponsored by the International Water Management Institute (IWMI) as part of its research program on Adaptation of African Agriculture to Climate Change.

23 In the cable written last year, a foreign ministry official of Egypt urged the US to help postpone a referendum on independence for Southern Sudan. The official said the creation of a non-viable state could threaten Egypt's access to the River Nile. Wikileaks