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The ability of any climate model to reproduce present-day climate fields is very important for the confidence in the projections of the future state of the same fields. It is against this background that the performance of the Global Coupled configuration 2 (GC2) of the Unified Model (UM), a Global Climate Model (GCM), was evaluated over the West African region (a climate-sensitive region) for two periods on 3 climatological time scales for precipitation (using the Global Precipitation Climatology Center data) and 2-m temperature where the Climate Research Unit Time Series dataset was used. The GC2's performance is also compared with 4 Coupled Model Intercomparison Project phase 6 (CMIP6) GCMs. Results indicate that spatial biases are of similar patterns across the domain for the two study periods for both variables, demonstrating the consistency of the model in reproducing the two climate variables over West Africa (WA). The simulation of temperature by the UM is better than precipitation. Biases are larger in the UM and the CMIP6 GCMs than the levels of observational uncertainties for precipitation, but for temperature, biases in all the models are within the levels of uncertainties found in the observations. Also, the holistic performance of the UM in the two fields is relatively better than the 4 CMIP6 GCMs. The two variables are also simulated better in the southern parts of the region than the northern parts of the domain by the UM. The analysis of the UM suggests a strong linkage between the two variables and therefore, a detailed investigation in how the model reproduces precipitation and temperature-based processes over WA is recommended in order to enhance the model's simulations of these climate variables. Also, the model is recommended for future investigations of precipitation and temperature climatologies over WA. [ABSTRACT FROM AUTHOR]

The article presents a study which evaluates the effect of urbanization on both global and regional climate in the U.S. It states that the research involves computation of the estimates of a reasonable average flux of sensible and latent heat for each of the different types of land-use categories including water, forest, and short vegetation. The research shows that urban land cover caused the largest proportionate sensible and latent heat fluxes during the winter of 1996.

The article offers information on the University Corporation for Atmospheric Research (UCAR) Africa Initiative (AI), an effort to help constrain the development of climate and weather in Africa. UCAR and AI worked together to improve the atmospheric sciences infrastructure in the continent. AI is making effort to encourage universities and government agencies to take on other efforts, such as atmospheric science capacity building, in different ways, in Africa. UCAR is expanding those activities it collaborated with AI. A weather radar network project is currently in progress as part of the effort to improve the atmospheric sciences infrastructure in the continent.

Two monthly gridded precipitation datasets of the Global Precipitation Climatology Project (GPCP; the multisatellite product) and the Global Precipitation Climatology Centre (GPCC) Variability Analysis of Surface Climate Observations (VASClimO; rain gauge data) are compared for a 22-yr period, from January 1979 to December 2000, over land areas (i.e., latitudes 4°–20°N and longitudes 18°W–15°E). The two datasets are consistent with respect to the spatial distribution of the annual and seasonal rainfall climatology over the domain and along latitudinal bands. However, the satellite generally overestimates rainfall. The inability of the GPCC data to capture the bimodal rainfall pattern along the Guinea coast (i.e., south of latitude 8°N) is an artifact of the interpolation of the rain gauge data. For interannual variability, the gridded multisatellite and gridded gauge datasets agree on the sign of the anomaly 15 out of the 22 yr (68% of the time) for region 1 (between longitude 5° and 18°W and north of latitude 8°N) and 18 out of the 22 yr (82% of the time) for region 2 (between longitude 5°W and 15°E and north of latitude 8°N). The datasets agreed on the sign of the anomaly 14 out of the 22 yr (64% of the time) over the Guinea Coast. The magnitudes of the anomaly are very different in all years. Most of the years during which the two datasets did not agree on the sign of the anomaly were years with El Niño events. The ratio of the seasonal root-mean-square differences to the seasonal mean rainfall range between 0.24 and 2.60. The Kendall’s tau statistic indicated statistically significant trends in both datasets, separately. [ABSTRACT FROM AUTHOR]

