Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples
<p>The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2021-07-01
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| Series: | Atmospheric Measurement Techniques |
| Online Access: | https://amt.copernicus.org/articles/14/5107/2021/amt-14-5107-2021.pdf |
| _version_ | 1818613664157007872 |
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| author | H. Deneke C. Barrientos-Velasco S. Bley A. Hünerbein S. Lenk A. Macke J. F. Meirink M. Schroedter-Homscheidt F. Senf P. Wang F. Werner J. Witthuhn |
| author_facet | H. Deneke C. Barrientos-Velasco S. Bley A. Hünerbein S. Lenk A. Macke J. F. Meirink M. Schroedter-Homscheidt F. Senf P. Wang F. Werner J. Witthuhn |
| author_sort | H. Deneke |
| collection | DOAJ |
| description | <p>The modification of an existing cloud property retrieval scheme for
the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument
on board the geostationary Meteosat satellites is described to utilize
its high-resolution visible (HRV) channel for increasing the spatial
resolution of its physical outputs. This results in products with a
nadir spatial resolution of <span class="inline-formula">1×1</span> km<span class="inline-formula"><sup>2</sup></span> compared to
the standard <span class="inline-formula">3×3</span> km<span class="inline-formula"><sup>2</sup></span> resolution offered by the
narrowband channels. This improvement thus greatly reduces the
resolution gap between current geostationary and polar-orbiting
meteorological satellite imagers. In the first processing step,
cloudiness is determined from the HRV observations by a
threshold-based cloud masking algorithm. Subsequently, a linear model
that links the 0.6 <span class="inline-formula">µ</span>m, 0.8 <span class="inline-formula">µ</span>m, and HRV
reflectances provides a physical constraint to incorporate the spatial
high-frequency component of the HRV observations into the retrieval of
cloud optical depth. The implementation of the method is described,
including the ancillary datasets used. It is demonstrated that the
omission of high-frequency variations in the cloud-absorbing
1.6 <span class="inline-formula">µ</span>m channel results in comparatively large
uncertainties in the retrieved cloud effective radius, likely due to
the mismatch in channel resolutions. A newly developed downscaling
scheme for the 1.6 <span class="inline-formula">µ</span>m reflectance is therefore applied
to mitigate the effects of this scale mismatch. Benefits of the
increased spatial resolution of the resulting SEVIRI products are
demonstrated for three example applications: (i) for a convective
cloud field, it is shown that significantly better agreement between
the distributions of cloud optical depth retrieved from SEVIRI and
from collocated MODIS observations is achieved. (ii) The temporal
evolution of cloud properties for a growing convective storm at
standard and HRV spatial resolutions are compared, illustrating an
improved contrast in growth signatures resulting from the use of the
HRV channel. (iii) An example of surface solar irradiance, determined
from the retrieved cloud properties, is shown, for which the HRV channel
helps to better capture the large spatiotemporal variability induced
by convective clouds. These results suggest that incorporating the HRV
channel into the retrieval has potential for improving Meteosat-based
cloud products for several application domains.</p> |
| first_indexed | 2024-12-16T16:05:42Z |
| format | Article |
| id | doaj.art-bb392c8128874a2c8d4ba2ff951fe4a5 |
| institution | Directory Open Access Journal |
| issn | 1867-1381 1867-8548 |
| language | English |
| last_indexed | 2024-12-16T16:05:42Z |
| publishDate | 2021-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Atmospheric Measurement Techniques |
| spelling | doaj.art-bb392c8128874a2c8d4ba2ff951fe4a52022-12-21T22:25:21ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482021-07-01145107512610.5194/amt-14-5107-2021Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examplesH. Deneke0C. Barrientos-Velasco1S. Bley2A. Hünerbein3S. Lenk4A. Macke5J. F. Meirink6M. Schroedter-Homscheidt7F. Senf8P. Wang9F. Werner10J. Witthuhn11Leibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, GermanyLeibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, GermanyESA Centre for Earth Observation, Largo Galileo Galilei, 1, 00044 Frascati RM, ItalyLeibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, GermanyLeibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, GermanyLeibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, GermanyRoyal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the NetherlandsGerman Aerospace Center (DLR), Institute of Networked Energy Systems, Carl-von-Ossietzky-Straße 15, 26129 Oldenburg, GermanyLeibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, GermanyRoyal Netherlands Meteorological Institute, Utrechtseweg 297, 3731 GA De Bilt, the NetherlandsJet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA 91109, USALeibniz Institute for Tropospheric Research, Permoserstraße 15, 04318 Leipzig, Germany<p>The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of <span class="inline-formula">1×1</span> km<span class="inline-formula"><sup>2</sup></span> compared to the standard <span class="inline-formula">3×3</span> km<span class="inline-formula"><sup>2</sup></span> resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 <span class="inline-formula">µ</span>m, 0.8 <span class="inline-formula">µ</span>m, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 <span class="inline-formula">µ</span>m channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 <span class="inline-formula">µ</span>m reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.</p>https://amt.copernicus.org/articles/14/5107/2021/amt-14-5107-2021.pdf |
| spellingShingle | H. Deneke C. Barrientos-Velasco S. Bley A. Hünerbein S. Lenk A. Macke J. F. Meirink M. Schroedter-Homscheidt F. Senf P. Wang F. Werner J. Witthuhn Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples Atmospheric Measurement Techniques |
| title | Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples |
| title_full | Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples |
| title_fullStr | Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples |
| title_full_unstemmed | Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples |
| title_short | Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples |
| title_sort | increasing the spatial resolution of cloud property retrievals from meteosat seviri by use of its high resolution visible channel implementation and examples |
| url | https://amt.copernicus.org/articles/14/5107/2021/amt-14-5107-2021.pdf |
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