A breeding site model for regional, dynamical malaria simulations evaluated using in situ temporary ponds observations

Daily observations of potential mosquito developmental habitats in a suburb of Kumasi in central Ghana reveal a strong variability in their water persistence times, which ranged between 11 and 81 days. The persistence of the ponds was strongly tied with rainfall, location and size of the puddles. A simple power-law relationship is found to fit the relationship between the average pond depth and area well. A prognostic water balance model is derived that describes the temporal evolution of the pond area and depth, incorporating the power-law geometrical relation. Pond area increases in response to rainfall, while evaporation and infiltration act as sink terms. Based on a range of evaluation metrics, the prognostic model is judged to provide a good representation of the pond coverage evolution at most sites. Finally, we demonstrate that the prognostic equation can be generalised and equally applied to a grid-cell to derive a fractional pond coverage, and thus can be implemented in spatially distributed models for relevant vector- borne diseases such as malaria

Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa

An energy budget model is developed to predict the water temperature of typical mosquito larval developmental habitats. It assumes a homogeneous mixed water column driven by empirically derived fluxes. The model shows good agreement at both hourly and daily time scales with 10-min temporal resolution observed water temperatures, monitored between June and November 2013 within a peri-urban area of Kumasi, Ghana. There was a close match between larvae development times calculated using either the model-derived or observed water temperatures. The water temperature scheme represents a significant improvement over assuming the water temperature to be equal to air temperature. The energy budget model requires observed minimum and maximum temperatures, information that is generally available from weather stations. Our results show that hourly variations in water temperature are important for the simulation of aquatic-stage development times. By contrast, we found that larval development is insensitive to sub-hourly variations. Modelling suggests that in addition to water temperature, an accurate estimation of degree-day development time is very important to correctly predict the larvae development times. The results highlight the potential of the model to predict water temperature of temporary bodies of surface water. Our study represents an important contribution towards the improvement of weather-driven dynamical disease models, including those designed for malaria early forecasting systems

Mosquito breeding site water temperature observations and simulations towards improved vector-borne disease models for Africa

An energy budget model is developed to predict the water temperature of typical mosquito larval developmental habitats. It assumes a homogeneous mixed water column driven by empirically derived fluxes. The model shows good agreement at both hourly and daily time scales with 10-min temporal resolution observed water temperatures, monitored between June and November 2013 within a peri-urban area of Kumasi, Ghana. There was a close match between larvae development times calculated using either the model-derived or observed water temperatures. The water temperature scheme represents a significant improvement over assuming the water temperature to be equal to air temperature. The energy budget model requires observed minimum and maximum temperatures, information that is generally available from weather stations. Our results show that hourly variations in water temperature are important for the simulation of aquatic-stage development times. By contrast, we found that larval development is insensitive to sub-hourly variations. Modelling suggests that in addition to water temperature, an accurate estimation of degree-day development time is very important to correctly predict the larvae development times. The results highlight the potential of the model to predict water temperature of temporary bodies of surface water. Our study represents an important contribution towards the improvement of weather-driven dynamical disease models, including those designed for malaria early forecasting systems

A process-based validation of GPM IMERG and its sources using a mesoscale rain gauge network in the West African forest zone

Using a two-year dataset (2016–17) from 17 one-minute rain gauges located in the moist forest region of Ghana, the performance of Integrated Multisatellite Retrievals for GPM, version 6b (IMERG), is evaluated based on a subdaily time scale, down to the level of the underlying passive microwave (PMW) and infrared (IR) sources. Additionally, the spaceborne cloud product Cloud Property Dataset Using SEVIRI, edition 2 (CLAAS-2), available every 15 min, is used to link IMERG rainfall to cloud-top properties. Several important issues are identified: 1) IMERG’s proneness to low-intensity false alarms, accounting for more than a fifth of total rainfall; 2) IMERG’s overestimation of the rainfall amount from frequently occurring weak convective events, while that of relatively rare but strong mesoscale convective systems is underestimated, resulting in an error compensation; and 3) a decrease of skill during the little dry season in July and August, known to feature enhanced low-level cloudiness and warm rain. These findings are related to 1) a general oversensitivity for clouds with low ice and liquid water path and a particular oversensitivity for low cloud optical thickness, a problem which is slightly reduced for direct PMW overpasses; 2) a pronounced negative bias for high rain intensities, strongest when IR data are included; and 3) a large fraction of missed events linked with rainfall out of warm clouds, which are inherently misinterpreted by IMERG and its sources. This paper emphasizes the potential of validating spaceborne rainfall products with high-resolution rain gauges on a subdaily time scale, particularly for the understudied West African region

