04 Jun 2024
 | 04 Jun 2024
Status: this preprint is open for discussion.

Downscaling the probability of heavy rainfall over the Nordic countries

Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler

Abstract. We used empirical-statistical downscaling to derive local statistics for 24-hr and sub-daily precipitation over the Nordic countries, based on large-scale information provided by global climate models. The local statistics included probabilities for heavy precipitation and intensity-duration-frequency curves for sub-daily rainfall. The downscaling was based on estimating key parameters defining the shape of mathematical curves describing probabilities and return-values, namely the annual wet-day frequency fw and the wet-day mean precipitation μ. Both parameters were used as predictands representing local precipitation statistics as well as predictors representing large-scale conditions. We used multi-model ensembles of global climate model (CMIP6) simulations, calibrated on the ERA5 reanalysis, to derive local projections for future outlooks. Our analysis included an evaluation of how well the global climate models reproduced the predictors, in addition to assessing the quality of downscaled precipitation statistics. The evaluation suggested that present global climate models capture essential covariance, and there was a good match between annual wet-day frequency and wet-day mean precipitation derived from ERA5 and local rain gauges in the Nordic region. Furthermore, the ensemble downscaled results for fw and μ were approximately normally distributed which may justify using the ensemble mean and standard deviation to describe the ensemble spread. Hence, our efforts provide a demonstration for how empirical-statistical downscaling can be used to provide practical information on heavy rainfall which subsequently may be used for impact studies. Future projections for the Nordic region indicated little increase in precipitation due to more wet days, but most of the contribution comes from increased mean intensity. The west coast of Norway had the highest probabilities of receiving more than 30 mm/day precipitation, but the strongest relative trend in this probability was projected over northern Finland. Furthermore, the highest estimates for trends in 10-year and 25-year return-values were projected over western Norway where they were high from the outset. Our results also suggested that future precipitation intensity is sensitive to future emissions whereas the wet-day frequency is less sensitive.

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Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler

Status: open (until 30 Jul 2024)

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Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler
Rasmus E. Benestad, Kajsa M. Parding, and Andreas Dobler


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Short summary
The paper presents a method for deriving the chance of heavy downpour, the maximum amount expected at various intervals, and explain how the rainfall changes. It suggests that increases are more due to increased amounts on wet days rather than more wet days, and the rainfall intensity is found to be sensitive to future greenhouse gas emissions while the number of wet days appears to be less affected.