Handbook of Hydrometeorological Ensemble Forecasting

Sharing from the Editor-in-Chief

Since the book was published online on Springer Nature Link in January 2019, it has received widespread attention from the academic community and has been read and downloaded up to 53,000 times. The book was awarded the ASLI (The Atmospheric Science Librarians International) Selection Award at the annual meeting of the American Meteorological Society in January 2020, an annual global event for meteorologists. The book is the most authoritative and comprehensive introduction to the achievements and progress in the field of hydrometeorological ensemble forecasting. It has been unanimously selected by the committee of "Springer Nature: China's New Development Award" as one of the 2020 award-winning books, highlighting the extensive recognition of the book's contribution to SDGs.

Springer: 
As a founding member of the International Hydrological Ensemble Prediction Experiment (HEPEX) and Chairman of the Asian region, could you please tell our readers about the significance of hydrological ensemble prediction research and the impact it can have on the lives of the general public?


Duan: 
Hydrometeorological forecasts are statements on the future space-time variation of hydro-meteorological variables such as precipitation, air temperature, soil moisture, runoff, and water surface area of rivers. Hydrometeorological forecasts are closely related to our daily life and socio-economic activities. Its accuracy and reliability can help us significantly reduce the damage caused by water- and weather-related natural disasters, as well as to optimize water resource management, which is particularly important for the planning and design of public utilities and the operation and planning of industrial and agricultural production.

Since the hydrometeorological system is a complex and chaotic system, hydrometeorological forecasts are inevitably uncertain. Traditional deterministic, single-valued forecasts are inadequate to meet many needs of emergency and water resources managers while emerging ensemble forecasting approach is the way forward. The key advantage of ensemble forecasts over deterministic forecasts is that deterministic forecasts only predict one likely scenario of an impending event, but ensemble forecasts also give associated uncertainty information that is critical for making risk-based decisions. With ensemble forecasts, one can determine the probability distribution of forecasted event and associated socio-economic effect (e.g., economic losses or benefits) so that the decision maker can make the optimal risk decision. Hydrometeorological ensemble forecasts are generated by processing uncertainties from different sources. With the continuous advancement of hydrometeorological models, observational systems and data assimilation methods, statistical analysis methods, as well as computational technology, ensemble forecasting approaches have been incorporated into operational hydrometeorological forecasting systems in many countries around the world. These methods are widely used in emergency management and for optimal water allocation, bringing many substantial socio-economic benefits to the society.


Springer: 
We learned that China Meteorological Administration (CMA) and Hohai University have recently opened the "CMA-Hohai University Joint Laboratory for Hydrometeorology", could you introduce the research frontier and the latest development of the laboratory?


Duan: 
As mentioned above, the hydrometeorological ensemble forecasting method has become the standard for operational centers in Europe and North America, and our national meteorological agencies have already adopted the ensemble forecasting approach for medium- and long-term meteorological forecasts. However, the operational hydrological forecasting centers still rely on the traditional deterministic prediction method. Recently Hohai University and China Meteorological Administration (CMA) have established the Joint Research Laboratory for Hydrometeorology with a key aim to jointly develop new hydrometeorological ensemble forecasting methods. The new joint lab adheres to China’s national policy on science and technology development, addresses national strategic needs, establishes mechanisms conducive to joint efforts for scientific and technological innovation, increases innovation capacity in key scientific and technological research fields of hydrology and meteorology through open cooperation, promotes effective transfer of science and technology into operational practice, and nurtures next-generation scientists and cultivates outstanding young talents. By embracing the urgent scientific needs of the country and the industry, the joint laboratory will focus on four key areas: hydrometeorological disaster monitoring; forecasting and warning; ecological and environmental impact assessment; and hydroclimatic impact assessment and water resource management. Among which, the disaster early warning and forecasting includes the joint development of hydrometerological ensemble prediction methods, construction of a cloud-based application platform for global-scale hydrometeorological forecasting, decision support system for emergency management and optimization of water resources. Although ensemble methods are still at the relatively early development stage globally, I believe the establishment of the Joint Laboratory will give us the opportunity to speed up China’s development in hydrometerological ensemble forecasting capability and catch up with our European and American peers in this area.
 


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CNPF-HSS-SDG20-Author-Image © Springer Nature

Qingyun Duan (EIC)

National Chair Professor and Chief Scientist of Faculty of Geographical Science at Beijing Normal University

CNPF-HSS-SDG20-Author-Image © Springer Nature

Florian Pappenberger (Co-EIC)

Director of Forecasts at the European Centre For Medium-Range Weather Forecasts

CNPF-HSS-SDG20-Author-Image © Springer Nature

Andy Wood

Development and Operations Hydrologist for the U.S. National Weather Service, the Chair of the Hydrology Committee of the American Meteorological Society (AMS), an associate editor of the AMS Journal of Hydrometeorology, and a co-leader of the Hydrologic Ensemble Prediction Experiment (HEPEX)

CNPF-HSS-SDG20-Author-Image © Springer Nature

Hannah L. Cloke  (Co-EIC)

Hydrologist and physical geographer specializing in land surface modeling, flood forecasting, applications of Numerical Weather Predictions and catchment hydrology

CNPF-HSS-SDG20-Author-Image © Springer Nature

John Schaake  (Co-EIC)

Formerly Chief Scientist with Office of Hydrologic Development, NOAA National Weather Service

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