Naakka, T, Nygård, T, Tjernström, M et al. (3 more authors) (2019) The impact of radiosounding observations on numerical weather prediction analyses in the Arctic. Geophysical Research Letters, 46 (14). pp. 8527-8535. ISSN 0094-8276
Abstract
The radiosounding network in the Arctic, despite being sparse, is a crucial part of the atmospheric observing system for weather prediction and reanalysis. The spatial coverage of the network was evaluated using a numerical weather prediction model, comparing radiosonde observations from Arctic land stations and expeditions in the central Arctic Ocean with operational analyses and background fields (12h forecasts) from ECMWF for January 2016 – September 2018. The results show that the impact of radiosonde observations on analyses has large geographical variation. In data‐sparse areas, such as the central Arctic Ocean, high‐quality radiosonde observations substantially improve the analyses, while satellite observations are not able to compensate for the large spatial gap in the radiosounding network. In areas where the network is reasonably dense, the quality of background field is more related to how radiosonde observations are utilized in the assimilation and to the quality of those observations.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2019, American Geophysical Union. All Rights Reserved. This is the published version of a paper published in Geophysical Research Letters. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Radiosoundings; Observational network; Data assimilation; Arctic |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Funding Information: | Funder Grant number NERC NE/R009686/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Jul 2019 10:20 |
Last Modified: | 18 Jan 2020 01:40 |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1029/2019GL083332 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148780 |