Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010
A growing body of research indicates that biomass and industrial aerosols from mid-latitudes have a broad range of effects on arctic climatological systems. Pollutant aerosols directly and indirectly perturb solar reflection and thermal radiative emission in the atmosphere, and soot accelerates melt...
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Arctic Data Center
2017
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dataone:doi:10.18739/A2TS1X 2023-11-08T14:14:16+01:00 Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 Quentin Coopman Timothy J. Garrett Jerome Riedi Douglas P. Finch Latitudes greater than 65 degree north above ocean ENVELOPE(-180.0,180.0,85.0,65.0) BEGINDATE: 2005-03-15T00:00:00Z ENDDATE: 2010-09-30T00:00:00Z 2017-12-12T00:00:00Z https://doi.org/10.18739/A2TS1X unknown Arctic Data Center Dataset 2017 dataone:urn:node:ARCTIC https://doi.org/10.18739/A2TS1X 2023-11-08T13:41:09Z A growing body of research indicates that biomass and industrial aerosols from mid-latitudes have a broad range of effects on arctic climatological systems. Pollutant aerosols directly and indirectly perturb solar reflection and thermal radiative emission in the atmosphere, and soot accelerates melting when it accumulates on snow. Nonetheless, much remains unknown about how pollution plumes are modifying arctic cloud properties and precipitation. Consequently, the impact of pollution on the arctic climate system is not well understood. Past research into aerosol-cloud interactions in the Arctic has generally focused on small time and spatial scales, using a combination of aircraft and numerical modeling work. Less research has investigated these processes over climatological time scales and pan-Arctic spatial scales. In this data set researchers co-localized space-based observations with numerical model and reanalysis output to spatially and temporally co-localized pollution, cloud, and meteorological parameters. This package contains a Python script that contains a function (Read_PM*) to read input files (.p) and provides co-localized information of cloud microphysical properties, CO concentration, and atmospheric parameters. Dataset Arctic Arctic Data Center (via DataONE) Arctic ENVELOPE(-180.0,180.0,85.0,65.0) |
institution |
Open Polar |
collection |
Arctic Data Center (via DataONE) |
op_collection_id |
dataone:urn:node:ARCTIC |
language |
unknown |
description |
A growing body of research indicates that biomass and industrial aerosols from mid-latitudes have a broad range of effects on arctic climatological systems. Pollutant aerosols directly and indirectly perturb solar reflection and thermal radiative emission in the atmosphere, and soot accelerates melting when it accumulates on snow. Nonetheless, much remains unknown about how pollution plumes are modifying arctic cloud properties and precipitation. Consequently, the impact of pollution on the arctic climate system is not well understood. Past research into aerosol-cloud interactions in the Arctic has generally focused on small time and spatial scales, using a combination of aircraft and numerical modeling work. Less research has investigated these processes over climatological time scales and pan-Arctic spatial scales. In this data set researchers co-localized space-based observations with numerical model and reanalysis output to spatially and temporally co-localized pollution, cloud, and meteorological parameters. This package contains a Python script that contains a function (Read_PM*) to read input files (.p) and provides co-localized information of cloud microphysical properties, CO concentration, and atmospheric parameters. |
format |
Dataset |
author |
Quentin Coopman Timothy J. Garrett Jerome Riedi Douglas P. Finch |
spellingShingle |
Quentin Coopman Timothy J. Garrett Jerome Riedi Douglas P. Finch Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 |
author_facet |
Quentin Coopman Timothy J. Garrett Jerome Riedi Douglas P. Finch |
author_sort |
Quentin Coopman |
title |
Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 |
title_short |
Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 |
title_full |
Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 |
title_fullStr |
Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 |
title_full_unstemmed |
Collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the Arctic, 2005-2010 |
title_sort |
collocation of cloud microphysical properties from space-based instruments, carbon monoxide concentration from a numerical model, and meteorological parameters from reanalysis in the arctic, 2005-2010 |
publisher |
Arctic Data Center |
publishDate |
2017 |
url |
https://doi.org/10.18739/A2TS1X |
op_coverage |
Latitudes greater than 65 degree north above ocean ENVELOPE(-180.0,180.0,85.0,65.0) BEGINDATE: 2005-03-15T00:00:00Z ENDDATE: 2010-09-30T00:00:00Z |
long_lat |
ENVELOPE(-180.0,180.0,85.0,65.0) |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_doi |
https://doi.org/10.18739/A2TS1X |
_version_ |
1782012662489546752 |