Numerical Simulation of Surface Energy and Water Balances over a Semiarid Grassland Ecosystem in the West African Savanna

To understand surface energy exchange processes over the semiarid regions in West Africa, numerical simulations of surface energy and water balances were carried out using a one-dimensional multilayer atmosphere-SOil-VEGetation (SOLVEG) model for selected days of the dry and rainy seasons over a savanna grassland ecosystem in Sumbrungu in the Upper East region of Ghana. The measured Bowen ratio was used to partition the residual energy into the observed sensible heat flux () and latent heat flux (LE) in order to investigate the impact of the surface energy closure on model performance. The results showed that the model overall reproduced the diurnal changes in the observed energy fluxes, especially the net radiation (Rn), compared to half-hourly eddy covariance flux measurements, for the study periods. The performance measure in terms of the correlation coefficient (), centred root mean square error (RMSE), and normalized standard deviation (σ) between the simulated and LE and their corresponding uncorrected observed values ranged between R = 0.63–0.99 and 0.83–0.94, RMSE = 0.88–1.25 and 0.88–1.92, and = 0.95–2.23 and 0.13–2.82 for the dry and rainy periods respectively, indicating a moderate to good model performance. The partitioning of and LE by SOLVEG was generally in agreement with the observations during the dry period but showed clear discrepancies during the rainy period, particularly after rainfall events. Further sensitivity tests over longer simulation periods (e.g., 1 year) are required to improve model performance and to investigate seasonal exchanges of surface energy fluxes over the West African Savanna ecosystems in more details

West Africa's moist convective environment as observed by the Atmospheric Infrared Sounder (AIRS)

Knowledge of the seasonal positioning of the Intertropical Discontinuity (ITD) is critical to understanding seasonal moist convective processes and associated rainfall over West Africa. This study constitutes a new analysis of the seasonality of moist convection over West Africa, relative to the ITD, based on NASA's Atmospheric Infrared Sounder (AIRS) measurements from 2003 to 2018. Results show that AIRS resolves the seasonal march of the ITD, including its inherent diurnal-scale variations. AIRS captures the north–south daytime skin temperature dipole around the ITD, with greater relative temperatures to the north, especially during March–August. In the vicinity of the nighttime ITD, AIRS profiles indicate increased instability that is characteristic of nocturnal thunderstorm propagation. For seven Ghana weather stations, we show that AIRS positive moisture and equivalent potential temperature anomalies coincide with observed thunderstorm days. On these thunderstorm days, the mean latitude of the AIRS-derived ITD is displaced 3°, 0.2°, and 2° north of its DJF, MAM, and SON climatological positions, respectively, and 1.2° south in JJA. Among four common thunderstorm initiation indices considered, the K-index is determined to be most skillful. The findings of this study contribute to the Global Challenges Research Fund, African Science for Weather Information and Forecasting Techniques project's mission to build local tropical weather forecasting capacity and capabilities in West Africa

Verification of satellite and model products against a dense rain gauge network for a severe flooding event in Kumasi, Ghana

