All-sky hourly estimation over East Asia using Himawari-8 AHI and multi-source data: investigating the main climatic drivers of afternoon depression and intraday variability in gross primary productivity

Summary

Intraday observations from geostationary satellites provide key information for estimating terrestrial productivity and analyzing environmental drivers, but cloud cover often hinders continuous monitoring. In this study, we addressed this limitation by combining multi-source data and a data-driven approach to develop hourly, all-sky, regional-scale gross primary productivity (GPP). Our all-sky GPP showed strong consistency with ground measurements in East Asia (coefficient of determination (R2) = 0.86, root mean squared error = 2.4 μmol CO₂/m²/s) and outperformed conventional hourly GPP products derived from the observations of International Space Station (ISS) sensors and polar-orbiting satellites. To investigate how the importance of input variables differs between clear-sky and cloudy-s