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Volume 17, issue 7 | Copyright

Special issue: Risk and uncertainty estimation in natural hazards

Nat. Hazards Earth Syst. Sci., 17, 993-1001, 2017
https://doi.org/10.5194/nhess-17-993-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 03 Jul 2017

Research article | 03 Jul 2017

Simple and approximate estimations of future precipitation return values

Rasmus E. Benestad, Kajsa M. Parding, Abdelkader Mezghani, and Anita V. Dyrrdal Rasmus E. Benestad et al.
  • The Norwegian Meteorological Institute, Henrik Mohns Plass 1, Oslo, 0313, Norway

Abstract. We present estimates of future 20-year return values for 24h precipitation based on multi-model ensembles of temperature projections and a crude method to quantify how warmer conditions may influence precipitation intensity. Our results suggest an increase by as much as 40–50% projected for 2100 for a number of locations in Europe, assuming the high Representative Concentration Pathway (RCP) 8.5 emission scenario. The new strategy was based on combining physical understandings with the limited information available, and it utilised the covariance between the mean seasonal variations in precipitation intensity and the North Atlantic saturation vapour pressure. Rather than estimating the expected values and interannual variability, we tried to estimate an upper bound for the response in the precipitation intensity based on the assumption that the seasonal variations in the precipitation intensity are caused by the seasonal variations in temperature. Return values were subsequently derived from the estimated precipitation intensity through a simple and approximate scheme that combined the 1-year 24h precipitation return values and downscaled annual wet-day mean precipitation for a 20-year event. The latter was based on the 95th percentile of a multi-model ensemble spread of downscaled climate model results. We found geographical variations in the shape of the seasonal cycle of the wet-day mean precipitation which suggest that different rain-producing mechanisms dominate in different regions. These differences indicate that the simple method used here to estimate the response of precipitation intensity to temperature was more appropriate for convective precipitation than for orographic rainfall.

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We propose a strategy for quantifying the maximum effect a temperature change has on heavy precipitation amounts, making use of the limited available sources of information: laws of physics, seasonal variations, mathematical estimation of probability, and s large number of climate model results. An upper bound is estimated rather than the most likely value.
We propose a strategy for quantifying the maximum effect a temperature change has on heavy...
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