A 26-year simulation (1980-2005) was performed with the Weather Research and Forecast (WRF) model over the Volta Basin in West Africa. This was to investigate the ability of a climate version of WRF to reproduce present day temperature and precipitation over the Volta Basin. The ERA-Interim reanalysis and one realization of the ECHAM6 global circulation model (GCM) data were dynamically downscaled using two nested domains within the WRF model. The outer domain had a horizontal resolution of 50 km and covered the whole of West Africa while the inner domain had a horizontal resolution of 10 km. It was observed that biases in the respective forcing data were carried over to the RCM, but also the RCM itself contributed to the mean bias of the model. Also, the biases in the 50-km domain were transferred unchanged, especially in the case of temperature, to the 10-km domain, but, for precipitation, the higher-resolution simulations increased the mean bias in some cases. While in general, WRF underestimated temperature in both the outer (mean biases of −1.6 and −2.3 K for ERA-Interim and ECHAM6, respectively) and the inner (mean biases of −0.9 K for the reanalysis and −1.8 K for the GCM) domains, WRF slightly underestimated precipitation in the coarser domain but overestimated precipitation in the finer domain over the Volta Basin. The performance of the GCM, in general, is good, particularly for temperature with mean bias of −0.7 K over the outer domain. However, for precipitation, the added value of the RCM cannot be overlooked, especially over the whole West African region on the annual time scale (mean biases of −3% for WRF and −8% for ECHAM6). Over the whole Volta Basin and the Soudano-Sahel for the month of April and spring (MAM) rainfall, respectively, mean bias close to 0% was simulated. Biases in the interannual variability in both temperature and precipitation over the basin were smaller in the WRF than the ECHAM6. High spatial pattern correlations between 0.7 and 0.8 were achieved for the autumn precipitation and low spatial correlation in the range of 0.0 and 0.2 for the winter season precipitation over the whole basin and all the three belts over the basin. [ABSTRACT FROM AUTHOR]

Climate extremes pose threats to lives and properties. It is therefore critical to assess the dynamics of climate extremes in the future. Knowledge of the appropriate models to be used for projection helps reduces uncertainties in model projections. The study assesses the evolution of 8 extreme temperature indices over the Volta Basin for the 1985–2014 period. Consequently, the ability of 40 Coupled Model Intercomparison Project Phase 6 (CMIP6) models in reproducing these extremes is assessed. The biases and the M-scores of the annual spatial distribution of indices are determined. It is observed that the temperature extremes are frequent and profound in the Sahel, indicating that the Sahel is susceptible to extreme temperature changes. The warm indices showed positive trends, while the cold indices mainly showed negative trends. Most of the models had difficulty reproducing the climatologies of the indices. However, the CMCC-ESM2, MPI-ESM-1-2-HAM, MIROC6, and AWI-CM-1-1-MR reproduced the TNN, TNX, TXN, and TXX well while the MIROC6, MRI-ESM2-0, INM-CM4-8, and MIROC6 showed robust performance in reproducing the TN10P, TN90P, TX10P, and TX90P respectively. Poor performance of models may be due to poor simulation of sub-grid features such as vegetation cover, and clouds as a result of coarse grid sizes. Warming of the basin poses a significant impact on agriculture, drought occurrence, and seasonal to annual scale precipitation distribution. Southern sections of the basin may be vulnerable to temperature-related extremes as a result of deforestation and urbanization. [ABSTRACT FROM AUTHOR]

Sub-seasonal forecasts provide forecast information on the 1-4 week timescale and are produced by a number of global weather forecast providers, including the European Centre for Medium-Range Weather Forecasts (ECMWF). The development and application of new sub-seasonal forecasting products in the agricultural sectors of Ghana and Kenya are described. Using a co-production approach transforms the role of the forecast user from merely a recipient of forecast information to being involved in the forecast product development process. Experiences of co-producing sub-seasonal forecast products for agricultural application in Kenya and Ghana. [Extracted from the article]

A selected number of global climate models (GCMs) from the fifth Coupled Model Intercomparison Project (CMIP5) were evaluated over the Volta Basin for precipitation. Biases in models were computed by taking the differences between the averages over the period (1950–2004) of the models and the observation, normalized by the average of the observed for the annual and seasonal timescales. The Community Earth System Model, version 1-Biogeochemistry (CESM1-BGC), the Community Climate System Model Version 4 (CCSM4), the Max Planck Institute Earth System Model, Medium Range (MPI-ESM-MR), the Norwegian Earth System Model (NorESM1-M), and the multimodel ensemble mean were able to simulate the observed climatological mean of the annual total precipitation well (average biases of 1.9% to 7.5%) and hence were selected for the seasonal and monthly timescales. Overall, all the models (CESM1-BGC, CCSM4, MPI-ESM-MR, and NorESM1-M) scored relatively low for correlation (<0.5) but simulated the observed temporal variability differently ranging from 1.0 to 3.0 for the seasonal total. For the annual cycle of the monthly total, the CESM1-BGC, the MPI-ESM-MR, and the NorESM1-M were able to simulate the peak of the observed rainy season well in the Soudano-Sahel, the Sahel, and the entire basin, respectively, while all the models had difficulty in simulating the bimodal pattern of the Guinea Coast. The ensemble mean shows high performance compared to the individual models in various timescales. [ABSTRACT FROM AUTHOR]

