An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F19%3A00505587" target="_blank" >RIV/68378289:_____/19:00505587 - isvavai.cz</a>

Alternative codes found

RIV/68378289:_____/19:00507882 RIV/86652079:_____/19:00505587 RIV/86652079:_____/19:00507882 RIV/00216208:11310/19:10398770

Result on the web

<a href="https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.5462" target="_blank" >https://rmets.onlinelibrary.wiley.com/doi/10.1002/joc.5462</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/joc.5462" target="_blank" >10.1002/joc.5462</a>

Result language

angličtina

Original language name

An intercomparison of a large ensemble of statistical downscaling methods over Europe: Results from the VALUE perfect predictor cross-validation experiment

Original language description

VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process-based, etc.). Here we describe the participating methods and first results from the first experiment, using 'perfect reanalysis (and reanalysis-driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics-including bias correction-and weather generators) with a total of over 50 downscaling methods representative of the most common techniques. Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method-to-method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor-predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO-CORDEX initiative (where VALUE activities have merged and follow on). Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value-cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value-cost.eu/validationportal.

Czech name

—

Czech description

—

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

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

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

36

Pages from-to

3750-3785

UT code for WoS article

000474001900006

EID of the result in the Scopus database

2-s2.0-85044278878