Weather and climate services involve the production, translation, transfer, and use of scientific information for decision-making. They include long term climate projections, monthly to seasonal forecasts and daily weather forecasts. They are particularly useful (i) for several climate sensitive sectors such as agriculture, water resources, health, energy, disaster risk reduction and (ii) in developing countries where vulnerability to climate change and weather shocks is high. This interdisciplinary session aims at showing tools, results, methodologies that could lead in fine to an operational improvement of WCS in developing countries. It focuses not only on models improvement but also on how to interact with end-users, assess WCS added value, broadcast information, avoid inequalities access, involve the private sector etc. The session will focus particularly on feedbacks and results from different case studies located in the global South.

Co-organized by EOS4/AS4/HS12/NH9
Convener: Philippe Roudier | Co-conveners: Pauline Dibi Kangah, Seyni Salack, Ibrahima Sy, Catherine Vaughan
| Attendance Fri, 08 May, 08:30–10:15 (CEST)

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Chat time: Friday, 8 May 2020, 08:30–10:15

Chairperson: Philippe Roudier
D2016 |
Stefan Liersch, Holger Hoff, and Seyni Salack

From our experience in West Africa it is obvious that the concept of climate services is not yet well understood or established in all user groups. Also some scientists still wonder if they have not been working on generating knowledge and information about climate change impacts for decades anyway. In some climate services projects, scientists find themselves in a new role, "selling" their products to users who are not necessarily aware of the existence of the product, where an attempt is made to create a demand. In other projects the demand is clear from the beginning. However, the introduction of the term or the concept of climate services has the potential to add a new dimension to the world of climate impact research and especially its application. It influences the attitude of scientists towards the applicability of their results in the direction of more targeted and demand-driven or ideally even co-produced information and services. Understanding scientific information as a service rather than as self-sufficient information for the scientific community, helps to better meet the needs of users. To improve the production and particularly the use of climate services both parties (producer and user) are challenged. To a certain extent, the scientist has to rethink and see the results as a valuable product that can be easily understood and used by others. This often requires a redesign, not necessarily of the product itself but the way it is presented. The user, in turn, must formulate precisely which information is useful to support her or his daily work, e.g. integrating climate change information into development plans for natural resources, sustainable energy planning or adaptation and mitigation strategies. This part in particular poses a real challenge, as the user does not always urgently need the information that a project intends to provide (bad timing) or is not in a position to adequately formulate the type of information required by the institution where she or he is employed. In this case, scientists occasionally face situations where they try to anticipate what kind of information is really useful for the user. Hence, communication between producer and user is key, but is normally not trivial, because of different backgrounds, expertise, language etc. It’s a process that requires facilitation by skilled staff.In the CIREG project in West Africa we elicited the stakeholder’s information demand in a first workshop. Apparently, the greatest need was formulated as capacity building for planning instruments for water and energy management in the context of climate change. By training on these tools, we gain access to the stakeholders and gain insight into their actual information needs. The willingness to share data and information also increases with this kind of cooperation and can lead to real co-production. However, data availability and the willingness to share is a challenge in many developing countries. Research projects are usually too short to identify the need for information, to jointly develop information and at the same time to guarantee and observe its uptake.

How to cite: Liersch, S., Hoff, H., and Salack, S.: Climate services: The product or the user, which came first?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21847, https://doi.org/10.5194/egusphere-egu2020-21847, 2020.

D2017 |
pascal Venzac, christine David, and morgane Lovat

Create weather ecosystems to make weather and climate services more efficient in developing countries

Pascal Venzac, Christine David, Morgane Lovat

WeatherForce – France

Over the last decade, extreme events are more and more frequent and/or intensive. 85% of the world's population is affected by these events. But, 75% of the most vulnerable countries has no or little reliable, accurate and effective weather information. Effective forecasts and early warnings could however make the difference between life and death in those countries. Weather data are crucial for local populations and governments who can exploit it to optimize their economic development and prevent major social and health crises.

By international agreement, National Meteorology and Hydrology Services (NMHS) are the government's authoritative source of weather, climate and water information. But, some NMHS in developing countries have difficulties to deploy and maintain operational infrastructure like rain gauge recorder for example. In addition, rain gauges provide only local information, measuring rainfall level in the specific geographic location.

WeatherForce was created in August 2016, by two experts from Météo-France Group (French National Meteorological Service) to help meet the challenges of national weather services in developing countries.

