Process‐based evaluation of the VALUE perfect predictor experiment of statistical downscaling methods

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F19%3A00517240" target="_blank" >RIV/68378289:_____/19:00517240 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11310/19:10398773

Result on the web

<a href="https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5911" target="_blank" >https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5911</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/joc.5911" target="_blank" >10.1002/joc.5911</a>

Result language

angličtina

Original language name

Process‐based evaluation of the VALUE perfect predictor experiment of statistical downscaling methods

Original language description

Statistical downscaling methods (SDMs) are techniques used to downscale and/or bias-correct climate model results to regional or local scales. The European network VALUE developed a framework to evaluate and inter-compare SDMs. One of VALUE's experiments is the perfect predictor experiment that uses reanalysis predictors to isolate downscaling skill. Most evaluation papers for SDMs employ simple statistical diagnostics and do not follow a process-based rationale. Thus, in this paper, a process-based evaluation has been conducted for the more than 40 participating model output statistics (MOS, mostly bias correction) and perfect prognosis (PP) methods, for temperature and precipitation at 86 weather stations across Europe. The SDMs are analysed following the so-called ´regime-oriented´ technique, focussing on relevant features of the atmospheric circulation at large to local scales. These features comprise the North Atlantic Oscillation, blocking and selected Lamb weather types and at local scales the bora wind and the western Iberian coastal-low level jet. The representation of the local weather response to the selected features depends strongly on the method class. As expected, MOS is unable to generate process sensitivity when it is not simulated by the predictors (ERA-Interim). Moreover, MOS often suffers from an inflation effect when a predictor is used for more than one station. The PP performance is very diverse and depends strongly on the implementation. Although conditioned on predictors that typically describe the large-scale circulation, PP often fails in capturing the process sensitivity correctly. Stochastic generalized linear models supported by well-chosen predictors show improved skill to represent the sensitivities.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10510 - Climatic research

Project

<a href="/en/project/LD12059" target="_blank" >LD12059: Development, validation, and implementation of statistical downscaling methods</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

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

Name of the periodical

International Journal of Climatology

ISSN

0899-8418

e-ISSN

—

Volume of the periodical

39

Issue of the periodical within the volume

9 Special Issue

Country of publishing house

GB - UNITED KINGDOM

Number of pages

26

Pages from-to

3868-3893

UT code for WoS article

000474001900010

EID of the result in the Scopus database

2-s2.0-85057773069