Seasonal predictions of precipitation, among others, are important to help mitigate the effects of drought and floods on agriculture, hydropower generation, disasters, and many more. This work seeks to obtain a suitable combination of physics schemes of the Weather Research and Forecasting (WRF) model for seasonal precipitation simulation over Ghana. Using the ERA-Interim reanalysis as forcing data, simulation experiments spanning eight months (from April to November) were performed for two different years: a dry year (2001) and a wet year (2008). A double nested approach was used with the outer domain at 50 km resolution covering West Africa and the inner domain covering Ghana at 10 km resolution. The results suggest that the WRF model generally overestimated the observed precipitation by a mean value between 3% and 64% for both years. Most of the scheme combinations overestimated (underestimated) precipitation over coastal (northern) zones of Ghana for both years but estimated precipitation reasonably well over forest and transitional zones. On the whole, the combination of WRF Single-Moment 6-Class Microphysics Scheme, Grell-Devenyi Ensemble Cumulus Scheme, and Asymmetric Convective Model Planetary Boundary Layer Scheme simulated the best temporal pattern and temporal variability with the least relative bias for both years and therefore is recommended for Ghana. [ABSTRACT FROM AUTHOR]

The Global Energy and Water Cycle Exchanges (GEWEX) project was created more than 30 years ago within the framework of the World Climate Research Programme (WCRP). The aim of this initiative was to address major gaps in our understanding of Earth's energy and water cycles given a lack of information about the basic fluxes and associated reservoirs of these cycles. GEWEX sought to acquire and set standards for climatological data on variables essential for quantifying water and energy fluxes and for closing budgets at the regional and global scales. In so doing, GEWEX activities led to a greatly improved understanding of processes and our ability to predict them. Such understanding was viewed then, as it remains today, essential for advancing weather and climate prediction from global to regional scales. GEWEX has also demonstrated over time the importance of a wider engagement of different communities and the necessity of international collaboration for making progress on understanding and on the monitoring of the changes in the energy and water cycles under ever increasing human pressures. This paper reflects on the first 30 years of evolution and progress that has occurred within GEWEX. This evolution is presented in terms of three main phases of activity. Progress toward the main goals of GEWEX is highlighted by calling out a few achievements from each phase. A vision of the path forward for the coming decade, including the goals of GEWEX for the future, are also described. [ABSTRACT FROM AUTHOR]

Understanding the environmental evolution of mesoscale convective systems (MCSs) is critical for forecasting weather in West Africa. This study investigated the thermodynamic and synoptic environments of MCSs over West Africa on 26 (storm 1) and 28 (storm 2) June 2018. Primary datasets used to assess the diurnal evolution of the storms were obtained from ERA5. The results showed a trapped gravity wave, enhanced by a well‐established African Easterly Jet and monsoon trough, was responsible for the initiation of storm 1. Both storms also initiated in the presence of several moist lower (925–850 hPa) to mid‐tropospheric (600 hPa) cyclonic and anticyclonic vortices, controlling inland moisture advection. The lower troposphere was moistened through moisture advection by the West African westerly jet for storm 1 and the nocturnal low‐level jet prior to initiation for storm 2. For both storms, the evolution of outgoing longwave radiation showed a consistent atmosphere of deep afternoon convection. Boundary layer height increased significantly during storm evolution to support the increasing ascent of warm air. Vegetation cover differences may have also likely aided the evolution of storm 2. The passage of gravity waves from decaying storms can aid forecasters to nowcast likely regions of afternoon convection with high accuracy. Under the GCRF African Science for Weather Information and Forecasting Techniques (SWIFT), these findings are crucial in fulfilling the project's aims of improving weather forecasting capability and communication over West Africa. [ABSTRACT FROM AUTHOR]

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics, and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The Global Challenges Research Fund (GCRF) African Science for Weather Information and Forecasting Techniques (SWIFT) project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement, and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training, modeling and operational prediction, and communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather forecasting "Testbeds"—the first of their kind in Africa—which have been used to bring new evaluation tools, research insights, user perspectives, and communications pathways into a semioperational forecasting environment. [ABSTRACT FROM AUTHOR]

The article discusses the delayed onset of wet season in Nigeria in 2015. Topics discussed include the use of land and generation atmosphere climate models to determine the late onsets, the role of sea surface temperatures (SSTs) on the alteration of the 2015 late onset on rainy season, and the representation of intertropical discontinuity (ITD).

