Probabilistic forecasting of dry spells in Kenya and Australia

Kenya and the Murray Darling Basin (MDB) of Australia are largely arid or semi-arid and are important agricultural areas. However, persistent dry periods and the timing of dry spells directly impact on availability of soil moisture and hence crop production in these regions. Research in these regions has not yielded desirable impacts in addressing this problem. This study aimed at examining the characteristics of dry spells and development of monthly dry spell forecasts in these regions. Daily rainfall datasets from 30 locations in Kenya and 47 locations in the MDB were used in the analysis of monthly dry spells. The length of both monthly dry spells and dry spells going across months were separately calculated and compared. The best parametric distribution functions (pdfs) describing the empirical dry spell distribution were examined. A generalized linear model (GLM) and a generalized additive model (GAM) were used to determine the temporal and spatial trends in dry spell length and in forecasting of dry spells at 1-, 3-, and 6-month lead times. Overall, the monthly dry spell lengths mostly followed a lognormal distribution. The mean monthly dry spell length underestimated the observed dry spell length in these regions while the monthly dry spell parameters were negatively correlated with the mean annual and monthly rainfall in Kenya and in the MDB. Increasing dry spell trends occurred in most months and in some locations and the probability of drought risk in the cropping season reach up to 50% in Kenya and 77% in the MDB. The greatest increases were in June-September in Kenya and in autumn season in the MDB. Increasing rates in observed trends in both regions were ≥ 0.026 days/year or 1 day to 37 days increase over the entire period. The performance of binary and continuous forecasts at 1-, 3-, and 6-month lagged SOI phases and SSTs showed modest skill (R2) ranging from < 20% – 72% in Kenya and MDB for the total number of dry days and the maximum dry spell length in a month but better skill was indicated in Kenya than in the MDB. The challenge still remaining is to find a way to capture all the inter-intra annual variability in the dry spell series at the monthly and seasonal time frames. The current skill may be improved by including other predictors in the model such as NINO4, Pacific Ocean thermocline and tropospheric wind anomalies. The current findings can have implications for agriculture in these regions

Probabilistic forecasting of dry spells in Kenya and Australia

Kenya and the Murray Darling Basin (MDB) of Australia are largely arid or semi-arid and are important agricultural areas. However, persistent dry periods and the timing of dry spells directly impact on availability of soil moisture and hence crop production in these regions. Research in these regions has not yielded desirable impacts in addressing this problem. This study aimed at examining the characteristics of dry spells and development of monthly dry spell forecasts in these regions. Daily rainfall datasets from 30 locations in Kenya and 47 locations in the MDB were used in the analysis of monthly dry spells. The length of both monthly dry spells and dry spells going across months were separately calculated and compared. The best parametric distribution functions (pdfs) describing the empirical dry spell distribution were examined. A generalized linear model (GLM) and a generalized additive model (GAM) were used to determine the temporal and spatial trends in dry spell length and in forecasting of dry spells at 1-, 3-, and 6-month lead times. Overall, the monthly dry spell lengths mostly followed a lognormal distribution. The mean monthly dry spell length underestimated the observed dry spell length in these regions while the monthly dry spell parameters were negatively correlated with the mean annual and monthly rainfall in Kenya and in the MDB. Increasing dry spell trends occurred in most months and in some locations and the probability of drought risk in the cropping season reach up to 50% in Kenya and 77% in the MDB. The greatest increases were in June-September in Kenya and in autumn season in the MDB. Increasing rates in observed trends in both regions were ≥ 0.026 days/year or 1 day to 37 days increase over the entire period. The performance of binary and continuous forecasts at 1-, 3-, and 6-month lagged SOI phases and SSTs showed modest skill (R2) ranging from < 20% – 72% in Kenya and MDB for the total number of dry days and the maximum dry spell length in a month but better skill was indicated in Kenya than in the MDB. The challenge still remaining is to find a way to capture all the inter-intra annual variability in the dry spell series at the monthly and seasonal time frames. The current skill may be improved by including other predictors in the model such as NINO4, Pacific Ocean thermocline and tropospheric wind anomalies. The current findings can have implications for agriculture in these regions

Understanding the role of user needs and perceptions related to sub-seasonal and seasonal forecasts on farmers decisions in Kenya: a systematic review

One major challenge facing farmers and other end-users of weather and climate information in Kenya is the linkage between their perceptions, needs and engagements with producers of the information. This is highlighted by increased interest in understanding the constraints on appropriate use of weather and climate information by farmers in decision making. Farmers face extreme weather impacts which constraint the use and choice of the appropriate weather information and other services. The choice between sub-seasonal and seasonal forecasts can enable better decisions by farmers if the forecast information is reliable and integrated through a co-production process.The objective of this study was to analyse the user needs and perceptions of crop farmers, pastoralists and agro-pastoralists in relation to sub-seasonal and seasonal forecasts for 5 counties in Kenya. A total of 200 peer-reviewed and grey literatures were systematically reviewed to understand how the needs and perceptions of users of weather and climate information shaped access and use in decision making. The study also reviewed whether sub-seasonal and seasonal forecasts were adopted and used appropriately.Results show that farmers' perceptions shaped the choice of weather and climate information while sub-seasonal and seasonal forecasts were used for diverse applications. Gender, availability of resources, access and mode of communication were some of the factors influencing use of the information. One lesson learnt was that farmers combined weather and climate information with other coping practices such as agronomic practices and water efficiency management. However, a number of challenges were faced by the users such as insufficient resources, lack of access to information and poor engagement with weather forecasters and extension services.2 This is a provisional file, not the final typeset article This study recommends stakeholder engagements with producers in development of products and services to improve uptake and use of forecasts in decision making

