Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...

ECMWF Integrated Forecasting System (IFS) single-site (Oden) Cloudnet output during MOCCHA - data are used in McCusker et al. : Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System, Atmospheric Chemistry and Physics, 2023. IFS data are passed through the Cloudne...

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Main Authors: McCusker, Gillian, Vuellers, Jutta
Format: Dataset
Language:English
Published: NERC EDS Centre for Environmental Data Analysis 2023
Subjects:
Online Access:https://dx.doi.org/10.5285/4c0e990d61454c22be9030777c7fbe89
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spelling ftdatacite:10.5285/4c0e990d61454c22be9030777c7fbe89 2023-05-15T14:55:19+02:00 Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ... McCusker, Gillian Vuellers, Jutta 2023 application/xml https://dx.doi.org/10.5285/4c0e990d61454c22be9030777c7fbe89 https://catalogue.ceda.ac.uk/uuid/4c0e990d61454c22be9030777c7fbe89 en eng NERC EDS Centre for Environmental Data Analysis https://catalogue.ceda.ac.uk/uuid/7f35130cb8c947bf9013594aec6b3043 Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access. Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ . When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ https://services.ceda.ac.uk/cedasite/register/info Atmospheric sciences and Earth Observation Imagery dataset Dataset 2023 ftdatacite https://doi.org/10.5285/4c0e990d61454c22be9030777c7fbe89 2023-04-03T13:00:40Z ECMWF Integrated Forecasting System (IFS) single-site (Oden) Cloudnet output during MOCCHA - data are used in McCusker et al. : Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System, Atmospheric Chemistry and Physics, 2023. IFS data are passed through the Cloudnet algorithm to produce calibrated model data that may be used for direct comparisons with observations. Cloudnet combines cloud radar, ceilometer, microwave radiometer, and radiosonde profiles averaged to a common grid at the cloud radar resolution to derive a set of retrieved cloud properties. The Cloudnet products are designed to be used for evaluation of weather forecast models as well as fundamental process studies of cloud. From a modelling perspective, Cloudnet converts liquid and ice mass mixing ratios to the respective cloud water contents for direct comparison with observations, as well as filtering ice water contents for values that would be unobservable by radar. Note that the latitude/longitude ... Dataset Arctic DataCite Metadata Store (German National Library of Science and Technology) Arctic
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic Atmospheric sciences and Earth Observation Imagery
spellingShingle Atmospheric sciences and Earth Observation Imagery
McCusker, Gillian
Vuellers, Jutta
Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...
topic_facet Atmospheric sciences and Earth Observation Imagery
description ECMWF Integrated Forecasting System (IFS) single-site (Oden) Cloudnet output during MOCCHA - data are used in McCusker et al. : Evaluating Arctic clouds modelled with the Unified Model and Integrated Forecasting System, Atmospheric Chemistry and Physics, 2023. IFS data are passed through the Cloudnet algorithm to produce calibrated model data that may be used for direct comparisons with observations. Cloudnet combines cloud radar, ceilometer, microwave radiometer, and radiosonde profiles averaged to a common grid at the cloud radar resolution to derive a set of retrieved cloud properties. The Cloudnet products are designed to be used for evaluation of weather forecast models as well as fundamental process studies of cloud. From a modelling perspective, Cloudnet converts liquid and ice mass mixing ratios to the respective cloud water contents for direct comparison with observations, as well as filtering ice water contents for values that would be unobservable by radar. Note that the latitude/longitude ...
format Dataset
author McCusker, Gillian
Vuellers, Jutta
author_facet McCusker, Gillian
Vuellers, Jutta
author_sort McCusker, Gillian
title Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...
title_short Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...
title_full Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...
title_fullStr Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...
title_full_unstemmed Microbiology-Ocean-Cloud Coupling in the High Arctic (MOCCHA): ECMWF Integrated Forecasting System Cloudnet outputs ...
title_sort microbiology-ocean-cloud coupling in the high arctic (moccha): ecmwf integrated forecasting system cloudnet outputs ...
publisher NERC EDS Centre for Environmental Data Analysis
publishDate 2023
url https://dx.doi.org/10.5285/4c0e990d61454c22be9030777c7fbe89
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geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation https://catalogue.ceda.ac.uk/uuid/7f35130cb8c947bf9013594aec6b3043
op_rights Access to these data is available to any registered CEDA user. Please Login or Register for an account to gain access.
Use of these data is covered by the following licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/ . When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
https://services.ceda.ac.uk/cedasite/register/info
op_doi https://doi.org/10.5285/4c0e990d61454c22be9030777c7fbe89
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