The Footprint of Urban Areas on Global Climate as Characterized by MODIS

2005 ◽  
Vol 18 (10) ◽  
pp. 1551-1565 ◽  
Author(s):  
Menglin Jin ◽  
Robert E. Dickinson ◽  
Da Zhang

Abstract One mechanism for climate change is the collected impact of changes in land cover or land use. Such changes are especially significant in urban areas where much of the world’s population lives. Satellite observations provide a basis for characterizing the physical modifications that result from urbanization. In particular, the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the National Aeronautics and Space Administration (NASA) Terra satellite measures surface spectral albedos, thermal emissivities, and radiative temperatures. A better understanding of these measurements should improve our knowledge of the climate impact of urbanization as well as our ability to specify the parameters needed by climate models to compute the impacts of urbanization. For this purpose, it is useful to contrast urban areas with neighboring nonurban surfaces with regard to their radiative surface temperatures, emissivities, and albedos. Among these properties, surface temperatures have been most extensively studied previously in the context of the “urban heat island” (UHI). Nevertheless, except for a few detailed studies, the UHI has mostly been characterized in terms of surface air temperatures. To provide a global analysis, the zonal average of these properties are presented here measured over urban areas versus neighboring nonurban areas. Furthermore, individual cities are examined to illustrate the variations of these variables with land cover under different climate conditions [e.g., in Beijing, New York, and Phoenix (a desert city of the United States)]. Satellite-measured skin temperatures are related to the surface air temperatures but do not necessarily have the same seasonal and diurnal variations, since they are more coupled to surface energy exchange processes and less to the overlying atmospheric column. Consequently, the UHI effects from skin temperature are shown to be pronounced at both daytime and nighttime, rather than at night as previously suggested from surface air temperature measurements. In addition, urban areas are characterized by albedos much lower than those of croplands and deciduous forests in summer but similar to those of forests in winter. Thus, urban surfaces can be distinguished from nonurban surfaces through use of a proposed index formed by multiplying skin temperature by albedo.


Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1377
Author(s):  
Weifang Shi ◽  
Nan Wang ◽  
Aixuan Xin ◽  
Linglan Liu ◽  
Jiaqi Hou ◽  
...  

Mitigating high air temperatures and heat waves is vital for decreasing air pollution and protecting public health. To improve understanding of microscale urban air temperature variation, this paper performed measurements of air temperature and relative humidity in a field of Wuhan City in the afternoon of hot summer days, and used path analysis and genetic support vector regression (SVR) to quantify the independent influences of land cover and humidity on air temperature variation. The path analysis shows that most effect of the land cover is mediated through relative humidity difference, more than four times as much as the direct effect, and that the direct effect of relative humidity difference is nearly six times that of land cover, even larger than the total effect of the land cover. The SVR simulation illustrates that land cover and relative humidity independently contribute 16.3% and 83.7%, on average, to the rise of the air temperature over the land without vegetation in the study site. An alternative strategy of increasing the humidity artificially is proposed to reduce high air temperatures in urban areas. The study would provide scientific support for the regulation of the microclimate and the mitigation of the high air temperature in urban areas.



2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.



2015 ◽  
Vol 10 (3) ◽  
pp. 239-246 ◽  
Author(s):  
Aleksandra Deluka-Tibljaš ◽  
Sanja Šurdonja ◽  
Sergije Babić ◽  
Marijana Cuculić

Heat islands are areas that have higher air temperatures than their surroundings. It has been proven that the use of certain types of pavement surface materials contributes to the occurrence of heat islands. The heat island effect is dominant in urban areas, mainly in city centres. To identify potentially favourable pavement surface materials that are suitable for the use on surfaces in urban areas, an extensive analysis of in-place material temperatures was conducted in the city centre of Rijeka (Croatia) during the summer of 2011 and 2012. The measurements included temperatures of pavement surfaces made of asphalt, concrete and stone. The analysis results identified local materials whose use help to reduce or mitigate the effect of additional heating in the urban environment caused by emission of heat from pavement surfaces. In terms of additional heating of urbanized areas, asphalt has proven to be significantly less favourable than other analysed materials. In addition to the materials selected for the use in wearing courses, their characteristics and the microclimates of the locations where they will be placed must be taken into consideration. Among the standard paving materials, in terms of heating and temperature, concrete is more favourable than asphalt because the differences between concrete surface temperatures and air temperatures are significantly smaller than between asphalt surface temperatures and air temperatures. Stone surfaces have proven to be the most favourable. The analysis results presented can be used to establish clear guidelines for using specific materials under specific conditions.



