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Clark A.J.,National Oceanic and Atmospheric Administration | Weiss S.J.,National Oceanic and Atmospheric Administration | Kain J.S.,National Oceanic and Atmospheric Administration | Jirak I.L.,National Oceanic and Atmospheric Administration | And 21 more authors.
Bulletin of the American Meteorological Society | Year: 2012

The NOAA Hazardous Weather Testbed (HWT) conducts annual spring forecasting experiments organized by the Storm Prediction Center and National Severe Storms Laboratory to test and evaluate emerging scientific concepts and technologies for improved analysis and prediction of hazardous mesoscale weather. A primary goal is to accelerate the transfer of promising new scientific concepts and tools from research to operations through the use of intensive real-time experimental forecasting and evaluation activities conducted during the spring and early summer convective storm period. The 2010 NOAA/HWT Spring Forecasting Experiment (SE2010), conducted 17 May through 18 June, had a broad focus, with emphases on heavy rainfall and aviation weather, through collaboration with the Hydrometeorological Prediction Center (HPC) and the Aviation Weather Center (AWC), respectively. In addition, using the computing resources of the National Institute for Computational Sciences at the University of Tennessee, the Center for Analysis and Prediction of Storms at the University of Oklahoma provided unprecedented real-time conterminous United States (CONUS) forecasts from a multimodel Storm-Scale Ensemble Forecast (SSEF) system with 4-km grid spacing and 26 members and from a 1-km grid spacing configuration of the Weather Research and Forecasting model. Several other organizations provided additional experimental high-resolution model output. This article summarizes the activities, insights, and preliminary findings from SE2010, emphasizing the use of the SSEF system and the successful collaboration with the HPC and AWC. © 2012 American meteorological society. Source


Tollerud E.I.,National Oceanic and Atmospheric Administration | Etherton B.,National Oceanic and Atmospheric Administration | Toth Z.,National Oceanic and Atmospheric Administration | Jankov I.,Developmental Testbed Center | And 11 more authors.
Bulletin of the American Meteorological Society | Year: 2013

The Developmental Testbed Center (DTC) has established the DTC Ensemble Task (DET) as a new testbed platform. The DET is intended to serve as a bridge between research and operations. The goal of the DET is to provide an environment in which extensive testing and evaluation of ensemble-related techniques can be conducted such that the results are immediately relevant to the operational centers. One guiding assumption of the DET is that it can function best as an independent evaluator of ensemble forecasting systems and their elements as a joint venture. The DET is a joint venture primarily between the National Center for Atmospheric Research (NCAR) and the Earth Systems Research Laboratory (ESRL), and is well positioned to serve the established function. Another associated assumption is that forecast centers with or without research branches will lack the resources to compare several competing modeling components originating in the research community in the face of operational demands. Source


