In this section
@article{Sparks:2017:10.1007/s00477-017-1433-9,
author = {Sparks, NJ and Hardwick, SR and Schmid, M and Toumi, R},
doi = {10.1007/s00477-017-1433-9},
journal = {Stochastic Environmental Research and Risk Assessment},
pages = {771--784},
title = {IMAGE: a multivariate multi-site stochastic weather generator for European weather and climate},
url = {http://dx.doi.org/10.1007/s00477-017-1433-9},
volume = {32},
year = {2017}
}
TY - JOUR
AB - Capturing the spatial and temporal correlation of multiple variables in a weather generator is challenging. A new massively multi-site, multivariate daily stochastic weather generator called IMAGE is presented here. It models temperature and precipitation variables as latent Gaussian variables with temporal behaviour governed by an auto-regressive model whose residuals and parameters are correlated through resampling of principle component time series of empirical orthogonal function modes. A case study using European climate data demonstrates the model’s ability to reproduce extreme events of temperature and precipitation. The ability to capture the spatial and temporal extent of extremes using a modified Climate Extremes Index is demonstrated. Importantly, the model generates events covering not observed temporal and spatial scales giving new insights for risk management purposes.
AU - Sparks,NJ
AU - Hardwick,SR
AU - Schmid,M
AU - Toumi,R
DO - 10.1007/s00477-017-1433-9
EP - 784
PY - 2017///
SN - 1436-3240
SP - 771
TI - IMAGE: a multivariate multi-site stochastic weather generator for European weather and climate
T2 - Stochastic Environmental Research and Risk Assessment
UR - http://dx.doi.org/10.1007/s00477-017-1433-9
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000425537800013&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/57789
VL - 32
ER -