3A.2 Training Forecasters in Riverine and Flash Flooding Forecast, Analysis, Warning and Decision Support Using AWIPS-2

Monday, 23 January 2017: 4:15 PM
604 (Washington State Convention Center )
Jill D. Hardy, CIMMS/Univ. of Oklahoma and NWS/OCLO/WDTD, Norman, OK; and A. C. Wood, D. A. Morris, G. M. Schoor, J. G. Gibbs, M. A. Magsig, A. B. Zwink, T. Pham, and E. P. Jacobsen

As a response to several recommendations in recent service assessments by the National Weather Service (NWS), staff at the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at the University of Oklahoma in conjunction with the Warning Decision Training Division (WDTD) developed the ability to use archived hydrological data in training simulations for NWS forecasters.  These simulations use the WES-2 Bridge (Weather Event Simulator for AWIPS-2) that provides archived data playback capabilities in AWIPS-2.

Between the fall of 2015 and the summer of 2016, WDTD released two training simulations to NWS forecast offices and river forecast centers.  The simulations focus on two different parts of a significant flash flooding event that transitioned into riverine floods.  The flash flood simulation is also part of an ongoing hydrometeorological training course (“Warning Operations Course – Flash Flood”) and focuses on the forecast and warning process of the flash flood event, including using conceptual models and ingredients-based methodologies in the forecast process and using the Flash Flood Monitoring and Prediction (FFMP) application of AWIPS for the warning process.  The riverine simulation focuses on using basic hydrological tools in AWIPS to analyze observed precipitation estimates and on using observed and forecast hydrographs in the decision-making process of generating river flood warnings.  The ability to use hydrographs in AWIPS-2 in a displaced real-time training simulation is a new capability developed in WES-2 Bridge by CIMMS.

This paper describes the training course and the accompanying training simulations and technology.  The current state and future evolution of both the training material and simulation capability are discussed.

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