Satellite-based rainfall data reveal a recent drying trend in central equatorial Africa

West-central Uganda, a biodiversity hotspot on the eastern edge of central equatorial Africa (CEA), is a region coping with balancing food security needs of a rapidly growing human population dependent on subsistence agriculture with the conservation of critically endangered species. Documenting and understanding rainfall trends is thus of critical importance in west-central Uganda, but sparse information exists on rainfall trends in CEA during the past several decades. The recently created African Rainfall Climatology version 2 (ARC2) dataset has been shown to perform satisfactorily at identifying rainfall days and estimating seasonal rainfall totals in west-central Uganda. Therefore, we use ARC2 data to assess rainfall trends in west-central Uganda and other parts of equatorial Africa from 1983–2012. The core variables examined were three-month rainfall variables for west-central Uganda, and annual rainfall variables and seasonal rainfall totals for a transect that extended from northwestern Democratic Republic of the Congo to southern Somalia. Significant decreases in rainfall in west-central Uganda occurred for multiple three-month periods centered on boreal summer, and rainfall associated with the two growing seasons decreased by 20 % from 1983–2012. The drying trend in west-central Uganda extended westward into the Congo rainforest. Rainfall in CEA was significantly correlated with the Atlantic Multidecadal Oscillation (AMO) at the annual scale and during boreal summer and autumn. Two other possible causes of the decreasing rainfall in CEA besides North Atlantic Ocean sea-surface temperatures (e.g., AMO), are the warming of the Indian Ocean and increasing concentrations of carbonaceous aerosols over tropical Africa from biomass burning.     

Weakened interannual variability of the contrast in rainfall between the eastern equatorial Pacific and equatorial Atlantic since 2000

最近的研究表明与厄尔尼诺相关的热带太平洋的年际变化在2000年之后出现减弱。我们在研究中发现这种2000年之后的年际变化的减弱不仅局限在热带太平洋区域,在整个赤道东太平洋与大西洋耦合气候系统中都可以发现年际变化在2000年之后显著减弱的现象。特别地,赤道东太平洋与赤道大西洋之间降雨差异的年际变化也在2000年之后出现显著的减弱。这种降雨差异年际变化的减弱与赤道东太平洋与大西洋之间纬向海温梯度以及跨越南美洲低空纬向风的年际变化在2000年之后的减弱存在密切的联系。     

Intra-seasonal rainfall and piped water revenue variability in rural Africa

Rainfall patterns influence water usage and revenue from user payments in rural Africa. We explore these dynamics by examining monthly rainfall against 4,888 records of rural piped water revenue in Ghana, Rwanda, and Uganda and quantifying revenue changes over 635 transitions between dry and wet seasons.Results show operators experience revenue variability at regional and intra-seasonal scales. Revenues fall by an average of 30 percent during the wettest months of the year in climate regimes with consistent wet season rainfall. However, seasonally stable revenues are observed in areas where consecutive dry days are common during the wet season, potentially reflecting a dependency on reliable services. We also find changes in tariff level, waterpoint connection type, and payment approach do not consistently prevent or increase seasonal revenue variability.Local revenue generation underpins delivery of drinking water services. Where rainfall patterns remain consistent, piped water operators can expect to encounter seasonal revenue reductions regardless of whether services are provided on or off premises and of how services are paid for. Revenue projections that assume consistent volumetric demand year-round may lead to shortfalls that threaten sustainability and undermine the case for future investment. Intra-seasonal rainfall analysis can enhance rural piped water revenue planning by offering localised insight into demand dynamics and revealing where climate variability may increase dependency on reliable services.     

Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models

Climate Dynamics - The present study explored the performance of the current coupled models obtained from the Asia Pacific Economic Cooperation (APEC) Climate Centre (APCC) in representing the...     

