Farhani N., Carreau Julie, Kassouk Z., Mougenot Bernard, Le Page Michel, Lili-Chabaane Z., Zitouna-Chebbi R., Boulet Gilles. (2022). Regional sub-daily stochastic weather generator based on reanalyses for surface water stress estimation in central Tunisia. Environmental Modelling and Software, 155, p. 105448 [16 p.]. ISSN 1364-8152.
Titre du document
Regional sub-daily stochastic weather generator based on reanalyses for surface water stress estimation in central Tunisia
Farhani N., Carreau Julie, Kassouk Z., Mougenot Bernard, Le Page Michel, Lili-Chabaane Z., Zitouna-Chebbi R., Boulet Gilles
Source
Environmental Modelling and Software, 2022,
155, p. 105448 [16 p.] ISSN 1364-8152
We present MetGen: a sub-daily multi-variable stochastic weather generator implemented as an R library that can be used to perform gap-filling and to extend in time meteorological observation series. MetGen is tailored to provide surrogate series of air temperature, relative air humidity, global radiation and wind speed needed for surface water stress estimation that requires sub-daily resolution. Multiple gauged stations can be used to increase the calibration data although spatial dependence is not modeled. The approach relies on Generalized Linear Models that use, among their covariates, large-scale variables derived from ERA5 reanalyses. MetGen aims at preserving key features of the meteorological variables along with inter-variable dependencies. We illustrate the abilities of MetGen using a case study with three stations in central Tunisia. We consider as alternatives a univariate and a multivariate bias correction techniques along with the un-processed large-scale variables.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020]
;
Sciences du milieu [021]
;
Bioclimatologie [072]
