Low-income countries' hydrometeorological services often face considerable constraints in delivering the information needed to effectively drive early warning and climate adaptation, which, if improved, could generate socioeconomic benefits of about USD1.4 billion per year. Modern weather forecasting adopts a cascading approach where numerical products eveloped by global producing centers feed regional and national models, with national forecasters assimilating these and other data to produce information customized for local users. The system depends on global producing centers sharing their products, often through voluntary action without dedicated financing, which is not sustainable and oes not fully leverage the capacity of global producing centers to provide tailored information. It would be economically viable for global producing centers to provide their full suite of services to low-income countries, producing likely global socioeconomic benefits of USD200 million to USD500 million per year, outweighing the costs by about 80 to one. Existing global producing centers' capacities and their potential benefits for low-income countries fulfill the utilitarian principal. Global numerical weather prediction should therefore be treated as a global public good. However, although recent global evelopment and climate agreements clearly suggest that improving forecasting in low-income countries should be a target of international cooperation, official development assistance financing of high-income country global producing centers to provide products to low-income countries would be considered tied aid. Specialized mechanisms, such as the Green Climate Fund, could provide legitimate means to finance global producing centers to provide global public services in support of low-income countries. However, to realize the potential benefits, significant investment is needed in regional and national forecasting, early warning, and preparedness capacities.