Abstract Spatio-temporal variation in the Martian surface temperature (MST) is an indicator of ground level thermal processes and hence a building block for climate models. However, the distribution of MST exhibits different levels of spatial aggregation or heterogeneity, and varies in space and time. Furthermore, the effect of regional differences in meteorological or environmental factors on the MST is not well understood. Thus, we investigated the degree of spatial autocorrelation of MST across the surface of Mars globally by Moran’s I, and identified the hot spots by GetisOrd Gi*. We also estimated the regional differences in the influence of seasonally dominant factors including thermal inertia (TI), albedo, surface pressure, latitude, dust and slope on MST by a geographically weighted regression model. The results indicate (1) that MST is spatially aggregated and hot and cold spots varied over time and space. (2) Hemispheric differences in topography, surface TI and albedo were primarily responsible for the hemispheric asymmetry of hot spots. (3) The dominant factors varied by geographical locations and seasons. For example, the seasonal Hadley circulation dominates at the low-latitudes and CO2 circulation at the high-latitudes. (4) Regions with extreme variations in topography and low TI were sensitive to meteorological and environmental factors such as dust and CO2 ice. We conclude that the spatial autocorrelation of MST and the spatial and seasonal heterogeneity of influencing factors must be considered when simulating Martian climate models. This work provides a reference for further exploration of Martian climatic processes.
Keywords methods: analytical – planets and satellites: surfaces – methods: statistical – planets and satellites: fundamental parameters
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