Rainfall and circulation changes accompanying the Indian monsoon onset are examined, focusing on the African continent and neighboring areas. The Indian Meteorological Department official monsoon onset dates over Kerala (MOK; on average on 1 June) are used. Composites are formed at a pentad (5 days) time scale to compare pre-and postonset conditions. Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) data for 1979-2007 indicate that a substantial rainfall decrease over several parts of Africa is associated with MOK. Significant rainfall anomalies, after removal of the mean seasonal cycle, are found in eastern Africa and the nearby western Indian Ocean. Indian monsoon onset dates over the period 1958-2001 are correlated at 0.55 with the cessation dates of the March-May rainy season (the long rains) averaged over Kenya and northern Tanzania. The rainy season cessation leads the onset by 12 days, on average. An early cessation of the March-May rains tends to precede an early onset over India. Over East Africa, the rainfall decrease is associated with a strengthening of the southerly winds (Somali jet) shortly before MOK, enhancing wind divergence and wind shear.A weaker rainfall signal is noted over western Africa and the Gulf of Guinea. MOK coincides with a pause in the progression of the West African monsoon. The pause is associated with anomalous descent over the Sahel, culminating two to three pentads after MOK. Composite maps further indicate that MOK is followed over much of the African continent by a sea level pressure rise and, between India and North Africa, a westward propagation of easterly wind and positive geopotential height anomalies. Many of these signals are associated with MaddenJulian oscillations, but independent features, suggesting Rossby wave propagation over North Africa, are also found to connect MOK and West Africa. Overall, these results are indicative of a large-scale adjustment of the atmospheric dynamics across both eastern and western Africa in conjunction with the monsoon onset over India.
More often daily climate data have been used in hydrological models to estimate flood flows in small data scarce urban and rural catchments where flow peaking and recession are quick within short periods of few hours. This study assesses magnitudes of error of using daily climate data to simulate flood flow hydrographs of a small urban river catchment, Msimbazi River. Spot discharge measurements were available for Apr-May 2014 and MarMay 2015 periods.10-minutes climate records were available at one station, daily temperatures at two stations while daily rainfall records at several stations within the catchment. Visual analysis characterise rainfall events during the 2011, 2014 and 2015 floods, Thiessen-polygon was used for catchment rainfall, Hargreave-Samani model for catchment potential evapotranspiration and flow hydrographs were estimated by calibrated HBV model. Length weighted channel slope was estimated from segment slopes established from available topographical maps and used in estimating time of concentration for the catchment using Kirpich method. Results indicated that simulated flood hydrographs using 10-minutes climate inputs produced higher flood peaks for both December 2011 (peak: 471.6 m3 /s) and April 2014 (peak: 393.5 m3 /s) and expected hydrograph recession behaviour reproducing the Kirpich estimate of time of concentration of 7 hours. Simulated flood peaks using daily climate inputs were 252.3 m3 /s for December 2011 and 205 m3 /s for the April 2014 event being 53% and 52% of those simulated from 10-minutes climate inputs. Despite usefulness of 10-minute climate data, these data are required at more stations within the catchment for reliable simulation of fast receding urban floods and therefore more automatic weather stations are needed in Dar es Salaam.
Urban communities in developing countries are one of the most vulnerable areas to extreme rainfall events. The availability of local information on extreme rainfall is therefore critical for proper planning and management of urban flooding impacts. This study examined the past and future characteristics of extreme rainfall in the urban catchments of Dar es Salaam, Tanzania. Investigation of trends and frequency of annual, seasonal and extreme rainfall was conducted, with the period 1967–2017 taken as the past scenario and 2018–2050 as the future scenario; using data from four key ground-based weather stations and RCM data respectively. Mann–Kendall trend analysis and Sen's slope estimator were used in studying changes in rainfall variability. Frequencies of extreme rainfall events were modeled using the Generalized Pareto model. Overall, the results of trend analysis provided evidence of a significant increase in annual and seasonal maximum rainfall and intensification of extreme rainfall in the future under the RCP4.5 CO2 concentration scenario. It was determined that extreme rainfall will become more frequent in the future, and their intensities were observed to increase approximately between 20 and 25% relative to the past. The findings of this study may help to develop adaptation strategies for urban flood control in Dar es Salaam.
Over the past half-century, the risk of urban flooding in Dar es Salaam has increased due to changes in land cover coupled with climatic changes. This paper aimed to quantify the impacts of climate and land-cover changes on the magnitudes and frequencies of flood runoffs in urban Dar es Salaam, Tanzania. A calibrated and validated SWAT rainfall-runoff model was used to generate flood hydrographs for the period 1969–2050 using historical rainfall data and projected rainfall based on the CORDEX-Africa regional climate model. Results showed that climate change has a greater impact on change in peak flows than land-cover change when the two are treated separately in theory. It was observed that, in the past, the probability of occurrence of urban flooding in the study area was likely to be increased up to 1.5-fold by climate change relative to land-cover change. In the future, this figure is estimated to decrease to 1.1-fold. The coupled effects of climate and land-cover changes cause a much bigger impact on change in peak flows than any separate scenario; this scenario represents the actual scenario on the ground. From the combined effects of climate and land-cover changes, the magnitudes of mean peak flows were determined to increase between 34.4 and 58.6% in the future relative to the past. However, the change in peak flows from combined effects of climate and land-cover changes will decrease by 36.3% in the future relative to the past; owing to the lesser variations in climate and land-cover changes in the future compared with those of the past.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.