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dc.contributor.authorYuan, P.
dc.contributor.authorHunegnaw, A.
dc.contributor.authorAlshawaf, F.
dc.contributor.authorAwange, Joseph
dc.contributor.authorKlos, A.
dc.contributor.authorTeferle, F.N.
dc.contributor.authorKutterer, H.
dc.date.accessioned2021-11-25T02:36:53Z
dc.date.available2021-11-25T02:36:53Z
dc.date.issued2021
dc.identifier.citationYuan, P. and Hunegnaw, A. and Alshawaf, F. and Awange, J. and Klos, A. and Teferle, F.N. and Kutterer, H. 2021. Feasibility of ERA5 integrated water vapor trends for climate change analysis in continental Europe: An evaluation with GPS (1994–2019) by considering statistical significance. Remote Sensing of Environment. 260: ARTN 112416.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/86607
dc.identifier.doi10.1016/j.rse.2021.112416
dc.description.abstract

Although the statistical significances for the trends of integrated water vapor (IWV) are essential for a correct interpretation of climate change signals, obtaining accurate IWV trend estimates with realistic uncertainties remains a challenge. This study evaluates the feasibility of the IWV trends derived from the newly released fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) for climate change analysis in continental Europe. This is achieved by comparing the trends derived from in-situ ground-based Global Positioning System (GPS)’s daily IWV series from 1994 to 2019 at 109 stations. The realistic uncertainties and statistical significances of the IWV trends are evaluated with the time series analysis on their noise characteristics and proper noise models. Results show that autoregressive moving average ARMA(1,1) noise model is preferred rather than the commonly assumed white noise (WN) or first-order autoregressive AR(1) noise for about 68% of the ERA5 and GPS IWV series. An improper noise model would misevaluate the trend uncertainty of an IWV time series, compared with its specific preferred noise model. For example, ARMA(1,1) may misevaluate the standard deviations of their trend estimates (0.1–0.3 kg m−2 decade−1) by 10%. Nevertheless, ARMA(1,1) is recommended as the default noise model for the ERA5 and GPS IWV series. However, the preferred noise model for each ERA5 minus GPS (E-G) IWV series should be specifically determined, because the AR(1)-related models can result in an underestimation on its trend uncertainty by 90%. In contrast, power-law (PL) model can lead to an overestimation by up to nine times. The E-G IWV trends are within −0.2–0.4 kg m−2 decade−1, indicating that the ERA5 is a potential data source of IWV trends for climate change analysis in continental Europe. The ERA5 and GPS IWV trends are consistent in their magnitudes and geographical patterns, lower in Northwest Europe (0–0.4 kg m−2 decade−1) but higher around the Mediterranean Sea (0.6–1.4 kg m−2 decade−1).

dc.languageEnglish
dc.publisherELSEVIER SCIENCE INC
dc.subjectScience & Technology
dc.subjectLife Sciences & Biomedicine
dc.subjectTechnology
dc.subjectEnvironmental Sciences
dc.subjectRemote Sensing
dc.subjectImaging Science & Photographic Technology
dc.subjectEnvironmental Sciences & Ecology
dc.subjectClimate change
dc.subjectWater vapor
dc.subjectIWV
dc.subjectTrend
dc.subjectUncertainty
dc.subjectTime series
dc.subjectNoise
dc.subjectERA5
dc.subjectGPS
dc.subjectTIME-SERIES
dc.subjectNOISE
dc.subjectAUTOCORRELATION
dc.subjectMETEOROLOGY
dc.subjectREANALYSES
dc.subjectMODELS
dc.subjectREGION
dc.subjectDELAY
dc.titleFeasibility of ERA5 integrated water vapor trends for climate change analysis in continental Europe: An evaluation with GPS (1994–2019) by considering statistical significance
dc.typeJournal Article
dcterms.source.volume260
dcterms.source.issn0034-4257
dcterms.source.titleRemote Sensing of Environment
dc.date.updated2021-11-25T02:36:52Z
curtin.departmentSchool of Earth and Planetary Sciences (EPS)
curtin.accessStatusIn process
curtin.facultyFaculty of Science and Engineering
curtin.contributor.orcidAwange, Joseph [0000-0003-3533-613X]
curtin.contributor.researcheridAwange, Joseph [A-3998-2008]
curtin.identifier.article-numberARTN 112416
dcterms.source.eissn1879-0704
curtin.contributor.scopusauthoridAwange, Joseph [6603092635]


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