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Modeling the scaling of short‐duration precipitation extremes with temperature

Hans Van de Vyver, Bert Van Schaeybroeck (UGent) , Rozemien De Troch (UGent) , Rafiq Hamdi (UGent) and Piet Termonia (UGent)
(2019) EARTH AND SPACE SCIENCE. 6(10). p.2031-2041
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Abstract
The Clausius-Clapeyron (CC) relation expresses the exponential increase in the moisture-holding capacity of air of approximately 7%/degrees C. Earlier studies show that extreme hourly precipitation increases with daily mean temperature, consistent with the CC relation. Recent studies at specific locations found that for temperatures higher than around 12 degrees C, hourly precipitation extremes scale at rates higher than the CC scaling, a phenomenon that is often referred to as "super-CC scaling." These scalings are typically estimated by collecting rainfall data in temperature bins, followed by a linear fit or a visual inspection of the precipitation quantiles in each bin. In this study, a piecewise linear quantile regression model is presented for a more flexible, and robust estimation of the scaling parameters, and their associated uncertainties. Moreover, we use associated information criteria to prove statistically whether or not a pronounced super-CC scaling exists. The techniques were tested on stochastically simulated data and, when applied to hourly station data across Western Europe and Scandinavia, revealed large uncertainties in the scaling rates. Finally, goodness-of-fit measures indicated that the dew point temperature is a better scaling predictor than temperature.
Keywords
extreme precipitation, climate change, quantile regression, CLIMATE-CHANGE, FLOOD RISK, INCREASE, SENSITIVITY, REGRESSION, TRENDS

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MLA
Van de Vyver, Hans, et al. “Modeling the Scaling of Short‐duration Precipitation Extremes with Temperature.” EARTH AND SPACE SCIENCE, vol. 6, no. 10, 2019, pp. 2031–41, doi:10.1029/2019ea000665.
APA
Van de Vyver, H., Van Schaeybroeck, B., De Troch, R., Hamdi, R., & Termonia, P. (2019). Modeling the scaling of short‐duration precipitation extremes with temperature. EARTH AND SPACE SCIENCE, 6(10), 2031–2041. https://doi.org/10.1029/2019ea000665
Chicago author-date
Van de Vyver, Hans, Bert Van Schaeybroeck, Rozemien De Troch, Rafiq Hamdi, and Piet Termonia. 2019. “Modeling the Scaling of Short‐duration Precipitation Extremes with Temperature.” EARTH AND SPACE SCIENCE 6 (10): 2031–41. https://doi.org/10.1029/2019ea000665.
Chicago author-date (all authors)
Van de Vyver, Hans, Bert Van Schaeybroeck, Rozemien De Troch, Rafiq Hamdi, and Piet Termonia. 2019. “Modeling the Scaling of Short‐duration Precipitation Extremes with Temperature.” EARTH AND SPACE SCIENCE 6 (10): 2031–2041. doi:10.1029/2019ea000665.
Vancouver
1.
Van de Vyver H, Van Schaeybroeck B, De Troch R, Hamdi R, Termonia P. Modeling the scaling of short‐duration precipitation extremes with temperature. EARTH AND SPACE SCIENCE. 2019;6(10):2031–41.
IEEE
[1]
H. Van de Vyver, B. Van Schaeybroeck, R. De Troch, R. Hamdi, and P. Termonia, “Modeling the scaling of short‐duration precipitation extremes with temperature,” EARTH AND SPACE SCIENCE, vol. 6, no. 10, pp. 2031–2041, 2019.
@article{8631808,
  abstract     = {{The Clausius-Clapeyron (CC) relation expresses the exponential increase in the moisture-holding capacity of air of approximately 7%/degrees C. Earlier studies show that extreme hourly precipitation increases with daily mean temperature, consistent with the CC relation. Recent studies at specific locations found that for temperatures higher than around 12 degrees C, hourly precipitation extremes scale at rates higher than the CC scaling, a phenomenon that is often referred to as "super-CC scaling." These scalings are typically estimated by collecting rainfall data in temperature bins, followed by a linear fit or a visual inspection of the precipitation quantiles in each bin. In this study, a piecewise linear quantile regression model is presented for a more flexible, and robust estimation of the scaling parameters, and their associated uncertainties. Moreover, we use associated information criteria to prove statistically whether or not a pronounced super-CC scaling exists. The techniques were tested on stochastically simulated data and, when applied to hourly station data across Western Europe and Scandinavia, revealed large uncertainties in the scaling rates. Finally, goodness-of-fit measures indicated that the dew point temperature is a better scaling predictor than temperature.}},
  author       = {{Van de Vyver, Hans and Van Schaeybroeck, Bert and De Troch, Rozemien and Hamdi, Rafiq and Termonia, Piet}},
  issn         = {{2333-5084}},
  journal      = {{EARTH AND SPACE SCIENCE}},
  keywords     = {{extreme precipitation,climate change,quantile regression,CLIMATE-CHANGE,FLOOD RISK,INCREASE,SENSITIVITY,REGRESSION,TRENDS}},
  language     = {{eng}},
  number       = {{10}},
  pages        = {{2031--2041}},
  title        = {{Modeling the scaling of short‐duration precipitation extremes with temperature}},
  url          = {{http://doi.org/10.1029/2019ea000665}},
  volume       = {{6}},
  year         = {{2019}},
}
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