Using co-production to improve the appropriate use of sub-seasonal forecasts in Africa

Forecasts on sub-seasonal to seasonal (S2S) timescales have huge potential to aid preparedness and disaster risk reduction planning decisions in a variety of sectors. However, realising this potential depends on the provision of reliable information that can be appropriately applied in the decision-making context of users. This study describes the African SWIFT (Science for Weather Information and Forecasting Techniques) forecasting testbed which brings together researchers, forecast producers and users from a range of African and UK institutions. The forecasting testbed is piloting the provision of real-time, bespoke S2S forecast products to decision-makers in Africa. Drawing on data from the kick-off workshop and initial case study examples, this study critically reflects on the co-production process. Specifically, having direct access to real-time data has allowed user-guided iterations to the spatial scale, timing, visualisation and communication of forecast products to make them more actionable for users. Some key lessons for effective co-production are emerging. First, it is critical to ensure there is sufficient resource to support co-production, especially in the early co-exploration of needs. Second, all the groups in the co-production process require capacity building to effectively work in new knowledge systems. Third, evaluation should be ongoing and combine meteorological verification with decision-makers feedback. Ensuring the sustainability of project-initiated services within the testbed hinges on integrating the knowledge-exchanges between individuals in the co-production process into shaping sustainable pathways for improved operational S2S forecasting within African institutions

Effect of cytomegalovirus infection on breastfeeding transmission of HIV and on the health of infants born to HIV-infected mothers

Cytomegalovirus (CMV) infection can be acquired in utero or postnatally through horizontal transmission and breastfeeding. The effect of postnatal CMV infection on postnatal HIV transmission is unknown

Evaluating Nurses' Implementation of an Infant-Feeding Counseling Protocol for HIV-Infected Mothers: The Ban Study in Lilongwe, Malawi

A process evaluation of nurses’ implementation of an infant-feeding counseling protocol was conducted for the Breastfeeding, Antiretroviral and Nutrition (BAN) Study, a prevention of mother-to-child transmission of HIV clinical trial in Lilongwe, Malawi. Six trained nurses counseled HIV-infected mothers to exclusively breastfeed for 24 weeks postpartum and to stop breastfeeding within an additional four weeks. Implementation data were collected via direct observations of 123 infant feeding counseling sessions (30 antenatal and 93 postnatal) and interviews with each nurse. Analysis included calculating a percent adherence to checklists and conducting a content analysis for the observation and interview data. Nurses were implementing the protocol at an average adherence level of 90% or above. Although not detailed in the protocol, nurses appropriately counseled mothers on their actual or intended formula milk usage after weaning. Results indicate that nurses implemented the protocol as designed. Results will help to interpret the BAN Study’s outcomes

Plasma Micronutrient Concentrations Are Altered by Antiretroviral Therapy and Lipid-Based Nutrient Supplements in Lactating HIV-Infected Malawian Women

Background: Little is known about the influence of antiretroviral therapy with or without micronutrient supplementation on the micronutrient concentrations of HIV-infected lactating women in resource-constrained settings

Adherence to extended postpartum antiretrovirals is associated with decreased breast milk HIV-1 transmission

Estimate association between postpartum antiretroviral adherence and breastmilk HIV-1 transmissio

Sensitivity of some African heavy rainfall events to microphysics and planetary boundary layer schemes: impacts on localised storms

High‐resolution numerical weather prediction (NWP) simulations of heavy rainfall events are known to be strongly sensitive to the choice of the sub‐grid scale parameterization schemes. In the African continent, studies on such a choice at the convective‐resolving scales are not numerous. By exploiting a state‐of‐theart NWP model, the Weather Research and Forecasting (WRF) model, the sensitivity of the simulation of three heavy rainfall events in sub‐Saharan Africa to the microphysical (MP) and planetary boundary layer (PBL) schemes is studied. Validating the numerical outputs against rainfall satellite estimates, ground based weather stations, radiosonde profiles and satellite‐derived cloud top temperature maps with an object‐based tool, the best performing setup is identified. In terms of heavy rainfall forecast location, it is found that the PBL scheme has a larger impact than the MP, which is shown to control the cloud top temperature simulation. Among the schemes considered, the best performances are reached with a 6‐class single‐moment microphysical scheme and a non‐local planetary boundary layer scheme which properly includes the vertical mixing by the large eddies in the atmosphere

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