Agroclimatic Zonning of Nigeria Based on Rainfall Characteristics and Index of Drought Proneness

Nigeria, a country in sub-Saharan West Africa that depends largely on rainfall distribution for its agricultural practices has been categorised into three major climatic zones based on its rainfall characteristics and drought-proneness analysis. The data used comprises of daily rainfall of thirty years (1983 to 2012) for the thirty-eight climatic stations spread over the country. Rainfall characteristics such as onset dates, cessation dates, length of rainy season and rainfall amount within the seasons for thirty years were extracted over each of these stations for the analysis. Rainfall distribution during the rainy season was also investigated by using two-state Markov chain analysis of order one and two. The result is useful in making some pre-sowing decisions such as site selection for a particular crop and specie selection for a particular zone. The first zone has earliest rainfall onset dates, latest cessation dates and hence, having longest length of rainy season in the country. It also has the highest (lowest) Markovian probability of a wet (dry) week after a previously wet week and hence least prone to drought occurrence. Therefore, this zone is tagged “rain-forest” (Guinea). Followed closely is the zone II which is the “Savannah” and lies on the north of the zone I. On the northern part of zone II is the zone III with the shortest length of rainy season termed “Sahel”. Despite the fact that Sahel zone has the latest onset, earliest cessation and hence shortest length of rainy season, it is most prone to drought occurrence, while Savana has moderate values between those of zones I and III. Keywords: Rainfall onset, rainfall cessation, length of rainy season, drought-proneness, zones

Understanding the response of sorghum cultivars to nitrogen applications in the semi-arid Nigeria using the agricultural production systems simulator

The Agricultural Production Systems simulator (APSIM) model was calibrated and evaluated using two improved sorghum varieties conducted in an experiment designed in a randomized complete block, 2014–2016 at two research stations in Nigeria. The results show that the model replicated the observed yield accounting for yield differences and variations in phenological development between the two sorghum cultivars. For early-maturing cultivar (ICSV-400), the model indicated by low accuracy with root means square error (RMSE) for biomass and grain yields of 20.3% and 23.7%. Meanwhile, Improved-Deko (medium-maturing) cultivar shows the model was calibrated with low RMSE (11.1% for biomass and 13.9% for grain). Also, the model captured yield response to varying Nitrogen (N) fertilizer applications in the three agroecological zones simulated. The N-fertilizer increased simulated grain yield by 26–52% for ICSV-400 and 19–50% for Improved-Deko compared to unfertilized treatment in Sudano-Sahelian zone. The insignificant yield differences between N-fertilizer rates of 60 and 100 kgha−1 suggests 60 kgNha−1 as the optimal rate for Sudano-Sahelian zone. Similarly, grain yield increased by 23–57% for ICSV-400 and 19–59% for Improved Deko compared to unfertilized N-treatment while the optimal mean grain yield was simulated at 80 kgNha−1 in the Sudan savanna zone. In the northern Guinea savanna, mean simulated grain yield increased by 8–20% for ICSV-400 and 12–23% for Improved-Deko when N-fertilizer was applied compared to unfertilized treatment. Optimum grain yield was obtained at 40 kgha−1. Our study suggests a review of blanket recommended fertilizer rates across semi-arid environments for sorghum to maximize productivity and eliminate fertilizer losses, means of adaptation strategies to climate variability

GCRF African SWIFT Testbed 1 Report

This document describes the activities and outcomes of the GCRF African Science for Weather Information and Forecasting Techniques (SWIFT) Weather Forecasting Testbed 1. Testbed 1 was conducted in the first part of 2019, from an operational forecasting office at IMTR Nairobi, at the Kenya Meteorological Department (KMD). Other centres connected to the Testbed by video-conference. The Testbed was designed to support SWIFT’s programme of research capability-building in the science of weather prediction. New forecasting and evaluation products were tested. The outcomes of the Testbed will be used to steer the research and development of these tools, as well as to provide meteorological case studies and to stimulate new hypotheses. Successes of Testbed 1 include the real-time use of satellite-based Nowcasting products (NWC SAF products), convection-permitting model ensembles from the UK Met Office and systematic forecast evaluation. Testbed 1 also devised and refined an effective programme of work for operational synoptic forecasting, nowcasting and evaluation, which could form the basis for new Standard Operating Procedures

