The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations
Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world.Retrievals of cloud optical...
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Online Access: | http://www.osti.gov/servlets/purl/1610847 https://www.osti.gov/biblio/1610847 https://doi.org/10.5194/amt-12-5087-2019 |
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ftosti:oai:osti.gov:1610847 2023-07-30T03:55:33+02:00 The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations Shonk, Jonathan K. P. Chiu, Jui-Yuan Christine Marshak, Alexander Giles, David M. Huang, Chiung-Huei Mace, Gerald G. Benson, Sally Slutsker, Ilya Holben, Brent N. 2023-07-03 application/pdf http://www.osti.gov/servlets/purl/1610847 https://www.osti.gov/biblio/1610847 https://doi.org/10.5194/amt-12-5087-2019 unknown http://www.osti.gov/servlets/purl/1610847 https://www.osti.gov/biblio/1610847 https://doi.org/10.5194/amt-12-5087-2019 doi:10.5194/amt-12-5087-2019 54 ENVIRONMENTAL SCIENCES 2023 ftosti https://doi.org/10.5194/amt-12-5087-2019 2023-07-11T09:41:15Z Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world.Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid.This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice.Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence ofice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %. Other/Unknown Material Aerosol Robotic Network SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) Atmospheric Measurement Techniques 12 9 5087 5099 |
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Open Polar |
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SciTec Connect (Office of Scientific and Technical Information - OSTI, U.S. Department of Energy) |
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ftosti |
language |
unknown |
topic |
54 ENVIRONMENTAL SCIENCES |
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54 ENVIRONMENTAL SCIENCES Shonk, Jonathan K. P. Chiu, Jui-Yuan Christine Marshak, Alexander Giles, David M. Huang, Chiung-Huei Mace, Gerald G. Benson, Sally Slutsker, Ilya Holben, Brent N. The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations |
topic_facet |
54 ENVIRONMENTAL SCIENCES |
description |
Clouds present many challenges to climate modelling. To develop and verify the parameterisations needed to allow climate models to represent cloud structure and processes, there is a need for high-quality observations of cloud optical depth from locations around the world.Retrievals of cloud optical depth are obtainable from radiances measured by Aerosol Robotic Network (AERONET) radiometers in “cloud mode” using a two-wavelength retrieval method. However, the method is unable to detect cloud phase, and hence assumes that all of the cloud in a profile is liquid.This assumption has the potential to introduce errors into long-term statistics of retrieved optical depth for clouds that also contain ice.Using a set of idealised cloud profiles we find that, for optical depths above 20, the fractional error in retrieved optical depth is a linear function of the fraction of the optical depth that is due to the presence ofice cloud (“ice fraction”). Clouds that are entirely ice have positive errors with magnitudes of the order of 55 % to 70 %. We derive a simple linear equation that can be used as a correction at AERONET sites where ice fraction can be independently estimated. Using this linear equation, we estimate the magnitude of the error for a set of cloud profiles from five sites of the Atmospheric Radiation Measurement programme. The dataset contains separate retrievals of ice and liquid retrievals; hence ice fraction can be estimated. The magnitude of the error at each location was related to the relative frequencies of occurrence in thick frontal cloud at the mid-latitude sites and of deep convection at the tropical sites – that is, of deep cloud containing both ice and liquid particles. The long-term mean optical depth error at the five locations spans the range 2–4, which we show to be small enough to allow calculation of top-of-atmosphere flux to within 10 % and surface flux to about 15 %. |
author |
Shonk, Jonathan K. P. Chiu, Jui-Yuan Christine Marshak, Alexander Giles, David M. Huang, Chiung-Huei Mace, Gerald G. Benson, Sally Slutsker, Ilya Holben, Brent N. |
author_facet |
Shonk, Jonathan K. P. Chiu, Jui-Yuan Christine Marshak, Alexander Giles, David M. Huang, Chiung-Huei Mace, Gerald G. Benson, Sally Slutsker, Ilya Holben, Brent N. |
author_sort |
Shonk, Jonathan K. P. |
title |
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations |
title_short |
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations |
title_full |
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations |
title_fullStr |
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations |
title_full_unstemmed |
The impact of neglecting ice phase on cloud optical depth retrievals from AERONET cloud mode observations |
title_sort |
impact of neglecting ice phase on cloud optical depth retrievals from aeronet cloud mode observations |
publishDate |
2023 |
url |
http://www.osti.gov/servlets/purl/1610847 https://www.osti.gov/biblio/1610847 https://doi.org/10.5194/amt-12-5087-2019 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_relation |
http://www.osti.gov/servlets/purl/1610847 https://www.osti.gov/biblio/1610847 https://doi.org/10.5194/amt-12-5087-2019 doi:10.5194/amt-12-5087-2019 |
op_doi |
https://doi.org/10.5194/amt-12-5087-2019 |
container_title |
Atmospheric Measurement Techniques |
container_volume |
12 |
container_issue |
9 |
container_start_page |
5087 |
op_container_end_page |
5099 |
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1772817467085684736 |