The importance of simulated errors in observing system simulation experiments

Observing System Simulation Experiments (OSSEs) for numerical weather prediction rely on simulated observations that should include simulated observation errors in order to realistically represent the behaviour of real data. Real observations include many types of error, such as instrument error, re...

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Autores principales:	Nikki C. PrivÉ, Ronald M. Errico, Will McCarty
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	data assimilation observing system simulation experiment observation error Oceanography GC1-1581 Meteorology. Climatology QC851-999
Acceso en línea:	https://doaj.org/article/b0e9ff9bf69a4bc7b6b14da9676d8281
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spelling	oai:doaj.org-article:b0e9ff9bf69a4bc7b6b14da9676d82812021-12-01T14:40:58ZThe importance of simulated errors in observing system simulation experiments1600-087010.1080/16000870.2021.1886795https://doaj.org/article/b0e9ff9bf69a4bc7b6b14da9676d82812021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/16000870.2021.1886795https://doaj.org/toc/1600-0870Observing System Simulation Experiments (OSSEs) for numerical weather prediction rely on simulated observations that should include simulated observation errors in order to realistically represent the behaviour of real data. Real observations include many types of error, such as instrument error, representativeness error, and observation operator error, with some portion of this error being correlated in time and space or possibly between data types. Data assimilation systems are designed to account for random, uncorrelated errors, but are not yet adept at handling correlated errors; as a result, the correlated errors are more readily incorporated into the analysis increment by the data assimilation system than uncorrelated errors. In this work, the role of correlated observation errors in modifying the behaviour of the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE framework is investigated. The effects on analysis increment, analysis error, forecast errors and observation impacts of including or neglecting correlated simulated errors is explored. The use of correlated observations for calibration and validation of the OSSE is also discussed.Nikki C. PrivÉRonald M. ErricoWill McCartyTaylor & Francis Grouparticledata assimilationobserving system simulation experimentobservation errorOceanographyGC1-1581Meteorology. ClimatologyQC851-999ENTellus: Series A, Dynamic Meteorology and Oceanography, Vol 73, Iss 1, Pp 1-17 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	data assimilation observing system simulation experiment observation error Oceanography GC1-1581 Meteorology. Climatology QC851-999
spellingShingle	data assimilation observing system simulation experiment observation error Oceanography GC1-1581 Meteorology. Climatology QC851-999 Nikki C. PrivÉ Ronald M. Errico Will McCarty The importance of simulated errors in observing system simulation experiments
description	Observing System Simulation Experiments (OSSEs) for numerical weather prediction rely on simulated observations that should include simulated observation errors in order to realistically represent the behaviour of real data. Real observations include many types of error, such as instrument error, representativeness error, and observation operator error, with some portion of this error being correlated in time and space or possibly between data types. Data assimilation systems are designed to account for random, uncorrelated errors, but are not yet adept at handling correlated errors; as a result, the correlated errors are more readily incorporated into the analysis increment by the data assimilation system than uncorrelated errors. In this work, the role of correlated observation errors in modifying the behaviour of the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO) OSSE framework is investigated. The effects on analysis increment, analysis error, forecast errors and observation impacts of including or neglecting correlated simulated errors is explored. The use of correlated observations for calibration and validation of the OSSE is also discussed.
format	article
author	Nikki C. PrivÉ Ronald M. Errico Will McCarty
author_facet	Nikki C. PrivÉ Ronald M. Errico Will McCarty
author_sort	Nikki C. PrivÉ
title	The importance of simulated errors in observing system simulation experiments
title_short	The importance of simulated errors in observing system simulation experiments
title_full	The importance of simulated errors in observing system simulation experiments
title_fullStr	The importance of simulated errors in observing system simulation experiments
title_full_unstemmed	The importance of simulated errors in observing system simulation experiments
title_sort	importance of simulated errors in observing system simulation experiments
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/b0e9ff9bf69a4bc7b6b14da9676d8281
work_keys_str_mv	AT nikkicprive theimportanceofsimulatederrorsinobservingsystemsimulationexperiments AT ronaldmerrico theimportanceofsimulatederrorsinobservingsystemsimulationexperiments AT willmccarty theimportanceofsimulatederrorsinobservingsystemsimulationexperiments AT nikkicprive importanceofsimulatederrorsinobservingsystemsimulationexperiments AT ronaldmerrico importanceofsimulatederrorsinobservingsystemsimulationexperiments AT willmccarty importanceofsimulatederrorsinobservingsystemsimulationexperiments
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The importance of simulated errors in observing system simulation experiments

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