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Advances in Science and Research Contributions in Applied Meteorology and Climatology
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Volume 10, issue 1
Adv. Sci. Res., 10, 59–64, 2013
https://doi.org/10.5194/asr-10-59-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
Adv. Sci. Res., 10, 59–64, 2013
https://doi.org/10.5194/asr-10-59-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

  15 Apr 2013

15 Apr 2013

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

C. Lussana

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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, https://doi.org/10.5194/asr-3-105-2009, 2009{a}.
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