WeatherForce works in close partnerships with NMHS to strengthen their fundamental role and implement weather ecosystems for local development with a sustainable business model.

The WeatherForce platform, first weather collaborative platform is designed to help:

  • public institutions that need accurate weather data or predictive indicators to help them make informed decisions to protect local populations and infrastructures.
  • universities or research institutes that need a platform to easily access data to code, modify and share their algorithms.
  • startups incubators that look for reliable data to create innovative applications to help local populations cope with climate change
  • private companies that need custom weather services to improve their performance.

Our platform aggregates global data (satellite images, global forecasts, etc.) transposed into a local geographic context (IoT sensors, local stations, field expertise). It is opened to local research and innovation ecosystems to offer them access to its qualified data and develop new weather indicators contributing to the creation of a meteorological common.

WeatherForce aims to increase local sustainability by making weather data available to all through a weather ecosystem.

Regarding the business model, it is based on revenue sharing, the NMHS receives a commission payment in relation to the revenue generated. WeatherForce sells services to private companies (agribusiness...) and shares the part dedicated with NMHS. The contribution from NMHS is based on the local expertise and data. We do not ask the NMHS to pay a subscription fee for the platform.

To summarize, we create through Public Partner Engagement (PPE) weather ecosystems that promote dialogue between private actors and public authorities; collaboration for better policies, new business opportunities and sustainable business model.

The WeatherForce solution connects local actors to each other but also to the rest of the world thanks to our open-source platform designed to allow collaborations between other weather ecosystems worldwide.

How to cite: Venzac, P., David, C., and Lovat, M.: Create weather ecosystems to make weather and climate services more efficient in developing countries, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4587, https://doi.org/10.5194/egusphere-egu2020-4587, 2020.

D2018 |
Marco Gaetani, Benjamin Sultan, Serge Janicot Serge Janicot, Mathieu Vrac, Robert Vautard, Adjoua Moise Famien, Roberto Buizza, and Mario Martina

Independence in energy production is a key aspect of development in West African countries, which are facing fast population growth and climate change. Sustainable development is based on the availability of renewable energy sources, which are tightly tied to climate variability and change. In the context of current and projected climate change, development plans need reliable assessment of future availability of renewable resources.

In this study, the change in the availability of photovoltaic (PV) and wind energy in West Africa in the next decades is assessed. Specifically, the time of emergence (TOE) of climate change in PV and wind potential is estimated in 29 CMIP5 climate projections.

The ensemble robustly simulates a shift into a warmer climate in West Africa, which already occurred, and projects a decrease in solar radiation at the surface to occur by the 70s. The reduction in solar radiation is associated with a projected increase in the monsoonal precipitation in the 21st century. It results a likely change into climate conditions less favourable for PV energy production by the 40s. On the other hand, the projected change in the monsoonal dynamics will drive the increase in low level winds over the coast, which in turn will result in a robustly simulated shift into climate conditions favourable to wind power production by mid-century. Results show that climate model projections are skilful at providing usable information for adaptation measures to be taken in the energy sector.

How to cite: Gaetani, M., Sultan, B., Serge Janicot, S. J., Vrac, M., Vautard, R., Famien, A. M., Buizza, R., and Martina, M.: Future change in renewable energy availability in West Africa: a time of emergence approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20842, https://doi.org/10.5194/egusphere-egu2020-20842, 2020.

D2019 |
Manuel Rauch, Jan Bliefernicht, Patrick Laux, Seyni Salack, Moussa Waongo, and Harald Kunstmann

Seasonal forecasts for monsoonal rainfall characteristics like the onset of the rainy season (ORS) are crucial in semi-arid regions to better support decision-making in water resources management, rain-fed agriculture and other socio-economic sectors. However, forecasts for these variables are rarely produced by weather services in a quantitative way. To overcome this problem, we developed an approach for seasonal forecasting of the ORS using global seasonal forecasts. The approach is not computationally intensive and is therefore operational applicable for forecasting centers in developing countries. It consists of a quantile-quantile-transformation for eliminating systematic differences between ensemble forecasts and observations, a fuzzy-rule based method for estimating the ORS date and a graphical method for an improved visualization of probabilistic ORS forecasts, called the onset of the rainy season index (ORSI). The performance of the approach is evaluated from 2000 to 2010 for several climate zones (Sahel, Sudan and Guinean zone) in West Africa, using hindcasts from the Seasonal Forecasting System 4 of ECMWF. Our studies show that seasonal ORS forecasts can be skillful for individual years and specific regions like the Guinean coasts, but also associated with large uncertainties, in particular for longer lead times. The spatial verification of the ORS fields emphasizes the importance of selecting appropriate performance measures to avoid an overestimation of the forecast skill. The ORSI delivers crucial information about an early, mean and late onset of the rainy season and it is much easier to interpret for users compared to the common categorical formats used in seasonal forecasting. Moreover, the new index can be transferred to other seasonal forecast variables, providing an important alternative to the common forecast formats used in seasonal forecasting. In this presentation we show (i) the operational practice of seasonal forecasting of ORS and other monsoonal precipitation characteristics, (ii) the methodology and results of the new ORS approach published in Rauch et al. (2019) and (iii) first results of an advanced statistical algorithm using ECMW-SYS5 hindcasts over a period of 30 years (1981-2010) in combination with an improved observational database.