Economic value and latent demand for agricultural drought forecast: Emerging market for weather and climate information in Central-Southern Nigeria

Provision of weather and climate services are expected to improve the capacity for rural households’ preparedness and response plans to weather shocks. With increase in public investments in developing and communicating weather information on local scale in Nigeria, uncertainty in timescales that meet farmers’ needs and economic value of the information is still poorly understood. It is now a policy concern on whether farmers’ preferences and demands might increase its uptake. This study analyzed the economic value, latent demand, and emerging market of weather and climate information in Central-Southern Nigeria. Farm-level cross-sectional data reveals that 76% of the respondents were willing to pay for improved weather information and early warnings in taking climate smart decisions. Within farmers who showed positive responses, 86% would pay for sub-seasonal to seasonal weather information while 38% would pay for medium and short range weather information respectively. The economic value of sub-seasonal to seasonal weather information was estimated at N1600 ($3.60) per year per capita with total aggregated value of N1.3 billion ($2.9 m) yearly for the derived savannah area. Predictive total market value of N17.43billion ($39 m) would be obtained from improved weather information in Nigeria. Simulated results of 5$193,360) for service providers. Large farm size, good farm-income, mobile phone dissemination channels, and location-specific information were drivers of farmers’ uptake decisions of weather information in the dry savannah area. The huge emerging market for improved weather information should be developed into a public–private market to efficiently facilitate uptake and use in Nigeria

Exploring the need for developing impact-based forecasting in West Africa

While conventional weather forecasts focus on meteorological thresholds for extreme events, Impact-Based Forecasts (IBF) integrate information about the potential severity of weather impacts with their likelihood of occurrence. As IBF provides an indication of local risk, there is an increasing uptake of this approach globally. Despite the vulnerability of West Africa to severe weather, and the potential benefits of such a risk-based approach for informing disaster risk reduction, IBF remains rarely used in this region. To meet this need, three national workshops were held in Ghana, Nigeria and Senegal with forecasters, project researchers and users of Climate Information Services (CIS) from key sectors (e.g. agriculture, water resources, disaster risk reduction). In addition, a more localised district level workshop was held in Northern Ghana to explore needs at a subnational scale in Tamale District. The objectives of these workshops were to evaluate the current use of forecast products provided by National Meteorological and Hydrological Services (NMHSs) and to explore the potential for applying IBF. Findings indicate a recognition that the quality of forecast products provided by NMHSs in West Africa has substantially improved in recent years. However, challenges remain related to user understanding, clarity about forecast uncertainty, insufficient spatial and temporal resolution of forecasts leading to limited trust in forecasts. The workshops identified high demand for weather information related to storms, droughts and heatwaves in all the three countries. Dust storms were identified as having strong potential for IBF application in both Nigeria and Senegal. To increase the uptake of CIS by users in West Africa, NMHSs will need to develop and implement user-tailored IBF in their normal weather forecast approaches and improve communication channels with user communities. There is an urgent need for governments in West Africa to enhance the capacity of NMHSs to incorporate IBF as a routine forecast activity by first establishing a National Framework for Climate Services with user engagement as a key first pillar

