Articles | Volume 10, issue 1
Adv. Sci. Res., 10, 59–64, 2013
Adv. Sci. Res., 10, 59–64, 2013

  15 Apr 2013

15 Apr 2013

An empirical method for estimating probability density functions of gridded daily minimum and maximum temperature

C. Lussana

Related authors

Ensemble-based statistical interpolation with Gaussian anamorphosis for the spatial analysis of precipitation
Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, and Christoffer A. Elo
Nonlin. Processes Geophys., 28, 61–91,,, 2021
Short summary
TITAN automatic spatial quality control of meteorological in-situ observations
Line Båserud, Cristian Lussana, Thomas N. Nipen, Ivar A. Seierstad, Louise Oram, and Trygve Aspelien
Adv. Sci. Res., 17, 153–163,,, 2020
Short summary
seNorge_2018, daily precipitation, and temperature datasets over Norway
Cristian Lussana, Ole Einar Tveito, Andreas Dobler, and Ketil Tunheim
Earth Syst. Sci. Data, 11, 1531–1551,,, 2019
Short summary
seNorge2 daily precipitation, an observational gridded dataset over Norway from 1957 to the present day
Cristian Lussana, Tuomo Saloranta, Thomas Skaugen, Jan Magnusson, Ole Einar Tveito, and Jess Andersen
Earth Syst. Sci. Data, 10, 235–249,,, 2018
Short summary
A spatial bootstrap technique for parameter estimation of rainfall annual maxima distribution
F. Uboldi, A. N. Sulis, C. Lussana, M. Cislaghi, and M. Russo
Hydrol. Earth Syst. Sci., 18, 981–995,,, 2014

Cited articles

Katz, R. W.: Statistics of extremes in climate change, Climatic Change, 100, 71–76, 2010.
Katz, R. W. and Brown, B. G.: Extreme events in a changing climate: Variability is more important than averages, Climatic Change, 21, 289–302, 1992.
Klein Tank, A. M. G., Zwiers, F. W., and Zhang, X.: Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation, Climate data and monitoring, WMO, 2009.
Lanzante, J. R.: Resistant, robust and nonparametric techniques for the analysis of climate data: Theory and examples, including applications to historical radiosonde station data, Int. J. Climatol., 16, 1197–1226, 1996.
Lussana, C., Salvati, M. R., Pellegrini, U., and Uboldi, F.: Efficient high-resolution 3-D interpolation of meteorological variables for operational use, Adv. Sci. Res., 3, 105–112,, 2009{a}.