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Attribution of Precipitation Changes on a Regional Scale by Neural Network Modeling: A Case Study
CNR, Institute of Atmospheric Pollution Research, via Salaria km 29.300, I-00015 Monterotondo Stazione, Rome, Italy
Katholieke Universiteit Leuven, Department ESAT/SISTA, Leuven, Belgium
* Author to whom correspondence should be addressed.
Received: 24 May 2010; in revised form: 19 June 2010 / Accepted: 6 July 2010 / Published: 6 July 2010
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
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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.
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.
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.