Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions
International audience The cloud particle size distribution (PSD) is a key parameter for the retrieval of microphysical and optical properties from remote-sensing instruments, which in turn are necessary for determining the radiative effect of clouds. Current representations of PSDs for ice clouds r...
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ftinsu:oai:HAL:hal-04591846v1 2024-06-23T07:50:51+00:00 Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions García, Irene Bartolomé Sourdeval, Odran Spang, Reinhold Krämer, Martina Institut für Energie- und Klimaforschung - Stratosphäre (IEK-7) Forschungszentrum Jülich GmbH Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) Institute for Atmospheric Physics Mainz (IPA) Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU) 2024-04-19 https://hal.univ-lille.fr/hal-04591846 https://hal.univ-lille.fr/hal-04591846/document https://hal.univ-lille.fr/hal-04591846/file/acp-24-1699-2024.pdf https://doi.org/10.5194/acp-24-1699-2024 en eng HAL CCSD European Geosciences Union info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-24-1699-2024 hal-04591846 https://hal.univ-lille.fr/hal-04591846 https://hal.univ-lille.fr/hal-04591846/document https://hal.univ-lille.fr/hal-04591846/file/acp-24-1699-2024.pdf doi:10.5194/acp-24-1699-2024 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1680-7316 EISSN: 1680-7324 Atmospheric Chemistry and Physics https://hal.univ-lille.fr/hal-04591846 Atmospheric Chemistry and Physics, 2024, Atmos. Chem. Phys., 24, ⟨10.5194/acp-24-1699-2024⟩ [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/article Journal articles 2024 ftinsu https://doi.org/10.5194/acp-24-1699-2024 2024-06-06T00:00:14Z International audience The cloud particle size distribution (PSD) is a key parameter for the retrieval of microphysical and optical properties from remote-sensing instruments, which in turn are necessary for determining the radiative effect of clouds. Current representations of PSDs for ice clouds rely on parameterizations that were largely based on aircraft in situ measurements where the distribution of small ice crystals were uncertain. This makes current parameterizations deficient to simulate remote-sensing observations sensitive to small ice, such as from lidar and thermal infrared instruments. In this study we fit the in situ PSDs of ice crystals from the JULIA (JÜLich In situ Aircraft data set) database, which consists of 11 campaigns covering the tropics, midlatitudes and the Arctic, consistently processed and considered more robust in their measurements of small ice. For the fitting, we implement an established approach to PSD parameterizations, which consists of finding an adequate set of parameters for a modified gamma function after normalization of both PSD axes. These parameters are constrained to match in situ measurements when predicting microphysical properties from the PSDs, via a cost function minimization method. We selected the ice water content and the ice crystal number concentration, which are currently key parameters for modern satellite retrievals and model microphysics schemes. We found that a bimodal parameterization yields better results than a monomodal one. The bimodal parameterization has a lower spread for almost all ice crystal sizes over the entire range of analyzed temperatures and fits better the observations, especially for particles between 20 and about 110 µm at temperatures between −60 and −20 ∘C. For this temperature range, the root mean square error for the retrieved Nice is reduced from 0.36 to 0.20. This demonstrates a clear advantage to considering the bimodality of PSDs, e.g., for satellite retrievals. Article in Journal/Newspaper Arctic Institut national des sciences de l'Univers: HAL-INSU Arctic Atmospheric Chemistry and Physics 24 3 1699 1716 |
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Open Polar |
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Institut national des sciences de l'Univers: HAL-INSU |
op_collection_id |
ftinsu |
language |
English |
topic |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
spellingShingle |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere García, Irene Bartolomé Sourdeval, Odran Spang, Reinhold Krämer, Martina Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions |
topic_facet |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
description |
International audience The cloud particle size distribution (PSD) is a key parameter for the retrieval of microphysical and optical properties from remote-sensing instruments, which in turn are necessary for determining the radiative effect of clouds. Current representations of PSDs for ice clouds rely on parameterizations that were largely based on aircraft in situ measurements where the distribution of small ice crystals were uncertain. This makes current parameterizations deficient to simulate remote-sensing observations sensitive to small ice, such as from lidar and thermal infrared instruments. In this study we fit the in situ PSDs of ice crystals from the JULIA (JÜLich In situ Aircraft data set) database, which consists of 11 campaigns covering the tropics, midlatitudes and the Arctic, consistently processed and considered more robust in their measurements of small ice. For the fitting, we implement an established approach to PSD parameterizations, which consists of finding an adequate set of parameters for a modified gamma function after normalization of both PSD axes. These parameters are constrained to match in situ measurements when predicting microphysical properties from the PSDs, via a cost function minimization method. We selected the ice water content and the ice crystal number concentration, which are currently key parameters for modern satellite retrievals and model microphysics schemes. We found that a bimodal parameterization yields better results than a monomodal one. The bimodal parameterization has a lower spread for almost all ice crystal sizes over the entire range of analyzed temperatures and fits better the observations, especially for particles between 20 and about 110 µm at temperatures between −60 and −20 ∘C. For this temperature range, the root mean square error for the retrieved Nice is reduced from 0.36 to 0.20. This demonstrates a clear advantage to considering the bimodality of PSDs, e.g., for satellite retrievals. |
author2 |
Institut für Energie- und Klimaforschung - Stratosphäre (IEK-7) Forschungszentrum Jülich GmbH Helmholtz-Gemeinschaft = Helmholtz Association-Helmholtz-Gemeinschaft = Helmholtz Association Laboratoire d’Optique Atmosphérique - UMR 8518 (LOA) Institut national des sciences de l'Univers (INSU - CNRS)-Université de Lille-Centre National de la Recherche Scientifique (CNRS) Institute for Atmospheric Physics Mainz (IPA) Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU) |
format |
Article in Journal/Newspaper |
author |
García, Irene Bartolomé Sourdeval, Odran Spang, Reinhold Krämer, Martina |
author_facet |
García, Irene Bartolomé Sourdeval, Odran Spang, Reinhold Krämer, Martina |
author_sort |
García, Irene Bartolomé |
title |
Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions |
title_short |
Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions |
title_full |
Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions |
title_fullStr |
Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions |
title_full_unstemmed |
Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions |
title_sort |
technical note: bimodal parameterizations of in situ ice cloud particle size distributions |
publisher |
HAL CCSD |
publishDate |
2024 |
url |
https://hal.univ-lille.fr/hal-04591846 https://hal.univ-lille.fr/hal-04591846/document https://hal.univ-lille.fr/hal-04591846/file/acp-24-1699-2024.pdf https://doi.org/10.5194/acp-24-1699-2024 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
ISSN: 1680-7316 EISSN: 1680-7324 Atmospheric Chemistry and Physics https://hal.univ-lille.fr/hal-04591846 Atmospheric Chemistry and Physics, 2024, Atmos. Chem. Phys., 24, ⟨10.5194/acp-24-1699-2024⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/acp-24-1699-2024 hal-04591846 https://hal.univ-lille.fr/hal-04591846 https://hal.univ-lille.fr/hal-04591846/document https://hal.univ-lille.fr/hal-04591846/file/acp-24-1699-2024.pdf doi:10.5194/acp-24-1699-2024 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/acp-24-1699-2024 |
container_title |
Atmospheric Chemistry and Physics |
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24 |
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3 |
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1699 |
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1716 |
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