A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0
Détails
Etat: Public
Version: Final published version
ID Serval
serval:BIB_0F13D13B7E69
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0
Périodique
Geoscientific Model Development Discussions
ISSN
1991-962X
Statut éditorial
Publié
Date de publication
2017
Peer-reviewed
Oui
Volume
10
Pages
3771-3791
Langue
anglais
Résumé
While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject to considerable uncertainty, and represent extremely large data files with associated computational costs of data input/output and file transfer. For periods before the recent past or in the future, global meteorological forcing can be provided by climate model output, but the quality of these data at high temporal resolution is low, particularly for daily precipitation frequency and amount. Here, we present GWGEN, a globally applicable statistical weather generator for the temporal downscaling of monthly climatology to daily meteorology. Our weather generator is parameterized using a global meteorological database and simulates daily values of five common variables: minimum and maximum temperature, precipitation, cloud cover, and wind speed. GWGEN is lightweight, modular, and requires a minimal set of monthly mean variables as input. The weather generator may be used in a range of applications, for example, in global vegetation, crop, soil erosion, or hydrological models. While GWGEN does not currently perform spatially autocorrelated multi-point downscaling of daily weather, this additional functionality could be implemented in future versions.
Mots-clé
wgen, weathergen, ghcn, eecra, richardson, geng
Site de l'éditeur
Open Access
Oui
Création de la notice
11/10/2017 15:53
Dernière modification de la notice
20/08/2019 13:35