Downscaling the probability of heavy rainfall over the Nordic countries

<p>We used empirical–statistical downscaling to derive local statistics for 24 h 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...

Full description

Saved in:
Bibliographic Details
Main Authors: R. E. Benestad, K. M. Parding, A. Dobler
Format: Article
Language:English
Published: Copernicus Publications 2025-01-01
Series:Hydrology and Earth System Sciences
Online Access:https://hess.copernicus.org/articles/29/45/2025/hess-29-45-2025.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1841558594320859136
author R. E. Benestad
K. M. Parding
A. Dobler
author_facet R. E. Benestad
K. M. Parding
A. Dobler
author_sort R. E. Benestad
collection DOAJ
description <p>We used empirical–statistical downscaling to derive local statistics for 24 h 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 (IDF) 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, <span class="inline-formula"><i>f</i><sub>w</sub></span>, and the wet-day mean precipitation, <span class="inline-formula"><i>μ</i></span>. 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 and 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 aspects of the covariance, and there was a good match between annual wet-day frequency and wet-day mean precipitation derived from ERA5 on the one hand and local rain gauges in the Nordic region on the other. Furthermore, the ensemble downscaled results for annual <span class="inline-formula"><i>f</i><sub>w</sub></span> and <span class="inline-formula"><i>μ</i></span> 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 d<span class="inline-formula"><sup>−1</sup></span> 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.</p>
format Article
id doaj-art-8a8156a1a3874955adf656cbd31f0f7e
institution Kabale University
issn 1027-5606
1607-7938
language English
publishDate 2025-01-01
publisher Copernicus Publications
record_format Article
series Hydrology and Earth System Sciences
spelling doaj-art-8a8156a1a3874955adf656cbd31f0f7e2025-01-06T08:37:06ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382025-01-0129456510.5194/hess-29-45-2025Downscaling the probability of heavy rainfall over the Nordic countriesR. E. Benestad0K. M. Parding1A. Dobler2Norwegian Meteorological Institute, Henrik Mohns plass 1, Oslo 0313, NorwayNorwegian Meteorological Institute, Henrik Mohns plass 1, Oslo 0313, NorwayNorwegian Meteorological Institute, Henrik Mohns plass 1, Oslo 0313, Norway<p>We used empirical–statistical downscaling to derive local statistics for 24 h 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 (IDF) 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, <span class="inline-formula"><i>f</i><sub>w</sub></span>, and the wet-day mean precipitation, <span class="inline-formula"><i>μ</i></span>. 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 and 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 aspects of the covariance, and there was a good match between annual wet-day frequency and wet-day mean precipitation derived from ERA5 on the one hand and local rain gauges in the Nordic region on the other. Furthermore, the ensemble downscaled results for annual <span class="inline-formula"><i>f</i><sub>w</sub></span> and <span class="inline-formula"><i>μ</i></span> 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 d<span class="inline-formula"><sup>−1</sup></span> 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.</p>https://hess.copernicus.org/articles/29/45/2025/hess-29-45-2025.pdf
spellingShingle R. E. Benestad
K. M. Parding
A. Dobler
Downscaling the probability of heavy rainfall over the Nordic countries
Hydrology and Earth System Sciences
title Downscaling the probability of heavy rainfall over the Nordic countries
title_full Downscaling the probability of heavy rainfall over the Nordic countries
title_fullStr Downscaling the probability of heavy rainfall over the Nordic countries
title_full_unstemmed Downscaling the probability of heavy rainfall over the Nordic countries
title_short Downscaling the probability of heavy rainfall over the Nordic countries
title_sort downscaling the probability of heavy rainfall over the nordic countries
url https://hess.copernicus.org/articles/29/45/2025/hess-29-45-2025.pdf
work_keys_str_mv AT rebenestad downscalingtheprobabilityofheavyrainfalloverthenordiccountries
AT kmparding downscalingtheprobabilityofheavyrainfalloverthenordiccountries
AT adobler downscalingtheprobabilityofheavyrainfalloverthenordiccountries