5 - Probabilistic hydrometeorological forecasting

Summary

ABSTRACT

The U.S. National Weather Service has supported the development of an integrated probabilistic hydrometeorological forecasting system. The system produces probabilistic quantitative precipitation forecasts that are used to produce probabilistic river stage forecasts; these in turn are input to optimal decision procedures for issuing flood warnings, operating waterways and barges, or controlling storage reservoirs. The system is designed based on Bayesian principles of probabilistic forecasting and rational decision making. This chapter outlines the system concept.

INTRODUCTION

Systems approach to hydrometeorological forecasting

That forecasts should be stated in probabilistic rather than categorical terms has been argued from operational (Cooke 1906) and decision-theoretic (Murphy 1991) perspectives for almost a century. Yet most operational systems produce deterministic forecasts and most research in physical and statistical sciences has been devoted to finding the “best” estimates rather than probability distributions of predictands. Undoubtedly, the leap from a deterministic frame of thought to one that not only admits our limited knowledge and information, but also quantifies uncertainty about future states of the environment, requires a vast and coordinated effort at two levels: engineering – to design probabilistic forecasting systems, and organizational – to alter the institutional mindset and modus operandi.

The U.S. National Weather Service (NWS) has embarked on making such a quantum change (Zevin 1994; Krzysztofowicz 1998). The goal is to increase the value of service to users by developing and implementing an integrated probabilistic hydrometeorological forecasting system.