Demonstration of a GOES-R Satellite Convective Toolkit to “Bridge the Gap” between Severe Weather Watches and Warnings: An Example from the 20 May 2013 Moore, Oklahoma, Tornado Outbreak

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.

Entrainment of stratospheric air and Asian pollution by the convective boundary layer in the southwestern U.S.

“…Figure 3d shows a weaker jet streak on the southeastern flank of this cyclone above Montana, Idaho, and Wyoming. These two systems created severe springtime weather across much of the U.S. including two major tornado outbreaks in the Midwest and Southern Plains [Gravelle et al, 2016] and record late season snowfall on the East Coast. Figure 5 represent the corresponding altitudes, which are roughly 6-7, 4-5, and 2-3 km asl over southern Nevada.…”

Severe Hail Fall and Hailstorm Detection Using Remote Sensing Observations

“…GOES-R features the Advanced Baseline Imager, which has 0.5-km horizontal resolution for visible imagery, 2 km for IR imagery, and an operational ''flex mode'' for image temporal resolution of 30 s to 1 min (Schmit et al 2005(Schmit et al , 2013. Several recent studies have assessed the potential utility of higher-resolution GOES imagery for severe weather operations (Cintineo et al 2013(Cintineo et al , 2014Gravelle et al 2016;Line et al 2016;Bedka and Khlopenkov 2016). While these studies documented the benefits of GOES-14 SRSOR observations for severe storm prediction, there remains a lack of focus on severe hail detection.…”

Impacts of assimilating all or GOES-like AHI infrared channels radiances on QPFs over Eastern China

“…In the past two decades, the United States geostationary operational environmental satellite program (GOES) observations were not only applied to nowcasting (Velden, 1996;Velden et al, 1997Velden et al, , 1998Mecikalski and Bedka, 2006;Mecikalski et al, 2015;Gravelle et al, 2016), but also extended to regional numerical weather prediction. For example, positive impacts of the GOES radiance assimilation on regional weather forecasts were demonstrated by Köpken et al (2004) and Okamoto (2013) for the Meteosat Visible and Infrared Imager (MVIRI); Szyndel et al (2005), Guedj et al (2011) and Stengel et al (2009) for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat-8, Zou et al (2011Zou et al ( , 2015 and Qin et al (2013) for the GOES imagers on board the United States On 7 October 2014, the Japan Meteorological Agency (JMA) successfully launched a Geostationary Meteorological Satellite (GMS) -Himawari-8.…”