Future intensification of precipitation and wind gust associated thunderstorms over Lake Victoria

Severe thunderstorms affect more than 30 million people living along the shores of Lake Victoria (East Africa). Thousands of fishers lose their lives on the lake every year. While deadly waves are assumed to be initiated by severe wind gusts, knowledge about thunderstorms is restricted to precipitation or environmental proxies. Here we use a regional climate model run at convection-permitting resolution to simulate both precipitation and wind gusts over Lake Victoria for a historical 10-year period. In addition, a pseudo global warming simulation provides insight into the region’s future climate. In this simulation, ERA5’s initial and boundary conditions are perturbed with atmospheric changes between 1995–2025 and 2070–2100, projected by CMIP6’s ensemble mean. It was found that future decreases in both mean precipitation and wind gusts over Lake Victoria can be attributed to a weaker mean mesoscale circulation that reduces the trigger for over-lake nighttime convection and decreases the mean wind shear. However, an intensification of extremes is projected for both over-lake precipitation and wind gusts. The observed 7 %K−1 Clausius–Clapeyron extreme precipitation scaling is ascribed to increased water vapor content and a compensation of weaker mesoscale circulations and stronger thunderstorm dynamics. More frequent wind gust extremes result from higher wind shear conditions and more compound thunderstorms with both intense rainfall and severe wind gusts. Overall, our study emphasizes Lake Victoria’s modulating role in determining regional current and future extremes, in addition to changes expected from the Clausius–Clapeyron relation

The Multi-Satellite Environmental and Socioeconomic Predictors of Vector-Borne Diseases in African Cities:Malaria as an Example

Remote sensing has been used for decades to produce vector-borne disease risk maps aiming at better targeting control interventions. However, the coarse and climatic-driven nature of these maps largely hampered their use in the fight against malaria in highly heterogeneous African cities. Remote sensing now offers a large panel of data with the potential to greatly improve and refine malaria risk maps at the intra-urban scale. This research aims at testing the ability of different geospatial datasets exclusively derived from satellite sensors to predict malaria risk in two sub-Saharan African cities: Kampala (Uganda) and Dar es Salaam (Tanzania). Using random forest models, we predicted intra-urban malaria risk based on environmental and socioeconomic predictors using climatic, land cover and land use variables among others. The combination of these factors derived from different remote sensors showed the highest predictive power, particularly models including climatic, land cover and land use predictors. However, the predictive power remained quite low, which is suspected to be due to urban malaria complexity and malaria data limitations. While huge improvements have been made over the last decades in terms of remote sensing data acquisition and processing, the quantity and quality of epidemiological data are not yet sufficient to take full advantage of these improvements

Modelling and mapping the intra-urban spatial distribution of Plasmodium falciparum parasite rate using very-high-resolution satellite derived indicators

BACKGROUND: The rapid and often uncontrolled rural-urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa's population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam. METHODS: Openly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2-10 years (PfPR2-10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2-10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population. RESULTS: The results suggest that the spatial distribution of PfPR2-10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2-10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values. CONCLUSIONS: The outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Evaluation framework for sub-daily rainfall extremes simulated by regional climate models

peer reviewedSub-daily precipitation extremes are high-impact events that can result in flash floods, sewer system overload, or landslides. Several studies have reported an intensification of projected short-duration extreme rainfall in a warmer future climate. Traditionally, regional climate models (RCMs) are run at a coarse resolution using deep-convection parameterization for these extreme events. As computational resources are continuously ramping up, these models are run at convection-permitting resolution, thereby partly resolving the small-scale precipitation events explicitly. To date, a comprehensive evaluation of convection-permitting models is still missing. We propose an evaluation strategy for simulated sub-daily rainfall extremes that summarizes the overall RCM performance. More specifically, the following metrics are addressed: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling and spatio-temporal clustering. The aim of this paper is: (i) to provide a statistical modeling framework for some of the metrics, based on extreme value analysis, (ii) to apply the evaluation metrics to a micro-ensemble of convection-permitting RCM simulations over Belgium, against high-frequency observations, and (iii) to investigate the added value of convection-permitting scales with respect to coarser 12-km resolution. We find that convection-permitting models improved precipitation extremes on shorter time scales (i.e, hourly or two-hourly), but not on 6h-24h time scales. Some metrics such as the diurnal cycle or the Clausius-Clapeyron rate are improved by convection-permitting models, whereas the seasonal cycle appears robust across spatial scales. On the other hand, the spatial dependence is poorly represented at both convection-permitting scales and coarser scales. Our framework provides perspectives for improving high-resolution atmospheric numerical modeling and datasets for hydrological applications

Modelling strategies for performing convection-permitting climate simulations

The computational cost still remains a limiting factor for performing convection-permitting climate simulations. Choosing a model set-up with the lowest computational cost without deteriorating the model performances is, therefore, of relevance before starting any decadal simulations at convection-permitting scale (CPS). In this study three different strategies that aim at reducing this computational cost are evaluated. These strategies are (1) excluding graupel in the microphysical scheme, (2) reducing the nesting steps to downscale from ERA-Interim scale to CPS and (3) reducing the domain size. To test these strategies, the COSMO-CLM regional model was integrated over a four-month summer period for Belgium and evaluated using both radar and rain-gauges precipitation data. It was found that excluding the graupel parametrization at CPS induces a dry bias, but that excluding the graupel parametrization in the parent nest of the CPS simulation does not impact daily accumulated precipitation. In addition, it was also found that the best downscaling strategy is to use two nesting steps, in our case 25 km and 2.8 km. The 7 km nest was found to be redundant. Finally, it was found that a minimum distance of ~150$\sim 150$ km between the evaluation domain and the lateral boundary is needed for daily precipitation to converge towards observed values. This indicates that the domain size must be large enough for the model to spin-up convective precipitation and in our case a domain size of 180×180$180 \times 180$ grid-points was found to be necessary. Our recommendations for CPS simulations at lowest computational cost are therefore (1) to include graupel parametrization at CPS but not in the parent nest, (2) to use two nesting steps to downscale from ERA-Interim to CPS and (3) to use a domain size large enough to allow for 150 km spatial spin-up

