Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions
<p>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 paramet...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2024-02-01
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| Series: | Atmospheric Chemistry and Physics |
| Online Access: | https://acp.copernicus.org/articles/24/1699/2024/acp-24-1699-2024.pdf |
| _version_ | 1797322683158888448 |
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| author | I. Bartolomé García I. Bartolomé García O. Sourdeval R. Spang M. Krämer M. Krämer |
| author_facet | I. Bartolomé García I. Bartolomé García O. Sourdeval R. Spang M. Krämer M. Krämer |
| author_sort | I. Bartolomé García |
| collection | DOAJ |
| description | <p>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 <span class="inline-formula">µ</span>m at temperatures between <span class="inline-formula">−60</span> and <span class="inline-formula">−20</span> <span class="inline-formula"><sup>∘</sup></span>C. For this temperature range, the root mean square error for the retrieved <span class="inline-formula"><i>N</i><sub>ice</sub></span> is reduced from 0.36 to 0.20. This demonstrates a clear advantage to considering the bimodality of PSDs, e.g., for satellite retrievals.</p> |
| first_indexed | 2024-03-08T05:17:49Z |
| format | Article |
| id | doaj.art-34083350656f45c58257f57e289a8887 |
| institution | Directory Open Access Journal |
| issn | 1680-7316 1680-7324 |
| language | English |
| last_indexed | 2024-03-08T05:17:49Z |
| publishDate | 2024-02-01 |
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| series | Atmospheric Chemistry and Physics |
| spelling | doaj.art-34083350656f45c58257f57e289a88872024-02-06T15:06:11ZengCopernicus PublicationsAtmospheric Chemistry and Physics1680-73161680-73242024-02-01241699171610.5194/acp-24-1699-2024Technical note: Bimodal parameterizations of in situ ice cloud particle size distributionsI. Bartolomé García0I. Bartolomé García1O. Sourdeval2R. Spang3M. Krämer4M. Krämer5Institute for Energy and Climate Research (IEK-7), Research Center Jülich, 52425 Jülich, Germanynow at: Institute of Geophysics and Meteorology, University of Cologne, 50969 Cologne, GermanyPhysics Department, University of Lille, CNRS, UMR 8518-LOA-Laboratoire d'Optique Atmosphérique, 59000 Lille, FranceInstitute for Energy and Climate Research (IEK-7), Research Center Jülich, 52425 Jülich, GermanyInstitute for Energy and Climate Research (IEK-7), Research Center Jülich, 52425 Jülich, GermanyInstitute for Physics of the Atmosphere (IPA), Johannes-Gutenberg University, 55122 Mainz, Germany<p>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 <span class="inline-formula">µ</span>m at temperatures between <span class="inline-formula">−60</span> and <span class="inline-formula">−20</span> <span class="inline-formula"><sup>∘</sup></span>C. For this temperature range, the root mean square error for the retrieved <span class="inline-formula"><i>N</i><sub>ice</sub></span> is reduced from 0.36 to 0.20. This demonstrates a clear advantage to considering the bimodality of PSDs, e.g., for satellite retrievals.</p>https://acp.copernicus.org/articles/24/1699/2024/acp-24-1699-2024.pdf |
| spellingShingle | I. Bartolomé García I. Bartolomé García O. Sourdeval R. Spang M. Krämer M. Krämer Technical note: Bimodal parameterizations of in situ ice cloud particle size distributions Atmospheric Chemistry and Physics |
| title | 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_short | 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 |
| url | https://acp.copernicus.org/articles/24/1699/2024/acp-24-1699-2024.pdf |
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