Impact of Assimilating High‐Resolution Atmospheric Motion Vectors on Convective Scale Short‐Term Forecasts: 2. Assimilation Experiments of GOES‐16 Satellite Derived Winds

Abstract

New-generation geostationary satellites, such as Geostationary Operational Environmental Satellites-16/17 (GOES-16/17), Himawari-8/9, Geostationary Korea Multipurpose Satellite-2A (GEO-KOMPSAT-2A/2B), EUMETSAT-Meteosat Third Generation, and Fengyun-4, and so on, can provide high-spatiotemporal-resolution atmospheric motion vector (AMV) products containing mesoscale or convective flow information. Recent studies showed that assimilating high-resolution AMVs has generally slightly positive or neutral impacts on the global and regional model analyses and forecasts, especially with small reductions in wind errors (

Impact of Assimilating High‐Resolution Atmospheric Motion Vectors on Convective Scale Short‐Term Forecasts: 3. Experiments With Radar Reflectivity and Radial Velocity

“…Given the fact that horizontal resolution of AMVs is driven by spatial and temporal resolution of ABI imageries as well as target scene size, the horizontal resolutions of AMVs generated from visible, water vapor, and longwave infrared bands are 7.5, 30, and 38 km, respectively (Daniels et al, 2012). There are only three layers of wind observations in AMV product: 1,000-700, 700-400, and 400-100 hPa, with band-depend acceptable height ranges as indicated in Zhao et al (2021b).…”

“…The forecast model is the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model version 3.6.1 (Skamarock et al, 2008). All forecast experiments in this research follow a similar configuration as in Zhao et al (2021b) wherein the simulation was performed on a 1.5-km spaced grid of 600 × 600 horizontal points and 51 vertical levels. Figure 2 illustrates the domain for each case, which is determined based on the "Day 1" Convective Outlook released by the Storm Prediction Center.…”

“…As in Zhao et al. (2021b), this study uses the GOES‐16 ABI Level 2 (L2) AMV product over the CONUS region generated by NOAA NESDIS Center for Satellite Applications and Research in NetCDF file format (Daniels et al., 2012). By tracing a set of targets, including cloud edges or moisture gradients, the ABI AMV product is derived from six selected spectral channels: visible band 2 (0.64 μm), shortwave infrared band 7 (3.9 μm), mid‐wave water vapor bands 8 (6.15 μm), 9 (7.0 μm), and 10 (7.4 μm), and longwave infrared band 14 (11.2 μm).…”

“…Recent research suggested slightly positive or neutral impacts on the global and regional NWP from the assimilation of high‐density or rapid‐scan AMV data, especially in the tropical cyclone track and intensity forecasts (Cherubini et al., 2006; Elsberry et al., 2018; Kim & Kim, 2018; Kim et al., 2017; Lean & Bormann, 2019; Lean et al., 2016; Le Marshall et al., 2008; Li et al., 2020; Lim et al., 2019; Mallick & Jones, 2020; Otsuka et al., 2015; Sawada et al., 2019; Velden et al., 2017; Wu et al., 2015; Yamashita, 2012, 2017). To our knowledge, there are few peer‐reviewed published research investigating the impacts of assimilating high‐spatiotemporal‐resolution AMV data on mesoscale and convective scale weather forecasts over land (Mallick & Jones, 2020; Zhao et al., 2021a, 2021b).…”

“…. To our knowledge, there are few peer-reviewed published research investigating the impacts of assimilating high-spatiotemporal-resolution AMV data on mesoscale and convective scale weather forecasts over land (Mallick & Jones, 2020;Zhao et al, 2021aZhao et al, , 2021b).…”