2016年-世界发展银行全球_Strengthening_National_Hydrometeorological_Services_through_Cascading_Forecasting___Investing_for_Sustainability_and_Impact_across_Global_Regional_and_National_Centers_33页_842kb

Summary of "Strengthening National Hydrometeorological Services through Cascading Forecasting"

Core Content

This paper explores the potential for improving hydrometeorological services in low-income countries (LICs) through the use of cascading forecasting systems. It argues that investing in these systems can lead to significant socioeconomic benefits, and that global numerical weather prediction (NWP) should be treated as a global public good.

Main Viewpoints

• Importance of Hydrometeorological Services: Weather and climate-related disasters are increasing in frequency and impact due to human development, environmental degradation, and climate change. These events cause loss of life, livelihoods, and economic damage, with the poorest countries bearing the brunt of the consequences.

• Cascading Forecasting System: Modern forecasting relies on a cascading approach where global NWP models provide initial and boundary conditions for regional and national models. National forecasters then use this data along with local observations to produce tailored forecasts and early warnings for local users.

• Current Limitations: While the cascading approach is effective, it depends on the voluntary sharing of data and products by global producing centers (GPCs), which is not sustainable. Many GPCs lack a dedicated mandate or budget for providing services to LICs.

• Economic Viability: Providing GPCs' full suite of services to LICs is economically viable, with estimated global socioeconomic benefits of US$200 million to US$500 million per year, far outweighing the costs.

• Need for Sustainable Financing: To ensure long-term sustainability, the paper advocates for the use of mechanisms such as the Green Climate Fund to finance GPCs in delivering global public services to LICs. It also highlights the ethical imperative for high-income countries to support this global public good.

• Regional and National Investment: While GPCs play a key role in the cascading system, significant investment is needed at the regional and national levels to improve forecasting, early warning, and risk management capacities. This includes building local capacity to interpret and utilize global data.

Key Information

• Socioeconomic Benefits: Improved NMHS capacities in all low- and middle-income countries could annually save up to 23,000 lives and prevent US$2 billion in financial losses due to disasters.

• Global Public Good: Global NWP is recognized as a global public good due to its utilitarian value and the ethical responsibility of high-income countries to ensure access for LICs.

• Cascading Forecasting Example: The paper uses the German Meteorological Service as an example, showing how global models feed into regional and national models to create a cascading system.

• SWFDP Projects: The Severe Weather Forecasting Demonstration Project (SWFDP) is highlighted as a successful example of how GPCs can support LICs through a cascading approach, improving severe weather forecasting, alerts, and service delivery.

• Value Chain: The value chain of hydrometeorological services includes observation, modeling, forecasting, and delivery. Communication and interpretation play a vital role in ensuring that these services lead to beneficial outcomes.

• Decision Types: The paper categorizes decisions into strategic, tactical, and operational, each with different timeframes and impacts on outcomes.

• Data Collection Method: The research involved semi-structured interviews with six GPCs and one RSMC between May and November 2015. These interviews provided insights into the costs and current financing models for delivering services to LICs.

Table of Interviewed GPCs and RSMC

Conclusion

The paper concludes that while the cascading forecasting system offers a promising way to improve hydrometeorological services in LICs, it requires sustained investment and the development of appropriate financing mechanisms. It also emphasizes the importance of building local capacity to interpret and use global data effectively, ensuring that the full potential of improved forecasting is realized.