Background

Seasonal climate forecasts play a crucial role in adapting to climate variability, particularly in regions where precipitation varies significantly from year to year. These forecasts are regularly produced by various operational meteorological centers worldwide, including AGRHYMET CCR-AOS. As a regional climate center, AGRHYMET CCR-AOS coordinates the development of consensus seasonal forecasts through Regional Climate Outlook Forums (RCOF), which bring together experts from National Meteorological and Hydrological Services (NMHS), basin organizations, and global climate centers. Seasonal forecasts provide prospective information about the upcoming season, with a particular focus on precipitation and temperatures.

However, a direct and linear translation of the information from seasonal forecasts to specific sectors such as water resources and agriculture can lead to inaccuracies. It is often automatically assumed that a year of rainfall deficit results in poor harvests, while a year of rainfall surplus leads to good agricultural production. Such interpretations are biased and can result in ineffective decision-making.

Integrating seasonal forecast data into biophysical models is a strategy to generate sector specific predictions and improve the quality of decision support information. This would contribute to a better understanding of the impacts of climate forecasts in the water and agriculture sectors, among others, thereby facilitating more informed decision-making. The regional center AGRHYMET CCR-AOS has developed approaches to utilize seasonal forecast information in crop and hydrological models, thus generating sector-specific seasonal predictions for agriculture and water. Therefore, it is important to strengthen the capacity of national meteorological and hydrological services in these approaches to enable their implementation in future seasonal prediction fora.

In this context, the regional center CCR-AOS AGRHYMET, in collaboration with the coordination of the West Africa cluster of the AICCRA project (Accelerating the Impact of CGIAR Climate Research for Africa), is organizing two regional capacity-building workshops from August 7th to 11th, 2023, in Ouagadougou, Burkina Faso. One workshop will focus on seasonal prediction of agricultural yields, while the other will address seasonal prediction of streamflow’s. These workshops aim to benefit the 17 countries within the CILSS-ECOWAS space and are targeted towards the national meteorological and hydrological services (NMHSs).

Objectives

The overall objective of this workshop is to enhance the capacity of National Meteorological and Hydrological Services (NMHS) in utilizing new tools that combine seasonal forecasts with impact models in the agriculture and water resources sectors.

Specifically, the objectives are as follows:

• Strengthen the participants' capacity in processing daily data from seasonal forecasts generated by climate models;
• Enhance the participants' capacity in stochastic disaggregation of forecasts from PRESASS and PRESAGG;
• Build the participants' capacity in utilizing the crop models and hydrological models;
• Strengthen the participants' capacity in combining climate forecasts with impact models (agronomic and hydrological) to provide sector-specific forecasts for these domains.

Expected outcomes

The expected outcomes of the workshop are as follows:

• Participants will enhance their abilities in handling daily data processing of seasonal forecasts derived from climate models;
• Participants will strengthen their skills in stochastic disaggregation of forecasts from PRESASS and PRESAGG;
• Participants will develop a stronger understanding of utilizing crop and hydrological models;
• Participants will improve their capabilities in integrating climate forecasts with impact models (agronomic and hydrological).

Attendees

Two (2) participants per country, specifically one from the meteorological service and one from the hydrological service, are invited to participate in this workshop. Female participation is strongly encouraged.

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