Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes

Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of... For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between‐type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between‐ and within‐type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901–2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long‐term variability of large‐scale circulation modes. Long‐term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within‐type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Geophysical Research: Atmospheres Wiley

Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes

Do Changing Weather Types Explain Observed Climatic Trends in the Rhine Basin? An Analysis of Within‐ and Between‐Type Changes

1IntroductionUnderstanding how hydrological change is linked to human‐induced climate change is important for water resources management and climate adaptation. Various studies investigate the variability and change of hydrologically relevant climate variables for central Europe. Specific regional scale weather patterns (WPs) or large‐scale circulation modes have been found to be related with hydrometeorological extremes; see, for example, Steirou et al. () for a review. However, the length of observational time series (mostly below 100 years) is often insufficient to investigate the statistical relationships between climatic conditions and rare flood events. A widespread approach to link hydrological extremes to variations of the large‐scale circulation is to force spatially distributed hydrological models at the catchment scale with the output from global climate models. To bridge the spatial gap between coarse global climate models and catchment models, numerous downscaling approaches have been developed; see, for example, Maraun et al. () for a review. In particular, the approach of conditioning a weather generator (WGN) by means of climate model output data offers the possibility to generate very long (≥10,000 years) synthetic time series at several locations considering the spatial correlation structure of meteorological variables (Elshamy et al., ; Fatichi et al., ; Fowler et al., , ; Hewitson & Crane, ; Kilsby et al., ; Kim et al., ; Lu et al., ; Steinschneider & Brown, ; te Linde et al., ). This approach is particularly suitable for a robust estimation of changes in floods since their statistical moments can be better captured using very long time series of climate time series.WGNs produce sequences of stationary weather. Hence, to be useful for climate change impact investigation, they need to be conditioned on large‐scale climate fields as simulated, for example, by climate models. A natural way to do this is to decompose the...
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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
©2018. American Geophysical Union. All Rights Reserved.
ISSN
2169-897X
eISSN
2169-8996
D.O.I.
10.1002/2017JD026654
Publisher site
See Article on Publisher Site

Abstract

For attributing hydrological changes to anthropogenic climate change, catchment models are driven by climate model output. A widespread approach to bridge the spatial gap between global climate and hydrological catchment models is to use a weather generator conditioned on weather patterns (WPs). This approach assumes that changes in local climate are characterized by between‐type changes of patterns. In this study we test this assumption by analyzing a previously developed WP classification for the Rhine basin, which is based on dynamic and thermodynamic variables. We quantify changes in pattern characteristics and associated climatic properties. The amount of between‐ and within‐type changes is investigated by comparing observed trends to trends resulting solely from WP occurrence. To overcome uncertainties in trend detection resulting from the selected time period, all possible periods in 1901–2010 with a minimum length of 31 years are analyzed. Increasing frequency is found for some patterns associated with high precipitation, although the trend sign highly depends on the considered period. Trends and interannual variations of WP frequencies are related to the long‐term variability of large‐scale circulation modes. Long‐term WP internal warming is evident for summer patterns and enhanced warming for spring/autumn patterns since the 1970s. Observed trends in temperature and partly in precipitation are mainly associated with frequency changes of specific WPs, but some amount of within‐type changes remains. The classification can be used for downscaling of past changes considering this limitation, but the inclusion of thermodynamic variables into the classification impedes the downscaling of future climate projections.

Journal

Journal of Geophysical Research: AtmospheresWiley

Published: Jan 16, 2018

Keywords: ; ; ; ;

References

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