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- Author or Editor: Craig S. Schwartz x
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Abstract
Beginning 7 April 2015, scientists at the U.S. National Center for Atmospheric Research (NCAR) began producing daily, real-time, experimental, 10-member ensemble forecasts with 3-km horizontal grid spacing across the entire conterminous United States. Graphical forecast products were posted in real time to the Internet, where they attracted a large following from both forecasters and researchers across government, academia, and the private sector. Although these forecasts were initially planned to terminate after one year, the project was extended through 30 December 2017 because of the enthusiastic community response. This article details the motivation for the NCAR ensemble project and describes the project’s impacts throughout the meteorological community. Classroom and operational use of the NCAR ensemble are discussed in addition to the diverse application of NCAR ensemble output for research purposes. Furthermore, some performance statistics are provided, and the NCAR ensemble website and data visualization approach are described. We hope the NCAR ensemble’s success will motivate additional experimental forecast demonstrations that transcend current operational capabilities, as forward-looking forecast systems are needed to accelerate operational development and provide students, young scientists, and forecasters with glimpses of what future modeling systems may look like. Additionally, the NCAR ensemble dataset is publicly available and can be used for meaningful research endeavors concerning many meteorological topics.
Abstract
Beginning 7 April 2015, scientists at the U.S. National Center for Atmospheric Research (NCAR) began producing daily, real-time, experimental, 10-member ensemble forecasts with 3-km horizontal grid spacing across the entire conterminous United States. Graphical forecast products were posted in real time to the Internet, where they attracted a large following from both forecasters and researchers across government, academia, and the private sector. Although these forecasts were initially planned to terminate after one year, the project was extended through 30 December 2017 because of the enthusiastic community response. This article details the motivation for the NCAR ensemble project and describes the project’s impacts throughout the meteorological community. Classroom and operational use of the NCAR ensemble are discussed in addition to the diverse application of NCAR ensemble output for research purposes. Furthermore, some performance statistics are provided, and the NCAR ensemble website and data visualization approach are described. We hope the NCAR ensemble’s success will motivate additional experimental forecast demonstrations that transcend current operational capabilities, as forward-looking forecast systems are needed to accelerate operational development and provide students, young scientists, and forecasters with glimpses of what future modeling systems may look like. Additionally, the NCAR ensemble dataset is publicly available and can be used for meaningful research endeavors concerning many meteorological topics.
Abstract
The Mesoscale Predictability Experiment (MPEX) was conducted from 15 May to 15 June 2013 in the central United States. MPEX was motivated by the basic question of whether experimental, subsynoptic observations can extend convective-scale predictability and otherwise enhance skill in short-term regional numerical weather prediction.
Observational tools for MPEX included the National Science Foundation (NSF)–National Center for Atmospheric Research (NCAR) Gulfstream V aircraft (GV), which featured the Airborne Vertical Atmospheric Profiling System mini-dropsonde system and a microwave temperature-profiling (MTP) system as well as several ground-based mobile upsonde systems. Basic operations involved two missions per day: an early morning mission with the GV, well upstream of anticipated convective storms, and an afternoon and early evening mission with the mobile sounding units to sample the initiation and upscale feedbacks of the convection.
A total of 18 intensive observing periods (IOPs) were completed during the field phase, representing a wide spectrum of synoptic regimes and convective events, including several major severe weather and/or tornado outbreak days. The novel observational strategy employed during MPEX is documented herein, as is the unique role of the ensemble modeling efforts—which included an ensemble sensitivity analysis—to both guide the observational strategies and help address the potential impacts of such enhanced observations on short-term convective forecasting. Preliminary results of retrospective data assimilation experiments are discussed, as are data analyses showing upscale convective feedbacks.
Abstract
The Mesoscale Predictability Experiment (MPEX) was conducted from 15 May to 15 June 2013 in the central United States. MPEX was motivated by the basic question of whether experimental, subsynoptic observations can extend convective-scale predictability and otherwise enhance skill in short-term regional numerical weather prediction.
Observational tools for MPEX included the National Science Foundation (NSF)–National Center for Atmospheric Research (NCAR) Gulfstream V aircraft (GV), which featured the Airborne Vertical Atmospheric Profiling System mini-dropsonde system and a microwave temperature-profiling (MTP) system as well as several ground-based mobile upsonde systems. Basic operations involved two missions per day: an early morning mission with the GV, well upstream of anticipated convective storms, and an afternoon and early evening mission with the mobile sounding units to sample the initiation and upscale feedbacks of the convection.
A total of 18 intensive observing periods (IOPs) were completed during the field phase, representing a wide spectrum of synoptic regimes and convective events, including several major severe weather and/or tornado outbreak days. The novel observational strategy employed during MPEX is documented herein, as is the unique role of the ensemble modeling efforts—which included an ensemble sensitivity analysis—to both guide the observational strategies and help address the potential impacts of such enhanced observations on short-term convective forecasting. Preliminary results of retrospective data assimilation experiments are discussed, as are data analyses showing upscale convective feedbacks.
Abstract
Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.
Abstract
Since its initial release in 2000, the Weather Research and Forecasting (WRF) Model has become one of the world’s most widely used numerical weather prediction models. Designed to serve both research and operational needs, it has grown to offer a spectrum of options and capabilities for a wide range of applications. In addition, it underlies a number of tailored systems that address Earth system modeling beyond weather. While the WRF Model has a centralized support effort, it has become a truly community model, driven by the developments and contributions of an active worldwide user base. The WRF Model sees significant use for operational forecasting, and its research implementations are pushing the boundaries of finescale atmospheric simulation. Future model directions include developments in physics, exploiting emerging compute technologies, and ever-innovative applications. From its contributions to research, forecasting, educational, and commercial efforts worldwide, the WRF Model has made a significant mark on numerical weather prediction and atmospheric science.
