Decheng Zhou

The footprint of urban heat island effect in China

Urban heat island (UHI) is one major anthropogenic modification to the Earth system that transcends its physical boundary. Using MODIS data from 2003 to 2012, we showed that the UHI effect decayed exponentially toward rural areas for majority of the 32 Chinese cities. We found an obvious urban/rural temperature “cliff”, and estimated that the footprint of UHI effect (FP, including urban area) was 2.3 and 3.9 times of urban size for the day and night, respectively, with large spatiotemporal heterogeneities. We further revealed that ignoring the FP may underestimate the UHI intensity in most cases and even alter the direction of UHI estimates for few cities. Our results provide new insights to the characteristics of UHI effect and emphasize the necessity of considering city- and time-specific FP when assessing the urbanization effects on local climate.

Spatiotemporal trends of urban heat island effect along the urban development intensity gradient in China

Urban heat island (UHI) represents a major anthropogenic modification to the Earth system and its relationship with urban development is poorly understood at a regional scale. Using Aqua MODIS data and Landsat TM/ETM+ images, we examined the spatiotemporal trends of the UHI effect (ΔT, relative to the rural reference) along the urban development intensity (UDI) gradient in 32 major Chinese cities from 2003 to 2012. We found that the daytime and nighttime ΔT increased significantly (p<0.05, mostly in linear form) along a rising UDI for 27 and 30 out of 32 cities, respectively. More rapid increases were observed in the southeastern and northwestern parts of China in the day and night, respectively. Moreover, the ΔT trends differed greatly by season and during daytime in particular. The ΔT increased more rapidly in summer than in winter during the day and the reverse occurred at night for most cities. Inter-annually, the ΔT increased significantly in about one-third of the cities during both the day and night times from 2003 to 2012, especially in suburban areas (0.25<UDI≤0.5), with insignificant trends being observed for most of the remaining cities. We also found that the ΔT patterns along the UDI gradient were largely controlled by local climate-vegetation conditions, while that across years were dominated by human activities. Our results highlight the strong and highly diverse urbanization effects on local climate cross China and offer limitations on how these certain methods should be used to quantify UHI intensity over large areas. Furthermore, the impacts of urbanization on climate are complex, thus future research efforts should focus more toward direct observation and physical-based modeling to make credible predictions of the effects.

Climate–vegetation control on the diurnal and seasonal variations of surface urban heat islands in China

Remotely sensed surface urban heat islands (UHIs) have gained considerable interest in recent decades due to the easy access and the wall-to-wall coverage of satellite products. The magnitude or intensity of surface UHIs have been well documented at regional and global scales, yet a systematic evaluation of the temporal variability over large areas is still lacking. In this study, the diurnal and seasonal cycles of surface UHI intensities (SUHIIs) in China are examined using Aqua/Terra MODIS data from 2008 to 2012. Results show that the mean annual SUHIIs varied greatly in a diurnal cycle, characterized by a positive day-night difference (DND) in Southeast China and the opposite in Northeast and Northwest China. Also, the SUHIIs differed dramatically in a seasonal cycle, indicated by a positive summer-winter difference (SWD) in the day and a negative SWD at night, accompanied by the highly diverse DNDs across seasons and geographic regions. Northwest and Northeast China overall showed the largest DND and SWD (>3 °C), respectively. These diurnal and seasonal variations depend strongly on local climate-vegetation regimes, as indicated by a strong positive correlation between DND and precipitation (and air temperature) and a negative relationship between DND and vegetation activity across cities and seasons. In particular, SHUIIs were quadratically correlated with the mean annual precipitation across space, suggesting that there might be a threshold in terms of the effects induced by local background climate. Our findings highlight the importance of considering the temporal variability of UHIs for more accurate characterization of the associated ecological and social-economic consequences.

Contrasting effects of urbanization and agriculture on surface temperature in eastern China

The combined effect of urbanization and agriculture, two most pervasive land use activities, on the surface climate remains poorly understood. Using Moderate Resolution Imaging Spectroradiometer data over 2010–2015 and forests as reference, we showed that urbanization warmed the land surface temperature (LST), especially during the daytime and in growing seasons (maximized at 5.0 ± 2.0°C in May), whereas agriculture (dominated by double-cropping system) cooled the LST in two growing seasons during the daytime and all the months but July during the nighttime in Jiangsu Province, eastern China. Collectively, they had insignificant effects on the LST during the day (−0.01°C) and cooled the LST by −0.6°C at night. We also found large geographic variations associated with their thermal effects, indicated by a warming tendency southward. These spatiotemporal patterns depend strongly on vegetation activity, evapotranspiration, surface albedo, and the background climate. Our results emphasize the great potential of agriculture in offsetting the heating effects caused by rapid urbanization in China.

