WMO Technical Advisory under AIM for Scale

Project background

Climate change is increasingly affecting agriculture across the globe, especially in low- and middle-income countries (LMICs), where smallholder farmers face growing uncertainty from erratic rainfall, rising temperatures, and extreme weather events. These challenges threaten food security, livelihoods, and national economies.

To address these pressing issues, the Agriculture Innovation Mechanism for Scale (AIM for Scale) was launched as a bold initiative to bring evidence-based agricultural innovations to scale—starting with weather services.

WMO is involved in the AIM for Scale Programme Weather Package as a technical advisory partner supported by a grant from the International Affairs Office at the Presidential Court of the UAE. The initiative aims to scale climate services for farmers in countries across Africa, Asia, and South America. Current engagement includes Bangladesh, Chile, Ethiopia, Kenya, and Nigeria, with expansion to 30 countries planned by 2027.

WMO supports the initiative through technical advisory on the following aspects: Country engagement through NMHSs and WMO Regional Training Centres, coordination to align the programme with WMO priorities and initiatives., the application of climate services in the agriculture sector through innovative co-production processes, enhanced capacity building and trainings for NMHSs and extension actors ; guiding in development of AI-focused weather and agrometeorology training with partners like the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), University of Chicago and WMO Members and regional centres.

As WMO Secretary-General Professor Celeste Saulo stated during COP29, " More and better data leads to better weather forecasts, early warning systems and climate information services for agriculture and other vital economic sectors. Closing basic data gaps will also help inform AI models.” Professor Saulo added that “the agriculture sector is undoubtedly one of the most vulnerable sectors to climate variability and change. Additional partnerships are needed to ensure that farmers are involved in the coproduction of weather and climate services which will enhance resilience and adaptation in the
agriculture sector.” 

Objective(s)

AIM for Scale Weather Package seeks to expand cost-effective innovations that improve the livelihoods of small-scale farmers in LMICs by enhancing access to high-quality weather and agrometeorological information.

Outputs

Provide technical assistance for:

Country engagement and coordination with WMO Regional Training Centres
Technical advisory during curriculum and training development
Alignment with WMO standards, priorities, and initiatives. Related operational outputs: SO 1.2.06; SO 2.1.02

Expected outcomes

Strengthened national capacities in target countries to provide enhanced end-to-end agrometeorological warning products and services.
Increased visibility and sustainability of NMHSs in developing countries through demonstrated value of agromet early warning systems and services.
Improved preparedness and response to agricultural climate hazards.

Achievements

Convening Meeting: The AIM for Scale Secretariat held its first Convening Meeting for 2025 from 29 May to 31 May 2025, in Nairobi, Kenya. The meeting, hosted in collaboration with the Gates Foundation, brought together representatives from National Meteorological and Hydrological Services (NMHSs), Ministries of Agriculture (MoAs), multilateral development banks, international and regional organizations, research institutions, and other stakeholders to align on the next phase of work under the AIM for Scale Weather Package.

The WMO delivered a clear message: it is committed to providing technical advisory support for capacity-development projects at national, regional, and global levels. The WMO highlighted the importance of assessing and strengthening observational capacities—including network density, measured variables, use of satellite products, and improved data collection and sharing. The discussions emphasized local capacity building (training, Regional Training Centres, etc.), benchmarking, standardization, and improved information management to support decision-making and enhance information dissemination.

Training: The AI for Weather Training Program brought together experts to share perspectives on advances in weather forecasting and the role of AI alongside traditional numerical weather prediction. In a collaborative effort, the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and the NCM WMO Regional Training Centre hosted the training at their facilities for colleagues from the NMHSs and Ministries of Agriculture of Bangladesh, Chile, Ethiopia, Kenya, the UAE, and Nigeria.

The training program was developed by MBZUAI, the AI for Climate Initiative, and the Human-Centered Weather Forecast Initiative at the University of Chicago. It was supported by AIM for Scale and funded through a grant from the International Affairs Office at the Presidential Court of the UAE. WMO and ECMWF provided recommendations during curriculum development. Additionally, WMO delivered two presentations: one on impact-based forecasting in agrometeorology, and another on the Concept of Operations (CONOPS), emphasizing the importance of data sharing and the co-development of agrometeorological advisories for farmers.

Agrometeorological Capacity Assessment: WMO is currently discussing with AIM for Scale partners the provision of guidance on how to conduct assessments of end-to-end agrometeorological services in member countries.

COP30: WMO and AIM for Scale organized a side event at COP30, 19 th November 2025 titled “Scaling Innovative Approaches to Climate Services for Agriculture.” The session explored how WMO, AIM for Scale, and partners are working to enhance the application of climate services in the agriculture sector through innovative co-production processes, enhanced capacity building for NMHSs and extension actors, and the integration of advanced technologies such as artificial intelligence (AI) and machine learning (ML).

Speakers included representatives from AIM for Scale, WMO, ADB, ACMAD, the Gates Foundation, and the Inter-American Development Bank.