Rauch, M., Bliefernicht, J., Laux, P., Salack, S., Waongo, M., & Kunstmann, H. (2019). Seasonal forecasting of the onset of the rainy season in West Africa. Atmosphere, 10(9), 528.

How to cite: Rauch, M., Bliefernicht, J., Laux, P., Salack, S., Waongo, M., and Kunstmann, H.: Probabilistic forecasts of the onset of the rainy season using global seasonal forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-677, https://doi.org/10.5194/egusphere-egu2020-677, 2020.

D2020 |
Namrata Bhattacharya Mis

Agenda 2030 goal 11 commits towards making disaster risk reduction an integral part of sustainable social and economic development. Flooding poses some of the most serious challenges in front of developing nations by hitting hardest to the most vulnerable. Focussing on the urban poor, frequently at highest risk are characterised by inadequate housing, lack of services and infrastructure with high population growth and spatial expansion in dense, lower quality urban structures. Use of big data from within these low-quality urban settlement areas can be a useful step forward in generating information to have a better understanding of their vulnerabilities. Big data for resilience is a recent field of research which offers tremendous potential for increasing disaster resilience especially in the context of social resilience. This research focusses to unleash the unrealised opportunities of big data through the differential social and economic frames that can contribute towards better-targeted information generation in disaster management. The scoping study aims to contribute to the understanding of the potential of big data in developing particularly in low-income countries to empower the vulnerable population against natural hazards such as floods. Recognising the potential of providing real-time and long-term information for emergency management in flood-affected large urban settlements this research concentrates on flood hazard and use of remotely sensed data (NASA, TRMM, LANDSAT) as the big data source for quick disaster response (and recovery) in targeted areas. The research question for the scoping study is: Can big data source provide real-time and long- term information to improve emergency disaster management in urban settlements against floods in developing countries?  Previous research has identified several potentials that big data has on faster response to the affected population but few attempts have been made to integrate the factors to develop an aggregated conceptual output . An international review of multi-discipline research, grey literature, grass-root projects, and emerging online social discourse will appraise the concepts and scope of big data to highlight the four objectives of the research and answer the specific questions around existing and future potentials of big data, operationalising and capacity building by agencies, risk associated and prospects of maximising impact. The research proposes a concept design for undertaking a thematic review of existing secondary data sources which will  be used to provide a holistic picture of how big data can support in resilience through technological change within the specific scope of social and environmental contexts of developing countries. The implications of the study lie in the system integration and understanding of the socio-economics, political, legal and ethical contexts essential for investment decision making for strategic impact and resilience-building in developing nations.

How to cite: Bhattacharya Mis, N.: Big Data for flood management: Realising the benefits for developing countries, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19654, https://doi.org/10.5194/egusphere-egu2020-19654, 2020.

D2021 |
Michele Meroni, Felix Rembold, Ferdinando Urbano, Guido Lemoine, Hervé Kerdiles, Ana Perez-Hoyos, Gabor Csak, Maria Dimou, and Petar Vojnovic

Monitoring agricultural production in vulnerable developing countries is important for food security assessment and requires near real-time (NRT) information on crop growing conditions for early detection of possible production deficits. The public online ASAP system (Anomaly hot Spots of Agricultural Production) is an early warning decision support tool based on weather data and direct observation of crop status as provided by remote sensing. Although decision makers and food security analysts are the main targeted user groups, all the information is fully made available to the public in a simple and well documented online platform. The information further contributes to multi-agency early warning products such as the GEOGLAM Crop Monitor for Early Warning and food security assessments following the IPC-Cadre Harmonisé framework.

