Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images
<p>Radiative Transfer for TOVS (RTTOV) is a commonly used forward-operator software package for the data assimilation (DA) of satellite visible reflectance data. However, the wide choice of cloud optical parameterizations (COPs) in RTTOV poses challenges in discerning the optimal configuratio...
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Copernicus Publications
2025-07-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/18/3267/2025/amt-18-3267-2025.pdf |
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| author | Y. Zhou T. Cao L. Zhu |
| author_facet | Y. Zhou T. Cao L. Zhu |
| author_sort | Y. Zhou |
| collection | DOAJ |
| description | <p>Radiative Transfer for TOVS (RTTOV) is a commonly used forward-operator software package for the data assimilation (DA) of satellite visible reflectance data. However, the wide choice of cloud optical parameterizations (COPs) in RTTOV poses challenges in discerning the optimal configuration. In this study, the performance of different COPs was evaluated by comparing the observed and synthetic visible satellite images. Observed images (<span class="inline-formula"><i>O</i></span>) were provided by Fengyun-4B (FY-4B) and Himawari-9, two operational geostationary meteorological satellites covering East Asia. Synthetic images (<span class="inline-formula"><i>B</i></span>) were generated by RTTOV (v12.3) with the discrete ordinate method (DOM) and the Method for FAst Satellite Image Simulation (MFASIS). The inputs to RTTOV were provided by the 3 <span class="inline-formula">h</span> forecasts of the China Meteorological Administration Mesoscale (CMA-MESO) model and the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) data. On average for the domain, <span class="inline-formula"><i>B</i></span> was smaller than <span class="inline-formula"><i>O</i></span>, especially in cloudy situations. The minimum <span class="inline-formula"><i>O</i>−<i>B</i></span> bias was revealed for the COP of liquid water clouds in terms of effective diameter (<span class="inline-formula"><i>D</i><sub>eff</sub></span>) in combination with the COP of ice clouds developed by the Space Science and Engineering Center (SSEC), with the <span class="inline-formula"><i>D</i><sub>eff</sub></span> for ice clouds parameterized in terms of ice water content and temperature. Compared with the <span class="inline-formula"><i>O</i>−<i>B</i></span> biases, the standard deviations of the <span class="inline-formula"><i>O</i>−<i>B</i></span> departure were less sensitive to COPs. In addition, histogram analysis of reflectance indicated that the synthetic images with the minimum <span class="inline-formula"><i>O</i>−<i>B</i></span> bias resembled the observed images best. Therefore, the optimal cloud optical parameterization was proposed to be the “<span class="inline-formula"><i>D</i><sub>eff</sub></span> <span class="inline-formula">+</span> SSEC” suite.</p> |
| format | Article |
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| institution | DOAJ |
| issn | 1867-1381 1867-8548 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
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| spelling | doaj-art-8e15c0db1f3b40ed9340090d006e7bd22025-08-20T03:11:58ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482025-07-01183267328510.5194/amt-18-3267-2025Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic imagesY. Zhou0T. Cao1L. Zhu2School of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, ChinaSchool of Atmospheric Physics, Nanjing University of Information Science and Technology, Nanjing, ChinaShanghai Typhoon Institute of the China Meteorological Administration, Shanghai, China<p>Radiative Transfer for TOVS (RTTOV) is a commonly used forward-operator software package for the data assimilation (DA) of satellite visible reflectance data. However, the wide choice of cloud optical parameterizations (COPs) in RTTOV poses challenges in discerning the optimal configuration. In this study, the performance of different COPs was evaluated by comparing the observed and synthetic visible satellite images. Observed images (<span class="inline-formula"><i>O</i></span>) were provided by Fengyun-4B (FY-4B) and Himawari-9, two operational geostationary meteorological satellites covering East Asia. Synthetic images (<span class="inline-formula"><i>B</i></span>) were generated by RTTOV (v12.3) with the discrete ordinate method (DOM) and the Method for FAst Satellite Image Simulation (MFASIS). The inputs to RTTOV were provided by the 3 <span class="inline-formula">h</span> forecasts of the China Meteorological Administration Mesoscale (CMA-MESO) model and the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis (ERA5) data. On average for the domain, <span class="inline-formula"><i>B</i></span> was smaller than <span class="inline-formula"><i>O</i></span>, especially in cloudy situations. The minimum <span class="inline-formula"><i>O</i>−<i>B</i></span> bias was revealed for the COP of liquid water clouds in terms of effective diameter (<span class="inline-formula"><i>D</i><sub>eff</sub></span>) in combination with the COP of ice clouds developed by the Space Science and Engineering Center (SSEC), with the <span class="inline-formula"><i>D</i><sub>eff</sub></span> for ice clouds parameterized in terms of ice water content and temperature. Compared with the <span class="inline-formula"><i>O</i>−<i>B</i></span> biases, the standard deviations of the <span class="inline-formula"><i>O</i>−<i>B</i></span> departure were less sensitive to COPs. In addition, histogram analysis of reflectance indicated that the synthetic images with the minimum <span class="inline-formula"><i>O</i>−<i>B</i></span> bias resembled the observed images best. Therefore, the optimal cloud optical parameterization was proposed to be the “<span class="inline-formula"><i>D</i><sub>eff</sub></span> <span class="inline-formula">+</span> SSEC” suite.</p>https://amt.copernicus.org/articles/18/3267/2025/amt-18-3267-2025.pdf |
| spellingShingle | Y. Zhou T. Cao L. Zhu Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images Atmospheric Measurement Techniques |
| title | Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images |
| title_full | Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images |
| title_fullStr | Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images |
| title_full_unstemmed | Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images |
| title_short | Optimizing cloud optical parameterizations in Radiative Transfer for TOVS (RTTOV v12.3) for data assimilation of satellite visible reflectance data: an assessment using observed and synthetic images |
| title_sort | optimizing cloud optical parameterizations in radiative transfer for tovs rttov v12 3 for data assimilation of satellite visible reflectance data an assessment using observed and synthetic images |
| url | https://amt.copernicus.org/articles/18/3267/2025/amt-18-3267-2025.pdf |
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