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- Title
Assimilation of Transformed Retrievals From Satellite High‐Resolution Infrared Data Over the Central Pacific Area.
- Authors
Cherubini, Tiziana; Antonelli, Paolo; Businger, Steven; Scaccia, Paolo
- Abstract
A month‐long data assimilation experiment is carried out to assess the impact of CrIS and IASI Transformed Retrievals (TRs) on the accuracy of analyses and forecasts from a 3‐hr Weather Research and Forecasting cycling system implemented over the central North Pacific Ocean. Conventional observations and satellite MicroWave (MW) radiance data are assimilated along with TRs in comparative experiments. Both the NCEP Global Forecasting System and the European Centre for Medium‐Range Weather Forecasts analyses are used in the evaluation process. The results show that the assimilation of TRs alone, and in combination with MW radiance assimilation, have the greatest impact on the characterization of the moisture field in the middle atmospheric levels (800–300 hPa), and particularly in the lower portion (800–600 hPa). The latter improvement is likely due to a refinement in the vertical definition of the trade‐wind inversion. Plain Language Summary: A month‐long data assimilation experiment is carried out to assess the impact of hyper‐spectral sensor Transformed Retrievals (TRs) on the accuracy of analyses and forecasts from a 3‐hr Weather Research and Forecasting cycling system implemented over the central North Pacific Ocean. TRs are the result of a mathematical inversion process that compresses the informational content of the hyper‐spectral radiances into a limited number of uncorrelated parameters, and provides an ad hoc observation operator, for their assimilation within Numerical Weather Prediction models. Conventional observations and satellite MicroWave (MW) radiance data are assimilated along with TRs in comparative experiments. Both the NCEP Global Forecasting System and the European Centre for Medium‐Range Weather Forecasts analyses are used in the evaluation process. The results show that the assimilation of TRs, both alone, and in combination with MW radiance assimilation, have the greatest impact on the characterization of the moisture field in the middle atmospheric levels (800–300 hPa), and particularly in the lower portion (800–600 hPa). The latter improvement is likely due to a refinement in the vertical definition of the trade‐wind inversion. Key Points: Hyperspectral radiances are efficiently compressed into a limited number of uncorrelated parameters: the Transformed Retrievals (TRs)Assimilation of TRs is akin to assimilation of physical profilesThe assimilation of TRs results in a higher forecast accuracy in predicting the distribution of the water vapor
- Subjects
EUROPEAN Centre for Medium-Range Weather Forecasts (Organization); NUMERICAL weather forecasting; KALMAN filtering; METEOROLOGICAL research; WEATHER forecasting; WATER distribution; WATER vapor; BRIGHTNESS temperature
- Publication
Journal of Geophysical Research. Atmospheres, 2023, Vol 128, Issue 21, p1
- ISSN
2169-897X
- Publication type
Article
- DOI
10.1029/2022JD038153