Low resolution remote sensing (1 km) and meteorological (5-25 km) data are processed automatically every 10 days and vegetation anomaly warnings are triggered at the first sub-national administrative level. The severity of the warnings is based on the observed land surface phenology and three main derived indicators computed at the 1 km grid level: a proxy of the current season biomass production (the cumulative value of the Normalized Difference Vegetation index from the start of season); an indicator of precipitation deficit (the Standardized Precipitation Index at the 3 month scale); and a water-balance model output (the Water Requirement Satisfaction Index).Warning maps and summary information are published on a web GIS every ten days and then further analyzed by analysts every month. This results in the identification of hotspot countries with potentially critical crop or rangelands production conditions.

In addition to the hotspots analysis and the warning explorer, users can also zoom in to the parcel level thank to the so called High Resolution Viewer, a web interface based on Google Earth Engine that allows to visualize Sentinels (1 and 2) and Landsat imagery, plot temporal profiles and perform basic anomaly operation (e.g. current year NDVI anomaly with respect to a reference year).  

In the near future it is planned to make the anomaly warnings available also at the second sub-national level and to integrate meteorological forecasts in the warning system.

How to cite: Meroni, M., Rembold, F., Urbano, F., Lemoine, G., Kerdiles, H., Perez-Hoyos, A., Csak, G., Dimou, M., and Vojnovic, P.: Using global remote sensing and weather data efficiently for agricultural hotspots monitoring anywhere anytime: the ASAP online system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6735, https://doi.org/10.5194/egusphere-egu2020-6735, 2020.

D2022 |
Jorge Tamayo

The cooperation between Iberoamerican National Meteorological and Hydrological Services (NMHS) it is coordinated through the Conference of Directors of Iberoamerican NMHS (CIMHET), who takes advantage of the unique framework that provides the cultural and idiomatic heritage in the region. It is constituted by all 21 NMHSs of Iberoamerica, including Spain and Portugal. CIMHET provides a forum for dialogue between Iberoamerican NMHSs, recognized by World Meteorological Organization (WMO) as an example of cooperation and operability.
The Conference approves, at its annual meetings from 2003, an action plan over three strategic lines: Institutional strengthening and resource mobilization; provision of meteorological, climatic and hydrological services; education and training
Among the activities carried out in the latest action plans related to a better provision of Weather and Climate Services (WCS) includes the support for the creation and operation of Virtual Regional Centers for the Prevention of Severe Events, the development of a free database management system, namely MCH, which has been donated to WMO for distribution among interested NMHS, the implementation of a regional lightning detection network in Central America, or the development of downscaling climate change scenarios for Central America, with access to information and view via web.
In order to carry out the proper provision of WCS, it is also necessary to have sufficient and properly trained NMHS staff. Therefore, this activity, both for technical and management personnel, has been one of the fundamental elements in the activities carried out by CIMHET, with more than 60 courses and workshops from 2004, most of which have been face-to-face, attended by more than 1500 students.
It is also important to have the appropriate infrastructure and human resources so that NMHS can provide their services to society in a reliable and timely manner. For this, several modernization projects have been developed, mainly considering the needs of the different user sectors and showing their potential of NMHS for the different national social and economic sectors in case of solving their shortcomings.
Finally, intersectoral coordination mechanisms have been established with other Iberomerican networks with common interests, such as the Iberoamerican Network of Climate Change Offices (RIOCC) and the Conference of Iberoamerican Directors of Water (CODIA). A number of priority activities related to climate change adaptation issues linked to extreme hydrometeorological phenomena have been identified and started its development.

How to cite: Tamayo, J.: The experience of Iberoamerican Meteorological Cooperation in the improvement of the provision of Weather and Climate Services, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7476, https://doi.org/10.5194/egusphere-egu2020-7476, 2020.

D2023 |
Frank Ohene Annor, Nick van de Giesen, and Marie-Claire ten Veldhuis

Close to 80% of Sub-Saharan African farmers rely on rainfed agriculture.  This makes it important that the weather and climate in this region is well understood, since it accounts for more than 15% of the GDP for instance in Ghana and Kenya. However, uncertainties in weather forecast and climate projections are very high in particular for this region, which leads to poor weather and climate services for agriculture production. One of the underlying factors among many is the poor conditions of weather and climate infrastructure in Sub-Saharan Africa.  The Trans-African Hydro-Meteorological Observatory (TAHMO) together with some National Meteorological and Hydrological Services (NMHSs) in Africa and other partners through the TWIGA project (http://twiga-h2020.eu/) are building a network of weather and hydrological stations to address this need. This network builds on the over 500 TAHMO stations in countries of interest like Ghana, Kenya, Uganda, South Africa, and Mozambique.