The future of African nowcasting

Nowcasting (weather forecasting predictions from zero to several hours) has enormous value and potential in Africa, where populations and economic activity are highly vulnerable to rapidly changing weather conditions. Timely issuing of warnings, a few hours before an event, can enable the public and decision-makers to take action. Rainfall radar estimates are not widely available in Africa, nor likely to be in the coming years, and numerical weather prediction (NWP) currently has low skill over the African continent. Therefore, for the delivery of nowcasting in Africa, satellite products are the best practical option and needed urgently (Roberts et al., 2021). Fifteen minute (or faster) updates of MSG (Meteosat Second Generation) images and NWC-SAF (Nowcasting Satellite Applications Facility) products are crucial for nowcasting to warn users (e.g. fisherfolk on Lake Victoria, flooding in urban areas, etc.) on pending severe storms. The possibility to have such products every 10 minutes, as well as data from the forthcoming MTG (Meteosat Third Generation) lightning imager, would be highly beneficial to all African countries, saving lives and livelihoods where high population growth and the most extreme impacts of climate change combine

HIV-1 drug resistance mutations emerging on darunavir therapy in PI-naive and -experienced patients in the UK

\ua9 The Author 2016. Background: Darunavir is considered to have a high genetic barrier to resistance. Most darunavir-associated drug resistance mutations (DRMs) have been identified through correlation of baseline genotype with virological response in clinical trials. However, there is little information on DRMs that are directly selected by darunavir in clinical settings. Objectives: We examined darunavir DRMs emerging in clinical practice in the UK. Patients and methods: Baseline and post-exposure protease genotypes were compared for individuals in the UK Collaborative HIV Cohort Study who had received darunavir; analyses were stratified for PI history. A selection analysis was used to compare the evolution of subtype B proteases in darunavir recipients and matched PInaive controls. Results: Of 6918 people who had received darunavir, 386 had resistance tests pre- and post-exposure. Overall, 2.8% (11/386) of these participants developed emergent darunavir DRMs. The prevalence of baseline DRMs was 1.0% (2/198) among PI-naive participants and 13.8% (26/188) among PI-experienced participants. Emergent DRMs developed in 2.0% of the PI-naive group (4 mutations) and 3.7% of the PI-experienced group (12 mutations). Codon 77 was positively selected in the PI-naive darunavir cases, but not in the control group. Conclusions: Our findings suggest that although emergent darunavir resistance is rare, it may be more common among PI-experienced patients than those who are PI-naive. Further investigation is required to explore whether codon 77 is a novel site involved in darunavir susceptibility

Assessment of WRF Land Surface Model Performance over West Africa

Simulations with four land surface models (LSMs) (i.e., Noah, Noah-MP, Noah-MP with ground water GW option, and CLM4) using the Weather Research and Forecasting (WRF) model at 12 km horizontal grid resolution were carried out as two sets for 3 months (December–February 2011/2012 and July–September 2012) over West Africa. The objective is to assess the performance of WRF LSMs in simulating meteorological parameters over West Africa. The model precipitation was assessed against TRMM while surface temperature was compared with the ERA-Interim reanalysis dataset. Results show that the LSMs performed differently for different variables in different land-surface conditions. Based on precipitation and temperature, Noah-MP GW is overall the best for all the variables and seasons in combination, while Noah came last. Specifically, Noah-MP GW performed best for JAS temperature and precipitation; CLM4 was the best in simulating DJF precipitation, while Noah was the best in simulating DJF temperature. Noah-MP GW has the wettest Sahel while Noah has the driest one. The strength of the Tropical Easterly Jet (TEJ) is strongest in Noah-MP GW and Noah-MP compared with that in CLM4 and Noah. The core of the African Easterly Jet (AEJ) lies around 12°N in Noah and 15°N for Noah-MP GW. Noah-MP GW and Noah-MP simulations have stronger influx of moisture advection from the southwesterly monsoonal wind than the CLM4 and Noah with Noah showing the least influx. Also, analysis of the evaporative fraction shows sharp gradient for Noah-MP GW and Noah-MP with wetter Sahel further to the north and further to the south for Noah. Noah-MP-GW has the highest amount of soil moisture, while the CLM4 has the least for both the JAS and DJF seasons. The CLM4 has the highest LH for both DJF and JAS seasons but however has the least SH for both DJF and JAS seasons. The principal difference between the LSMs is in the vegetation representation, description, and parameterization of the soil water column; hence, improvement is recommended in this regard