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- Author or Editor: William E. Line x
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Abstract
The Geostationary Operational Environmental Satellite-14 (GOES-14) Imager was operated by the National Oceanic and Atmospheric Administration (NOAA) in an experimental rapid scan 1-min mode during parts of 2012, 2013, 2014, and 2015. This scan mode, known as the Super Rapid Scan Operations for GOES-R (SRSOR), emulates the high-temporal-resolution sampling that will be provided by the Advanced Baseline Imager on the next-generation GOES-R series. NOAA/National Weather Service/Storm Prediction Center (SPC) forecasters utilized the 1-min imagery extensively in operations when available over convectively active regions. They found it provided them with unique insight into relevant features and processes before, during, and after convective initiation. This paper introduces how the SRSOR datasets from GOES-14 were used by SPC forecasters and how these data are likely to be applied when available operationally from GOES-R. Several animations, included as supplemental material, showcase the rapid change of severe weather–related phenomena observed during the 2014 and 2015 SRSOR campaigns from the GOES-14 Imager.
Abstract
The Geostationary Operational Environmental Satellite-14 (GOES-14) Imager was operated by the National Oceanic and Atmospheric Administration (NOAA) in an experimental rapid scan 1-min mode during parts of 2012, 2013, 2014, and 2015. This scan mode, known as the Super Rapid Scan Operations for GOES-R (SRSOR), emulates the high-temporal-resolution sampling that will be provided by the Advanced Baseline Imager on the next-generation GOES-R series. NOAA/National Weather Service/Storm Prediction Center (SPC) forecasters utilized the 1-min imagery extensively in operations when available over convectively active regions. They found it provided them with unique insight into relevant features and processes before, during, and after convective initiation. This paper introduces how the SRSOR datasets from GOES-14 were used by SPC forecasters and how these data are likely to be applied when available operationally from GOES-R. Several animations, included as supplemental material, showcase the rapid change of severe weather–related phenomena observed during the 2014 and 2015 SRSOR campaigns from the GOES-14 Imager.
Abstract
Sea spray presents a significant hazard to vessels in the high latitudes. At issue is the accumulation of ice, which can destabilize, and at times, sink a ship. Many studies have focused on icing prediction systems, but a knowledge gap exists in the detection of sea spray using remote sensing data. The recent availability of data from new and advanced imagers on board NOAA satellites, specifically the GOES-R series Advanced Baseline Imager (ABI) and JPSS Visible Infrared Imaging Radiometer Suite (VIIRS), offers new tools for the detection and tracking of sea spray for forecasters. While ABI provides superior temporal coverage in order to capture the near-real-time evolution of sea spray, VIIRS contributes higher spatial detail, allowing for improved analysis of sea spray extent, particularly within smaller bodies of water. Forecasters can implement these detection techniques to help verify sea spray–related forecast products, and to pass along potentially life-saving information to their mariner core partners. This paper discusses the freezing sea spray hazard, and introduces newly identified methods for detecting and tracking sea spray using NOAA satellite data.
Abstract
Sea spray presents a significant hazard to vessels in the high latitudes. At issue is the accumulation of ice, which can destabilize, and at times, sink a ship. Many studies have focused on icing prediction systems, but a knowledge gap exists in the detection of sea spray using remote sensing data. The recent availability of data from new and advanced imagers on board NOAA satellites, specifically the GOES-R series Advanced Baseline Imager (ABI) and JPSS Visible Infrared Imaging Radiometer Suite (VIIRS), offers new tools for the detection and tracking of sea spray for forecasters. While ABI provides superior temporal coverage in order to capture the near-real-time evolution of sea spray, VIIRS contributes higher spatial detail, allowing for improved analysis of sea spray extent, particularly within smaller bodies of water. Forecasters can implement these detection techniques to help verify sea spray–related forecast products, and to pass along potentially life-saving information to their mariner core partners. This paper discusses the freezing sea spray hazard, and introduces newly identified methods for detecting and tracking sea spray using NOAA satellite data.
Abstract
With the launch of the Geostationary Operational Environmental Satellite–R (GOES-R) series in 2016, there will be continuity of observations for the current GOES system operating over the Western Hemisphere. The GOES-R Proving Ground was established in 2008 to help prepare satellite user communities for the enhanced capabilities of GOES-R, including new instruments, imagery, and products that will have increased spectral, spatial, and temporal resolution. This is accomplished through demonstration and evaluation of proxy products that use current GOES data, higher-resolution data provided by polar-orbiting satellites, and model-derived synthetic satellite imagery. The GOES-R demonstration products presented here, made available to forecasters in near–real time (within 20 min) via the GOES-R Proving Ground, include the 0–9-h NearCast model, 0–1-h convective initiation probabilities, convective cloud-top cooling, overshooting top detection, and a pseudo–Geostationary Lightning Mapper total lightning tendency diagnostic. These products are designed to assist in identifying areas of increasing convective instability, pre-radar echo cumulus cloud growth preceding thunderstorm formation, storm updraft intensity, and potential storm severity derived from lightning trends. In turn, they provide the warning forecaster with improved situational awareness and short-term predictive information that enhance their ability to monitor atmospheric conditions preceding and associated with the development of deep convection, a time period that typically occurs between the issuance of National Weather Service (NWS) Storm Prediction Center convective watches and convective storm warnings issued by NWS forecast offices. This paper will focus on how this GOES-R satellite convective toolkit could have been used by warning forecasters to enhance near-storm environment analysis and the warning-decision-making process prior to and during the 20 May 2013 Moore, Oklahoma, tornado event.
Abstract
With the launch of the Geostationary Operational Environmental Satellite–R (GOES-R) series in 2016, there will be continuity of observations for the current GOES system operating over the Western Hemisphere. The GOES-R Proving Ground was established in 2008 to help prepare satellite user communities for the enhanced capabilities of GOES-R, including new instruments, imagery, and products that will have increased spectral, spatial, and temporal resolution. This is accomplished through demonstration and evaluation of proxy products that use current GOES data, higher-resolution data provided by polar-orbiting satellites, and model-derived synthetic satellite imagery. The GOES-R demonstration products presented here, made available to forecasters in near–real time (within 20 min) via the GOES-R Proving Ground, include the 0–9-h NearCast model, 0–1-h convective initiation probabilities, convective cloud-top cooling, overshooting top detection, and a pseudo–Geostationary Lightning Mapper total lightning tendency diagnostic. These products are designed to assist in identifying areas of increasing convective instability, pre-radar echo cumulus cloud growth preceding thunderstorm formation, storm updraft intensity, and potential storm severity derived from lightning trends. In turn, they provide the warning forecaster with improved situational awareness and short-term predictive information that enhance their ability to monitor atmospheric conditions preceding and associated with the development of deep convection, a time period that typically occurs between the issuance of National Weather Service (NWS) Storm Prediction Center convective watches and convective storm warnings issued by NWS forecast offices. This paper will focus on how this GOES-R satellite convective toolkit could have been used by warning forecasters to enhance near-storm environment analysis and the warning-decision-making process prior to and during the 20 May 2013 Moore, Oklahoma, tornado event.
