Geophysical retrievals in an artificial intelligence (AI) framework for illuminating processes controlling water cycle

Virendra P. Ghate, Maria P. Cadeddu, Amanda Lenzi, Liu Zhengchun

Research output: Book/ReportOther report

Abstract / Description of output

Focal Area(s): This white paper responds to Focal Area #3: Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: This white paper addresses the water-cycle and data-model integration grand challenge. It leverages data from the Atmospheric Radiation Measurement (ARM) Climate Research Facility, and Next-Generation Ecosystem Experiment (NGEE), and Science Focus Area (SFA). The white paper focuses on controlling cloud, precipitation, and radiative properties as observed and simulated by the Earth System Models (ESM). The described framework can be readily applied to any other ensemble of instruments, including satellites and other ground-based networks.
Original languageEnglish
PublisherUS Department of Energy
Publication statusPublished - 15 Apr 2021

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