An R package for assessment of statistical downscaling methods for hydrological climate change impact studies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F17%3A73643" target="_blank" >RIV/60460709:41330/17:73643 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.envsoft.2017.03.036" target="_blank" >http://dx.doi.org/10.1016/j.envsoft.2017.03.036</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.envsoft.2017.03.036" target="_blank" >10.1016/j.envsoft.2017.03.036</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An R package for assessment of statistical downscaling methods for hydrological climate change impact studies

Popis výsledku v původním jazyce

Due to inherent bias the climate model simulated precipitation and temperature cannot be used to drive a hydrological model without pre-processing - statistical downscaling. This often consists of reducing the bias in the climate model simulations (bias correction) and/or transformation of the observed data in order to match the projected changes (delta change). The validation of the statistical downscaling methods is typically limited to the scale for which the transformation was calibrated and the driving variables (precipitation and temperature) of the hydrological model. The paper introduces an R package musica which provides ready to use tools for routine validation of statistical downscaling methods at multiple time scales as well as several advanced methods for statistical downscaling. The musica package is used to validate simulated runoff. It is shown that using conventional methods for downscaling of precipitation and temperature often leads to substantial biases in simulated runoff at all

Název v anglickém jazyce

An R package for assessment of statistical downscaling methods for hydrological climate change impact studies

Popis výsledku anglicky

Due to inherent bias the climate model simulated precipitation and temperature cannot be used to drive a hydrological model without pre-processing - statistical downscaling. This often consists of reducing the bias in the climate model simulations (bias correction) and/or transformation of the observed data in order to match the projected changes (delta change). The validation of the statistical downscaling methods is typically limited to the scale for which the transformation was calibrated and the driving variables (precipitation and temperature) of the hydrological model. The paper introduces an R package musica which provides ready to use tools for routine validation of statistical downscaling methods at multiple time scales as well as several advanced methods for statistical downscaling. The musica package is used to validate simulated runoff. It is shown that using conventional methods for downscaling of precipitation and temperature often leads to substantial biases in simulated runoff at all

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10503 - Water resources

Projekt

<a href="/cs/project/GA16-16549S" target="_blank" >GA16-16549S: Půdní a hydrologické sucho v měnícím se klimatu</a><br>

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

Environmental Modelling & Software

ISSN

1364-8152

e-ISSN

—

Svazek periodika

2017

Číslo periodika v rámci svazku

95

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

7

Strana od-do

22-28

Kód UT WoS článku

000406177500003

EID výsledku v databázi Scopus

2-s2.0-85013014176