Early Development Activities For The Integrated Hazard Information Services

Abstract

One component of the National Weather Service's (NWS) AWIPS II extended effort is the Integrated Hazard Information Services (IHIS) project. The primary goal of IHIS is to integrate into a single program three applications that currently generate hazardous weather watches, warnings, and advisories: 1) WarnGen, used to create short-fused severe weather warnings; 2) the Graphical Hazards Generator (GHG), used to generate long-fused hazardous weather warnings; and 3) RiverPro, used for creating longer-term river flood warnings. In October 2009, the Global Systems Division (GSD) of the Earth System Research Lab (ESRL) hosted a workshop attended by a wide variety of stakeholders, all of who make decisions based on hazardous weather information. Workshop participants widely agreed that we not only need more modern ways to generate and express hazardous weather information, but also that the NWS forecasters who generate this information could benefit greatly from weather impact information gathered by emergency managers, weather enterprise partners, and the general public. This concept suggests that the current paradigm of a more or less one-way flow where forecasters issue products should evolve into two-way collaboration where forecasters deliver hazardous weather forecast information and consumers upload hazardous weather impact information to assist forecasters and partners in a larger decision-support process. Our talk will discuss both components of the IHIS system: one used by forecasters embedded in the Common AWIPS Visualization Environment (CAVE), and a web-based system targeted for partners (such as emergency managers, broadcasters, and the public), and how both components will, to the extent possible, implement the same look and feel. A common database will ensure that everyone involved in the weather enterprise will view the same information. An application interface will allow users to process, display, and integrate information tailored to their specific needs. Social scientists will support and enhance the communication process between forecasters, partners, and the general public. While legacy products will be retained, we will describe new ways of communicating forecast information such as categorical, probabilistic, and best/worst case scenarios.