The EUPPBench postprocessing benchmark dataset v1.0

Demaeyer, Jonathan (avtor), Bhend, Jonas (avtor), Lerch, Sebastian (avtor), Primo, Cristina (avtor), Van Schaeybroeck, Bert (avtor), Atencia, Aitor (avtor), Bouallègue, Zied Ben (avtor), Chen, Jieyu (avtor), Dabernig, Markus (avtor), Evans, Gavin (avtor), Faganeli Pucer, Jana (avtor), Hooper, Ben (avtor), Horat, Nina (avtor), Jobst, David (avtor), Merše, Janko (avtor), Mlakar, Peter (avtor), Möller, Annette (avtor), Mestre, Olivier (avtor), Taillardat, Maxime (avtor), Vannitsem, Stéphane (avtor)

Statistical postprocessing of medium-range weather forecasts is an important component of modern forecasting systems. Since the beginning of modern data science, numerous new postprocessing methods have been proposed, complementing an already very diverse field. However, one of the questions that frequently arises when considering different methods in the framework of implementing operational postprocessing is the relative performance of the methods for a given specific task. It is particularly challenging to find or construct a common comprehensive dataset that can be used to perform such comparisons. Here, we introduce the first version of EUPPBench (EUMETNET postprocessing benchmark), a dataset of time-aligned forecasts and observations, with the aim to facilitate and standardize this process. This dataset is publicly available at https://github.com/EUPP-benchmark/climetlab-eumetnet-postprocessing-benchmark (31 December 2022) and on Zenodo (https://doi.org/10.5281/zenodo.7429236, Demaeyer, 2022b and https://doi.org/10.5281/zenodo.7708362, Bhend et al., 2023). We provide examples showing how to download and use the data, we propose a set of evaluation methods, and we perform a first benchmark of several methods for the correction of 2 m temperature forecasts.

• Jezik: Angleški jezik
• Ključne besede: benchmark dataset, ensemble weather forecasts, post-processing, temperature
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FRI - Fakulteta za računalništvo in informatiko
• Status publikacije: Objavljeno
• Različica publikacije: Objavljena publikacija
• Leto izida: 2023
• Št. strani: Str. 2635-2653
• Številčenje: Vol. 15, iss. 6
• PID: 20.500.12556/RUL-152342
• UDK: 004:551.509
• ISSN pri članku: 1866-3508
• DOI: 10.5194/essd-15-2635-2023
• COBISS.SI-ID: 157415427
• Datum objave v RUL: 21.11.2023

DEMAEYER, Jonathan, BHEND, Jonas, LERCH, Sebastian, PRIMO, Cristina, VAN SCHAEYBROECK, Bert, ATENCIA, Aitor, BOUALLÈGUE, Zied Ben, CHEN, Jieyu, DABERNIG, Markus, EVANS, Gavin, FAGANELI PUCER, Jana, HOOPER, Ben, HORAT, Nina, JOBST, David, MERŠE, Janko, MLAKAR, Peter, MÖLLER, Annette, MESTRE, Olivier, TAILLARDAT, Maxime in VANNITSEM, Stéphane, 2023, The EUPPBench postprocessing benchmark dataset v1.0. Earth system science data [na spletu]. 2023. Vol. 15, no. 6, p. 2635–2653. [Dostopano 3 maj 2025]. DOI 10.5194/essd-15-2635-2023. Pridobljeno s: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=slv&id=152342

Gradivo je del revije

• Naslov: Earth system science data
• Skrajšan naslov: Earth syst. sci. data
• Založnik: Copernicus Publications
• ISSN: 1866-3508
• COBISS.SI-ID: 517920537

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: podatkovna zbirka, ansambelske vremenske napovedi, statistično poprocesiranje, temperatura