Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle
International audience The multi-scale interactions at the origin of the links between clouds and water vapour are essential for the Earth's energy balance and thus the climate, from local to global. Knowledge of the distribution and variability of water vapour in the troposphere is indeed a ma...
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HAL CCSD
2020
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Online Access: | https://insu.hal.science/insu-04447520 https://doi.org/10.5194/egusphere-egu2020-21947 |
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Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQ |
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language |
English |
topic |
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
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[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology Michot, Veronique Brogniez, Hélène Vrac, Mathieu Thao, Soulivanh Chepfer, Helene Yiou, Pascal Dufour, Christophe Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
topic_facet |
[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology |
description |
International audience The multi-scale interactions at the origin of the links between clouds and water vapour are essential for the Earth's energy balance and thus the climate, from local to global. Knowledge of the distribution and variability of water vapour in the troposphere is indeed a major issue for the understanding of the atmospheric water cycle. At present, these interactions are poorly known at regional and local scales, i.e. within 100km, and are therefore poorly represented in numerical climate models. This is why we have sought to predict cloud scale relative humidity profiles in the intertropical zone, using a non-parametric statistical downscaling method called quantile regression forest. The procedure includes co-located data from 3 satellites: CALIPSO lidar and CloudSat radar, used as predictors and providing cloud properties at 90m and 1.4km horizontal resolution respectively; SAPHIR data used as a predictor and providing relative humidity at an initial horizontal resolution of 10km. Quantile regression forests were used to predict relative humidity profiles at the CALIPSO and CloudSat scales. These predictions are able to reproduce a relative humidity variability consistent with the cloud profiles and are confirmed by values of coefficients of determination greater than 0.7, relative to observed relative humidity, and Continuous Rank Probability Skill Score between 0 and 1, relative to climatology. Lidar measurements from the NARVAL 1&2 campaigns and radiosondes from the EUREC4A campaigns were also used to compare Relative Humidity profiles at the SAPHIR scale and at the scale of forest regression prediction by quantile regression. |
author2 |
Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) SPACE - LATMOS Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) |
format |
Conference Object |
author |
Michot, Veronique Brogniez, Hélène Vrac, Mathieu Thao, Soulivanh Chepfer, Helene Yiou, Pascal Dufour, Christophe |
author_facet |
Michot, Veronique Brogniez, Hélène Vrac, Mathieu Thao, Soulivanh Chepfer, Helene Yiou, Pascal Dufour, Christophe |
author_sort |
Michot, Veronique |
title |
Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
title_short |
Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
title_full |
Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
title_fullStr |
Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
title_full_unstemmed |
Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
title_sort |
estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle |
publisher |
HAL CCSD |
publishDate |
2020 |
url |
https://insu.hal.science/insu-04447520 https://doi.org/10.5194/egusphere-egu2020-21947 |
op_coverage |
Online, Unknown Region |
genre |
narval narval |
genre_facet |
narval narval |
op_source |
EGU General Assembly 2020 https://insu.hal.science/insu-04447520 EGU General Assembly 2020, May 2020, Online, Unknown Region. pp.21947, ⟨10.5194/egusphere-egu2020-21947⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/egusphere-egu2020-21947 insu-04447520 https://insu.hal.science/insu-04447520 BIBCODE: 2020EGUGA.2221947M doi:10.5194/egusphere-egu2020-21947 |
op_doi |
https://doi.org/10.5194/egusphere-egu2020-21947 |
_version_ |
1799468735088558080 |
spelling |
ftuniversailles:oai:HAL:insu-04447520v1 2024-05-19T07:50:08+00:00 Estimation of fine-scale relative humidity profiles: an issue for understanding the atmospheric water cycle Michot, Veronique Brogniez, Hélène Vrac, Mathieu Thao, Soulivanh Chepfer, Helene Yiou, Pascal Dufour, Christophe Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) SPACE - LATMOS Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS) Laboratoire des Sciences du Climat et de l'Environnement Gif-sur-Yvette (LSCE) Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR) Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Direction de Recherche Fondamentale (CEA) (DRF (CEA)) Laboratoire de Météorologie Dynamique (UMR 8539) (LMD) Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL)-École normale supérieure - Paris (ENS-PSL) Université Paris Sciences et Lettres (PSL)-Université Paris Sciences et Lettres (PSL) Online, Unknown Region 2020-05 https://insu.hal.science/insu-04447520 https://doi.org/10.5194/egusphere-egu2020-21947 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.5194/egusphere-egu2020-21947 insu-04447520 https://insu.hal.science/insu-04447520 BIBCODE: 2020EGUGA.2221947M doi:10.5194/egusphere-egu2020-21947 EGU General Assembly 2020 https://insu.hal.science/insu-04447520 EGU General Assembly 2020, May 2020, Online, Unknown Region. pp.21947, ⟨10.5194/egusphere-egu2020-21947⟩ [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology info:eu-repo/semantics/conferenceObject Conference papers 2020 ftuniversailles https://doi.org/10.5194/egusphere-egu2020-21947 2024-04-25T00:17:44Z International audience The multi-scale interactions at the origin of the links between clouds and water vapour are essential for the Earth's energy balance and thus the climate, from local to global. Knowledge of the distribution and variability of water vapour in the troposphere is indeed a major issue for the understanding of the atmospheric water cycle. At present, these interactions are poorly known at regional and local scales, i.e. within 100km, and are therefore poorly represented in numerical climate models. This is why we have sought to predict cloud scale relative humidity profiles in the intertropical zone, using a non-parametric statistical downscaling method called quantile regression forest. The procedure includes co-located data from 3 satellites: CALIPSO lidar and CloudSat radar, used as predictors and providing cloud properties at 90m and 1.4km horizontal resolution respectively; SAPHIR data used as a predictor and providing relative humidity at an initial horizontal resolution of 10km. Quantile regression forests were used to predict relative humidity profiles at the CALIPSO and CloudSat scales. These predictions are able to reproduce a relative humidity variability consistent with the cloud profiles and are confirmed by values of coefficients of determination greater than 0.7, relative to observed relative humidity, and Continuous Rank Probability Skill Score between 0 and 1, relative to climatology. Lidar measurements from the NARVAL 1&2 campaigns and radiosondes from the EUREC4A campaigns were also used to compare Relative Humidity profiles at the SAPHIR scale and at the scale of forest regression prediction by quantile regression. Conference Object narval narval Université de Versailles Saint-Quentin-en-Yvelines: HAL-UVSQ |