The observation network includes automatic weather stations, soil moisture sensors, Global Navigation Satellite System (GNSS) receivers, distributed temperature sensing (DTS), lightning sensors, neutron counters, evaporometers, laser speckle scintillometers, accelerometers for tree weighing, intervalometer rain gauges, flood mapper using citizen science mobile applications (Apps) and crop doctor using drones and Apps. The project has accelerated the Technology Readiness Levels (TRLs) of these innovations with some already set up for operational purposes delivering the first set of TWIGA services such as “How humid is my environment?; Crop detection and condition monitoring; Weather-based alerts for citizens/farmers; Area-specific near real-time weather forecast for farmers; Crop insurance based on soil index; Plastic accumulation monitor; Short-term prediction for solar energy; and Precipitable water vapour monitoring with TWIGA GNSS stations. These new innovations and the services developed using the value chain approach is a game changer for Sub-Saharan Africa.

How to cite: Annor, F. O., van de Giesen, N., and ten Veldhuis, M.-C.: Water, Weather and Climate Services for Africa: the case of Ghana and Kenya, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10714, https://doi.org/10.5194/egusphere-egu2020-10714, 2020.

D2024 |
Gerald Lim, Aurel Moise, Raizan Rahmat, and Bertrand Timbal

Southeast Asia (SEA) is a rapidly developing and densely populated region that is home to over 600 million people. This, together with the region’s high sensitivity, exposure and low adaptive capacities, makes it particularly vulnerable to climate change and extremes such as floods, droughts and tropical cyclones. While the last decade saw some countries in SEA develop their own climate change projections, studies were largely uncoordinated and most countries still lack the capability to independently produce robust future climate information. Following a proposal from the World Meteorological Organisation (WMO) Regional Association (RA) V working group on climate services, the ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series was conceived in 2017 to bridge these gaps in regional synergies. The ARCDAP series has been organised annually since 2018 by the ASEAN Specialised Meteorological Centre (hosted by Meteorological Service Singapore) with support from WMO through the Canada-funded Climate Risk and Early Warning Systems (Canada-CREWS) initiative.

This presentation will cover the activities and outcomes from the first two workshops, as well as the third which will be held in February 2020. The ARCDAP series has so far brought together representatives from ASEAN National Meteorological and Hydrological Services (NMHSs), climate scientists and end-users from policy-making and a variety of vulnerability and impact assessment (VIA) sectors, to discuss and identify best practices regarding the delivery of climate change information, data usage and management, advancing the science etc. Notable outputs include two comprehensive workshop reports and a significant regional contribution to the HadEX3 global land in-situ-based dataset of temperature and precipitation extremes, motivated by work done with the ClimPACT2 software.

The upcoming third workshop will endeavour to encourage the uptake of the latest ensemble of climate simulations from the Coupled Model Intercomparison Project (CMIP6) using CMIP-endorsed tools such as ESMValTool. This will address the need for ASEAN climate change practitioners to upgrade their knowledge of the latest global climate model database. It is anticipated that with continued support from WMO, the series will continue with the Fourth workshop targeting the assessment of downscaling experiments in 2021.

How to cite: Lim, G., Moise, A., Rahmat, R., and Timbal, B.: Building synergies in regional climate services for Southeast Asia: The ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15094, https://doi.org/10.5194/egusphere-egu2020-15094, 2020.

D2025 |
Hermen Westerbeeke, Deus Bamanya, and George Gibson

Since 2017, the governments of Uganda and the United Kingdom have been taking an innovative approach to mitigating the impacts of drought and floods on Ugandan society in the DFMS Project. Recognising both that the only sustainable solution to this issue is the continued capacity development in Uganda’s National Meteorological and Hydrological Services, and that it will take time for this capacity development to deliver results, the Drought & Flood Mitigation Service Project developed DFMS, bringing together meteorological, hydrological, and Earth observation information products and making these available to decision-makers in Uganda.

