Predicting Rainfall with Polarimetric Radar Data

نویسندگان

  • Nitin Kamra
  • James Preiss
چکیده

We explore a set of polarimetric radar data and rain gauge readings collected in the Midwestern US over several months, while aiming to improve existing rainfall prediction techniques with various supervised learning algorithms.1 We explore preprocessing techniques and evaluate Linear Regression and Feedforward Neural Networks models of summarized data against the Marshall-Palmer baseline.

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تاریخ انتشار 2015