The focus of this study is an intense heat episode that occurred on 9–13 July 2017 in Beijing, China, that resulted in severe impacts on natural and human variables, including record-setting daily electricity consumption levels. This event was observed and analyzed with a suite of local and mesoscale instruments, including a high-density automated weather station network, soil moisture sensors, and ground-based vertical instruments (e.g., a wind profiler, a ceilometer, and three radiometers) situated in and around the city, as well as electric power consumption data and analysis data from the U.S. National Centers for Environmental Prediction. The results show that the heat wave originated from dry adiabatic warming induced by the dynamic downslope and synoptic subsidence. The conditions were aggravated by the increased air humidity during subsequent days, which resulted in historically high records of the heat index (i.e., an index representing the apparent temperature that incorporates both air temperature and moisture). The increased thermal energy and decreased boundary layer height resulted in a highly energized urban boundary layer. The differences between urban and rural thermal conditions throughout almost the entire boundary layer were enhanced during the heat wave, and the canopy-layer urban heat island intensity (UHII) reached up to 8°C at a central urban station at 2300 local standard time 10 July. A double-peak pattern in the diurnal cycle of UHIIs occurred during the heat wave and differed from the single-peak pattern of the decadal average UHII cycles. Different spatial distributions of UHII values occurred during the day and night.

The geographic and temporal variability of the surface–3600-m cloud frequency and cloud-base height over the contiguous United States for a 5-yr period (2008–12) and the interannual variations for a 16-yr period (2000–15) are described using information from the Automated Surface Observing System (ASOS) observations. Clouds were separated into four categories by the cloud amount reported by ASOS: few (FEW), scattered (SCT), broken (BKN), and overcast (OVC). The geographic distributions and seasonal and diurnal cycles of the four categories of surface–3600-m cloud frequency have different patterns. Cloud frequency of FEW, SCT, and BKN peaks just after noon, whereas the frequency of OVC peaks in the early morning. However, the geographic distributions and seasonal and diurnal cycles of the four categories of the surface–3600-m cloud-base height are similar. The diurnal cycles of the cloud-base height within the surface–3600-m level present a minimum in the morning and peak in the late afternoon or early evening. Cloud frequency and cloud-base height within this range are closely related to surface air temperature and humidity conditions. From 2000 to 2015, the cloud frequency in the contiguous United States showed a positive trend of 0.28% yr−1 while the cloud-base height showed a negative trend of −4 m yr−1 for the surface–3600-m level, accompanied with a positive trend of precipitation days (0.14 days yr−1). Moreover, the increase of cloud frequency and the decrease of cloud-base height were most obvious in winter in the eastern half of the contiguous United States.

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Monitoring crop phenology has become a growing concern for food security. Crop phenology can be traditionally observed at plot scale in the field or recently at a much larger scale by satellites. In this study, we compared the spring phenology of winter wheat (Triticum sp.), quantified as the timing of start-of-spring-season (SOS), using 8 km resolution satellite data and ground observations at 112 agrometeorological stations across China from 1993 to 2008. We found that ground and satellite observations displayed opposing trends in winter wheat SOS. Ground observation exhibited a delayed onset of SOS at 86% of ground stations, whereas satellite data suggested an earlier arrival of SOS at 78% of stations. The meteorological SOS calculated from daily air temperature supported the earlier occurrence of SOS indicated by satellite data. Moreover, satellite data showed more agreement with meteorological data with respect to interannual SOS variations than did field phenology records. Given the dominant control of air temperature on winter wheat's spring phenology, satellite observation provides a reliable measure of the long-term trends and dynamics of SOS. Ground-observed SOS trends were impaired by data heterogeneity and limited spatial coverage. However, compared with ground observations, satellite-derived phenological timings are often lack of biological meanings. Therefore, integrating ground and satellite observations could enhance the monitoring of winter wheat SOS, which would increase the knowledge of vegetation's response to the changing climate and help to optimize timely crop management.

In this article, we argue that Confucian philosophies are vital to understanding contemporary Chinese geopolitics. Existing Western geopolitical frameworks, we contend, are insufficient for grasping the complex theories and historical legacies that underpin China’s foreign policy. This issue becomes particularly salient as scholars and the public alike try to manage complex and changing geopolitical ideas underpinning the Belt and Road Initiative, recently heralded by the Chinese state and epitomising China’s ambition for expanded global engagements. This article provides a much-needed critical assessment and review of Confucian ideas and their uptake in Chinese state theory, geographical imaginations, and geopolitical scripts. While Confucianism typically focuses on ideals of harmony, hierarchy, and normative social order, geopolitics analyses geographical influences on politics – in particular, violence and conflict. However, it is precisely within this contradictory dialectic that new possibilities for analysing the geopolitics of a rising global power can emerge.

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Future climate change predictions by global climate models or earth system models diverge significantly, most likely due to their different cloud responses to global warming. There is an uncertainty as to how the cloud frequency (or cloud fraction) and height will change, in turn, affecting the sign, and amount of cloud feedbacks. While satellite observations have been very useful in augmenting information on clouds, it is mostly related to cloud tops, and there is a lack of information on cloud base height (CBH). In this study, a unique record of CBH information was collected at 706 Automated Surface Observing System (ASOS) ceilometer stations to evaluate the ability of the North American Regional Reanalysis (NARR) model to correctly simulate similar information. It was found that NARR can capture the geographical distribution and the seasonal variation of CBH and cloud base frequency (CBF). On average, the CBF values of NARR were 7% fewer and the CBH values of NARR were 631 m lower than those from observations that span the distance from the surface to 7,600 m. NARR simulates CBH better in arid area in the west of the contiguous United States (CONUS) than in humid areas, where NARR frequently predicted cloud bases too low compared with observations. In the west coast area of the CONUS, the discontinuity between high cloud bases over arid inland areas and low marine cloud layers from the Pacific Ocean over coastal areas produced especially large deviations between the NARR-simulated and ASOS-observed CBHs.

25Clouds determine the amount of solar radiation incident to the surface. Accurately 26 quantifying cloud fraction is of great importance, but difficult to accomplish. Satellite 27 and surface cloud observations have different fields of view (FOVs); the lack of 28 conformity of different FOVs may cause large discrepancies when comparing 29 satellite-and surface-derived cloud fractions. From the viewpoint of surface-incident 30 solar radiation, this paper compares Moderate Resolution Imaging Spectroradiometer 31 (MODIS) Level-2 cloud-fraction data with three surface cloud-fraction datasets at five 32 surface-radiation budget network (SURFRAD) sites. The correlation coefficients 33 between MODIS and the surface cloud fractions are in the 0.80-0.91 range and vary at 34 different SURFRAD sites. In a number of cases, MODIS observations show a large 35 cloud-fraction bias compared with surface data. The variances between MODIS and 36 the surface cloud-fraction datasets are more apparent when small convective or 37 broken clouds exist in the FOVs. The magnitude of the discrepancy between MODIS 38 and surface-derived cloud fractions depends on the satellite view zenith angle (VZA) 39 of the satellite. On the average, compared to surface cloud-fraction data, MODIS 40 observes a larger cloud fraction at VZA >40 º and a smaller cloud fraction at VZA 41 <20 º . When comparing long-term MODIS averages with surface datasets, 42 Aqua/MODIS observes a higher annual mean cloud fraction, likely because 43 convective clouds are better developed in the afternoon when Aqua is observing.44 45 46 3