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Girma Mamo

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Girma Mamo
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Girma Mamo

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    Trend and variability of rainfall in Tigray, Northern Ethiopia: Analysis of meteorological data and farmers' perception
    (Academia Publishing, 2013) Gebre Hadgu; Tesfaye, K.; Girma Mamo; Belay Kassa
    Rainfall is the most important but variable climatic parameter in the semiarid tropics. In this study, the trend and variability of rainfall were compared with the perception of farmers in northern Ethiopia. Daily rainfall data obtained from five meteorological stations located in different agroecological zones were used to determine trends in annual and seasonal totals, onset and cessation dates, length of growing period (LGP) and dry spell length. Sen?s estimator and Mann-Kendall's statistical tests were used for trend detection. Two hundred fifty three farmers from three administrative areas (districts) that are close to the meteorological stations were interviewed in order to investigate farmers' perception on rainfall trend and variability in the study area. The results indicate that rainfall in the region is highly variable with a non-significant trend in both annual and seasonal totals for all stations. However, trends of rainfall events such as onset date, cessation date, LGP, and dry spell length were changed significantly in most stations, which agreed with the farmers? perception. Moreover, most stations experienced drought conditions in the last decade. The results suggest the need for designing appropriate agronomic and water management strategies to offset the negative impacts of rainfall variability in the study area.
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    Outlook of future climate in northwestern Ethiopia
    (Scientific Research Publishing, 2012) Dereje Ayalew; Tesfaye, K.; Girma Mamo; Birru Yitaferu; Wondimu Bayu
    Climate change is described as the most universal and irreversible environmental problem facing the planet Earth. While climate change is already manifesting in Ethiopia through changes in temperature and rainfall, its magnitude is poorly studied at regional levels. The objective of this paper was to assess and quantify the magnitude of future changes of climate parameters using Statistical Downscaling Mode (SDSM) version 4.2 in Amhara Regional State which is located between 8°45‘N and 13°45‘N latitude and 35°46‘E and 40°25‘E longitude. Daily climate data (1979- 2008) of rainfall, maximum and minimum temperatures were collected from 10 observed meteorological stations (predictand). The stations were grouped and compared using clustering and Markov chain model, whereas the degree of climate change in the study area was estimated using the coupled HadCM3 general circulation model (GCM) with A2a emission scenarios (Predictors). Both maximum and minimum temperatures showed an increasing trend; the increase in mean maximum temperature ranges between 1.55°C and 6.07°C and that of the mean minimum temperature ranges from 0.11°C and 2.81°C. While the amount of annual rainfall and rainy days decreased in the study Regions in the 2080s. The negative changes in rainfall and temperature obtained from the HadCM3 model in the current study are alarming and suggest the need for further study with several GCM models to confirm the current results and develop adaptation options.
    Publication