A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017

A dataset of microphysical cloud parameters from optically thin clouds, retrieved from infrared spectral radiances measured in summer 2017 in the Arctic, is presented. Measurements were conducted using a mobile Fourier-transform infrared (FTIR) spectrometer which was carried by the RV Polarstern . T...

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Main Authors: Richter, Philipp, Palm, Mathias, Weinzierl, Christine, Griesche, Hannes, Rowe, Penny M., Notholt, Justus
Format: Text
Language:English
Published: 2021
Subjects:
Online Access:https://doi.org/10.5194/essd-2021-284
https://essd.copernicus.org/preprints/essd-2021-284/
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spelling ftcopernicus:oai:publications.copernicus.org:essdd97053 2023-05-15T15:00:54+02:00 A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017 Richter, Philipp Palm, Mathias Weinzierl, Christine Griesche, Hannes Rowe, Penny M. Notholt, Justus 2021-09-06 application/pdf https://doi.org/10.5194/essd-2021-284 https://essd.copernicus.org/preprints/essd-2021-284/ eng eng doi:10.5194/essd-2021-284 https://essd.copernicus.org/preprints/essd-2021-284/ eISSN: 1866-3516 Text 2021 ftcopernicus https://doi.org/10.5194/essd-2021-284 2021-09-13T16:22:29Z A dataset of microphysical cloud parameters from optically thin clouds, retrieved from infrared spectral radiances measured in summer 2017 in the Arctic, is presented. Measurements were conducted using a mobile Fourier-transform infrared (FTIR) spectrometer which was carried by the RV Polarstern . This dataset contains retrieved optical depths and effective radii of ice and water, from which the liquid water path and ice water path are calculated. These water paths and the effective radii are compared with derived quantities from a combined cloud radar, lidar and microwave radiometer measurement synergy retrieval, called Cloudnet. Comparing the liquid water paths from the infrared retrieval and Cloudnet shows significant correlations with a standard deviation of 8.60 g · m −2 . Although liquid water path retrievals from microwave radiometer data come with a uncertainty of at least 20 g · m −2 , a significant correlation and a standard deviation of 5.32 g · m −2 between the results of clouds with a liquid water path of at most 20 g · m −2 retrieved from infrared spectra and results from Cloudnet can be seen. Therefore, despite its large uncertainty, the comparison with data retrieved from infrared spectra shows that optically thin clouds of the measurement campaign in summer 2017 can be observed well using microwave radiometers within the Cloudnet framework. Apart from this, the dataset of microphysical cloud properties presented here allows to perform calculations of the cloud radiative effects, when the Cloudnet data from the campaign are not available, which was from the 22nd July 2017 until the 19th August 2017. The dataset is published at Pangaea (Richter et al., 2021). Text Arctic Copernicus Publications: E-Journals Arctic
institution Open Polar
collection Copernicus Publications: E-Journals
op_collection_id ftcopernicus
language English
description A dataset of microphysical cloud parameters from optically thin clouds, retrieved from infrared spectral radiances measured in summer 2017 in the Arctic, is presented. Measurements were conducted using a mobile Fourier-transform infrared (FTIR) spectrometer which was carried by the RV Polarstern . This dataset contains retrieved optical depths and effective radii of ice and water, from which the liquid water path and ice water path are calculated. These water paths and the effective radii are compared with derived quantities from a combined cloud radar, lidar and microwave radiometer measurement synergy retrieval, called Cloudnet. Comparing the liquid water paths from the infrared retrieval and Cloudnet shows significant correlations with a standard deviation of 8.60 g · m −2 . Although liquid water path retrievals from microwave radiometer data come with a uncertainty of at least 20 g · m −2 , a significant correlation and a standard deviation of 5.32 g · m −2 between the results of clouds with a liquid water path of at most 20 g · m −2 retrieved from infrared spectra and results from Cloudnet can be seen. Therefore, despite its large uncertainty, the comparison with data retrieved from infrared spectra shows that optically thin clouds of the measurement campaign in summer 2017 can be observed well using microwave radiometers within the Cloudnet framework. Apart from this, the dataset of microphysical cloud properties presented here allows to perform calculations of the cloud radiative effects, when the Cloudnet data from the campaign are not available, which was from the 22nd July 2017 until the 19th August 2017. The dataset is published at Pangaea (Richter et al., 2021).
format Text
author Richter, Philipp
Palm, Mathias
Weinzierl, Christine
Griesche, Hannes
Rowe, Penny M.
Notholt, Justus
spellingShingle Richter, Philipp
Palm, Mathias
Weinzierl, Christine
Griesche, Hannes
Rowe, Penny M.
Notholt, Justus
A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017
author_facet Richter, Philipp
Palm, Mathias
Weinzierl, Christine
Griesche, Hannes
Rowe, Penny M.
Notholt, Justus
author_sort Richter, Philipp
title A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017
title_short A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017
title_full A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017
title_fullStr A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017
title_full_unstemmed A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017
title_sort dataset of microphysical cloud parameters, retrieved from emission-ftir spectra measured in arctic summer 2017
publishDate 2021
url https://doi.org/10.5194/essd-2021-284
https://essd.copernicus.org/preprints/essd-2021-284/
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source eISSN: 1866-3516
op_relation doi:10.5194/essd-2021-284
https://essd.copernicus.org/preprints/essd-2021-284/
op_doi https://doi.org/10.5194/essd-2021-284
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