Cloud feedback on sst variability in the western equatorial pacific in goals / lasg model

The cloud feedback on the SST variability in the western equatorial Pacific in GOALS / LASG model is studied in this paper. Two versions of the model, one with the diagnostic cloud and another with the prescribed cloud, are used. Both versions are integrated for 45 years. It is found that in the prescribed cloud run, the SST variability in the western equatorial Pacific is mainly of interdecadal time scale and the interannual variability is very weak. In the diagnostic cloud run, however, the interdecadal SST variability is depressed much and the interannual SST variability becomes much significant. The mechanism for the feedback is then explored. The variability of sea surface temperature (SST) in the western equatorial Pacific is found to be controlled mainly by the zonal wind anomaly, through the process of upwelling / downwelling in both versions. Then it is found that in the diagnostic cloud case, the negative feedback of the solar short wave (SW) flux acts significantly to balance the effect of upwelling / downwelling in addition to the latent flux. In addition, the variability of the SW flux is shown to be closely related to the variability of the middle and high cloud covers. Therefore, the negative feedback of the SW surface flux may have significant contribution to the cloud feedback on the SST variability.     

Spatial variability of rainfall at an experimental station in Niger,West Africa

Summary Variability of rainfall in the semi-arid regions can cause problems in evaluating experimental trials. To describe the spatial rainfall patterns over a large experimental station, rainfall was monitored during the 1986 and 1987 rainy seasons using 18 raingages over the 500 ha experimental station of ICRISAT Sahelian Center, in Niger, West Africa. Average relative variability of individual rain storms, defined as the percentage deviation from the mean, varied from 2 to 62%, while the variability over the rainy season was 17.1%. Isohyetal patterns of individual rain storms as well as seasonal totals showed distinct coherence in the spatial pattern over the station. The effects of total volume, duration, direction and intensity of storms and the time of year on the spatial correlations were analyzed. Storm value showed a large influence on the correlation decay with distance. Correlations in the W — E and SW — NE directions were higher in comparison to those in the N — S and NW — SE directions. Point rainfall measurements were better correlated with the network average rainfall than with the rainfall recorded at the meteorological station. Variograms among raingages revealed that the distance of independence was approximately 1 000 m for almost all storms. Use of a network of raingages over agricultural experiment stations reduces the average relative variability of areal rainfall estimates and provides a means to develop simple relations for estimation of point rainfall for individual applications.With 8 Figures     

Determination of seasonal rainfall variability, onset and cessation in semi-arid Tharaka district, Kenya

The study quantified rainfall variability for March–May (MAM) and October–December (OND) seasons in Tharaka district, Kenya. The parameters analysed were inter-annual variability of seasonal rainfall, onset and cessation using daily rainfall data in three agro-ecological zones’ stations. Percentage mean cumulative method was used to determine onset and cessation, and seasonal variability was estimated using rainfall variability indices. Although both seasons are highly variable, OND has been persistently below mean over time while MAM shows high within-season variability. Despite the near uniformity in the mean onset and cessation dates, the former is highly variable on an inter-annual scale. The two rainfall seasons are inherently dissimilar and therefore require specific cropping in agro-ecological zone LM4 and LM4-5. It is possible that farmers in IL5 are missing an opportunity by under-utilising MAM rainfall. The results should be incorporated in implications of climate variability and vulnerability assessment in semi-arid Tharaka district.     

Temporal rainfall variability in the Lake Victoria Basin in East Africa during the twentieth century

Water resources systems are designed and operated on assumption of stationary hydrology. Existence of trends and other changes in the data invalidates this assumption, and detection of the changes in hydrological time series should help us revise the approaches used in assessing, designing and operating our systems. In addition, trend and step change studies help us understand the impact of man’s activities (e.g. urbanisation, deforestation, dam construction, agricultural activities, etc.) on the hydrological cycle. Trends and step changes in the seasonal and annual total rainfall for 20 stations in the Lake Victoria basin were analysed. The seasonal rainfall for any station in a given year was defined in two ways: (1) fixed time period where the rainy seasons were taken as occurring from March–May (long rains) and from October–December (short rains); and (2) variable periods where the rainy seasons were taken as the three consecutive months with maximum total rainfall covering the period of January–June (long rains) and July–December (short rains), to take into account the fact that the onset of rainy seasons within the basin varies from year to year and from one station to the next. For each station, sub datasets were derived covering different periods (all available data at the station, 1941–1980, 1961–1990, 1971–end of each station’s time series). The trends were analysed using the Mann-Kendall method, while the step changes were analysed using the Worsley Likelihood method. The results show that positive trends predominate, with most stations showing trend being located in the northern part of the basin, though this pattern is not conclusive. In all, 17% of the cases have trends, of which 67% are positive. The 1960s represent a significant upward jump in the basin rainfall. Seasonal rainfall analysis shows that the short rains tend to have more trends than the long rains. The impact of the varying month of onset of the rainy season is that the results from analyzing the fixed-period and variable-period time series are rarely the same, meaning the two series have different characteristics. It may be argued that the variable-period time series are more reliable as a basis for analysing trends and step changes, since these time series reflect more closely the actual variability in rainy seasons from one year to the next. The fixed-period analysis would, on the other hand, find more practical use in planning.     