Detection of the Coupling between Vegetation Leaf Area and Climate in a Multifunctional Watershed, Northwestern China

Accurate detection and quantification of vegetation dynamics and drivers of observed climatic and anthropogenic change in space and time is fundamental for our understanding of the atmosphere–biosphere interactions at local and global scales. This case study examined the coupled spatial patterns of vegetation dynamics and climatic variabilities during the past three decades in the Upper Heihe River Basin (UHRB), a complex multiple use watershed in arid northwestern China. We apply empirical orthogonal function (EOF) and singular value decomposition (SVD) analysis to isolate and identify the spatial patterns of satellite-derived leaf area index (LAI) and their close relationship with the variability of an aridity index (AI = Precipitation/Potential Evapotranspiration). Results show that UHRB has become increasingly warm and wet during the past three decades. In general, the rise of air temperature and precipitation had a positive impact on mean LAI at the annual scale. At the monthly scale, LAI variations had a lagged response to climate. Two major coupled spatial change patterns explained 29% and 41% of the LAI dynamics during 1983–2000 and 2001–2010, respectively. The strongest connections between climate and LAI were found in the southwest part of the basin prior to 2000, but they shifted towards the north central area afterwards, suggesting that the sensitivity of LAI to climate varied over time, and that human disturbances might play an important role in altering LAI patterns. At the basin level, the positive effects of regional climate warming and precipitation increase as well as local ecological restoration efforts overwhelmed the negative effects of overgrazing. The study results offer insights about the coupled effects of climatic variability and grazing on ecosystem structure and functions at a watershed scale. Findings from this study are useful for land managers and policy makers to make better decisions in response to climate change in the study region.

Remote sensing of the urban heat island effect in a highly populated urban agglomeration area in East China

Increasingly urban agglomeration, representing a group of cities with a compact spatial organization and close economic links, can rise surface temperature in a continuous area due to decreasing distance between cities. Significant progress has been made in elucidating surface urban heat island intensity (SUHII) of a single city or a few big cities, but the SUHIIs patterns remain poorly understood in urban agglomeration regions. Using Aqua/Terra MODIS data over 2010-2015, we examined the SUHII variations and their drivers in Yangtze River Delta Urban Agglomeration (YRDUA) of east China. Instead of using the widely-used suburban/rural areas as references, this study predicted the unaffected reference temperature wall-to-wall from natural forests by a simple planar surface model. Results indicated that urbanization warmed the land surface regardless of urban area size in YRDUA, with the SUHII clearly larger in the day (2.6±0.9°C) than night (0.7±0.4°C). The SUHII varied markedly by cities, yet the largest did not happen in the presumed core cities. Also, the SUHII differed greatly in a seasonal cycle, with summer-winter difference of 4.2±0.9°C and 2.0±0.5°C in the day and night, respectively. Particularly, cooling effects of urban areas were observed in winter for the majority of cities at night. These spatiotemporal patterns depend strongly on the background climate (precipitation and air temperature), vegetation activity, surface albedo, and population density, with contrast mechanisms during the day and night. Further, we showed that ignoring urban agglomeration effect (using suburban/rural areas as the unaffected references) would lead to large biases of SUHII estimates in terms of magnitude and spatial distribution. Our results emphasize the necessity of considering cities altogether when assessing the urbanization effects on climate in an urban agglomeration area.

Quantifying the effects of overgrazing on mountainous watershed vegetation dynamics under a changing climate

Grazing is a major ecosystem disturbance in arid regions that are increasingly threatened by climate change. Understanding the long-term impacts of grazing on rangeland vegetation dynamics in a complex terrain in mountainous regions is important for quantifying dry land ecosystem services for integrated watershed management and climate change adaptation. However, data on the detailed long-term spatial distribution of grazing activities are rare, which prevents trend detection and environmental impact assessments of grazing. This study quantified the impacts of grazing on vegetation dynamics for the period of 1983-2010 in the Upper Heihe River basin, a complex multiple-use watershed in northwestern China. We also examined the relative contributions of grazing and climate to vegetation change using a dynamic grazing pressure method. Spatial grazing patterns and temporal dynamics were mapped at a 1 km × 1 km pixel scale using satellite-derived leaf area index (LAI) data. We found that overgrazing was a dominant driver for LAI reduction in alpine grasslands and shrubs, especially for the periods of 1985-1991 and 1997-2004. Although the recent decade-long active grazing management contributed to the improvement of LAI and partially offset the negative effects of increased livestock, overgrazing has posed significant challenges to shrub-grassland ecosystem recovery in the eastern part of the study basin. We conclude that the positive effects of a warming and wetting climate on vegetation could be underestimated if the negative long-term grazing effects are not considered. Findings from the present case study show that assessing long-term climate change impacts on watersheds must include the influences of human activities. Our study provides important guidance for ecological restoration efforts in locating vulnerable areas and designing effective management practices in the study watershed. Such information is essential for natural resource management that aims at meeting multiple demands of watershed ecosystem services in arid and semiarid rangelands.