Can spatio-temporal geostatistical methods improve high resolution regionalisation of meteorological variables?

By L. Spadavecchia, Mat Williams. 2009

82 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/83e8af3283492ea04145950529ca47e7f1f9118b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atmospheric Science

1. S. Ly
2. Catherine Charles
3. A. Dégre

In Global and Planetary Change

1. S. Ly
2. Catherine Charles
3. A. Dégre

In Water Science and Technology

1. S. Ly
2. Catherine Charles
3. A. Dégre

Citations in the corpus

• Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium (2011, background): “Spadavecchia and Williams (2009) varied the number of interpolation data used in both space and time and assessed its impact on interpolation skill of spatio-temporal geostatistical methods.”