Improved seasonal prediction of UK regional precipitation using atmospheric circulation

ABSTRACT The aim of this study is to further our understanding of whether skilful seasonal forecasts of the large‐scale atmospheric circulation can be downscaled to provide skilful seasonal forecasts of regional precipitation. A simple multiple linear regression model is developed to describe winter...

Full description

Bibliographic Details
Published in:International Journal of Climatology
Main Authors: Baker, L. H., Shaffrey, L. C., Scaife, A. A.
Other Authors: Natural Environment Research Council
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2017
Subjects:
Online Access:http://dx.doi.org/10.1002/joc.5382
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.5382
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5382
id crwiley:10.1002/joc.5382
record_format openpolar
spelling crwiley:10.1002/joc.5382 2024-06-02T08:11:27+00:00 Improved seasonal prediction of UK regional precipitation using atmospheric circulation Baker, L. H. Shaffrey, L. C. Scaife, A. A. Natural Environment Research Council 2017 http://dx.doi.org/10.1002/joc.5382 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.5382 https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5382 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor International Journal of Climatology volume 38, issue S1 ISSN 0899-8418 1097-0088 journal-article 2017 crwiley https://doi.org/10.1002/joc.5382 2024-05-03T10:49:42Z ABSTRACT The aim of this study is to further our understanding of whether skilful seasonal forecasts of the large‐scale atmospheric circulation can be downscaled to provide skilful seasonal forecasts of regional precipitation. A simple multiple linear regression model is developed to describe winter precipitation variability in nine UK regions. The model for each region is a linear combination of two mean sea‐level pressure (MSLP)‐based indices which are derived from the MSLP correlation patterns for precipitation in northwest Scotland and southeast England. The first index is a pressure dipole, similar to the North Atlantic Oscillation but shifted to the east; the second index is the MSLP anomaly centred over the UK. The multiple linear regression model describes up to 76% of the observed precipitation variability in each region and gives higher correlations with precipitation than using either of the two indices alone. The Met Office's seasonal forecast system (GloSea5) is found to have significant skill in forecasting the two MSLP indices for the winter season, in forecasts initialized around the start of November. Applying the multiple linear regression model to the GloSea5 hindcasts is shown to give improved skill over the precipitation forecast by the GloSea5, with the largest improvement in Scotland. Article in Journal/Newspaper North Atlantic North Atlantic oscillation Wiley Online Library International Journal of Climatology 38 S1
institution Open Polar
collection Wiley Online Library
op_collection_id crwiley
language English
description ABSTRACT The aim of this study is to further our understanding of whether skilful seasonal forecasts of the large‐scale atmospheric circulation can be downscaled to provide skilful seasonal forecasts of regional precipitation. A simple multiple linear regression model is developed to describe winter precipitation variability in nine UK regions. The model for each region is a linear combination of two mean sea‐level pressure (MSLP)‐based indices which are derived from the MSLP correlation patterns for precipitation in northwest Scotland and southeast England. The first index is a pressure dipole, similar to the North Atlantic Oscillation but shifted to the east; the second index is the MSLP anomaly centred over the UK. The multiple linear regression model describes up to 76% of the observed precipitation variability in each region and gives higher correlations with precipitation than using either of the two indices alone. The Met Office's seasonal forecast system (GloSea5) is found to have significant skill in forecasting the two MSLP indices for the winter season, in forecasts initialized around the start of November. Applying the multiple linear regression model to the GloSea5 hindcasts is shown to give improved skill over the precipitation forecast by the GloSea5, with the largest improvement in Scotland.
author2 Natural Environment Research Council
format Article in Journal/Newspaper
author Baker, L. H.
Shaffrey, L. C.
Scaife, A. A.
spellingShingle Baker, L. H.
Shaffrey, L. C.
Scaife, A. A.
Improved seasonal prediction of UK regional precipitation using atmospheric circulation
author_facet Baker, L. H.
Shaffrey, L. C.
Scaife, A. A.
author_sort Baker, L. H.
title Improved seasonal prediction of UK regional precipitation using atmospheric circulation
title_short Improved seasonal prediction of UK regional precipitation using atmospheric circulation
title_full Improved seasonal prediction of UK regional precipitation using atmospheric circulation
title_fullStr Improved seasonal prediction of UK regional precipitation using atmospheric circulation
title_full_unstemmed Improved seasonal prediction of UK regional precipitation using atmospheric circulation
title_sort improved seasonal prediction of uk regional precipitation using atmospheric circulation
publisher Wiley
publishDate 2017
url http://dx.doi.org/10.1002/joc.5382
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.5382
https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5382
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_source International Journal of Climatology
volume 38, issue S1
ISSN 0899-8418 1097-0088
op_rights http://onlinelibrary.wiley.com/termsAndConditions#vor
op_doi https://doi.org/10.1002/joc.5382
container_title International Journal of Climatology
container_volume 38
container_issue S1
_version_ 1800757604593434624