Dhr Modelling of Cycles in Rainfall and Riverflow Across Ghana » książka
Dhr Modelling of Cycles in Rainfall and Riverflow Across Ghana
ISBN-13: 9783659495151 / Angielski / Miękka / 2014 / 116 str.
Dynamic Harmonic Regression (DHR) model of Lancaster University has been used to capture the cycles (seasonal and inter-annual) and trends in rainfall and riverflow across the latitudinal gradient of Ghana. The model explicitly calculates uncertainty in the estimated cycles and trends and thereby ensures that the data are not over-interpreted. Consequently, the model robustly quantifies a range of differences in the rainfall and riverflow regime within-and-between the humid tropical regions of southern Ghana and semi-arid northern Ghana. Some of these regional characteristics propagate through to the riverflow regime, though local climatic phenomena and catchment characteristics can also be seen to impact. These findings have implications for climate simulation studies and for forecasting the incidence of floods and droughts in Ghana, a country so reliant on predictable rainfall and riverflow dynamics for its agricultural economy
Dynamic Harmonic Regression (DHR) model of Lancaster University has been used to capture the cycles (seasonal and inter-annual) and trends in rainfall and riverflow across the latitudinal gradient of Ghana. The model explicitly calculates uncertainty in the estimated cycles and trends and thereby ensures that the data are not over-interpreted. Consequently, the model robustly quantifies a range of differences in the rainfall and riverflow regime within-and-between the humid tropical regions of southern Ghana and semi-arid northern Ghana. Some of these regional characteristics propagate through to the riverflow regime, though local climatic phenomena and catchment characteristics can also be seen to impact. These findings have implications for climate simulation studies and for forecasting the incidence of floods and droughts in Ghana, a country so reliant on predictable rainfall and riverflow dynamics for its agricultural economy
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