My Climate Risk Interdisciplinary Learning Group

8 July 2024; 13:00-14:00 BST (GMT+1)

Presenter: Masilin Gudoshava

Biography

I am a Climate Modeling Expert at the IGAD Climate Prediction and Applications Centre (ICPAC) in Nairobi, Kenya. My work primarily involves sub-seasonal to seasonal forecasting. I have a particular interest in producing tailored forecasts that cater to the specific needs of various climate-sensitive sectors, such as agriculture, health and disaster management. My role also involves collaborating with stakeholders to ensure that the forecasts are practical, relevant, and effectively utilized.

Paper to be presented

Title:      Characterization and variability of Kiremt rainy season over Ethiopia.

Authors: Z. T Segele and T.J Lamb

Link to paper: Characterization and variability of Kiremt rainy season over Ethiopia | Meteorology and Atmospheric Physics (springer.com)

Session Highlights:

The July MCRILG session allowed us to dive into the hot topic of seasonal weather prediction for supporting decision-making. Our speaker was Dr Masilin Gudoshava, Climate Modelling Expert at the IGAD Climate Prediction and Applications Centre (ICPAC) in Nairobi, Kenya. ICPAC is a Climate Center accredited by the World Meteorological Organization that provides Climate Services to 11 East African Countries. Their services aim at creating resilience in a region deeply affected by climate change and extreme weather.

 Masilin’s talk illustrated how decision-making in the agriculture and water resources sectors be informed by rainfall predictions on the onset of the rainy season, at the sub-seasonal to seasonal timescale (S2S, between 2 weeks and 2 months). Starting from the research article “Characterization and variability of Kiremt rainy season over Ethiopia” by Z. T Segele and T.J Lamb, Masilin’s talk included broader considerations arising from her own research and operational work at ICPAC in the East Africa region.

 Climate Shocks in East Africa and regional background: East Africa is highly susceptible to extreme weather variations, experiencing dramatic shifts from droughts to floods. These floods are often linked to tropical cyclones or positive phases of the Indian Ocean Dipole (IOD), leading to a cascade of hazards and significant food insecurity across the region.

 East Africa encompasses a diverse range of climates, including arid, hyper-arid, humid, and sub-humid areas. Approximately 70% of the population depends on rainfed agriculture, primarily through pastoral and agro-pastoral activities. Consequently, any changes in the rainy seasons critically affect their livelihoods and food security.

 Onset of the Rainy Season: The onset of the rainy season is defined differently depending on the context, often based on specific thresholds of accumulated rainfall. For example, in the paper presented, the definition of onset follows one relevant to agriculture and is computed as the first day of the wet season when a wet spell (three consecutive days with at least 20mm of rain) is followed by no dry spell (at least seven dry days) within the next 21 days.

 The importance of onset in agriculture and water sectors decision-making: For farmers, the start of the rainy season is important for determining the timing of planting crops such as maize, sorghum, millet, and beans. Incorrect timing, especially late planting, can drastically reduce yields. Additionally, dry spells inform farmers about the need for irrigation, where accessible. Livestock, too, is dependent on rainfall for pasture regeneration and water availability, which affects migration patterns and potentially leads to conflicts as pastoral communities move in search of pasture.

 Understanding the onset of the rainy season also aids in planning irrigation schedules and managing reservoir operations, including timing for filling and release. This information is vital for groundwater recharge and river flow management. As an example, in Kenya there is currently significant collaboration between the Kenyan energy industry and the meteorological services providing sub-seasonal to seasonal rainfall predictions.

 Information dissemination: Once weather information is produced by meteorological services, the translation and communication to users’ needs to be carefully considered in order to provide value to them.  

 Several platforms are in place to disseminate climate information in East Africa, each targeting a different decision-making level. The GHACOF (Great Horn of Africa Climate Outlook Forum) engages regional stakeholders from various sectors, including agriculture, livestock, health, energy, disaster risk management, and conflict resolution. The NCOF (National Climate Outlook Forums) targets national users. The PSP (Participatory Scenario Planning) engages communities at the local level. The PICSA (Participatory Integrated Climate Services for Agriculture) focuses on the agricultural sector specifically at the local level. Finally, zooming back out the regional level, the East Africa Hazard Watch platform is an interactive web platform that disseminates information on pests, floods, and crop conditions, aiding in proactive disaster management.

 Co-production is considered an essential part of effective dissemination. In this context, co-production means using the inputs from users to co-develop and co-evaluate outputs. Integrating indigenous knowledge with climate forecasts has been shown to increase the uptake of climate information. This approach involves comparing observations from indigenous communities with scientific forecasts to enhance accuracy and relevance.

 Challenges of Rainfall Prediction: Several challenges affect the accuracy and dissemination of rainfall predictions. A major one in the East Africa context regards data limitation, as there are still too sparse observational data that hinder adequate model calibration. Model accuracy is another issue, which applies to other regions too, as weather and climate models still have significant uncertainties due to our imperfect knowledge of this complex physical system.

 In term of communication, effective dissemination of forecasts to end-users remains challenging. Major causes are the insufficient funding and time available to scientists and practitioners to test new approaches, scale up the ones that have proven to be effective, and deepen engagement with local communities.

 Masilin opened the Q&A part of the session by sharing her burning questions to improve climate information regarding rainy season forecasts and its application:

• Is there a need for multiple definitions of onset/cessation of rainy season to accommodate the diverse region and various sectors?
• Can we find socio-economic datasets that will be able to show us that the algorithm in onset/cessation in use is best for the application?
• Are there enough stakeholders involved in the co-production of forecast products?
• Can the information be further simplified for all users?

 The discussion started with few technical questions regarding the forecasting skill for onset. Masilin noted that rainfall forecasts for the October-November-December (OND) period tend to be more reliable due to well-understood climatic drivers. However, for the March-April-May (MAM) period, the skills is mostly good up to a few weeks, but less into the month timescales hence results in lower skill for onset.  The discussion then moved to communication, with a question regarding the study of the effectiveness of different ways of communicating risk. Masilin reported that people tended to prefer receiving information about absolute values, such as the probability of exceeding 300 or 400 mm of rainfall, rather than statements about whether rainfall will be above or below normal. Absolute values were more useful for planning specific agricultural activities like growing beans or maize. Another question verted on the role of factors in affecting the accuracy and usefulness of these forecasts. Masilin agreed that local difference can be very important, but also that tailoring information needs to be balance with the ability to reach as many people as possible. She reported the case of Ethiopia, where downscaled climate information is produced at local level and translated to local languages. She noted that automating these processes is where she sees the input of new technology, such as AI, to come into help in the future. A final question challenged the potential overemphasis by climate scientists in needing more climate information at smaller spatial scales, at the expense of understanding vulnerability at those local scales, which may be the dominant factor of impacts overall. Masilin responded by noting that there is a growing focus on impact-based forecasting, which incorporates vulnerability data, though collecting such data remains a challenge.

Written by Elena Saggioro. Reviewed by Masilin Gudoshava.