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Evaluation of the Performance of ENACTS MAP-ROOM Products over Tanzania

DOI: 10.4236/acs.2019.92014, PP. 202-212

Keywords: Climate Change, Rainfall, Temperature, ENACT-MAPROOM Products

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Tanzania has inadequate weather stations (28-synoptic weather stations), which are sparsely distributed over complex topographic terrain. Many places, especially rural areas, have no stations to monitor weather and climate. In this study, we evaluate the performance of ENACT-MAPROOM products over Tanzania with the aim of assessing their potential to supplement observed weather and climate data, especially over areas where there is limited number of weather stations. Monthly rainfall total and monthly averaged minimum and maximum temperatures from ENACT-MAPROOM are evaluated against observed data from 23 weather stations. The evaluation is limited to analyze how well the ENACT-MAPROOM products reproduce climatological trends, annual cycles and inter-annual variability of rainfall, minimum and maximum temperatures. Statistical analysis recommended by the World Meteorological Organization (WMO) that includes that correlation and trend analysis are used. It is found that ENACT-MAPROOM products reproduce the climatological trends, annual cycles and inter-annual variability of rainfall, minimum and maximum temperatures over most stations. The statistical relationship between ENACT-MAPROOM products against observed data from 23 weather stations using Pearson correlation coefficient indicates that ENACT-MAPROOM products bear strong and statistically significant correlation coefficient to observed data. The overall evaluation here finds high skills of ENACT-MAPROOM products in representing rainfall and temperature over Tanzania, suggesting their potential use in planning and decision making especially over areas with limited number of weather stations.


[1]  Luhunga, P.M, Mutayoba, E. and Ng’ongolo, H. (2014) Homogeneity of Monthly Mean Air Temperature of the United Republic of Tanzania with HOMER. Atmospheric and Climate Sciences, 4, 70-77.
[2]  Zambrano-Bigiarini, M., Nauditt, A., Birkel, C., Verbist, K. and Ribbe, L. (2017) Temporal and Spatial Evaluation of Satellite-Based Rainfall Estimates across the Complex Topographical and Climatic Gradients of Chile. Hydrology and Earth System Sciences, 21, 1295-1320.
[3]  Liu, Z. (2015) Evaluation of Precipitation Climatology Derived from TRMM Multi-Satellite Precipitation Analysis (TMPA) Monthly Product over Land with Two Gauged-Based Products. Climate, 3, 964-982.
[4]  Luhunga, P.M., Botai, J. and Kahimba, F. (2016) Evaluation of the Performance of CORDEX Regional Climate Models in Simulating Present Climate Conditions of Tanzania. Journal of Southern Hemisphere Earth Systems Science, 66, 33-55.
[5]  Dembélé, M. and Zwart, S.J. (2016) Evaluation and Comparison of Satellite-Based Rainfall Products in Burkina Faso, West Africa. International Journal of Remote Sensing, 37, 3995-4014.
[6]  Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S. and Hsu, K.-L. (2018) A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Inter-Comparisons. Reviews of Geophysics, 56, 79-107.
[7]  Dell, M., Benjamin, J.F. and Benjamin, A.O. (2014) What Do We Learn from the Weather? The New Climate-Economy Literature. Journal of Economic Literature, 52, 740-798
[8]  Barnston, A.G. and Tippett, M.K. (2014) Climate Information, Outlooks, and Understanding—Where Does the IRI Stand? Earth Perspectives, 1, 20.
[9]  Kijazi, A.L. and Reason, C.J.C. (2009) Analysis of the 2006 Floods over Northern Tanzania. International Journal of Climatology, 29, 955-970.
[10]  Kijazi, A.L. and Reason, C.J.C. (2009) Analysis of the 1998-2005 Droughts over the North-Eastern Highlands of Tanzania. Climate Research, 38, 209-223.
[11]  Hartkamp, A.D., De Beurs, K., Stein, A. and White, J.W. (1999) Interpolation Techniques for Climate Variables. NRG-GIS Series 99-01, MMYT, Mexico.
[12]  Ly, S., Charles, C. and Degre, A. (2013) Geostatistical Interpolation of Daily Rainfall at Catchment Scale: The Use of Several Variogram Models in the Ourthe and Ambleve Catchments, Belgium. Hydrology and Earth System Sciences, 15, 2259-2274.
[13]  Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S.C., Collins, W., Cox, P., Driouech, F., Emori, S. , Eyring, V., Forest, C., Gleckler, P., Guilyardi, E., Jakob, C., Kattsov, V., Reason, C. and Rummukainen, M. (2013) Evaluation of Climate Models. In: Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V. and Midgley, P.M., Eds., Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, New York, NY.
[14]  Gordon, N. and Shaykewich, J. (2000) Guidelines on Performance Assessment of Public Weather Services. WMO/TD No. 1023, 32.
[15]  Rodrigo, F.S. and Trigo, R.M. (2007) Trends in Daily Rainfall in the Iberian Peninsula from 1951 to 2002. International Journal of Climatology, 27, 513-529.
[16]  Ahmad, I., Tang, D., Wang, T.F., Wang, M. and Wagan, B. (2015) Precipitation Trends over Time Using Mann-Kendall and Spearman’s rho Tests in Swat River Basin, Pakistan. Advances in Meteorology, 2015, Article ID: 431860.


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