2020 ◽  
Vol 12 (15) ◽  
pp. 2503 ◽  
Author(s):  
Philip Lynch ◽  
Leonhard Blesius ◽  
Ellen Hines

An accelerating trend of global urbanization accompanying population growth makes frequently updated land use and land cover (LULC) maps critical. LULC maps have been widely created through the classification of remotely sensed imagery. Maps of urban areas have been both dichotomous (urban or non-urban) and entailing of discrete urban types. This study incorporated multispectral built-up indices, designed to enhance satellite imagery, for introducing new urban classification schemes. The indices examined are the new built-up index (NBI), the built-up area extraction index (BAEI), and the normalized difference concrete condition index (NDCCI). Landsat Level-2 data covering the city of Miami, FL, USA was leveraged with geographic data from the Florida Geospatial Data Library and Florida Department of Environmental Protection to develop and validate new methods of supervised and unsupervised classification of urban area. NBI was used to extract discrete urban features through object-oriented image analysis. BAEI was found to possess properties for visualizing and tracking urban development as a low-high gradient. NDCCI was composited with NBI and BAEI as the basis for a robust urban intensity classification scheme superior to that of the United States Geological Survey National Land Cover Database 2016. BAEI, implemented as a shadow index, was incorporated in a novel infill geosimulation of high-rise construction. The findings suggest that the proposed classification schemes are advantageous to the process of creating more detailed cartography in response to the increasing global demand.



2017 ◽  
Vol 10 (11) ◽  
pp. 4105-4127 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison L. Steiner

Abstract. We develop a prognostic model called Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type, and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in the Regional Climate Model version 4 (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model using (1) a taxa-specific land cover database, phenology, and emission potential, and (2) a plant functional type (PFT) land cover, phenology, and emission potential. The simulated surface pollen concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model; however, we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.



2013 ◽  
Vol 6 (2) ◽  
pp. 563-582 ◽  
Author(s):  
S. Faroux ◽  
A. T. Kaptué Tchuenté ◽  
J.-L. Roujean ◽  
V. Masson ◽  
E. Martin ◽  
...  

Abstract. The overall objective of the present study is to introduce the new ECOCLIMAP-II database for Europe, which is an upgrade for this region of the former initiative, ECOCLIMAP-I, already implemented at global scale. The ECOCLIMAP programme is a dual database at 1 km resolution that includes an ecosystem classification and a coherent set of land surface parameters that are primarily mandatory in meteorological modelling (notably leaf area index and albedo). Hence, the aim of this innovative physiography is to enhance the quality of initialisation and impose some surface attributes within the scope of weather forecasting and climate related studies. The strategy for implementing ECOCLIMAP-II is to depart from prevalent land cover products such as CLC2000 (Corine Land Cover) and GLC2000 (Global Land Cover) by splitting existing classes into new classes that possess a better regional character by virtue of the climatic environment (latitude, proximity to the sea, topography). The leaf area index (LAI) from MODIS and normalized difference vegetation index (NDVI) from SPOT/Vegetation (a global monitoring system of vegetation) yield the two proxy variables that were considered here in order to perform a multi-year trimmed analysis between 1999 and 2005 using the K-means method. Further, meteorological applications require each land cover type to appear as a partition of fractions of 4 main surface types or tiles (nature, water bodies, sea, urban areas) and, inside the nature tile, fractions of 12 plant functional types (PFTs) representing generic vegetation types – principally broadleaf forest, needleleaf forest, C3 and C4 crops, grassland and bare land – as incorporated by the SVAT model ISBA (Interactions Surface Biosphere Atmosphere) developed at Météo France. This landscape division also forms the cornerstone of a validation exercise. The new ECOCLIMAP-II can be verified with auxiliary land cover products at very fine and coarse resolutions by means of versatile land occupation nomenclatures.



