Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications
<p>Total column water vapor (TCWV) is important for the weather and climate. TCWV is derived from the Ozone Monitoring Instrument (OMI) visible spectra using the version 4.0 retrieval algorithm developed at the Smithsonian Astrophysical Observatory. The algorithm uses a retrieval window betwee...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-09-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://www.atmos-meas-tech.net/12/5183/2019/amt-12-5183-2019.pdf |
| _version_ | 1818564057634963456 |
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| author | H. Wang A. H. Souri G. González Abad X. Liu K. Chance |
| author_facet | H. Wang A. H. Souri G. González Abad X. Liu K. Chance |
| author_sort | H. Wang |
| collection | DOAJ |
| description | <p>Total column water vapor (TCWV) is important for the weather and climate.
TCWV is derived from the Ozone Monitoring Instrument (OMI) visible spectra
using the version 4.0 retrieval algorithm developed at the Smithsonian
Astrophysical Observatory. The algorithm uses a retrieval window between
432.0 and 466.5 nm and includes updates to reference spectra and water vapor
profiles. The retrieval window optimization results from the trade-offs
among competing factors.</p>
<p>The OMI product is characterized by comparing against commonly used
reference datasets – global positioning system (GPS) network data over land
and Special Sensor Microwave Imager/Sounder (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 a cloud fraction less
than <span class="inline-formula"><i>f</i>=0.05</span>–0.25 and cloud-top pressure greater than 750 mb (or
stricter), in addition to the data quality flag, fitting root mean square (RMS) and TCWV range
check. Over land, for <span class="inline-formula"><i>f</i>=0.05</span>, the overall mean of OMI–GPS is 0.32 mm
with a standard deviation (<span class="inline-formula"><i>σ</i></span>) of 5.2 mm; the smallest bias occurs
when TCWV <span class="inline-formula">=</span> 10–20 mm, and the best regression line corresponds to <span class="inline-formula"><i>f</i>=0.25</span>. Over the oceans, for <span class="inline-formula"><i>f</i>=0.05</span>, the overall mean of OMI–SSMIS is
0.4 mm (1.1 mm) with <span class="inline-formula"><i>σ</i>=6.5</span> mm (6.8 mm) for January (July); the
smallest bias occurs when TCWV <span class="inline-formula">=</span> 20–30 mm, and the best regression line
corresponds to <span class="inline-formula"><i>f</i>=0.15</span>. For both land and the oceans, the difference
between OMI and the reference datasets is relatively large when TCWV is less
than 10 mm. The bias for the version 4.0 OMI TCWV is much smaller than that for version 3.0.</p>
<p>As test applications of the version 4.0 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 the
Weather Research and Forecasting (WRF) model skill at simulating the
structure and intensity of the AR and the precipitation at the AR landfall.</p> |
| first_indexed | 2024-12-14T01:24:24Z |
| format | Article |
| id | doaj.art-c8384b9762d04125b4d0b922204d01d8 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-12-14T01:24:24Z |
| publishDate | 2019-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-c8384b9762d04125b4d0b922204d01d82022-12-21T23:22:15ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482019-09-01125183519910.5194/amt-12-5183-2019Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applicationsH. WangA. H. SouriG. González AbadX. LiuK. Chance<p>Total column water vapor (TCWV) is important for the weather and climate. TCWV is derived from the Ozone Monitoring Instrument (OMI) visible spectra using the version 4.0 retrieval algorithm developed at the Smithsonian Astrophysical Observatory. The algorithm uses a retrieval window between 432.0 and 466.5 nm and includes updates to reference spectra and water vapor profiles. The retrieval window optimization results from the trade-offs among competing factors.</p> <p>The OMI product is characterized by comparing against commonly used reference datasets – global positioning system (GPS) network data over land and Special Sensor Microwave Imager/Sounder (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 a cloud fraction less than <span class="inline-formula"><i>f</i>=0.05</span>–0.25 and cloud-top pressure greater than 750 mb (or stricter), in addition to the data quality flag, fitting root mean square (RMS) and TCWV range check. Over land, for <span class="inline-formula"><i>f</i>=0.05</span>, the overall mean of OMI–GPS is 0.32 mm with a standard deviation (<span class="inline-formula"><i>σ</i></span>) of 5.2 mm; the smallest bias occurs when TCWV <span class="inline-formula">=</span> 10–20 mm, and the best regression line corresponds to <span class="inline-formula"><i>f</i>=0.25</span>. Over the oceans, for <span class="inline-formula"><i>f</i>=0.05</span>, the overall mean of OMI–SSMIS is 0.4 mm (1.1 mm) with <span class="inline-formula"><i>σ</i>=6.5</span> mm (6.8 mm) for January (July); the smallest bias occurs when TCWV <span class="inline-formula">=</span> 20–30 mm, and the best regression line corresponds to <span class="inline-formula"><i>f</i>=0.15</span>. For both land and the oceans, the difference between OMI and the reference datasets is relatively large when TCWV is less than 10 mm. The bias for the version 4.0 OMI TCWV is much smaller than that for version 3.0.</p> <p>As test applications of the version 4.0 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 the Weather Research and Forecasting (WRF) model skill at simulating the structure and intensity of the AR and the precipitation at the AR landfall.</p>https://www.atmos-meas-tech.net/12/5183/2019/amt-12-5183-2019.pdf |
| spellingShingle | H. Wang A. H. Souri G. González Abad X. Liu K. Chance Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications Atmospheric Measurement Techniques |
| title | Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications |
| title_full | Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications |
| title_fullStr | Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications |
| title_full_unstemmed | Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications |
| title_short | Ozone Monitoring Instrument (OMI) Total Column Water Vapor version 4 validation and applications |
| title_sort | ozone monitoring instrument omi total column water vapor version 4 validation and applications |
| url | https://www.atmos-meas-tech.net/12/5183/2019/amt-12-5183-2019.pdf |
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