After the DFMS Platform was designed and developed in cooperation between a group of UK organisations that includes the Met Office and is led by the REA Group and five Ugandan government agencies including UNMA, led by the Ministry of Water and Environment (MWE), 2020 saw the start of a 2.5-year Demonstration Phase in which UNMA, MWE, and the other agencies will trial DFMS and DFMS will be fine-tuned to their needs. We will be presenting the first experiences with DFMS, including how it is being used related to SDG monitoring, and will showcase the platform itself in what we hope will be a very interactive session.

DFMS is a suite of information products and access only requires an Internet-connected device (e.g. PC, laptop, tablet, smart phone). Data and information are provided as maps or in graphs and tables, and several analysis tools allow for bespoke data processing and visualisation. Alarms can be tailored to indicate when observed or forecast parameters exceed user-defined thresholds. DFMS also comes with automatic programmable interfaces allowing it to be integrated with other automatic systems. The DFMS Platform is built using Open Source software, including Open Data Cube technology for storing and analysing Earth Observation data. It extensively uses (free) satellite remote sensing data, but also takes in data gathered in situ. By making the platform scalable and replicable, DFMS can be extended to contain additional features (e.g. related to landslides or crop diseases) or be rolled out in other countries in the region and beyond.

How to cite: Westerbeeke, H., Bamanya, D., and Gibson, G.: The Drought & Flood Mitigation Service in Uganda – First Results, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17108, https://doi.org/10.5194/egusphere-egu2020-17108, 2020.

D2026 |
| Highlight
Spyridon Paparrizos, Talardia Gbangou, Uthpal Kumar, Rebecca Sarku, Joreen Merks, Saskia Werners, Art Dewulf, Fulco Ludwig, and Eric van Slobbe

Water for agriculture in peri-urban areas is vital to safeguard sustainable food production. Due to the dynamics of urbanization in deltas as well as climate change, water availability (too much, not enough, too late or early) is becoming erratic and farmers cannot rely only on their own experience anymore for agricultural decision-making. The WaterApps project develops tailor made water and weather information services with and for farmers in peri-urban areas in the urbanizing deltas of Accra, Ghana and Khulna, Bangladesh to improve water and food security and contribute towards sustainable agriculture.

The project’s design framework initially focuses on the farmers that are involved and supported during its course in the study areas and assesses their needs. Based on the baseline needs assessment study and along with the farmers in a co-producing mode Climate Information Services are being developed that provide tailor-made water and weather information and are continuously monitored and evaluated to ensure their effectiveness.

WaterApps combines the latest information technology such as Apps, social media, etc. on knowledge sharing that are enhanced with the local farmers’ information needs, demands and preferences to produce tailor-made Climate Information Services.

It deals with the technical part & design aspects of the water and climate information services, such as: the skill of the provided information on different spatio-temporal scales and the role of Local Forecasting Knowledge in the study areas.

Currently, an APP is being developed which, besides displaying scientific forecast gives the possibility to farmers to provide their own indigenous forecast. Additionally, scientific and indigenous forecast are being integrated providing a hybrid forecast.

In Bangladesh, Farmers’ Fields Schools (FFS) have been initiated together with meetings and trainings. The objective was to engage with farmers on a weekly basis by providing long term weather forecast and discuss the relevance in relation to upcoming agricultural activities. Social media are employed to inform agricultural extension officers and stakeholders on a daily basis.

Both cases in Bangladesh and Ghana show the importance of two-way communication and co-production with and for farmers. The co-production of water and weather information services empowers and improves livelihoods of small/medium farmers and builds capacity for enhancing sustainable food production. Finally, it lays the ground for upscaling in other urban-rural delta zones in the developing world.

How to cite: Paparrizos, S., Gbangou, T., Kumar, U., Sarku, R., Merks, J., Werners, S., Dewulf, A., Ludwig, F., and van Slobbe, E.: WaterApps: co-producing tailor-made water and weather information services with and for farmers for sustainable agriculture in peri-urban delta areas in Ghana and Bangladesh, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5712, https://doi.org/10.5194/egusphere-egu2020-5712, 2020.

D2027 |
Frida Gyllensvärd, Christiana Photiadou, Berit Arheimer, Lorna Little, Elin Sjökvist, Katharina Klehmet, Thomas Bosshard, Léonard Santos, Maria Elenius, René Capell, and Isabel Ribeiro

The World Meteorological Organization (WMO), the Green Climate Fund (GCF) and the Swedish Meteorological and Hydrological Institute (SMHI) are collaborating on a project providing expert services for enhancing the climate science basis of GCF-funded activities. The goal is to ensure that the causal links between climate and climate impacts, and between climate action and societal benefits, are fully grounded in the best available climate data and science.  Five pilot countries are participating in this phase of the project: St Lucia, Democratic Republic of Congo, Cape Verde, Cambodia, and Paraguay, with an audience of national experts, international stakeholders, and policy and decision makers.

