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Statistical precipitation downscaling in central Sweden with the analogue method
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Air and Water Science.
2005 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 306, no 1-4, 174-190 p.Article in journal (Refereed) Published
Abstract [en]

Most climate predictions show significant consequences globally and regionally, but many of its critical impacts will occur at sub-regional and local scales. Downscaling methods are, thus, needed to assess effects of large-scale atmospheric circulation on local parameters such as precipitation and runoff. This study aims at evaluating the analogue method (AM) as a benchmark method for precipitation downscaling in northern Europe. The predictors used in this study were daily and monthly gridded sea-level pressures from 1960 to 1997 in an area 45-75 degrees N and 30 degrees W-40 degrees E with a resolution of 5 X 5 degrees long-lat. Analogues for daily and monthly precipitation at seven precipitation stations in south-central Sweden were established with two techniques, principal-component analysis (PCA) and the Teweles-Wobus score (TWS). The results showed that AM downscaling on both daily and monthly basis was commonly generally much better than a random baseline but depended on the objective function used for assessment; PCA and TWS produced similar results in most cases but TWS was superior in simulating precipitation duration and intensity. Downscaling was improved when seasonality was included and when the SLP field was confined to those geographical areas that contributed most to precipitation in south-central Sweden.

Place, publisher, year, edition, pages
2005. Vol. 306, no 1-4, 174-190 p.
Keyword [en]
analogue method, downscaling, precipitation, PCA, Teweles-Wobus score, Sweden
National Category
Oceanography, Hydrology, Water Resources
Identifiers
URN: urn:nbn:se:uu:diva-93485DOI: 10.1016/j.jhydrol.2004.09.008ISI: 000229413500012OAI: oai:DiVA.org:uu-93485DiVA: diva2:166974
Available from: 2005-09-09 Created: 2005-09-09 Last updated: 2017-12-14Bibliographically approved
In thesis
1. Statistical Downscaling of Precipitation from Large-scale Atmospheric Circulation: Comparison of Methods and Climate Regions
Open this publication in new window or tab >>Statistical Downscaling of Precipitation from Large-scale Atmospheric Circulation: Comparison of Methods and Climate Regions
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Statistisk nedskalning av nederbörd från storskalig atmosfärscirkulation : Jämförelse mellan metoder och klimatregioner
Abstract [en]

A global climate change may have large impacts on water resources on regional and global scales. General circulation models (GCMs) are the most used tools to evaluate climate-change scenarios on a global scale. They are, however, insufficiently describing the effects at the local scale. This thesis evaluates different approaches of statistical downscaling of precipitation from large-scale circulation variables, both concerning the method performance and the optimum choice of predictor variables.

The analogue downscaling method (AM) was found to work well as “benchmark” method in comparison to more complicated methods. AM was implemented using principal component analysis (PCA) and Teweles-Wobus Scores (TWS). Statistical properties of daily and monthly precipitation on a catchment in south-central Sweden, as well as daily precipitation in three catchments in China were acceptably downscaled.

A regression method conditioning a weather generator (SDSM) as well as a fuzzy-rule based circulation-pattern classification method conditioning a stochastical precipitation model (MOFRBC) gave good results when applied on Swedish and Chinese catchments. Statistical downscaling with MOFRBC from GMC (HADAM3P) output improved the statistical properties as well as the intra-annual variation of precipitation.

The studies show that temporal and areal settings of the predictor are important factors concerning the success of precipitation modelling. The MOFRCB and SDSM are generally performing better than the AM, and the best choice of method is depending on the purpose of the study. MOFRBC applied on output from a GCM future scenario indicates that the large-scale circulation will not be significantly affected. Adding humidity flux as predictor indicated an increased intensity both in extreme events and daily amounts in central and northern Sweden.

Publisher
64 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 93
Keyword
Hydrology, Statistical, Downscaling, Precipitation, Large-scale circulation, PCA, TWS, Weather pattern, Regression, Weather generator, Hydrologi
National Category
Oceanography, Hydrology, Water Resources
Identifiers
urn:nbn:se:uu:diva-5937 (URN)91-554-6344-4 (ISBN)
Public defence
2005-09-30, Axel Hambergssalen, Geocentrum, Villavägen 16, Uppsala, 10:00
Opponent
Supervisors
Available from: 2005-09-09 Created: 2005-09-09Bibliographically approved

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