The Impact of Sun‐Synchronous Local Time Sampling to Compute the Daily Mean <scp>OLR</scp> Utilising 15‐ <scp>min AGRI</scp> ‐Derived <scp>LW</scp> Fluxes

ABSTRACT Sun‐synchronous meteorological satellites offer comprehensive global coverage but are limited by their temporal resolution, providing only two observations per day. This limitation impedes the ability to capture diurnal variations in weather patterns, which are crucial for accurate climate change assessments. This study utilises 15‐min FY‐4B/AGRI OLR observations to investigate the influence of observation time on the accuracy of daily mean OLR. From a longwave perspective, we propose optimised observation time schemes for various satellite configurations aimed at enhancing global OLR accuracy. Comparing single, dual and tri‐satellite setups, the optimal observation times are identified, with afternoon (2:00 PM) being best for single satellite, a combination of morning (10:30 AM) and afternoon (2:00 PM) for dual satellite, and a combination of dusk–dawn (5:30 AM), morning (10:30 AM) and afternoon (2:00 PM) for tri‐satellite. EOF analysis shows that morning and afternoon observations are most sensitive to surface heating, while early morning and evening reflect cloud cover and water vapour effects. The study demonstrates that hourly observations reliably capture the diurnal variation of outgoing longwave radiation (OLR) and that combining two sun‐synchronous satellites reduces the root mean square error (RMSE) to below 1 W/m 2 . This research offers insights for optimising future satellite constellations and improving OLR estimation accuracy.