The scientific framework which we follow here is a compendium of available data, methods and tools for analysing and documenting the past, present and potential future climate conditions which a GCF-funded project or adaptation plan might seek to address. Through the WMO-GCF-SMHI project, the methodology, scientific framework, data, methods and tools to link global to local data are complemented by hands-on support, backed by access to relevant data and tools through a structured access platform.

In this presentation we elaborate on the lessons learnt from a number of workshops that were designed for the five pilot countries. The main focus of the workshops was a hands-on opportunity of national experts and international stakeholders to work with the WMO methodology in order to develop a GCF proposal for future funding. The participants in each country worked intensively during a five-day workshop on each step of the methodology: Problem definition, Identification of climate science basis, Interpretation of data analysis, selection of best adaptation/mitigation options, and assessment of adaptation/mitigation effectiveness.

Assessing past and current climate and climate projections is the basis for inferring real and potential climate change and related impacts. For this, SMHI has developed a new interactive online platform/service (https://climateinformation.org/) to facilitate the communication between the GCF and developing countries and provide access to state of the art climate data to be used in impact assessment planning. The new service provides data for robust climate analysis to underpin decision-making when planning measures for climate adaptation or mitigation. Readily available climate indicators will help defining future problems, assess climatic stressors, and analyse current and future risks. This makes a climate case, which is the basis for developing interventions and propose investments. In particular the service provides:

  • Easy access to many climate indicators, based on state-of-the-art climate science.
  • Instant summary reports of climate change for any site on the globe.
  • Guidance on how to link global changes to local observations.

How to cite: Gyllensvärd, F., Photiadou, C., Arheimer, B., Little, L., Sjökvist, E., Klehmet, K., Bosshard, T., Santos, L., Elenius, M., Capell, R., and Ribeiro, I.: The Climate Information platform: A climate science basis for climate adaptation and mitigation activities in developing countries , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21637, https://doi.org/10.5194/egusphere-egu2020-21637, 2020.

D2028 |
Judit Lienert, Jafet Andersson, and Francisco Silva Pinto

Floods are a serious concern in West Africa, and their severity will likely increase with climate change. The European Union-financed, inter- and transdisciplinary project FANFAR (https://fanfar.eu/) aims at providing an operational flood forecast and alert pilot system for West Africa, based on an open-source hydrological model employed in a cloud-based Information and Communications Technology (ICT) environment. To achieve this, an existing pilot ICT system is co-designed and co-adapted to meet needs and preferences of West African users. Four workshops are carried out in West Africa from 2018 to 2020, each with around 40 representatives from hydrological and emergency management agencies from 17 West African countries.

To better understand the stakeholders’ needs and preferences, and to prioritize the development of the FANFAR ICT flood forecasting and alert system, we use Multi-Criteria Decision Analysis (MCDA). This MCDA framework guides through a stepwise procedure to develop the FANFAR ICT system such that it best fulfils those objectives that are fundamentally important to stakeholders. The first steps of MCDA are problem structuring; starting with a stakeholder analysis to identify the most important participants for the co-design workshops. In the first co-design workshop (Niamey, Niger, 2018), we then used different problem structuring methods (PSMs) to brainstorm which objectives are fundamentally important to West African stakeholders, and which options (ICT system configurations) might achieve these objectives. To generate objectives, we used online and pen-and-paper surveys, group brainstorming, and plenary discussions. To generate options, we used a strategy generation table and the brainwriting-635 method. Between workshops, the FANFAR consortium post-processed the objectives and options. We also interviewed experts to predict how well an option achieves each objective; including the uncertainty, which is later propagated to the MCDA results with Monte Carlo simulation.

The refined objectives were again discussed in plenary sessions in co-design workshop 2 (Accra, Ghana, 2019), and we elicited the participants’ preferences in small group sessions. Weight elicitation captures the trade-offs stakeholders are willing to make regarding achieving objectives, if not all objectives can be fully fulfilled. We used the card procedure to elicit weights (Simos revised procedure), and the popular swing method. As additional preference information for the MCDA modelling, we elicited the shape of the most-important marginal value functions, which “translate” the objectives’ measurement-units to a neutral value between 0 (objective is not achieved) and 1 (fully achieved). To give one example: for the objective “high accuracy of information”, the best case is “100% accuracy”, translated to the value v=1; the worst case “0% accuracy” translates to v=0. Furthermore, we asked whether stakeholders agree with the implications of the commonly used (linear) additive aggregation model in MCDA (weighted average).

