Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models

By Juha Aalto, P. Pirinen, Juha Heikkinen, Ari K. Venäläinen. Theoretical and Applied Climatology, 2013

189 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/258add28a4314abc7d464c2cee9fff15d58151c8

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. Markus Dabernig
2. Achim Zeileis
3. Jakob W. Messner
4. Georg J. Mayr

In Environmental Engineering

1. Wei Sun
2. Chunxia Guo
3. Achim Zeileis
4. Yunqiang Zhu
5. Jakob W. Messner
6. Georg J. Mayr
7. Shengli Huang

In Global and Planetary Change

1. Markus Dabernig
2. Wei Sun
3. Chunxia Guo
4. Achim Zeileis
5. Yunqiang Zhu
6. Jakob W. Messner
7. Georg J. Mayr
8. Shengli Huang

Citations in the corpus

• Spatial ensemble post‐processing with standardized anomalies (2016, methodology): “A climatology with non-Euclidean distances as in Frei (2014) could be computed, or a spatial climatology for all stations could be fitted at once with a generalized additive model (GAM: Aalto et al.”
• Mapping the mean annual precipitation of China using local interpolation techniques (2014, background): “2011), Thiessen polygon (Goovaerts 2000), ordinary kriging (Grimes et al. 2010; Wagner et al. 2012; Juha et al. 2013), universal kriging (Kizza et al.”