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

Water

Antonello Pasini¹ 

[1] CNR, Institute of Atmospheric Pollution Research, via Salaria km 29.300, I-00015 Monterotondo Stazione, Rome, Italy

关键词: precipitation;    circulation patterns;    attribution;    neural networks;    Alps;   

DOI  :  10.3390/w2030321

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.