Data-Driven Models to Forecast the Impact of Temperature Anomalies on Rice Production in Southeast Asia
Sabrina De Nardi,
Claudio Carnevale,
Sara Raccagni
et al.
Abstract:Models are a core element in performing local estimation of the climate change input. In this work, a novel approach to perform a fast downscaling of global temperature anomalies on a regional level is presented. The approach is based on a set of data-driven models linking global temperature anomalies and regional and global emissions to regional temperature anomalies. In particular, due to the limited number of available data, a linear autoregressive structure with exogenous input (ARX) has been considered. T… Show more
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