2019
DOI: 10.3390/rs11030251
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The GEWEX Water Vapor Assessment: Overview and Introduction to Results and Recommendations

Abstract: To date, a large variety of water vapour data records from satellite and reanalysis are available. It is key to understand the quality and uncertainty of these data records in order to fully exploit these records and to avoid data being employed incorrectly or misinterpreted. Therefore, it is important to inform users on accuracy and limitations of these data records based on consistent inter-comparisons carried out in the framework of international assessments. Addressing this challenge is the major objective… Show more

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Cited by 36 publications
(44 citation statements)
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References 55 publications
(84 reference statements)
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“…Even for a given weather event, the distribution of the precipitation can have large variance. Shiu et al (2012) results suggest that reanalyses can reproduce the temperature-precipitation relationship as temperature increases, but the more recent reanalyses had higher variance than the older generation. The long-term collection of daily reanalyses precipitation here will help characterize and understand the state of the reanalyses abilities to reproduce the high-frequency occurrences of extreme precipitation.…”
Section: The Reanalysis Productsmentioning
confidence: 91%
“…Even for a given weather event, the distribution of the precipitation can have large variance. Shiu et al (2012) results suggest that reanalyses can reproduce the temperature-precipitation relationship as temperature increases, but the more recent reanalyses had higher variance than the older generation. The long-term collection of daily reanalyses precipitation here will help characterize and understand the state of the reanalyses abilities to reproduce the high-frequency occurrences of extreme precipitation.…”
Section: The Reanalysis Productsmentioning
confidence: 91%
“…Finally, the mean precipitation was added again. This approach was also applied by [24]. (2) For each region, for each metric and for the period January 2001-December 2013, the ensemble mean was computed.…”
Section: Time Seriesmentioning
confidence: 99%
“…As opposed to previous studies assessing the performance of break detection methods on benchmark time series (e.g., Venema et al, 2012), the analysis presented here is atypical in many aspects. First, although the homogenization of IWV time series with statistical break detection methods has already been presented in earlier studies (Ning et al, 2016; Schröder et al, 2016; Schröder et al, 2019; Vey et al, 2009), the assessment of the performance of these methods has never been checked for IWV. Venema et al (2012) showed that the break detection methods perform differently for temperature and precipitation, so a satisfactory performance for IWV data has not been guaranteed.…”
Section: Discussionmentioning
confidence: 99%
“…Therefore, in this study, we have used ERA‐Interim reanalysis IWV data extracted at the site locations. The drawbacks of this approach are representativeness differences between the two IWV data sets at a number of sites (Bock & Parracho, 2019) and the possible presence of inhomogeneities in the reference ERA‐Interim data set as well (Ning et al, 2016; Schröder et al, 2016; Schröder et al, 2019). Representativeness differences might result in seasonality and trends in the difference time series, while remaining inhomogeneities in ERA‐Interim, even after 4‐D variational bias correction in the data assimilation, might be responsible for trends in the differences time series.…”
Section: Discussionmentioning
confidence: 99%
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