Influence of spatial information resolution on the relation between elevation and temperature

International audienceThe association between elevation and temperature is analysed by simple linearcorrelations across several spatial scales. The minimum (tn) and maximum(tx) temperatures (response variables), expressed at two time scales (monthly anddaily), are observed for 102 weather stations in east central France from 1980 to2014 (12,784 days). Elevation (explanatory variable) is provided at 10 resolutions:50, 100, 200, 500 m, 1, 2, 4, 8, 12, and 16 km. The coefficient of determination,R2, is used to determine which resolution gives the best results. The slope given bythe regression is used to assess the drop in temperature per unit of elevation (temperaturelapse rate [TLR]). In most situations, monthly and daily temperatures areoptimally explained by the finest (50 m) resolution: the R2 is, respectively, 0.53and 0.24 for tn and 0.78 and 0.39 for tx. The coarser resolutions produce results ofmuch lower quality. However, in one circumstance (monthly mean of tn), the highestR2 value is obtained for the 4-km resolution, which is a meaningful result ascurrent regional climate models now achieve similar resolutions. Both monthly anddaily TLRs of tn and tx are, on average, slightly lower than −0.5 C/100 m at50-m resolution. The TLR decreases with resolution: it is only −0.23 C/100 m fortn and −0.13 C/100 m for tx at 16-km resolution. Other insightful results involvethe influence of the topographical context, which shows some additional effectwith that of elevation and which was quantified through partial correlations