The Global Data-Processing and Forecasting System (GDPFS) is an international mechanism that coordinates Member capacities to prepare and make meteorological analyses and forecast products available to all Members. It enables delivery of harmonized services and is currently organized as a network of Global, Regional and National Centres. The first table below shows the GDPFS Centres generating nowcasting and weather forecasting products for up to 30 days. The second table shows those providing long-range and climate forecasting - over 30 days. (Click to enlarge tables.)
Numerical Weather Prediction
The advances in Numerical Weather Prediction (NWP) in the last decades have been tremendous thanks to more, and better assimilated, observations, higher computing power and progress in our understanding of dynamics and physics. These advances, which have led to increasingly skilful weather forecasting, will become even more relevant in the future. Consequently, the emphasis in operational meteorology, hydrology, oceanography and climatology has shifted towards the implementation of increasingly sophisticated and diverse numerical models and applications in order to serve an ever-increasing variety of users. Operational NWP systems generally provide an accurate indication of developing weather events from hours to days ahead. They are, therefore, one of the most relevant components of routine and severe weather forecasting and warnings at National Meteorological and Hydrological Services. However, the weather forecasting capability among these National Services in varies enormously: the more advanced are making use of the progress in NWP, but those in the developing and least developed countries have seen little advancement due to limited budgets and reduced capabilities. And the gap is increasing.
Owing to the high computational cost of global and limited-area NWP models, including Ensemble Prediction Systems using multiple model runs, few Members have the operational capacity to implement such systems. Many of the latest advances in NWP systems, such as so-called “convection-permitting” models that are particularly suitable for severe weather forecasting in tropical and sub-tropical regions are extremely computationally intensive, thus they are supported only by the leading Meteorological Services. The Severe Weather Forecasting Demonstration Project (SWFDP) of the Global Data-Processing and Forecasting System makes products from NWP models, including Ensemble Prediction Systems, of the most advanced Members available to all using a Cascading Forecasting Process.
The cascading forecasting process
The GDPFS encompasses all systems operated by Members (including those jointly coordinated with other international organizations such as ICAO) and enables them to make use of the advances in NWP by providing a framework for sharing data related to operational meteorology, hydrology, oceanography and climatology. The main support for the exchange and delivery of these data is the WMO Information System (WIS). One of the key benefits of the WIS is the expansion of the range of centres that can connect to the system, increasing the range of Global Data-Processing and Forecasting System applications.
The SWFDP contributes to capacity building by helping developing countries to access and make use of existing NWP products for improving hazardous weather warnings. It encourages operational forecasters to use relevant standards and newly developed products and procedures. The Project outcomes:
- Enhanced capability for National Meteorological and Hydrological Services to forecast severe weather and issue warnings at the national level, including improved accuracy and longer lead-times;
- Establishment of processes for multi-hazard early warnings with national disaster management and civil protection authorities, with planned responses for protection of lives and property;
- Established forecast processes and Quality Management Systems (QMS), and strengthened forecast capabilities in support of other socio-economic (such as agriculture and food security, aviation, marine safety and transportation, etc.) at the national level;
- Raised awareness of the value of National Meteorological and Hydrological Services with national governments and their agencies, leading in the longterm to greater national support and investment…leading, in turn, to improved supply of observations and feedback into the Global Data-Processing and Forecasting System ; and
- Reduced loss of life and damage to property and contributions to the 2030 Development Agenda and the Sendai Framework for Disaster Risk Reduction.
Future Integrated, Seamless Global Data Processing and Forecasting System Collaborative Framework
A way forward for vision for a future Seamless Global Data-processing and Forecasting System (S/GDPFS) was approved by the World Meteorological Congress. Building on the existing architecture, the future S/GDPFS will become a flexible and adaptable ecosystem of independent centres that will expand and strengthen prediction of the environment, making impact-based forecasts and risk-based warnings accessible, thus enabling Members and partners to make better-informed decisions. The S/GDPFS will provide standardized state-of-the-art interfaces to facilitate partnerships and collaboration globally and regionally among jurisdictions, academia and the private sector to access and make available related information of relevance to the mandate of WMO across all timescales and domains of the Earth system. The S/GDPFS will, as much as possible, share authoritative weather, water, climate and related environmental data, products and services freely and openly and in a viable and sustainable way, ensuring no Members are left behind. As stated in the draft WMO strategic plan for 2020-2023 (Strategic Objective 2.3), the fundamental responsibility of GDPFS will be to enable access to, and use of, the state-of-the-art numerical analysis and prediction products at all temporal and spatial scales. It is a high priority that the Seamless GDPFS will assist Developing and Least Developed Countries to make significant progress towards community resilience and reaching Sustainable Development Goals.
A GDPFS evolution will allow the generation of products and delivery of services in environmental areas beyond the original paradigm of weather delivery system. It will take advantage of technological and social developments in order to increase its usefulness and maintain its relevance to Members by taking a verifiable Earth system approach. Most important, it will provide critical data to Developing and Least Developed Countries. Building on the existing architecture of the GDPFS, a future S/GDPFS will become an ecosystem of independent numerical predictive systems that will further strengthen the ability to predict changes to the state of the environment. It will facilitate the sharing of this predictive environmental data and re-usable content for the benefit of all our Members; so no Member is left behind.
Members will be better able to harness the increasing power and scope of environmental prediction infrastructure in order that enhanced information is available to make quicker and better decisions; improved access to information and data by NMHS saves time and resources, allowing them to add more value to their services; Members have the tools and skills to handle the growing and complex data and information; NMHSs have more time to apply skills and expertise through further automation of routine tasks; new observations, new science and new technologies are pulled through into operational services; and by 2025, in line with WIS 2.0 implementation plan milestones, the further development of S/GDPFS will result in substantial benefits for developing NMHSs.
The Future S/GDPFS will also bring benefits to broader user communities, including stakeholders responsible for preparedness for a wider variety of high-impact events; sectors impacted by weather and climate (e.g. energy, agriculture, health, integrated water resource management); and urban stakeholders, city planners, United Nations and other humanitarian agencies, including nongovernmental organizations.