Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting

Satellite-observed microwave radiances provide information on both surface and atmosphere. For operational weather forecasting, information on atmospheric temperature, humidity, cloud and precipitation is directly inferred using all-sky radiance data assimilation. In contrast, information on the sur...

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Main Author: Geer, Alan J
Format: Other/Unknown Material
Language:unknown
Published: Authorea, Inc. 2024
Subjects:
Online Access:http://dx.doi.org/10.22541/essoar.170431213.35796940/v1
id crwinnower:10.22541/essoar.170431213.35796940/v1
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spelling crwinnower:10.22541/essoar.170431213.35796940/v1 2024-09-15T18:34:14+00:00 Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting Geer, Alan J 2024 http://dx.doi.org/10.22541/essoar.170431213.35796940/v1 unknown Authorea, Inc. posted-content 2024 crwinnower https://doi.org/10.22541/essoar.170431213.35796940/v1 2024-08-27T04:33:03Z Satellite-observed microwave radiances provide information on both surface and atmosphere. For operational weather forecasting, information on atmospheric temperature, humidity, cloud and precipitation is directly inferred using all-sky radiance data assimilation. In contrast, information on the surface state, such as sea surface temperature (SST) and sea ice fraction, is typically provided through third-party retrieval products. Scientifically, this is a sub-optimal use of the observations, and practically it has disadvantages such as time delays of more than 48 hours. A better solution is to jointly estimate the surface and atmospheric state from the radiance observations. This has not been possible until now due to incomplete knowledge of the surface state and the radiative transfer that links this to the observed radiances. A new approach based on an empirical state and empirical sea ice surface emissivity model is used here to add sea ice state estimation, including sea ice concentration (SIC), to the European Centre for Medium-range Weather Forecasts atmospheric data assimilation system. The sea ice state is estimated using augmented control variables at the observation locations. The resulting SIC estimates are of good quality and they highlight apparent defects in the existing OCEAN5 sea ice analysis. The SIC estimates can also be used to track giant icebergs, which may provide a novel maritime application for passive microwave radiances. Further, the SIC estimates should be suitable for onward use in coupled ocean-atmosphere data assimilation. There is also increased coverage of microwave observations in the proximity of sea ice, leading to improved atmospheric forecasts out to day 4 in the Southern Ocean. Other/Unknown Material Sea ice Southern Ocean The Winnower
institution Open Polar
collection The Winnower
op_collection_id crwinnower
language unknown
description Satellite-observed microwave radiances provide information on both surface and atmosphere. For operational weather forecasting, information on atmospheric temperature, humidity, cloud and precipitation is directly inferred using all-sky radiance data assimilation. In contrast, information on the surface state, such as sea surface temperature (SST) and sea ice fraction, is typically provided through third-party retrieval products. Scientifically, this is a sub-optimal use of the observations, and practically it has disadvantages such as time delays of more than 48 hours. A better solution is to jointly estimate the surface and atmospheric state from the radiance observations. This has not been possible until now due to incomplete knowledge of the surface state and the radiative transfer that links this to the observed radiances. A new approach based on an empirical state and empirical sea ice surface emissivity model is used here to add sea ice state estimation, including sea ice concentration (SIC), to the European Centre for Medium-range Weather Forecasts atmospheric data assimilation system. The sea ice state is estimated using augmented control variables at the observation locations. The resulting SIC estimates are of good quality and they highlight apparent defects in the existing OCEAN5 sea ice analysis. The SIC estimates can also be used to track giant icebergs, which may provide a novel maritime application for passive microwave radiances. Further, the SIC estimates should be suitable for onward use in coupled ocean-atmosphere data assimilation. There is also increased coverage of microwave observations in the proximity of sea ice, leading to improved atmospheric forecasts out to day 4 in the Southern Ocean.
format Other/Unknown Material
author Geer, Alan J
spellingShingle Geer, Alan J
Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
author_facet Geer, Alan J
author_sort Geer, Alan J
title Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
title_short Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
title_full Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
title_fullStr Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
title_full_unstemmed Joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
title_sort joint estimation of sea ice and atmospheric state from microwave imagers in operational weather forecasting
publisher Authorea, Inc.
publishDate 2024
url http://dx.doi.org/10.22541/essoar.170431213.35796940/v1
genre Sea ice
Southern Ocean
genre_facet Sea ice
Southern Ocean
op_doi https://doi.org/10.22541/essoar.170431213.35796940/v1
_version_ 1810476021677293568