News Article
Site: http://www.nrl.navy.mil/media/news-releases/

Dr. Justin McLay, research meteorologist at the U.S. Naval Research Laboratory (NRL) Marine Meteorology Division, receives the esteemed Laboratory Scientist of the Quarter award honoring extraordinary service to the Department of Defense (DoD). McLay is bestowed the award for his distinguished accomplishments in leading the 'New Rules of Predictability' project and his key role in developing and transitioning the Navy Global Environmental Model (NAVGEM) Ensemble Forecast System (EFS). "Dr. McLay's development of the 'New Rules of Predictability' has been groundbreaking," said Dr. John Montgomery, Director of Research at NRL. "His sustained effort in developing an ensemble system and using ensemble information provide a fundamental understanding of the impact weather and climate change have on Navy assets, and offer unique and valuable contributions to overall Defense Department missions and goals." McLay is a recognized subject matter expert in the design and application of atmospheric ensemble predictions. His work on the 6.1 level predictability project and 6.4 level NAVGEM EFS may significantly enhance the current and future missions of the Navy and DoD in environmental information dominance. Providing detailed knowledge of future extreme weather variability and conditions (wind speeds, wave heights, air and sea temperatures, sea ice thickness and extent, and sea level) the ensemble will enable the Navy and DoD to adapt to future environmental impacts. Beginning his career in weather science as a certified weather observer for the National Weather Service (NWS), McLay worked to obtain a doctorate in atmospheric science from the University of Wisconsin-Madison where he had received both a bachelor's and master's degree in atmospheric science in 1997 and 2001 respectively. After receiving his Ph.D. in 2004, he was granted a post-doctoral appointment within the National Research Council (NRC) for a position at NRL-Monterey in the Global Modeling Section of the Atmospheric Dynamics and Prediction Branch. In 2007, McLay started his federal career at NRL-Montery, and progressed to improve the design of the now retired Navy Operational Global Atmospheric Prediction System (NOGAPS) EFS through the implementation of locally banded ensemble transform (ET) perturbations of the initial state. In March 2015 he led the successful transition of the Navy's first operational method for stochastic forcing of the NAVGEM global model (SKEB-mc), which improves the measurement of forecast uncertainty. McLay has authored or co-authored 17 journal publications and has led nine successful technical transitions for the Navy's NAVGEM global EPS. In April 2015 he received the Alan Berman Annual Research Publication Award for a study of statistical inference applied to model parameter uncertainty. He is currently Associate Editor for the Monthly Weather Review journal and a member of the American Meteorological Society (AMS) Weather Analysis and Forecasting Committee. McLay has presented his research at numerous conferences and workshops, including as an invited speaker on the topic of forecast time series behavior at the Developmental Testbed Center (DTC), National Center for Atmospheric Research (NCAR). About the U.S. Naval Research Laboratory The U.S. Naval Research Laboratory provides the advanced scientific capabilities required to bolster our country's position of global naval leadership. The Laboratory, with a total complement of approximately 2,500 personnel, is located in southwest Washington, D.C., with other major sites at the Stennis Space Center, Miss., and Monterey, Calif. NRL has served the Navy and the nation for over 90 years and continues to advance research further than you can imagine. For more information, visit the NRL website or join the conversation on Twitter, Facebook, and YouTube.


Clark A.J.,University of Oklahoma | Bullock R.G.,Developmental Testbed Center | Jensen T.L.,Developmental Testbed Center | Xue M.,University of Oklahoma | Kong F.,University of Oklahoma
Weather and Forecasting | Year: 2014

Meaningful verification and evaluation of convection-allowing models requires approaches that do not rely on point-to-point matches of forecast and observed fields. In this study, one such approach-a beta version of the Method for Object-Based Diagnostic Evaluation (MODE) that incorporates the time dimension [known asMODEtime-domain (MODE-TD)]-was applied to 30-h precipitation forecasts from four 4-km grid-spacing members of the 2010 Storm-Scale Ensemble Forecast system with different microphysics parameterizations. Including time in MODE-TD provides information on rainfall system evolution like lifetime, timing of initiation and dissipation, and translation. The simulations depicted the spatial distribution of time-domain precipitation objects across the United States quite well. However, all simulations overpredicted the number of objects, with the Thompson microphysics scheme overpredicting the most and theMorrison method the least. For the smallest smoothing radius and rainfall threshold used to define objects [8 km and 0.10 in. (1 in. 5 2.54 cm), respectively], the most common object duration was 3 h in both models and observations. With an increased smoothing radius and rainfall threshold, the most common duration became shorter. The simulations depicted the diurnal cycle of object frequencies well, but overpredicted object frequencies uniformly across all forecast hours. The simulations had spurious maxima in initiating objects at the beginning of the forecast and a corresponding spurious maximum in dissipating objects slightly later. Examining average object velocities, a slow bias was found in the simulations, which was most pronounced in the Thompson member. These findings should aid users and developers of convection-allowing models and motivate future work utilizing time-domain methods for verifying high-resolution forecasts. © 2014 American Meteorological Society. Source

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