Urban land use and anthropogenic heat (AH) emission can considerably influence the human thermal comfort during extreme heat events. In this study, a spatially heterogeneous AH emission data and updated urban land use data are integrated into the Weather Research and Forecasting model to simulate the physical processes of urban warming during summer. Simulations conducted in the Yangtze River Delta (YRD) of east China suggest that the mean urban heat island intensity reaches 1.49 °C in urbanized areas during summer, with AH emission making a considerable contribution. The warming effect due to urban land use is intensified during extremely hot days, but in contrast, the AH effects are slightly reduced. Urban development increases the total thermal discomfort hours by 27% in the urban areas of YRD, with AH and urban land use contributing nearly equal amount. By limiting the daytime latent heat release, urban land use reduces the daily maximum heat stress particularly during extremely hot days; however, such alleviations can be offset by the AH emission. Strategies for mitigation of urban heat island effect and heat stress in cities should therefore include measures to reduce AH emission.

Surface wind trends and variability over Antarctica and the Southern Ocean and their implications to wind energy in the region are analyzed using the gridded ERA-Interim reanalysis data between 1979 and 2017 and the Self-Organizing Map (SOM) technique. In general, surface winds are stronger over the coastal regions of East Antarctica and the Transantarctic Mountains and weaker over the Ross and Ronne ice shelves and the Antarctic Peninsula; and stronger in winter and weaker in summer. Winds in the southern Indian and Pacific Oceans and along coastal regions exhibit a strong interannual variability that appears to be correlated to the Antarctic Oscillation (AAO) index. A significantly positive trend in surface wind speeds is found across most regions and about 20% and 17% of the austral autumn and summer wind trends, respectively, and less than 1% of the winter and spring wind trends may be explained by the trends in the AAO index. Except for the Antarctic Peninsula, Ronne and Ross ice shelves, and small areas in the interior East Antarctica, most of the continent is found to be suitable for the development of wind power.

The characteristics of well-developed downslope winds observed by tethered balloon soundings at multiple locations over a low-angle slope in the Salt Lake Valley are studied using the Regional Atmospheric Modeling System (RAMS). The model successfully simulated the key properties of the observed wind and temperature structure and evolution and provided insight into the forcing mechanisms. The results show that, although the slope angle is only 1.6°, the buoyancy force associated with the local temperature perturbation caused by nocturnal cooling of the slope surface is capable of producing the unusually strong and deep downslope winds observed by the tethersondes. The hypothesis that the flow is produced locally by the temperature deficit is further confirmed by analysis of the momentum budget that indicates a very small contribution from advection to the downslope mass flux. The analysis also reveals the importance of the along-slope pressure gradient force, which has been neglected by some previous investigators. On an isolated slope, the pressure gradient force, which develops as the downslope-flow layer deepens with downslope distance, is important mostly in the upper part of the downslope wind layer where it counterbalances the buoyancy force. On a slope in a valley, the pressure gradient force interacts with the valley inversion to produce intermittency in the downslope jet and may also significantly slow the flow as the inversion strengthens during the night. The simulations for two different observational nights indicate that the maximum downslope wind speed is sensitive to ambient stability, with near-neutral ambient stability yielding a stronger downslope jet than does a more stable ambient atmosphere. Sensitivity studies suggest that an increase in down-valley winds leads to a decrease in the maximum downslope wind speed and an increase in the thickness of the downslope wind layer. An increase in slope roughness, on the other hand, increases the height of the downslope jet but has little effect on other properties. The downslope wind is stronger over a gentle 1.6° slope than over a much steeper slope of 11°, mainly because of the combination of the stronger buoyancy and weaker pressure gradient over the gentle slope.

The mean climatology, seasonal and interannual variability and trend of wind speeds at the hub height (80 m) of modern wind turbines over China and its surrounding regions are revisited using 33‐year (1979–2011) wind data from the Climate Forecast System Reanalysis (CFSR) that has many improvements including higher spatial resolution over previous global reanalysis products. Mean 80‐m wind speeds are consistently higher over China Seas and the ocean areas than over land, and inside China high winds are found in areas of Inner Mongolia and the Tibetan Plateau. There is a considerable seasonal variability that reflects primarily the influence of East and Southeast Asia Monsoon with generally higher speeds in winter followed by summer, and weaker winds in autumn, followed by spring. There is also a strong interannual variability, and regions of larger amplitude of variability coincide with regions of higher mean winds. A decreasing trend, dominated by a sharp decline beginning in 2005, is seen across China and the surrounding seas in summer and autumn, and the summer trends over land and over ocean appear to be related respectively to the Pacific Decadal Oscillation (PDO) and the East Asian summer monsoon. Trends are not consistent across the region in spring and winter, however, with positive trends over some areas in northeastern and northwestern China, Mongolia and tropical oceans whereas negative trends in other regions. Nearly all areas of China experience mean annual 80‐m wind speed less than 6.9 m s⁻¹ (wind power classes of 1–2) except for some areas of Inner Mongolia where mean annual 80‐m wind speeds exceed 6.9 m s⁻¹ (Classes 3 or higher, suitable for wind energy development). China Seas and ocean areas generally fall in Class 3 or above, with the Taiwan and Luzon Straights reaching the highest Class 7.