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Name of organizationLaunched inWhere does it operate?Public or private?What does it fund?Main sector (e.g. agriculture, disaster warning)Budget & fundingHow effective is it?
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Ignitia2015West Africa (Ghana, Burkina Faso, Mali, Nigeria)Private- Does own hyperlocal weather forecasts in the tropics based on a priorietary forecasting model
- Sends SMS to farmers with weather information (daily, monthly and seasonal forecasts)
- Flagship product: 48h forecast message via SMS		Agriculture$5.4 million raised in funding over 4 rounds (until July 2021) (Crunchbase)
=> ~$0.9 million per year		- Ignitia claims to be 2x as accurate as global models (84% accurate) (Website)
- Independent evaluation of rainfall forecasting accuracy in 2017 showed that 84% accuracy claim is exaggerated - rainfall forecasts are reliable but less so than Ignitia claims
- Independent 2018 impact assessment in Ghana showed benefits to farmers (decrease in farming expenses, increase in yields and incomes, optimized time spent on fields, benefits/spillovers to communities); however, less farmers use the messages than claimed by Ignitia
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Skymet Weather Services2003IndiaPrivate- Runs own meso and micro forecast NWP
- Sets up ground oversation units in Indian areas prone to natural calamities - had around 6,500 observation centers in 2021 (The Times of India, 2021)
- Developed many software tools for weather and climate decision support systems		No particular focus (provide weather services for various sectors: e.g. agriculture, power sector, insurance companies) (Wikipedia)$14.6 million total funding amount in 2022 (Crunchbase)
=> $1.6 million per year		- According to Wikipedia, Skymet has seen some successes and failures in its monsoon predictions (e.g. Skymet has reportedly predicted Indian monsoons during 2012, 2013 and 2014 before the India Meteorological Department; in other instances its monsoon predictions failed to deliver)
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Africa Hydromet Program (Regional Framework Program to Improve Hydrometeorological Services in Sub-Saharan Africa)201515 African countries (Burkina Faso, Chad, Cote D'Ivoire, The Democratic Republic of the Congo, Ghana, Kenya, Mali, Mozambique, Niger, Nigeria, Rwanda, Sierra Leone, Tanzania, Togo) and 4 regional climate centers Public- Partnership of development organizations (WBG, WMO, AfDB, AFD, UNDP) working to improve weather, water, and climate services throughout Africa
- Modernization of hydromet services for climate and disaster resilience (transforming observation infrastructure, collecting and interpreting data, and delivering climate services - including high-wuality weather forecasting)		Disaster warning seems primary focus; but also focus on improving agriculture and other economic sectors (World Bank)$600 million envisaged investments (World Bank)
$312 million spending in its first phase (5 years) (reliefweb, 2021)
=> 62.4 million per year		- Have not found any evaluations/assessments, but here is a list of its projects
- Across Africa, 26 million people benefitted from improved hydrometeorological services (reliefweb, 2021)
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CREWS (Climate Risk and Early-Warning Systems Initiative)201560 countries (least developed countries and small island developing states)Public- Provides increased access to early weather warnings and risk information in least developed countries and small island developing states
- Does not run own weather forecasts or try to improve weather forecasting		Disaster warning$77.6 million received in signed contributions to CREWS Trust Fund since 2015
$400 million additional mobilized resources on early warning and through projects in synergy with CREWS's work in 2021 (CREWS Annual Report 2021, p. 7)
=> $11 million + 57 million per year		- CREWS Annual Report 2021 (Have not looked at it in detail)
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SWFP (Severe Weather Forecasting Program) by WMO2006Over 80 developing countries in nine sub-regions (Southern Africa, Central Africa, South Pacific, Eastern Africa, South-East Asia, South Asia, Central Asia, West Africa, Eastern Carribbean)Public- Aims to strengthen capacity of WMO members to deliver improve forecasts and warnings of severe weather to save lives and livelihoods, and protect property and infrastructure
- Makes use of the "Cascading Forecasting Process" (from global to regional to national level)
- Since 2016, also focused on developing capacity of participating countries on impact-based forecast and warning services for improved decision-making
Disaster warmingHave not been able to find out amount of budget/funding. Funded mostly through donor contributions (Norway, CREWS, UN) (WMO, 2019)- Have not found any evaluations/assessments.
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Weather Impact2014Angola, Bangladesh, Burundi, Democratic Republic of the Congo, Ethiopia, Ghana, Kenya, Myanmar, South Africa, Spain, Netherlands, ZimbabwePrivate- Mission to deliver weather and climate services to optimize global food productivity and support climate adaptation
- Services offered: Weather and climate services (various weather forecasts, e.g. seasonal forecasts, start of rain season, extreme weather alerts), climate adaptation services (consultancy for e.g. agriculture, energy, finance and insurance), mobile app for farmers
- Have their own weather models (forecast global weather at 9km resolution based on ECMWF model)		AgricultureHave not been able to find out budget/funding. Given its focus and scope, we expect it to be very roughly ~2x Ignitia's budget.