We analyze and intercompare the performance of a set of ten regional climate models (RCMs) along with the ensemble mean of their statistics in simulating daily precipitation characteristics during the West African monsoon (WAM) period (June-July-August-September). The experiments are conducted within the framework of the COordinated Regional Downscaling Experiments for the African domain. We find that the RCMs exhibit substantial differences that are associated with a wide range of estimates of higher-order statistics, such as intensity, frequency, and daily extremes mostly driven by the convective scheme employed. For instance, a number of the RCMs simulate a similar number of wet days compared to observations but greater rainfall intensity, especially in oceanic regions adjacent to the Guinea Highlands because of a larger number of heavy precipitation events. Other models exhibit a higher wet-day frequency but much lower rainfall intensity over West Africa due to the occurrence of less frequent heavy rainfall events. This indicates the existence of large uncertainties related to the simulation of daily rainfall characteristics by the RCMs. The ensemble mean of the indices substantially improves the RCMs' simulated frequency and intensity of precipitation events, moderately outperforms that of the 95th percentile, and provides mixed benefits for the dry and wet spells. Although the ensemble mean improved results cannot be generalized, such an approach produces encouraging results and can help, to some extent, to improve the robustness of the response of the WAM daily precipitation to the anthropogenic greenhouse gas warming. [ABSTRACT FROM AUTHOR]

ABSTRACT We examine the ability of an ensemble of 10 Regional Climate Models ( RCMs), driven by ERA-Interim reanalysis, in skillfully reproducing key features of present-day precipitation and temperature (1990-2008) over West Africa. We explore a wide range of time scales spanning seasonal climatologies, annual cycles and interannual variability, and a number of spatial scales covering the Sahel, the Gulf of Guinea and the entire West Africa. We find that the RCMs show acceptable performance in simulating the spatial distribution of the main precipitation and temperature features. The occurrence of the West African Monsoon jump, the intensification and northward shift of the Saharan Heat Low ( SHL), during the course of the year, are shown to be realistic in most RCMs. They also capture the mean annual cycle of precipitation and temperature, including, single and double-peaked rainy seasons, in terms of timing and amplitude over the homogeneous sub-regions. However, we should emphasize that the RCMs exhibit some biases, which vary considerably in both magnitude and spatial extent from model to model. The interannual variability of seasonal anomalies is best reproduced in temperature rather than precipitation. The ensemble mean considerably improves the skill of most of the individual RCMs. This highlights the importance of performing multi-model assessment in properly estimating the response of the West African climate to global warming at seasonal, annual and interannual time scales. [ABSTRACT FROM AUTHOR]

An evaluation of precipitation and evapotranspiration simulated by mesoscale models is carried out within the African Monsoon Multidisciplinary Analysis (AMMA) program. Six models performed simulations of a mesoscale convective system (MCS) observed to cross part of West Africa in August 2005. Initial and boundary conditions are found to significantly control the locations of rainfall at synoptic scales as simulated with either mesoscale or global models. When initialized and forced at their boundaries by the same analysis, all models forecast a westward-moving rainfall structure, as observed by satellite products. However, rainfall is also forecast at other locations where none was observed, and the nighttime northward propagation of rainfall is not well reproduced. There is a wide spread in the rainfall rates across simulations, but also among satellite products. The range of simulated meridional fluctuations of evapotranspiration (E) appears reasonable, but E displays an overly strong zonal symmetry. Offline land surface modeling and surface energy budget considerations show that errors in the simulated E are not simply related to errors in the surface evaporative fraction, and involve the significant impact of cloud cover on the incoming surface shortwave flux. The use of higher horizontal resolution (a few km) enhances the variability of precipitation, evapotranspiration, and precipitable water (PW) at the mesoscale. It also leads to a weakening of the daytime precipitation, less evapotranspiration, and smaller PW amounts. The simulated MCS propagates farther northward and somewhat faster within an overall drier atmosphere. These changes are associated with a strengthening of the links between PW and precipitation. [ABSTRACT FROM AUTHOR]