The first webinar coordinated by the three sister projects FOCUS-Africa, DOWN2EARTH, and CONFER was held on 13 October, with the title “Understanding Seasonal Forecasts: Q&A with Climate Scientists”. This was the first in a series of webinars that the three projects will arrange. This article will summarise the webinar and explain some of the main points that were discussed.
Diana Njeru (Moderator) is a development professional with 10 years of experience managing projects that use media and communication to help reduce poverty, improve health, save lives and support people in understanding their rights. She is currently the Project Director at BBC Media Action, where she manages climate change projects that train local media to provide life-saving information to communities affected by climate change. She has a BA in Political Science.
Diana is also passionate about development photography and uses photography to communicate the human condition, bring attention to social injustice, promote cultural understanding and encourage positive change.
Maurine Ambani (World Food Program): Maurine has over 10 years of experience in developing Climate Services in Africa, towards targeted use of weather and climate information in adaptive decision making and anticipatory action. She works extensively to facilitate linkages and dialogue between scientists, technical experts in various fields, operational teams and communities. Maurine currently serves as the WFP Regional Coordinator for Forecast based Financing (FbF) in Eastern Africa, supporting countries in the region to implement the FbF approach.
Roberto Buizza (FOCUS-Africa): Roberto has a degree in Physics, a PhD in Mathematics, and a Master in Business Administration. After 4 years at the ‘Centro di Ricerca Termica e Nucleare’ of the Electricity Board of Italy (CRTN/ENEL), in 1991 he joined the European Centre for Medium-Range Weather Forecasts, where he had been a key developer of its prediction systems, and served as Head of the Predictability Division and Lead Scientist. In November 2018 he joined ‘Scuola Superiore Sant’Anna’ of Pisa, as Full Professor in Physics, where he has established a new initiative on climate with the support also Scuola Superiore Sant’Anna and Scuola Normale Superiore of Pisa, and Istituto Studi Superiori Scuola IUSS of Pavia. Expert in numerical weather prediction, Earth-system modelling, ensemble methods and predictability, he has more than 230 publications, of which 115 are in the peer-reviewed literature.
Teferi Demissie (CONFER): Teferi is a senior climate researcher at NORCE and CCAFS East Africa. He has expertise in African climate and climate modelling with a particular focus on investigating local and remote mechanisms responsible for the climate variability in East Africa. Demissie has extensive experience working with the National Meteorological Services of East Africa. He is currently working on the Horizon 2020 project CONFER, and other projects in Africa funded from NFR and NORAD. He has a PhD in Atmospheric Physics and Dynamics from the Norwegian University of Science and Technology (NTNU).
Summary of the Webinar
People from various countries participated in the webinar: Somalia, Eritrea, Kenya, UK etc. This was great for the discussion, and people from several sectors were represented – from students to people working with water management. In the following, some of the main questions raised will be summarised.
How Forecasts are Made and Produced (generally)
Forecasts for 1 week ahead or 3 months ahead are made in a similar way. However, you cannot expect a forecast for months ahead to be as detailed or as accurate as for a few days ahead. There are four main ingredients to forecasts: science, models, observations (mainly from satellites), and computers.
These four ingredients create a forecast, which can be used for products that are disseminated to users.
Forecasting in Africa in Particular
So, what is different about seasonal forecasting in Africa? One of the four ingredients of forecasts is computers, and thus computation. The resources required to do the computations needed to make a seasonal forecast might not be available in Africa. Instead, we can use statistical methods. We can then use the observed relationship between other variables, for example, Sea Surface Temperature (SST) and rainfall. These methods are in some ways easier because they require less computational resources, but they also have some disadvantages, like the fact that they assume historical relationships will persist in the future. With a changing climate, that is not necessarily the case.
Scarcity of data is also a problem in the African region. However, the Copernicus Climate Data and the American climate centre now produce data that is freely available, which is a good thing for the region. That way, one does not need to use resources on gathering data but can use already existing data to produce forecasts in the region. The fact that organizations are making their data freely available is helping, but it is important to note that it is not possible to do a good forecast without information from the ground (from stations on the ground) from African meteorological departments as well.
How to Interpret Forecasts and Make Use of them in Decision Making
Even though seasonal forecasts are made in the same way as daily or weekly forecasts, they cannot be interpreted in the same way. Seasonal forecasts tell us something about the probability of how the weather conditions will be, and we need to have that in mind when we use seasonal forecasts for decision-making. That means that the forecast for example tells you that there is a 70% chance of October being warmer or colder than normal, but it does not tell you how warm it will be on a specific day in October.
You can read more about how we create and interpret seasonal forecasts here: https://www.climatefutures.no/en/how-do-we-create-forecasts/
Capacity Building and How to Use Forecasts for Decision Making
First, people need to understand the forecast. Second, they need to know how to act in different scenarios. Training people in understanding and using forecasts is an important part of capacity building in the region. This is a topic that several of the participants were interested in: how and where can they acquire the skills to analyse the seasonal forecasts. Today we have several centres, like ICPAC, that offer this kind of training.
The world food program is responding by focus-based financing. This is a way for people to be able to properly interpret seasonal forecasts, for example by figuring out what probability means and understanding the skill of the forecast. This can help answer questions like: How good is a forecast? How much should I rely on it? It is about a community being able to interpret a forecast and immediately knowing how to act, and thus where to put their resources and finances.
Is a seasonal forecast enough for decision-making? That depends on the degree to which we can translate a forecast into real-life situations. Is the precipitation predicted sufficiently to have water for our livestock to produce enough milk for our children? Usually, if you have a forecast telling you there will be a drought in three months, there are some actions you can already take. This will help you be prepared, even if the drought is not as bad as first predicted.
Creating a guided framework for CSOs and risk management organisations can be helpful. If we can agree on specific actions that we will implement for a certain forecast. This can be a good advocacy instrument, especially if governments commit to it. Hopefully, this can lead to fewer headlines about climate-induced disasters, but more of how we will be able to manage the changing climate in an anticipatory manner.
Furthermore, we need an enhanced engagement from the media in this process. We need the alerts to be widespread, and people need to know what to expect from different alerts and forecasts. This way, we all have a guiding framework to be able to take action based on forecasts.
Why Trust Forecasts if they are Wrong? What Makes them Wrong?
Errors in the models are one reason why forecasts are wrong. CONFER and DOWN2EARTH recently published a paper about the strong relationship between the SST in the Indian Ocean and the rainfall over Eastern Africa, which explains how knowledge about errors in models are very important to improve the forecasts. If we know a model’s error, we can adjust the forecast thereafter to create a more accurate forecast.
It can be difficult to know which forecast providers to trust because their information can differ. This is because they use different models, that also have different errors. Centres like ICPAC for example use an average of the different models. They look at how well the models are doing and use an average to create forecasts.
What Happens Next?
This is the first of a series of webinars that the three sister projects will arrange, and hopefully, it can be a step towards understanding forecasts better. When people understand how to interpret forecasts, they are more likely to use them in decision-making. Creating understandable forecasts and training the users in how to understand them and make use of them is crucial. Otherwise, forecasts will get more accurate but at the same time, they will be less used.
Watch the whole webinar and discussion here.