Floods as a result of severe storms cause significant impacts on lives and properties. Therefore, timely and accurate forecasts of the storms will reduce the associated risks. In this study, we look at the characteristics of a storm on 28 June, 2018 in Kumasi from a rain gauge network and satellite data, and reanalysis data. The storm claimed at least 8 lives and displaced 293 people in Kumasi, Ghana. The ability of satellite and reanalysis data to capture the temporal variations of the storm was assessed using a high temporal resolution (accumulation per minute) rain gauge data. We employed the observation data from the Dynamics–Aerosol–Chemistry–Cloud Interactions in West Africa (DACCIWA) rain gauges to assess the storm's onset, duration, and cessation. Subsequently, the performance of the ERA5 reanalysis and Global Precipitation Measurement (GPM) satellite precipitation estimates in capturing the rainfall is assessed. Both GPM and the ERA5 had difficulty reproducing the hourly pattern of the rain. However, the GPM produced variability that is similar to the observed. Generally, the region of maximum rainfall was located in the southern parts of the study domain in ERA5, while GPM placed it in the northern parts. The study contributes a verification measure to improve weather forecasting in Ghana as part of the objectives of the GCRF African Science for Weather Information and Forecasting Techniques (SWIFT) project

Numerical Simulation of Surface Energy and Water Balances over a Semiarid Grassland Ecosystem in the West African Savanna

To understand surface energy exchange processes over the semiarid regions in West Africa, numerical simulations of surface energy and water balances were carried out using a one-dimensional multilayer atmosphere-SOil-VEGetation (SOLVEG) model for selected days of the dry and rainy seasons over a savanna grassland ecosystem in Sumbrungu in the Upper East region of Ghana. The measured Bowen ratio was used to partition the residual energy into the observed sensible heat flux (H) and latent heat flux (LE) in order to investigate the impact of the surface energy closure on model performance. The results showed that the model overall reproduced the diurnal changes in the observed energy fluxes, especially the net radiation (Rn), compared to half-hourly eddy covariance flux measurements, for the study periods. The performance measure in terms of the correlation coefficient (R), centred root mean square error (RMSE), and normalized standard deviation (σ) between the simulated H and LE and their corresponding uncorrected observed values ranged between R = 0.63–0.99 and 0.83–0.94, RMSE = 0.88–1.25 and 0.88–1.92, and σ = 0.95–2.23 and 0.13–2.82 for the dry and rainy periods respectively, indicating a moderate to good model performance. The partitioning of H and LE by SOLVEG was generally in agreement with the observations during the dry period but showed clear discrepancies during the rainy period, particularly after rainfall events. Further sensitivity tests over longer simulation periods (e.g., 1 year) are required to improve model performance and to investigate seasonal exchanges of surface energy fluxes over the West African Savanna ecosystems in more details

Revisiting the agro-climatic zones of Ghana: a re-classification in conformity with climate change and variability

The Ghana Meteorological Agency delineated Ghana’s geographical space into four agro-climatic zones namely the north, transition, forest and coastal zones. Since the demarcation in the 1960s, previous studies have rarely provided a more dis-aggregated agro-climatic zone map in tandem with contemporary climate change and variability. The continued use of this age-old classified zones is a disservice to the public. In this study, therefore, we evaluated the existing agro-climatic zone map of Ghana and reconstructed it to a more appropriate and dis-aggregated map that reflect current climate change and variability impact. This was achieved by quantifying the contrast in rainfall and temperature amount over a 30 year period for different climate windows and mapped out areas with similar rainfall and temperature regimes. Our findings revealed significant changes in the existing agro-climatic zones especially in terms of number, the boundary size and geographical orientation of the zones. The newly proposed map consist of five distinctive climate zones namely: the Sudan Savannah, Guinea Savannah, Transition, Forest and Coastal zones. The Sudan and Guinea Savannah zones showed a southerly expansion. The transition zone shriveled in size as the Guinea Savannah zone took over most of it, notably in the southeast. The forest zone shrank in size with a northwest shift while the coastal belt grew to encompass the whole coast of Ghana. These changes are strong evidence of climate change and possible food production changes. These findings are useful to agriculture sector in planning their activities, the health sector in predicting specific diseases caused by changes in weather and climate, Ghana Meteorological Agency for weather forecasting purposes, and the National Disaster Management in identifying disaster prone zones