=> (estimated) $2 million per year		- Weather Impact's dclaimed quality of forecasts (Website):
- High spatial resolution (9 km)
- Precipitation probability 80% accurate for 1 week ahead
- Available in every local language
- Based on best quality weather models, state of the art satelline data, WMO validated ground sations and crowd sourced rain observations
- Claim that according to farmer evaluations, 100% of farmers evaluate their rainfall forecast as usefl; 96% of farmers evaluate their forecast as very accurate or close to accurate
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SWIFT (Science for Weather Information and Forecasting Techniques)2017 (ran until March 2022)Senegal, Ghana, Niger, Nigeria, KenyaPublic- Built capacity within African forecasting agencies and improved communication links to forecast users
- Improved tropical forecasting ability on hourly and seasonal timescales
- Assisted African partners to develop capacity for sustained training of weather forecasters
- Translated results to the wider developing world
- Benefitted African populations, public and private sector organisations
- Create FASTA nowcasting weather app for West Aftica		Various sectors (aviation, agriculture, energy, water, emergency response)~$11 million (£9 million) in total
=> $2.2 million per year		- Have not found any evaluations/assessments.
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GBON (Global Basic Observing Network)2019All WMO member countriesPublic- International agreement between WMC and its 193 member countries to set out an obligation for all WMO members to acquire and exchange essential surface-based observational data at a minimum level of spatial resolution and time interval
- Based on the principle of global free and unrestricted data-sharing and collaboration among nations for a critical global public good		No specific sectorUnclearUnclear
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SOFF (Systematic Observations Financing Facility) by WMOExpected to begin operations in June 2022Aims to support 68 small island development states and least developed countries in initial 5-year implementation periodPublic- UN multi-partner trust fund
- Goal is to provide financial and technical assistance to LDCs and SIDS with the goal of meeting the GBON standards of observational data sharing on a sustainable basis
- In first 5 years, plan to establish or rehabilitate up to 400 data-gathering stations
- Plans to achieve sustained GBON compliance, which will lead to > 10-fold increase of observational data from radiosonde observations and > 20-fold increase of data from weather stations, which will be internationally shared		No specific sector$200 million estimated total cost over first three 3 years of which roughly 60% is committed (SOFF Terms of Reference, 2021, p. 69)
=> $67 million per year		Not yet launched
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The Climate Corporation2006GlobalPrivate- Aims to help all the world’s farmers sustainably increase their productivity with digital tools
- The integrated Climate FieldView digital agriculture platform provides farmers with a comprehensive, connected suite of digital tools. Bringing together seamless field data collection, advanced agronomic modeling, and local weather monitoring into simple mobile and web software solutions		Agriculture$108.8 million total funding amount (Crunchbase)
=> $6.8 million per year		Unclear
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The Weather Company by IBM1982GlobalPrivate- Major focus seems to be on priorietary weather forecasting technology and AI, based on weather data from other providers
- Example technology: IBM GRAF (a high-precision, rapidly updating global weather model that uses high resolution weather data, IBM GRAF weather model updates hourly and at a 3km resolution to provide a clearer picture of weather activity around the globe)
- Also deploys some weather observing stations, e.g. in South America and Africa (source)
- Operates weather.com		No specific sectorTotal funding/budget unclear. In 2015, IBM bought the Weather Company for $2 billion (source).
=> $61 million per year		- According to an independent evaluation by ForecastWatch (2017-2020), some findings on the weather company:
- The Weather Company is the overall most accurate forecast provider globally.
- The Weather Company was 3.5x more likely to be the most accurate of any other provider studied.i
- This gap between The Weather Company and other weather providers studied has increased every year of the study.iii
- The Weather Company is the most accurate provider most often in each region compared, including the U.S., Canada, Central America, South America, Europe, Africa, Middle East and Asia-Pacific.
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CONFER2020-202411 countries in East AfricaPublic- Multi-national collaboration/research project to bolster resilience to climate impacts and reduce disaster risks in East Africa
- Main goal: to co-develop dedicated climate services for the water, energy and food security sectors, to enhance their ability to plan for and adapt to seasonal climate fluctuations
- Second goal: improve on the accracy and local detail of numerical prediction model outputs for East Africa, with a particular focus on seasonal prediction
- Third goal: develop statistical and machine learning tools to obtain a new level of seasonal forecast skill		Disaster warning, water, energy, and food security sectors$7 million total cost (European Commission)
=> $1.8 million per year		Unclear
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