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Downscaling of GCM forecasts to streamflow over Scandinavia

Nilsson, Patrik LU ; Bertacchi Uvo, Cintia LU ; Landman, Willem A and Nguyen, Tinh D (2008) In Nordic Hydrology 39(1). p.17-26
Abstract
A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south-western Norway. The physical interpretation of the forecasting skill is that stations close to the Norwegian coast are directly exposed to prevailing... (More)
A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south-western Norway. The physical interpretation of the forecasting skill is that stations close to the Norwegian coast are directly exposed to prevailing winds from the Atlantic ocean, which constitute the principal source of predictive information from the atmosphere on the seasonal timescale. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
neural networks, statistic, model output, general circulation model, downscaling, forecasting
in
Nordic Hydrology
volume
39
issue
1
pages
17 - 26
publisher
IWA Publishing
external identifiers
  • wos:000254044500003
  • scopus:41949134010
ISSN
1996-9694
DOI
10.2166/nh.2008.027
language
English
LU publication?
yes
id
965c9b54-adf4-4a10-a2c1-edb2a1c0175d (old id 1185053)
date added to LUP
2008-09-02 15:36:27
date last changed
2017-01-01 04:29:41
@article{965c9b54-adf4-4a10-a2c1-edb2a1c0175d,
  abstract     = {A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south-western Norway. The physical interpretation of the forecasting skill is that stations close to the Norwegian coast are directly exposed to prevailing winds from the Atlantic ocean, which constitute the principal source of predictive information from the atmosphere on the seasonal timescale.},
  author       = {Nilsson, Patrik and Bertacchi Uvo, Cintia and Landman, Willem A and Nguyen, Tinh D},
  issn         = {1996-9694},
  keyword      = {neural networks,statistic,model output,general circulation model,downscaling,forecasting},
  language     = {eng},
  number       = {1},
  pages        = {17--26},
  publisher    = {IWA Publishing},
  series       = {Nordic Hydrology},
  title        = {Downscaling of GCM forecasts to streamflow over Scandinavia},
  url          = {http://dx.doi.org/10.2166/nh.2008.027},
  volume       = {39},
  year         = {2008},
}