2015 ◽  
Vol 8 ◽  
pp. ASWR.S21560
Author(s):  
Komariah ◽  
Masateru Senge ◽  
Sumani ◽  
Widyatmani Sih Dewi ◽  
Kohei Yoshiyama ◽  
...  

This article is discussing the impacts of land cover change from paddy field to barren land in small scale area (1,516.5 km2), on the surrounding local climate components in central Java, Indonesia. Data of several climate components from 2000-2010 were collected from weather stations that located separately. The land covers were dominated with cropland and little forest on eastern site, and settlements (urban) on western site. This study confirmed that the decrease in 13.1% of paddy field and the increase in 12.4% of barren land had significantly resulted in low daily actual vapor pressure (ea) during dry months with low rainfalls. The eastern areas that were originally occupied by croplands and trees, responded to the decrease of paddy fields by the increasing of air temperatures. The air temperatures and their variations at urban areas located in the western part were not distinctly affected by the land cover change.



2016 ◽  
Vol 29 (19) ◽  
pp. 6923-6935 ◽  
Author(s):  
Michael A. Rawlins ◽  
Raymond S. Bradley ◽  
Henry F. Diaz ◽  
John S. Kimball ◽  
David A. Robinson

Abstract This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada.



Climate ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 12 ◽  
Author(s):  
Jeremy S. Hoffman ◽  
Vivek Shandas ◽  
Nicholas Pendleton

The increasing intensity, duration, and frequency of heat waves due to human-caused climate change puts historically underserved populations in a heightened state of precarity, as studies observe that vulnerable communities—especially those within urban areas in the United States—are disproportionately exposed to extreme heat. Lacking, however, are insights into fundamental questions about the role of historical housing policies in cauterizing current exposure to climate inequities like intra-urban heat. Here, we explore the relationship between “redlining”, or the historical practice of refusing home loans or insurance to whole neighborhoods based on a racially motivated perception of safety for investment, with present-day summertime intra-urban land surface temperature anomalies. Through a spatial analysis of 108 urban areas in the United States, we ask two questions: (1) how do historically redlined neighborhoods relate to current patterns of intra-urban heat? and (2) do these patterns vary by US Census Bureau region? Our results reveal that 94% of studied areas display consistent city-scale patterns of elevated land surface temperatures in formerly redlined areas relative to their non-redlined neighbors by as much as 7 °C. Regionally, Southeast and Western cities display the greatest differences while Midwest cities display the least. Nationally, land surface temperatures in redlined areas are approximately 2.6 °C warmer than in non-redlined areas. While these trends are partly attributable to the relative preponderance of impervious land cover to tree canopy in these areas, which we also examine, other factors may also be driving these differences. This study reveals that historical housing policies may, in fact, be directly responsible for disproportionate exposure to current heat events.



2018 ◽  
Vol 57 (10) ◽  
pp. 2267-2283 ◽  
Author(s):  
Dongwei Liu ◽  
C. S. B. Grimmond ◽  
Jianguo Tan ◽  
Xiangyu Ao ◽  
Jie Peng ◽  
...  

AbstractA simple model, the Surface Temperature and Near-Surface Air Temperature (at 2 m) Model (TsT2m), is developed to downscale numerical model output (such as from ECMWF) to obtain higher-temporal- and higher-spatial-resolution surface and near-surface air temperature. It is evaluated in Shanghai, China. Surface temperature (Ts) and near-surface air temperature (Ta) submodels account for variations in land cover and their different thermal properties, resulting in spatial variations of surface and air temperature. The net all-wave radiation parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature submodel, the objective hysteresis model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near-surface air temperature submodel considers the horizontal and vertical energy changes for a column of well-mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land-cover types, values are more similar. Downscaled, higher-temporal- and higher-spatial-resolution air temperatures are compared to observations at 110 automatic weather stations across Shanghai. After downscaling with TsT2m, the average forecast accuracy of near-surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stress.



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