Statistical downscaling of the urban heat island of Hamburg using a statistical model and regional climate model results
Abstract
A linear statistical model relating the nocturnal urban heat island (UHI) intensity of Hamburg with meteorological conditions is constructed from observations taken by the German Meteorological Service (DWD). To find the appropriate predictors the relationship between different meteorological variables and the UHI of Hamburg is analyzed. Results and physical plausibility suggest that cloud cover, wind speed and relative humidity are the relevant variables and can be used to construct a statistical model. The parameters for the statistical model are determined with the generalized least square method. With the help of the statistical model up to 42% of the UHI variance can be explained. The statistical model is then used to statistically downscale results from climate runs of the regional climate models (RCM) REMO and CLM. Both RCMs were driven with to realizations of the A1B SRES emission scenario of the global climate model ECHAM5/MPI-OM. The resulting values for the future UHI are analyzed with respect to monthly averages and the frequency distribution. Results show that changes in the UHI are different for the different months. In April and for the end of the century in December a significant change (decrease of UHI) can be found in the results of both RCMs and for both realizations, but no significant changes of the UHI for the relevant summer months. REMO results show no significant changes for the summer, while CLM results suggest significant increase in July and August. The frequency distribution of the summer UHI shows no significant changes for REMO. For CLM the frequency distribution changes significantly only in one realization at the end of the century.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2010
- Bibcode:
- 2010AGUFMGC51A0744H
- Keywords:
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- 1637 GLOBAL CHANGE / Regional climate change;
- 3309 ATMOSPHERIC PROCESSES / Climatology