Free access
Issue
Ann. For. Sci.
Volume 67, Number 8, December 2010
Article Number 804
Number of page(s) 6
Section Original articles
DOI http://dx.doi.org/10.1051/forest/2010051
Published online 28 October 2010
  • Alexandersson H., 1986. A homogeneity test applied to precipitation data. J. Climatol. 6: 661–675. [CrossRef]
  • Bala G., Caldeira K., Wickett M., Phillips T.J., Lobell D.B., Delire C., and Mirin A., 2007. Combined climate and carbon-cycle effects of large-scale deforestation. Proc. Natl. Acad. Sci. USA 104: 6550–6555. [CrossRef]
  • Daly C., Halbleib M., Smith J.I., Gibson W.P., Doggett M.K., Taylor G.H., Curtis J., and Pasteris P.P., 2008. Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int. J. Climatol. 28: 2031–2064. [CrossRef]
  • De Vries W., Vel E., Reinds G.J., Deelstra H., Klap J.M., Leeters E.E.J.M.,Hendriks C.M.A.,Kerkvoorden M., Landmann G., Herkendell J., Haussmann T., and Erisman J.W., 2003. Intensive monitoring of forest ecosystems in Europe – 1. Objectives, set-up and evaluation strategy. For. Ecol. Manage. 174: 77–95. [CrossRef]
  • Diodato N. and Ceccarelli M., 2005. Interpolation processes using multivariate geostatistics for mapping of climatological precipitation mean in the Sannio Mountains (southern Italy). Earth. Surf. Proc. Land. 30: 259–268. [CrossRef]
  • Dorninger M., Schneider S., and Steinacker R., 2008. On the interpolation of precipitation data over complex terrain. Meteorol. Atmos. Phys. 101: 175–189. [CrossRef]
  • Ferretti M., Bussotti F., Cenni E., and Cozzi A., 1999. Implementation of quality assurance procedures in the Italian programs of forest condition monitoring. Water Air Soil Pollut. 116: 371–376. [CrossRef]
  • Gallo K.P.,Easterling D.R., and Peterson T.C., 1996. The influence of land use/land cover on climatological values of the diurnal temperature range. J. Climate 9: 2941–2944. [CrossRef]
  • Houston T.D. and Hiederer R., 2009. Applying quality assurance procedures to environmental monitoring data: a case study. J. Environ. Monitor. 11: 774–781. [CrossRef]
  • Hutchinson M.F., Mckenney D.W., Lawrence K., Pedlar J.H., Hopkinson R.F., Milewska E., and Papadopol P., 2009. Development and testing of Canada-wide interpolated spatial models of daily minimum-maximum temperature and precipitation for 1961–2003. J. Appl. Meteorol. Clim. 48: 725–741. [CrossRef]
  • Innes J.L., 1994. Climatic sensitivity of temperate forests. Environ. Pollut. 83: 237–243. [CrossRef] [PubMed]
  • Kang S.Y., Kim S., and Lee D., 2002. Spatial and temporal patterns of solar radiation based on topography and air temperature. Can. J. For. Res. 32: 487–497. [CrossRef]
  • Klingaman N.P., Butke J., Leathers D.J., Brinson K.R., and Nickl E., 2008. Mesoscale simulations of the land surface effects of historical logging in a moist continental climate regime. J. Appl. Meteorol. Clim. 47: 2166–2182. [CrossRef]
  • Luo W., Taylor M.C., and Parker S.R., 2008. A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and Wales. Int. J. Climatol. 28: 947–959. [CrossRef]
  • Miller D.G., Rivington M., Matthews K.B., Buchan K., and Bellocchi G., 2008. Testing the spatial applicability of the Johnson-Woodward method for estimating solar radiation from sunshine duration data. Agric. For. Meteorol. 148: 466–480. [CrossRef]
  • O’Neal M.A., Hanson B., Leathers D.J., and Goldstein A., 2009. Estimating land cover – induced increases in daytime summer temperatures near Mt. Adans, Washington. Phys. Geogr. 30: 130–143.
  • Österle H., Werner P.C., and Gerstengarbe F.W., 2006. Qualitätsprüfung, Ergänzung und Homogenisierung der täglichen Datenreihen in Deutschland, 1951-2003: ein neuer Datensatz. 7. Deutsche Klimatagung. Klimatrends: Vergangenheit und Zukunft. http://www.meteo.physik.uni-muenchen.de/dkt/poster.html.
  • Peterson T.C., 2003. Assessment of urban versus rural in situ surface temperatures in the contiguous United States: No difference found. J. Climate 16: 2941–2959. [CrossRef]
  • Peterson T.C.,Easterling D.R., Karl T.R., Groisman P., Nicholls N., Plummer N., Torok S., Auer I., Boehm R., Gullett D., Vincent L., Heino R., Tuomenvirta H., Mestre O., Szentimrey T., Salinger J., Forland E.J.,Hanssen-Bauer I.,Alexandersson H., Jones P., and Parker D., 1998. Homogeneity adjustments of in situ atmospheric climate data: A review. Int. J. Climatol. 18: 1493–1517. [CrossRef]
  • Solberg S., Dobbertin M., Reinds G. J., Lange H., Andreassen K., Garcia Fernandez P., Hildingsson A., and de Vries W., 2009. Analyses of the impact of changes in atmospheric deposition and climate on forest growth in European monitoring plots: A stand growth approach. For. Ecol. Manage. 258: 1735–1750. [CrossRef]
  • Spadavecchia L. and Wiliams M., 2009. Can spatio-temporal geostatistical methods improve high resolution regionalisation of meteorological variables? Agric. For. Meteorol. 149: 1105–1117.
  • Stahl K., Moore R.D., Floyer J.A., Asplin M.G., and McKendry I.G., 2006. Comparison of approaches in a large region with complex topography and highly variable station density. Agric. For. Meteorol. 139: 224–236. [CrossRef]
  • Strack J.E., Pielke R.A., Steyaert L.T., and Knox R.G., 2008. Sensitivity of June near-surface temperatures and precipitation in the eastern United States to historical land cover changes since European settlement. Water Resour. Res. 44: W11401.
  • Thornton F.C., Running S.W., and White M.A., 1997. Generating surfaces of daily meteorological variables over large regions of complex terrain. J. Hydrol. 190: 214–251. [CrossRef]
  • Vicente-Serrano S.M.,Saz-Sanchez M.A., and Cuadrat J.M., 2003. Comparative analysis of interpolation methods in the middle Ebro Valley (Spain): application to annual precipitation and temperature. Clim. Res. 24: 161–180. [CrossRef]