Influences of urbanization on surface characteristics as derived from the Moderate‐Resolution Imaging Spectroradiometer: A case study for the Beijing metropolitan area

Wang, Kaicun; Wang, Jiankai; Wang, Pucai; Sparrow, Michael; Yang, Juan; Chen, Hongbin

doi:10.1029/2006jd007997

Cited by 149 publications

(67 citation statements)

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“…The nighttime SUHII in summer was lowest, which was consistent with most of the previous studies [40,66,75], but not consistent with the study of [76]. Nighttime SUHII in spring was the strongest in this study, which was different from summer in the study of [76] and winter in the studies of [40,66,75].…”

Section: Uncertaintiessupporting

confidence: 44%

“…With regard to nighttime SUHII, it was greater than daytime SUHII except for summer, and the monthly and seasonal variations of nighttime SUHII were more stable than that of daytime (Figure 4), which was also found in the cities of northern China [40,66], but different from most of the US cities [28] and global mean trend deduced from 419 global big cities [46]. In the BTH region, monthly mean nighttime SUHII was not significantly correlated with monthly mean ∆LAI/∆albedo/background nighttime LST, suggesting different driving mechanism compared with daytime SUHII.…”

Section: Possible Mechanisms Of Seasonal Suhii Variationsmentioning

confidence: 75%

“…Few studies attempted to explain winter daytime urban cool island, Wang et al [66] tried to explain it by simulating LST assigning specific thermal inertia values to soil (882 W·s 1/2 ·m −2 ·K −1 ) and urban (concrete) (1428 W·s 1/2 ·m −2 ·K −1 ) types, and they found lower thermal inertia of dry bare soil in the rural areas can explain the negative SUHII in winter. In winter, land surface is mainly covered by bare soil with sparse vegetation, thus it is conducive to increase LST than urban areas, and in turn lead to the urban cool island.…”

Section: Possible Mechanisms Of Seasonal Suhii Variationsmentioning

confidence: 99%

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Different Patterns in Daytime and Nighttime Thermal Effects of Urbanization in Beijing-Tianjin-Hebei Urban Agglomeration

et al. 2017

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Surface urban heat island (SUHI) in the context of urbanization has gained much attention in recent decades; however, the seasonal variations of SUHI and their drivers are still not well documented. In this study, the Beijing-Tianjin-Hebei (BTH) urban agglomeration, one of the most typical areas experiencing drastic urbanization in China, was selected to study the SUHI intensity (SUHII) based on remotely sensed land surface temperature (LST) data. Pure and unchanged urban and rural pixels from 2000 to 2010 were chosen to avoid non-concurrency between land cover data and LST data and to estimate daytime and nighttime thermal effects of urbanization. Different patterns of the seasonal variations were found in daytime and nighttime SUHIIs. Specifically, the daytime SUHII in summer (4 • C) was more evident than in other seasons while a cold island phenomenon was found in winter; the nighttime SUHII was always positive and higher than the daytime one in all the seasons except summer. Moreover, we found the highest daytime SUHII in August, which is the growing peak stage of summer maize, while nighttime SUHII showed a trough in the same month. Seasonal variations of daytime SUHII showed higher significant correlations with the seasonal variations of ∆LAI (leaf area index) (R 2 = 0.81, r = −0.90) compared with ∆albedo (R 2 = 0.61, r = −0.78) and background daytime LST (R 2 = 0.69, r = 0.83); moreover, agricultural practices (double-cropping system) played an important role in the seasonal variations of daytime SUHII. Seasonal variations of the nighttime SUHII did not show significant correlations with either of seasonal variations of ∆LAI, ∆albedo, and background nighttime LST, which implies different mechanisms in nighttime SUHII variation needing future studies.

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Section: Uncertaintiessupporting

confidence: 44%

Section: Possible Mechanisms Of Seasonal Suhii Variationsmentioning

confidence: 75%

Section: Possible Mechanisms Of Seasonal Suhii Variationsmentioning

confidence: 99%

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Different Patterns in Daytime and Nighttime Thermal Effects of Urbanization in Beijing-Tianjin-Hebei Urban Agglomeration

et al. 2017

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“…The correlation coefficients between R s and DTR are the highest in humid areas and lower in arid or semiarid areas because the fraction of absorbed R s generating H also depends on variable soil moisture resulting from the frequency and intensity of precipitation (15,16). Besides its dependence on surface wetness (17), the partitioning of surface-absorbed R s between H and latent heat flux (λE) depends on land-cover conditions (18,19) and atmospheric evaporative demand (20). In humid areas, both H and λE generally increase with R s (21,22), but under warm conditions the latter increases more (23).…”

Section: Significancementioning

confidence: 99%

Contribution of solar radiation to decadal temperature variability over land

Wang

Dickinson

2013

Proc. Natl. Acad. Sci. U.S.A.

