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The Forbio Climate Data Set for Climate Analyses : Volume 12, Issue 1 (03/06/2015)

By Delvaux, C.

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Book Id: WPLBN0003972436
Format Type: PDF Article :
File Size: Pages 7
Reproduction Date: 2015

Title: The Forbio Climate Data Set for Climate Analyses : Volume 12, Issue 1 (03/06/2015)  
Author: Delvaux, C.
Volume: Vol. 12, Issue 1
Language: English
Subject: Science, Advances, Science
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Historic
Publication Date:
2015
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Journée, M., Bertrand, C., & Delvaux, C. (2015). The Forbio Climate Data Set for Climate Analyses : Volume 12, Issue 1 (03/06/2015). Retrieved from http://www.worldebookfair.org/


Description
Description: Royal Meteorological Institute of Belgium, Brussels, Belgium. In the framework of the interdisciplinary FORBIO Climate research project, the Royal Meteorological Institute of Belgium is in charge of providing high resolution gridded past climate data (i.e. temperature and precipitation). This climate data set will be linked to the measurements on seedlings, saplings and mature trees to assess the effects of climate variation on tree performance. This paper explains how the gridded daily temperature (minimum and maximum) data set was generated from a consistent station network between 1980 and 2013. After station selection, data quality control procedures were developed and applied to the station records to ensure that only valid measurements will be involved in the gridding process. Thereafter, the set of unevenly distributed validated temperature data was interpolated on a 4 km × 4 km regular grid over Belgium. The performance of different interpolation methods has been assessed. The method of kriging with external drift using correlation between temperature and altitude gave the most relevant results.

Summary
The FORBIO Climate data set for climate analyses

Excerpt
Aguilar, E., Auer, I., Brunet, M., Peterson, T., and Wieringa, J.: Guidelines on climate metadata and homogenization, World Climate Programme Data and Monitoring WCDMP-No. 53, WMO-TD No. 1186, World Meteorological Organization, Geneva, 2003.; Bolstad, P. V., Swift, L., Collins, F., and Régnière, J.: Measured and predicted air temperatures at basin to regional scales in the southern Appalachian mountains, Agr. Forest Meteorol., 91, 161–176, 1998.; Bossard, M. and Feranec, J.: Otahel, Jaffrain, Gabriel, CORINE Land Cover technical guide – Addendum 2000, Tech. rep., Technical Report 40, EEA, Copenhagen, http://www.eea.eu.int (last access: 8 January 2015), 2000.; Boulanger, J.-P., Aizpuru, J., Leggieri, L., and Marino, M.: A procedure for automated quality control and homogenization of historical daily temperature and precipitation data (APACH): part 1: quality control and application to the Argentine weather service stations, Climatic Change, 98, 471–491, 2010.; Daly, C.: Guidelines for assessing the suitability of spatial climate data sets, Int. J. Climatol., 26, 707–721, 2006.; Feng, S., Hu, Q., and Qian, W.: Quality control of daily meteorological data in China, 1951–2000: a new dataset, Int. J. Climatol., 24, 853–870, 2004.; Dong, J., Chen, J., Brosofske, K., and Naiman, R.: Modelling air temperature gradients across managed small streams in western Washington, J. Environ. Manage., 53, 309–321, 1998.; Frick, C., Steiner, H., Mazurkiewicz, A., Riediger, U., Rauthe, M., Reich, T., and Gratzki, A.: Central European high-resolution gridded daily data sets (HYRAS): Mean temperature and relative humidity, Meteorol. Z., 23, 15–32, 2014.; Hair, J. F.: Multivariate data analysis, Prentice Hall, Upper Saddle River, 2009.; Haylock, M., Hofstra, N., Klein Tank, A., Klok, E., Jones, P., and New, M.: A European daily high-resolution gridded data set of surface temperature and precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113, D20119, doi:10.1029/2008JD10201, 2008.; Lookingbill, T. R. and Urban, D. L.: Spatial estimation of air temperature differences for landscape-scale studies in montane environments, Agr. Forest Meteorol., 114, 141–151, 2003.; McCutchan, M. H. and Fox, D. G.: Effect of elevation and aspect on wind, temperature and humidity, J. Clim. Appl. Meteorol., 25, 1996–2013, 1986.; Pebesma, E. J.: Multivariable geostatistics in S: the gstat package, Comput. Geosci., 30, 683–691, 2004.; Sciuto, G., Bonaccorso, B., Cancelliere, A., and Rossi, G.: Probabilistic quality control of daily temperature data, Int. J. Climatol., 33, 1211–1227, 2013.; Wackernagel, H.: Multivariable geostatistics: an introduction with applications, Springer-Verlag, Berlin, 1995.

 

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