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Water 2010, 2(3), 321-332; doi:10.3390/w2030321
Article

Attribution of Precipitation Changes on a Regional Scale by Neural Network Modeling: A Case Study

1,*  and 2
Received: 24 May 2010; in revised form: 19 June 2010 / Accepted: 6 July 2010 / Published: 6 July 2010
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Abstract: On a regional scale, climate variability masks any direct link between external forcings and precipitation values. Thus, the problem of attribution of precipitation changes splits into two distinct steps: understanding how forcings influence circulation patterns and finding relationships between these patterns and the behavior of precipitation. Here, we deal with this second step, by analyzing data about eight circulation indices and their influence on precipitation anomalies in an extended Italian Alpine region. The methods used are bivariate nonlinear analysis and neural network modeling. We identify the most influential circulation patterns in each season and work out neural network models that are able to substantially describe the climate variability of precipitation at this regional scale.
Keywords: precipitation; circulation patterns; attribution; neural networks; Alps precipitation; circulation patterns; attribution; neural networks; Alps
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Pasini, A.; Langone, R. Attribution of Precipitation Changes on a Regional Scale by Neural Network Modeling: A Case Study. Water 2010, 2, 321-332.

AMA Style

Pasini A, Langone R. Attribution of Precipitation Changes on a Regional Scale by Neural Network Modeling: A Case Study. Water. 2010; 2(3):321-332.

Chicago/Turabian Style

Pasini, Antonello; Langone, Rocco. 2010. "Attribution of Precipitation Changes on a Regional Scale by Neural Network Modeling: A Case Study." Water 2, no. 3: 321-332.


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