Modelling the water balance of Lake Victoria (East Africa) - Part 1: Observational analysis

Lake Victoria is the largest lake in Africa and one of the two major sources of the Nile river. The water level of Lake Victoria is determined by its water balance, consisting of precipitation on the lake, evaporation from the lake, inflow from tributary rivers and lake outflow, controlled by two hydropower dams. Due to a scarcity of in situ observations, previous estimates of individual water balance terms are characterized by substantial uncertainties, which means that the water balance is often not closed independently. In this first part of a two-paper series, we present a water balance model for Lake Victoria, using state-of-the-art remote sensing observations, high-resolution reanalysis downscaling and outflow values recorded at the dam. The uncalibrated computation of the individual water balance terms yields lake level fluctuations that closely match the levels retrieved from satellite altimetry. Precipitation is the main cause of seasonal and interannual lake level fluctuations, and on average causes the lake level to rise from May to July and to fall from August to December. Finally, our results indicate that the 2004–2005 drop in lake level can be about half attributed to a drought in the Lake Victoria Basin and about half to an enhanced outflow, highlighting the sensitivity of the lake level to human operations at the outflow dam.ISSN:1027-5606ISSN:1607-793

Modelling the water balance of Lake Victoria (East Africa) - Part 2: Future projections

Lake Victoria, the second largest freshwater lake in the world, is one of the major sources of the Nile river. The outlet to the Nile is controlled by two hydropower dams of which the allowed discharge is dictated by the Agreed Curve, an equation relating outflow to lake level. Some regional climate models project a decrease in precipitation and an increase in evaporation over Lake Victoria, with potential important implications for its water balance and resulting level. Yet, little is known about the potential consequences of climate change for the water balance of Lake Victoria. In this second part of a two-paper series, we feed a new water balance model for Lake Victoria presented in the first part with climate simulations available through the COordinated Regional Climate Downscaling Experiment (CORDEX) Africa framework. Our results reveal that most regional climate models are not capable of giving a realistic representation of the water balance of Lake Victoria and therefore require bias correction. For two emission scenarios (RCPs 4.5 and 8.5), the decrease in precipitation over the lake and an increase in evaporation are compensated by an increase in basin precipitation leading to more inflow. The future lake level projections show that the dam management scenario and not the emission scenario is the main controlling factor of the future water level evolution. Moreover, inter-model uncertainties are larger than emission scenario uncertainties. The comparison of four idealized future management scenarios pursuing certain policy objectives (electricity generation, navigation reliability and environmental conservation) uncovers that the only sustainable management scenario is mimicking natural lake level fluctuations by regulating outflow according to the Agreed Curve. The associated outflow encompasses, however, ranges from 14m3day−1 (−85%) to 200m3day−1 (+100%) within this ensemble, highlighting that future hydropower generation and downstream water availability may strongly change in the next decades even if dam management adheres to he Agreed Curve. Our results overall underline that managing the dam according to the Agreed Curve is a key prerequisite for sustainable future lake levels, but that under this management scenario, climate change might potentially induce profound changes in lake level and outflow volume.ISSN:1027-5606ISSN:1607-793

Estimating the effect of rainfall on the surface temperature of a tropical lake

We make use of a unique high-quality, long-term observational dataset on a tropical lake to assess the effect of rainfall on lake surface temperature. The lake in question is Lake Kivu, one of the African Great Lakes, and was selected for its remarkably uniform climate and availability of multi-year over-lake meteorological observations. Rain may have a cooling effect on the lake surface by lowering the near-surface air temperature, by the direct rain heat flux into the lake, by mixing the lake surface layer through the flux of kinetic energy and by convective mixing of the lake surface layer. The potential importance of the rainfall effect is discussed in terms of both heat flux and kinetic energy flux. To estimate the rainfall effect on the mean diurnal cycle of lake surface temperature, the data are binned into categories of daily rainfall amount. They are further filtered based on comparable values of daily mean net radiation, which reduces the influence of radiative-flux differences. Our results indicate that days with heavy rainfall may experience a reduction in lake surface temperature of approximately 0.3 K by the end of the day compared to days with light to moderate rainfall. Overall this study highlights a new potential control on lake surface temperature and suggests that further efforts are needed to quantify this effect in other regions and to include this process in land surface models used for atmospheric prediction.ISSN:1027-5606ISSN:1607-793

Drivers of furture changes in East African precipitation

Precipitation amounts over East Africa have been declining over the last decades. These changes and future climate change over the region are highly debated. This study analyzes drivers of future precipitation changes over East Africa by applying a classification of circulation patterns on 15 historical and future members of the COordinated Regional climate Downscaling EXperiment. Typical circulation types (CTs) are obtained. Under a high emission scenario, changes in the frequency of occurrence of these CTs attribute for 23% of the total change in precipitation over East Africa by the end of the century. The remaining part (77%) is not related to East African synoptics, e.g. changes in moisture content, local/mesoscale feedbacks, and changes in moisture influx. These other effects comprise increases in precipitation close to the equator and the Somali region, while decreases are found over northwestern Ethiopia, the Sudan region and the lake areas.ISSN:1748-9326ISSN:1748-931