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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-89
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-89
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 29 Apr 2019

Submitted as: research article | 29 Apr 2019

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This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Atmospheric Measurement Techniques (AMT) and is expected to appear here in due course.

OMI Total Column Water Vapor Version 4 Validation and Applications

Huiqun Wang, Amir Hossein Souri, Gonzalo Gonzalez Abad, Xiong Liu, and Kelly Chance Huiqun Wang et al.
  • Smithsonian Astrophysical Observatory, 60 Garden Street, Cambridge, Massachusetts 02138, USA

Abstract. Total Column Water Vapor (TCWV) is important for the weather and climate. TCWV is derived from the OMI visible spectra using the Version 4 retrieval algorithm developed at the Smithsonian Astrophysical Observatory. The algorithm uses a retrieval window between 432.0 and 466.5 nm and includes various updates. The retrieval window optimization results from the trade-offs among competing factors. The OMI product is characterized by comparing against commonly used reference datasets – GPS network data over land and SSMIS data over the oceans. We examine how cloud fraction and cloud top pressure affect the comparisons. The results lead us to recommend filtering OMI data with cloud fraction < 5–15 % and cloud top pressure > 750 mb or stricter criteria, in addition to the main data quality, fitting RMS and TCWV range check. The mean of OMI-GPS is 0.85 mm with a standard deviation (σ) of 5.2 mm. Smaller differences between OMI and GPS (0.2 mm) occur when TCWV is within 10–20 mm. The bias is much smaller than the previous version. The mean of OMI-SSMIS is 1.2–1.9 mm (σ = 6.5–6.8 mm), with better agreement for January than for July. Smaller differences between OMI and SSMIS (0.3–1.6 mm) occur when TCWV is within 10–30 mm. However, the relative difference between OMI and the reference datasets is large when TCWV is less than 10 mm. As test applications of the Version 4 OMI TCWV over a range of spatial and temporal scales, we find prominent signals of the patterns associated with El Niño and La Niña, the high humidity associated with a corn sweat event and the strong moisture band of an Atmospheric River (AR). A data assimilation experiment demonstrates that the OMI data can help improve WRF’s skill at simulating the structure and intensity of the AR and the precipitation at the AR landfall.

Huiqun Wang et al.
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Interactive discussion
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Status: closed
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Huiqun Wang et al.
Huiqun Wang et al.
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Short summary
Total Column Water Vapor (TCWV) is retrieved from the spectra obtained by the Ozone Monitoring Instrument (OMI). Data filtering criteria are recommended. The OMI data compare well with reference datasets for intermediate amount of water vapor over both land and the oceans. The data are useful for a variety of studies spanning a range of spatial and temporal scales, such as Atmospheric River (AR), corn sweat and El Niño / La Niña.
Total Column Water Vapor (TCWV) is retrieved from the spectra obtained by the Ozone Monitoring...
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