"Summer Land" in the 'N. E. D.'

The cooling effect of the ocean on the Southern California coastal zone is investigated using a high‐resolution (4‐km) gridded surface meteorological data set (gridMET) of daily maximum temperature (Tmax), with focus on summer mean conditions, taken as the July–August–September (JAS) average. An empirical orthogonal function analysis reveals a coastal mode of JAS temperature covariability, distinct from a more energetic inland mode, that captures Tmax averaged across the Southern California coastal plain. The coastal mode temperature correlates significantly with, and has similar amplitude to, regional sea surface temperature (SST). High (low) summer land and sea surface temperatures, as well as inversion layer temperature differences, are associated with decreases (increases) of northerly coastal wind speeds and coastal cloudiness. The number of extreme heat days on land increases as regional SST increases (4.3 days °C−1), with heat wave days 10 times more likely during peak warm versus cool coastal mode years. The coastal zone was notably warmer and heat wave days peaked during the well documented marine heat wave events of 2014/15 and 2018 off Southern California. The marine variability associated with the coastal mode also has strong expression off the Baja California peninsula, presumably due to strong covarying winds in that area. As in previous studies, higher ocean temperatures are attributed to weaker summer winds, with associated reductions in ocean surface heat loss, coastal upwelling, and cloudiness.

The escalating impact of global climate change on the urban heat island effect presents a significant challenge for sustainable urban planning and the preservation of thermal comfort in metropolitan areas. The impact of land use composition on land surface temperature varies across different locations and climate zones. This study employed spatial regression, including Spatial Lag Model (SLM) and Spatial Error Model (SEM), to investigate the correlation between land use types and temperature in four East Asian metropolises: Beijing, Seoul, Tokyo, and Taipei. Moderate Resolution Imaging Spectroradiometer (MODIS) datasets are applied to generate the summer land surface temperature. At the same time, Sentinel-2 imageries and Visible Infrared Imaging Radiometer Suite (VIIRS) are integrated to derive the land use and cover, effectively distinguishing high- and low-development areas. The results indicate that Tokyo experienced the most severe heat among the four metropolises during the summer of 2020. Both spatial lag and spatial error models can effectively improve the OLS model, making its coefficients more representative. Additionally, we observe that low-density building areas have a higher impact on temperature than high-density building areas. The outcome of this study can be utilized to develop effective large-scale strategies for mitigating the urban heat island effect.

A large-scale afforestation project has been carried out since 1999 in the Loess Plateau of China. However, vegetation-induced changes in land surface temperature (LST) through the changing land surface energy balance have not been well documented. Using satellite measurements, this study quantified the contribution of vegetation restoration to the changes in summer LST and analyzed the effects of different vegetation restoration patterns on LST during both daytime and nighttime. The results show that the average daytime LST decreased by 4.3°C in the vegetation restoration area while the average nighttime LST increased by 1.4°C. The contributions of the vegetation restoration project to the changes in daytime LST and nighttime LST are 58% and 60%, respectively, which are far greater than the impact of climate change. The vegetation restoration pattern of cropland (CR) converting into artificial forest (AF) has a cooling effect during daytime and a warming effect at nighttime, while the conversion of CR to grassland has an opposite effect compared with the conversion of CR to AF. Our results indicate that increasing evapotranspiration caused by the vegetation restoration on the Loess Plateau is the controlling factor of daytime LST change, while the nighttime LST change is affected by soil humidity and air humidity.