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Advances in Meteorology
Volume 2014, Article ID 232457, 13 pages
Research Article

Energy Budget on Various Land Use Areas Using Reanalysis Data in Florida

1Applied Hydrometeorological Research Institute, Nanjing University of Information Science & Technology, No. 219 Ningliu Road, Nanjing, Jiangsu 210044, China
2Department of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, FL 32816, USA
3Center for Space and Remote Sensing Research, National Central University, Chung-Li 32001, Taiwan

Received 10 December 2013; Revised 24 March 2014; Accepted 24 March 2014; Published 29 April 2014

Academic Editor: Eugene Rozanov

Copyright © 2014 Chi-Han Cheng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Energy budget is closely related to the hydrological cycle through evapotranspiration (ET) or latent heat. Hence, quantifying the energy budget on different land uses is critical for understanding the water budget and providing useful land use information for decision makers. However, traditional methods, including in situ measurements and model-only approaches, have deficiencies in data availability, and we have still not yet fully realized how well the energy budgets presented in reanalysis data sets. Therefore, in this study, North American regional reanalysis (NARR) data set from 1992 to 2002 were employed to investigate the energy budget on various land uses (lake, wetland, agriculture, forest, and urban) at a regional scale in Florida. The results showed that the lake and urban areas had high values of energy budget, evaporation, and low Bowen ratio, while the wetland areas have the opposite treads because of the lowest evaporation rate. During drought periods, Bowen ratio, surface temperature, and sensible heat were becoming higher than those of normal years conditions. Finally, by comparing with the observed data, we found NARR had better assimilation of precipitation observations and demonstrated the land use effects from the different coefficient of correlation relationships.