Use of Satellite Data Products for Studying Long-Term Changes in Ambient Air Temperature, Relative Humidity and Heat Load

Using satellite data products across 41 years, this study explores the combined effect of summer (15 May–15 September) ambient temperatures and relative humidity on the exposure to excessive heat of people living in northern Israel. Specifically, we fused 126 Landsat satellite image data collected between 1984 and 2024 with surface meteorological observations, topographical, and land-use data. The ambient temperature (Ta) was estimated by a Random Forest (RF) regression model, with the Landsat land surface temperature (LST) as its main input. A complete spatial cover of the ambient relative humidity (RH) was obtained by a hybrid model based on Bolton’s equations. Namely, we used (i) Ta estimates of the RF model to obtain the saturation vapor pressure; (ii) a spatial interpolation of dew point temperature measurements by certified meteorological stations across the whole study area; (iii) estimates of the surface air pressure based on a digital elevation model; and (iv) thermodynamic equations for calculating the ambient vapor pressure. Initially, we calculated Ta and RH at noontime in summer at all the grid cells of each Landsat image, accounting for all the qualified Landsat images in each summer. Next, we evaluated the summer-average estimates against corresponding in situ Israel Meteorological Service (IMS) stations’ average summer measurements. Finally, we studied long-term trends over the whole study area, revealing significant summer noontime long-term trends in Ta, RH and the heat index (HI) over the study area (Ta: 0.03–0.14 °C/summer; RH: 0.05–0.18%/summer; HI: 0.08–0.82 °C/summer), as well as changes in their spatial patterns.