Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites
ABSTRACT Developed for short‐term (0–48 h) wind power forecasting purposes, high‐resolution meteorological forecasts for Eastern Canada are available from Environment Canada's Numerical Weather Prediction (NWP) model configured on a limited area (GEM‐LAM). This paper uses 3 years of forecast da...
Published in: | Wind Energy |
---|---|
Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2012
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1002/we.1538 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fwe.1538 https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.1538 |
id |
crwiley:10.1002/we.1538 |
---|---|
record_format |
openpolar |
spelling |
crwiley:10.1002/we.1538 2024-06-02T08:11:46+00:00 Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites Bédard, Joël Yu, Wei Gagnon, Yves Masson, Christian 2012 http://dx.doi.org/10.1002/we.1538 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fwe.1538 https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.1538 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor Wind Energy volume 16, issue 8, page 1131-1147 ISSN 1095-4244 1099-1824 journal-article 2012 crwiley https://doi.org/10.1002/we.1538 2024-05-03T10:57:37Z ABSTRACT Developed for short‐term (0–48 h) wind power forecasting purposes, high‐resolution meteorological forecasts for Eastern Canada are available from Environment Canada's Numerical Weather Prediction (NWP) model configured on a limited area (GEM‐LAM). This paper uses 3 years of forecast data from this model for the region of North Cape (Prince Edward Island, Canada). Although the model resolution is relatively high (2.5 km), statistical analysis and site inspection reveal that the model does not have a sufficiently refined grid to properly represent the meteorological phenomena over this complex coastal site. To cope with such representation error, a generalized Geophysic Model Output Statistics (GMOS) module is developed and applied to reduce the forecast error of the NWP forecasts. GMOS differs from other Model Output Statistics (MOS) that are widely used by meteorological centres in the following aspects: (i) GMOS takes into account the surrounding geophysical parameters such as surface roughness, terrain height, etc., along with wind direction; (ii) GMOS can be directly applied for model output correction without any training. Compared with other methods, GMOS using a multiple grid point approach improves the GEM‐LAM predictions root mean squared error by 1–5% for all time horizons and most meteorological conditions. Also, the topographic signature of the forecast error (uneven directional distribution of the forecast error related to the surface characteristics) due to misrepresentation issues is significantly reduced. The NWP forecasts combined with GMOS outperform the persistence model from a 2 h horizon, instead of 3 h using MOS. Finally, GMOS is applied and validated at two other sites located in New Brunswick, Canada. Similar improvements on the forecasts were observed, thus showing the general applicability of GMOS. Copyright © 2012 John Wiley & Sons, Ltd. Article in Journal/Newspaper North Cape Prince Edward Island Wiley Online Library Canada North Cape ENVELOPE(165.700,165.700,-70.650,-70.650) Wind Energy 16 8 1131 1147 |
institution |
Open Polar |
collection |
Wiley Online Library |
op_collection_id |
crwiley |
language |
English |
description |
ABSTRACT Developed for short‐term (0–48 h) wind power forecasting purposes, high‐resolution meteorological forecasts for Eastern Canada are available from Environment Canada's Numerical Weather Prediction (NWP) model configured on a limited area (GEM‐LAM). This paper uses 3 years of forecast data from this model for the region of North Cape (Prince Edward Island, Canada). Although the model resolution is relatively high (2.5 km), statistical analysis and site inspection reveal that the model does not have a sufficiently refined grid to properly represent the meteorological phenomena over this complex coastal site. To cope with such representation error, a generalized Geophysic Model Output Statistics (GMOS) module is developed and applied to reduce the forecast error of the NWP forecasts. GMOS differs from other Model Output Statistics (MOS) that are widely used by meteorological centres in the following aspects: (i) GMOS takes into account the surrounding geophysical parameters such as surface roughness, terrain height, etc., along with wind direction; (ii) GMOS can be directly applied for model output correction without any training. Compared with other methods, GMOS using a multiple grid point approach improves the GEM‐LAM predictions root mean squared error by 1–5% for all time horizons and most meteorological conditions. Also, the topographic signature of the forecast error (uneven directional distribution of the forecast error related to the surface characteristics) due to misrepresentation issues is significantly reduced. The NWP forecasts combined with GMOS outperform the persistence model from a 2 h horizon, instead of 3 h using MOS. Finally, GMOS is applied and validated at two other sites located in New Brunswick, Canada. Similar improvements on the forecasts were observed, thus showing the general applicability of GMOS. Copyright © 2012 John Wiley & Sons, Ltd. |
format |
Article in Journal/Newspaper |
author |
Bédard, Joël Yu, Wei Gagnon, Yves Masson, Christian |
spellingShingle |
Bédard, Joël Yu, Wei Gagnon, Yves Masson, Christian Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
author_facet |
Bédard, Joël Yu, Wei Gagnon, Yves Masson, Christian |
author_sort |
Bédard, Joël |
title |
Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
title_short |
Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
title_full |
Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
title_fullStr |
Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
title_full_unstemmed |
Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
title_sort |
development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites |
publisher |
Wiley |
publishDate |
2012 |
url |
http://dx.doi.org/10.1002/we.1538 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fwe.1538 https://onlinelibrary.wiley.com/doi/pdf/10.1002/we.1538 |
long_lat |
ENVELOPE(165.700,165.700,-70.650,-70.650) |
geographic |
Canada North Cape |
geographic_facet |
Canada North Cape |
genre |
North Cape Prince Edward Island |
genre_facet |
North Cape Prince Edward Island |
op_source |
Wind Energy volume 16, issue 8, page 1131-1147 ISSN 1095-4244 1099-1824 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/we.1538 |
container_title |
Wind Energy |
container_volume |
16 |
container_issue |
8 |
container_start_page |
1131 |
op_container_end_page |
1147 |
_version_ |
1800758010508738560 |