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  Feasibility of ERA5 integrated water vapor trends for climate change analysis in continental Europe: An evaluation with GPS (1994–2019) by considering statistical significance

Yuan, P., Hunegnaw, A., Alshawaf, F., Awange, J., Klos, A., Teferle, F. N., 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, 112416.
https://doi.org/10.1016/j.rse.2021.112416

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 Creators:
Yuan, Peng1, Author              
Hunegnaw, Addisu2, Author
Alshawaf, Fadwa2, Author
Awange, Joseph2, Author
Klos, Anna2, Author
Teferle, Felix Norman2, Author
Kutterer, Hansjörg2, Author
Affiliations:
10 Pre-GFZ, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146023              
2External Organizations, ou_persistent22              

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 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).

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Language(s): eng - English
 Dates: 20212021
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.rse.2021.112416
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Title: Remote Sensing of Environment
Source Genre: Journal, SCI, Scopus
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Pages: - Volume / Issue: 260 Sequence Number: 112416 Start / End Page: - Identifier: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals427
Publisher: Elsevier