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  Scale Matching of Multiscale Digital Elevation Model (DEM) Data and the Weather Research and Forecasting (WRF) Model: a Case Study of Meteorological Simulation in Hong Kong

Zhang, C., Lin, H., Chen M, M., & Yang, L. (2014). Scale Matching of Multiscale Digital Elevation Model (DEM) Data and the Weather Research and Forecasting (WRF) Model: a Case Study of Meteorological Simulation in Hong Kong. Arabian Journal of Geosciences, 7, 2215-2223. doi:10.1007/s12517-014-1273-6.

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 Creators:
Zhang , C., Author
Lin , H., Author
Chen M, M., Author
Yang, Liang1, Author           
Affiliations:
1CRG Climate Change and Security, Research Area C: Climate Change and Social Dynamics, The CliSAP Cluster of Excellence, External Organizations, Bundesstraße 53, 20146 Hamburg, DE, ou_2025295              

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 Abstract: It is becoming easier to combine geographical data and dynamic models to provide information for problem solving and geographical cognition. However, the scale dependencies of the data, model, and process can confuse the results. This study extends traditional scale research in static geographical patterns to dynamic processes and focuses on the combined scale effect of multiscale geographical data and dynamic models. The capacity for topographical expression under the combined scale effect was investigated by taking multiscale topographical data and meteorological processes in Hong Kong as a case study. A meteorological simulation of the combined scale effect was evaluated against data from Hong Kong Observatory stations. The experiments showed that (1) a digital elevation model (DEM) using 3 arc sec data with a 1 km resolution Weather Research and Forecasting (WRF) model gives better topographical expression and meteorological reproduction in Hong Kong; (2) a fine-scale model is sensitive to the resolution of the DEM data, whereas a coarse-scale model is less sensitive to it; (3) better topographical expression alone does not improve weather process simulation; and (4) uncertainty arising from a scale mismatch between the DEM data and the dynamic model may account for 38 % of the variance in certain meteorological variables (e.g., temperature). This case study gives a clear explanation of the significance and implementation of scale matching for multiscale geographical data and dynamic models.

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Language(s): eng - English
 Dates: 20142014-06-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1007/s12517-014-1273-6
 Degree: -

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Title: Arabian Journal of Geosciences
Source Genre: Journal
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Pages: - Volume / Issue: 7 Sequence Number: - Start / End Page: 2215 - 2223 Identifier: -