Interannual variability of East African rainfall: role of seasonal transitions of the low-level cross-equatorial flow

Climate Dynamics - During boreal spring and fall, the low-level cross-equatorial flow along the East African coast weakens and reverses. These transition periods are embedded within the East...     

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre’s climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.     

Interannual winter rainfall variability in SW South Africa and large scale ocean–atmosphere interactions

Summary The Southwestern Cape (SWC) region of South Africa is characterized by winter rainfall mainly via cold fronts and by substantial interannual variability. Evidence is presented that interannual variability in SWC winter rainfall is related to sea-surface temperature (SST) and sea-ice anomalies in the central South Atlantic and adjoining Southern Ocean and to large scale ocean–atmosphere interaction in this region. During wet winters, the jet is strengthened just upstream of the SWC and significant cyclonic anomalies extend from the SW Atlantic over the region. SST tends to be anomalously warm (cool) in the SW Atlantic and SE Atlantic (central South Atlantic) and sea-ice extent increased in the central South Atlantic sector of the Southern Ocean. These patterns favor increased cyclogenesis upstream, a more northward track of midlatitude depressions, local intensification near the SWC and enhanced rainfall. Roughly the reverse patterns occur during dry winters. Some preliminary results from atmospheric GCM experiments are presented which help support these findings. Received November 9, 2001 Revised December 28, 2001     

Caribbean Sea rainfall variability during the rainy season and relationship to the equatorial Pacific and tropical Atlantic SST

The present study investigates the Caribbean Sea rainfall variability during the early and late rainy seasons and its association with sea surface temperature (SST) and air?Csea interaction based on observational estimates, the NCEP Climate Forecast System (CFS) and Global Forecast System (GFS) simulations, and the CFS retrospective forecasts. Analysis of the observational estimates indicates that air?Csea interaction is important over the Caribbean Sea, whereas the atmospheric forcing of SST dominates over the Gulf of Mexico. The CFS simulation captures the basic elements of this observed air?Csea relationship. The GFS simulation produces spurious SST forcing of the atmosphere over the Gulf of Mexico largely due to prescribing SST. The CFS forecasts capture the air?Csea relationship in the late rainy season (August?COctober), but cannot reproduce the SST forcing of atmosphere over the Caribbean Sea in the early rainy season (May?CJuly). An empirical orthogonal function (EOF) analysis indicates that the leading modes of percent anomalies of the rainy season precipitation have the largest loading in the southern Caribbean Sea in observations. The model simulations and forecasts skillfully reproduce the spatial pattern, but not the temporal evolution. The Caribbean Sea rainfall variability in the early rainy season is mainly due to the tropical North Atlantic (TNA) SST anomalies in observations, is contributed by both the TNA and eastern equatorial Pacific (EEP) SST anomalies in the CFS simulation, and has an overly large impact from the EEP SST anomalies in the GFS simulation and the CFS forecasts. The observed Caribbean Sea rainfall variability in the late rainy season has a leading impact from the EEP SST anomalies, with a secondary contribution from the TNA SST anomalies. In comparison, the model simulations and forecasts overestimate the impacts of the EEP SST anomalies due to an earlier development and longer duration of the El Ni?o-Southern Oscillation in the CFS compared to observations.     

Seasonal variability of rainfall extremes

Monthly rainfall extremes have been analyzed for three stations in Southern Ontario. The double exponential probability distribution was fitted to the extreme values for each month considered, each duration selected, and sets of annual extremes. A station‐year approach yielded monthly and annual extreme value distributions for the lumped region of Southern Ontario. The analysis has revealed a pronounced seasonal pattern in the rainfall extremes – the amount of rain expected with a selected probability of occurrence during the summer being considerably greater than the rainfall that might be expected to be exceeded at the same probability level during the spring or fall. The extent of the seasonal variability was found also to vary with duration. The implications of the variability are seen to be significant for the estimation of the magnitude and frequency of floods.