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. Local short-term temperature variations at the surfaceare mainly dominated by small-scale processes coupled through the surfaceenergy balance terms, which are well known but whose specific contributionand importance on the hourly scale still need to be further analyzed. Amethod to determine each of these terms based almost exclusively onobservations is presented in this paper, with the main objective being to estimatetheir importance in hourly near-surface temperature variations at the SIRTAobservatory, near Paris. Almost all terms are estimated from the multi-yeardataset SIRTA-ReOBS, following a few parametrizations. The four main termsacting on temperature variations are radiative forcing (separated into clear-sky and cloudy-sky radiation), atmospheric heat exchange, ground heatexchange, and advection. Compared to direct measurements of hourlytemperature variations, it is shown that the sum of the four terms gives agood estimate of the hourly temperature variations, allowing a betterassessment of the contribution of each term to the variation, with anaccurate diurnal and annual cycle representation, especially for theradiative terms. A random forest analysis shows that whatever the season,clouds are the main modulator of the clear-sky radiation for 1 htemperature variations during the day and mainly drive these 1 htemperature variations during the night. Then, the specific role of cloudsis analyzed exclusively in cloudy conditions considering the behavior ofsome classical meteorological variables along with lidar profiles. Cloudradiative effect in shortwave and longwave and lidar profiles show aconsistent seasonality during the daytime, with a dominance of mid- andhigh-level clouds detected at the SIRTA observatory, which also affectsnear-surface temperatures and upward sensible heat flux. During thenighttime, despite cloudy conditions and having a strong cloud longwaveradiative effect, temperatures are the lowest and are therefore mostlycontrolled by larger-scale processes at this time.

Estimation of the terms acting on local 1 h surface temperature variations in Paris region: the specific contribution of clouds