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131

117

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Global air temperature has become the primary metric for judging global climate change. The variability of global temperature on a decadal timescale is still poorly understood. This paper examines further one suggested hypothesis, that variations in solar radiation reaching the surface (R s ) have caused much of the observed decadal temperature variability. Because R s only heats air during the day, its variability is plausibly related to the variability of diurnal temperature range (daily maximum temperature minus its minimum). We show that the variability of diurnal temperature range is consistent with the variability of R s at timescales from monthly to decadal. This paper uses long comprehensive datasets for diurnal temperature range to establish what has been the contribution of R s to decadal temperature variability. It shows that R s over land globally peaked in the 1930s, substantially decreased from the 1940s to the 1970s, and changed little after that. Reduction of R s caused a reduction of more than 0.2°C in mean temperature during May to October from the 1940s through the 1970s, and a reduction of nearly 0.2°C in mean air temperature during November to April from the 1960s through the 1970s. This cooling accounts in part for the near-constant temperature from the 1930s into the 1970s. Since then, neither the rapid increase in temperature from the 1970s through the 1990s nor the slowdown of warming in the early twenty-first century appear to be significantly related to changes of R s .global dimming | global brightening | global warming | surface incident solar radiation | decadal variability G lobal temperature has become the primary metric for judging global climate change, although many other factors are recognized to be of comparable importance. The overall increase of global temperature over the last century has been largely attributed to the increase of greenhouse gases (1). Less well understood are the reasons for the variability of this increase on a decadal timescale. In particular, warming from 1900 to 1940 was followed by three decades of flat or slightly decreasing temperature, then three decades of very rapid temperature increase, then so far in this century, very little additional increase. The two most plausible explanations for the decadal variability are natural climate variability and variable degrees of cooling from anthropogenic releases of sulfur gas producing sulfate aerosols (2). This effect has long been proposed as a mechanism to counter greenhouse warming (3), has become the basis for many geoengineering proposals (4), and has been used to attribute the lack of warming so far this century to the rapid growth of aerosols in Asia (5).Besides the difference in sign of their temperature effects, sulfate aerosols are distinguished from greenhouse gases in that they only affect daytime radiation, i.e., surface incident solar radiation (R s ). Some kinds of natural variability can also act through affecting R s , i.e., those involving cloud properties.Changes of aerosol loading and ...

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“…Currently, approximately 54% of the world's population lives in urban areas, and this proportion is expected to increase to 66% by 2050 [1]. The rapid urbanization process leads to the replacement of natural surfaces with man-made features such as pavements, buildings and other infrastructure, which have altered the radiative, thermal, and moisture properties of the urban environment [2,3]. In addition, population growth in urban areas has increased anthropogenic heat generated from traffic use, air conditioning facilities, and industrial activities.…”

Section: Introductionmentioning

confidence: 99%

A Satellite-Derived Climatological Analysis of Urban Heat Island over Shanghai during 2000–2013

Huang

Guo

et al. 2017

Remote Sensing

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Abstract:The urban heat island is generally conducted based on ground observations of air temperature and remotely sensing of land surface temperature (LST). Satellite remotely sensed LST has the advantages of global coverage and consistent periodicity, which overcomes the weakness of ground observations related to sparse distributions and costs. For human related studies and urban climatology, canopy layer urban heat island (CUHI) based on air temperatures is extremely important. This study has employed remote sensing methodology to produce monthly CUHI climatology maps during the period 2000-2013, revealing the spatiotemporal characteristics of daytime and nighttime CUHI during this period of rapid urbanization in Shanghai. Using stepwise linear regression, daytime and nighttime air temperatures at the four overpass times of Terra/Aqua were estimated based on time series of Terra/Aqua-MODIS LST and other auxiliary variables including enhanced vegetation index, normalized difference water index, solar zenith angle and distance to coast. The validation results indicate that the models produced an accuracy of 1.6-2.6 • C RMSE for the four overpass times of Terra/Aqua. The models based on Terra LST showed higher accuracy than those based on Aqua LST, and nighttime air temperature estimation had higher accuracy than daytime. The seasonal analysis shows daytime CUHI is strongest in summer and weakest in winter, while nighttime CUHI is weakest in summer and strongest in autumn. The annual mean daytime CUHI during 2000-2013 is 1.0 and 2.2 • C for Terra and Aqua overpass, respectively. The annual mean nighttime CUHI is about 1.0 • C for both Terra and Aqua overpass. The resultant CUHI climatology maps provide a spatiotemporal quantification of CUHI with emphasis on temperature gradients. This study has provided information of relevance to urban planners and environmental managers for assessing and monitoring urban thermal environments which are constantly being altered by natural and anthropogenic influences.

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Influences of urbanization on surface characteristics as derived from the Moderate‐Resolution Imaging Spectroradiometer: A case study for the Beijing metropolitan area

Cited by 149 publications

References 50 publications

Different Patterns in Daytime and Nighttime Thermal Effects of Urbanization in Beijing-Tianjin-Hebei Urban Agglomeration

Different Patterns in Daytime and Nighttime Thermal Effects of Urbanization in Beijing-Tianjin-Hebei Urban Agglomeration

Contribution of solar radiation to decadal temperature variability over land

A Satellite-Derived Climatological Analysis of Urban Heat Island over Shanghai during 2000–2013

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