TY - JOUR
T1 - Benefits of the Advanced Baseline Imager (ABI) for ensemble-based analysis and prediction of severe thunderstorms
AU - Zhang, Yunji
AU - Stensrud, David J.
AU - Clothiaux, Eugene E.
N1 - Funding Information:
This manuscript benefited from the comments of the three anonymous reviewers. This work was primarily supported by NASA under Grant NNX15AQ51G and NOAA Office of Weather and Air Quality under Grant NA18OAR4590369. NASA Grant 80NSSC19K0728 and ONR Grant N000141812517 also supported this research through their focus on radar and satellite radiance assimilation. The numerical experiments were performed on the Stampede 2 supercomputer of the Texas Advanced Computing Center (TACC) through the Extreme Science and Engineering Discovery Environment (XSEDE) program supported by the National Science Foundation (NSF).
Publisher Copyright:
© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).
PY - 2021/2
Y1 - 2021/2
N2 - Recent studies have demonstrated advances in the analysis and prediction of severe thunderstorms and other weather hazards by assimilating infrared (IR) all-sky radiances into numerical weather prediction models using advanced ensemble-based techniques. It remains an open question how many of these advances are due to improvements in the radiance observations themselves, especially when compared with radiance observations from preceding satellite imagers. This study investigates the improvements gained by assimilation of IR all-sky radiances from the Advanced Baseline Imager (ABI) on board GOES-16 compared to those from its predecessor imager. Results show that all aspects of the improvements in ABI compared with its predecessor imager-finer spatial resolution, shorter scanning intervals, and more channels covering a wider range of the spectrum-contribute to more accurate ensemble analyses and forecasts of the targeted severe thunderstorm event, but in different ways. The clear-sky regions within the assimilated all-sky radiance fields have a particularly beneficial influence on the moisture fields. Results also show that assimilating different IR channels can lead to oppositely signed increments in the moisture fields, a by-product of inaccurate covariances at large distances resulting from sampling errors. These findings pose both challenges and opportunities in identifying appropriate vertical localizations and IR channel combinations to produce the best possible analyses in support of severe weather forecasting.
AB - Recent studies have demonstrated advances in the analysis and prediction of severe thunderstorms and other weather hazards by assimilating infrared (IR) all-sky radiances into numerical weather prediction models using advanced ensemble-based techniques. It remains an open question how many of these advances are due to improvements in the radiance observations themselves, especially when compared with radiance observations from preceding satellite imagers. This study investigates the improvements gained by assimilation of IR all-sky radiances from the Advanced Baseline Imager (ABI) on board GOES-16 compared to those from its predecessor imager. Results show that all aspects of the improvements in ABI compared with its predecessor imager-finer spatial resolution, shorter scanning intervals, and more channels covering a wider range of the spectrum-contribute to more accurate ensemble analyses and forecasts of the targeted severe thunderstorm event, but in different ways. The clear-sky regions within the assimilated all-sky radiance fields have a particularly beneficial influence on the moisture fields. Results also show that assimilating different IR channels can lead to oppositely signed increments in the moisture fields, a by-product of inaccurate covariances at large distances resulting from sampling errors. These findings pose both challenges and opportunities in identifying appropriate vertical localizations and IR channel combinations to produce the best possible analyses in support of severe weather forecasting.
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U2 - 10.1175/MWR-D-20-0254.1
DO - 10.1175/MWR-D-20-0254.1
M3 - Article
AN - SCOPUS:85102514674
SN - 0027-0644
VL - 149
SP - 313
EP - 332
JO - Monthly Weather Review
JF - Monthly Weather Review
IS - 2
ER -