TITLE: IowaRain: A Statewide Rain Event Dataset Based on Weather Radars and Quantitative Precipitation Estimation 

ABSTRACT: Effective environmental planning and management to address climate change
could be achieved through extensive environmental modeling with machine
learning and conventional physical models. In order to develop and improve
these models, practitioners and researchers need comprehensive benchmark
datasets that are prepared and processed with environmental expertise that they
can rely on. This study presents an extensive dataset of rainfall events for
the state of Iowa (2016-2019) acquired from the National Weather Service Next
Generation Weather Radar (NEXRAD) system and processed by a quantitative
precipitation estimation system. The dataset presented in this study could be
used for better disaster monitoring, response and recovery by paving the way
for both predictive and prescriptive modeling.
Effective environmental planning and management to address climate change
could be achieved through extensive environmental modeling with machine
learning and conventional physical models. In order to develop and improve
these models, practitioners and researchers need comprehensive benchmark
datasets that are prepared and processed with environmental expertise that they
can rely on. This study presents an extensive dataset of rainfall events for
the state of Iowa (2016-2019) acquired from the National Weather Service Next
Generation Weather Radar (NEXRAD) system and processed by a quantitative
precipitation estimation system. The dataset presented in this study could be
used for better disaster monitoring, response and recovery by paving the way
for both predictive and prescriptive modeling.
IowaRain: A Statewide Rain Event Dataset Based on Weather Radars and Quantitative Precipitation Estimation
http://arxiv.org/abs/2107.03432v1