Combining GOES-R and ECOSTRESS land surface temperature data to investigate diurnal variations of surface urban heat island

Abstract

The surface urban heat island (SUHI) phenomenon is characterized by both high spatial and temporal variability, while its diurnal (i.e., diel) variations have rarely been investigated because traditional satellites and sensors flying on polar orbits (e.g., Landsat, MODIS) have no diurnal sampling capability. Here we combined land surface temperature (LST) data from the Geostationary Operational Environmental Satellites (GOES-R) and the Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to explore the diurnal variations of SUHI and thermal differentiation among various land covers over the Boston Metropolitan Area. With the combined use of the LST data from GOES-R and ECOSTRESS, we took advantage of the strengths of both GOES-R (i.e., high frequency in each day and night) and ECOSTRESS (i.e., much finer spatial resolution). The SUHI intensity of the urban-core and suburban areas both exhibited clear diurnal patterns for different seasons: a continuous increase in the SUHI intensity from sunrise to noon and a decrease thereafter to sunset, followed by a relatively low and constant intensity during nighttime. The LST contrasts among different land cover types were clearly larger in the daytime than at nighttime and peaked around midday. At noon in summer, the LST of ‘Developed, High Intensity’ was 2.6 °C higher than that of ‘Developed, Medium Intensity’, and about 4.6 °C higher than that of “Developed, Open Space” and “Developed, Low Intensity”. Controlling the percent impervious surface in construction land at a relatively low level (e.g., below ~49%) could effectively alleviate the impacts of SUHI. Compared with GOES-R data, ECOSTRESS LST is suitable for monitoring the diurnal variations of intracity thermal environment at the subdistrict (or neighborhood) scale. Our study highlights the value of the combined use of geostationary satellite and ECOSTRESS LST in exploring the diurnal cycling of the SUHI, and can help inform urban planning and land-based climate mitigation policies in the context of climate change.