Multisite bias correction of precipitation data from regional climate models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F17%3A73644" target="_blank" >RIV/60460709:41330/17:73644 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985874:_____/17:00462443

Výsledek na webu

<a href="http://dx.doi.org/10.1002/joc.4890" target="_blank" >http://dx.doi.org/10.1002/joc.4890</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/joc.4890" target="_blank" >10.1002/joc.4890</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multisite bias correction of precipitation data from regional climate models

Popis výsledku v původním jazyce

The characteristics of precipitation in regional climate model simulations deviate considerably from those of the observed data, therefore, bias correction is a standard part of most climate change impact assessment studies. The standard approach is that the corrections are calibrated and applied separately for individual spatial points and meteorological variables. For this reason, the correlation and covariance structures of the observed and corrected data differ, although the individual observed and corrected data sets correspond well in their statistical indicators. This inconsistency may affect impact studies using corrected simulations. This study presents a new approach to the bias correction utilizing principal components in combination with quantile mapping, which allows for the correction of multivariate data sets. The proposed procedure significantly reduces the bias in covariance and correlation structures, as well as that in the distribution of individual variables. This is in contras

Název v anglickém jazyce

Multisite bias correction of precipitation data from regional climate models

Popis výsledku anglicky

The characteristics of precipitation in regional climate model simulations deviate considerably from those of the observed data, therefore, bias correction is a standard part of most climate change impact assessment studies. The standard approach is that the corrections are calibrated and applied separately for individual spatial points and meteorological variables. For this reason, the correlation and covariance structures of the observed and corrected data differ, although the individual observed and corrected data sets correspond well in their statistical indicators. This inconsistency may affect impact studies using corrected simulations. This study presents a new approach to the bias correction utilizing principal components in combination with quantile mapping, which allows for the correction of multivariate data sets. The proposed procedure significantly reduces the bias in covariance and correlation structures, as well as that in the distribution of individual variables. This is in contras

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10510 - Climatic research

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

INTERNATIONAL JOURNAL OF CLIMATOLOGY

ISSN

0899-8418

e-ISSN

—

Svazek periodika

37

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

13

Strana od-do

2934-2946

Kód UT WoS článku

000404849200011

EID výsledku v databázi Scopus

2-s2.0-84992371652