Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F15%3A67739" target="_blank" >RIV/60460709:41330/15:67739 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5194/hess-19-1827-2015" target="_blank" >http://dx.doi.org/10.5194/hess-19-1827-2015</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5194/hess-19-1827-2015" target="_blank" >10.5194/hess-19-1827-2015</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

Popis výsledku v původním jazyce

Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods(SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchmen

Název v anglickém jazyce

Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe

Popis výsledku anglicky

Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods(SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchmen

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Hydrology and Earth System Sciences

ISSN

1027-5606

e-ISSN

—

Svazek periodika

19

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

21

Strana od-do

1827-1847

Kód UT WoS článku

000353877000014

EID výsledku v databázi Scopus

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