contributor author | Gallo, Burkely T.;Clark, Adam J.;Jirak, Israel;Kain, John S.;Weiss, Steven J.;Coniglio, Michael;Knopfmeier, Kent;Correia, James;Melick, Christopher J.;Karstens, Christopher D.;Iyer, Eswar;Dean, Andrew R.;Xue, Ming;Kong, Fanyou;Jung, Youngsun;Shen, Feifei;Thomas, Kevin W.;Brewster, Keith;Stratman, Derek;Carbin, Gregory W.;Line, William;Adams-Selin, Rebecca;Willington, Steve | |
date accessioned | 2018-01-03T11:03:14Z | |
date available | 2018-01-03T11:03:14Z | |
date copyright | 6/22/2017 12:00:00 AM | |
date issued | 2017 | |
identifier other | waf-d-16-0178.1.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4246625 | |
description abstract | AbstractLed by NOAA?s Storm Prediction Center and National Severe Storms Laboratory, annual spring forecasting experiments (SFEs) in the Hazardous Weather Testbed test and evaluate cutting-edge technologies and concepts for improving severe weather prediction through intensive real-time forecasting and evaluation activities. Experimental forecast guidance is provided through collaborations with several U.S. government and academic institutions, as well as the Met Office. The purpose of this article is to summarize activities, insights, and preliminary findings from recent SFEs, emphasizing SFE 2015. Several innovative aspects of recent experiments are discussed, including the 1) use of convection-allowing model (CAM) ensembles with advanced ensemble data assimilation, 2) generation of severe weather outlooks valid at time periods shorter than those issued operationally (e.g., 1?4 h), 3) use of CAMs to issue outlooks beyond the day 1 period, 4) increased interaction through software allowing participants to create individual severe weather outlooks, and 5) tests of newly developed storm-attribute-based diagnostics for predicting tornadoes and hail size. Additionally, plans for future experiments will be discussed, including the creation of a Community Leveraged Unified Ensemble (CLUE) system, which will test various strategies for CAM ensemble design using carefully designed sets of ensemble members contributed by different agencies to drive evidence-based decision-making for near-future operational systems. | |
publisher | American Meteorological Society | |
title | Breaking New Ground in Severe Weather Prediction: The 2015 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment | |
type | Journal Paper | |
journal volume | 32 | |
journal issue | 4 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/WAF-D-16-0178.1 | |
journal fristpage | 1541 | |
journal lastpage | 1568 | |
tree | Weather and Forecasting:;2017:;volume( 032 ):;issue: 004 | |
contenttype | Fulltext | |