We will present and discuss main results of the MCDA-modeling. Our main aim is to give some insights into the participatory co-design process employed in FANFAR, and recommendations for other projects. We will discuss the problem structuring and preference elicitation methods, and how well they worked in this interesting West African context.

How to cite: Lienert, J., Andersson, J., and Silva Pinto, F.: Co-designing a flood forecasting and alert system in West Africa with decision-making methods: the transdisciplinary project FANFAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8127, https://doi.org/10.5194/egusphere-egu2020-8127, 2020.

D2029 |
Emmanuel Nyadzi, Saskia Werners, Robbert Biesbroek, and Fulco Ludwig

Extreme weather events and climate change are affecting the livelihoods of farmers across the globe. Accessible and actionable weather and seasonal climate information can be used as an adaptation tool to support farmers to take adaptive farming decisions. There are increasing calls to integrate scientific forecast with indigenous forecast to improve weather and seasonal climate information at local scale. In Northern Ghana, farmers lament about the quality of scientific forecast information thereby depending on their own indigenous forecast for taking adaptive decisions. To improve this, we developed an integrated probability forecast (IPF) method to combine scientific and indigenous forecast into a single forecast and tested its reliability using binary forecast verification method as a proof of concept. We also evaluated the acceptability of IPF among farmers by computing an index from multiple-response questions with good internal consistency check. Results show that, for reliability, IPF on average performed better than indigenous and scientific forecast at a daily timescale. At seasonal timescale, indigenous forecast overall performed better followed by IPF and then scientific forecast. However, IPF has far greater acceptability potential.  About 93% of farmers prefer IPF method as this provides a reliable forecast, requires less time and at the same time helps deal with contradicting forecast information. Results also show that farmers already use insights from both forecasts (complementary) to inform their farm decisions. However, their complementary method does not resolve the issues of contradicting forecast information. We conclude that, as a proof of concept, integrating indigenous and scientific forecast has high acceptability and can potentially increase forecast reliability and uptake.




How to cite: Nyadzi, E., Werners, S., Biesbroek, R., and Ludwig, F.: Combining Indigenous and Scientific Forecast for Improved Climate Services in Ghana, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22322, https://doi.org/10.5194/egusphere-egu2020-22322, 2020.

D2030 |
Talardia Gbangou, Rebecca Sarku, Erik Vanslobbe, Fulco Ludwig, Gordana Kranjac-Berisavljevic, Spyridon Paparrizos, and Art Dewulf

Many West African farmers struggle to cope with changing weather and climatic conditions that keep them from making optimal decisions and meeting food and income security. The development of more accessible and credible weather and climate services (WCIS) can help local farmers improve their adaptive capacity. Such adequate WCIS often requires a joined collaboration between farmers and scientists to co-create an integrated local and scientific forecasting knowledge. We examine (i) the design requirements (i.e. Both technical and non-technical tools) and (ii) evaluate the outcomes of a successful implementation of the co-production and delivery of WCIS in Ada East district, Ghana. We implemented a user-driven design approach in a citizen science experiment involving prototype design and testing, training workshops, and interviews with farmers, agricultural and meteorological extension agents from 2018 to 2019. Farmers were handed with digital tools (i.e. Smart phones with web and mobile applications) and rain gauges as research instruments to collect and receive weather forecast data, and interact with scientists.

               Our results show that farmers’ engagement increased over time and is associated with the trainings and the improvement of the design features of the applications used. The evaluation shows an increase in the usability of tools, the reach or networking with other farmers, and the understanding of uncertainty (probabilistic) aspect of the forecasts over time. Local farmers evaluated both the local and scientific forecasts as accurate enough and useful for their daily farming decisions. We concluded that using modern technology in a co-production process, with targeted training, can improve the access and use of weather forecasts information.

How to cite: Gbangou, T., Sarku, R., Vanslobbe, E., Ludwig, F., Kranjac-Berisavljevic, G., Paparrizos, S., and Dewulf, A.: Success of the co-production and delivery of local and scientific weather forecasts information with and for smallholder farmers in Ghana, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22514, https://doi.org/10.5194/egusphere-egu2020-22514, 2020.