SEARCH · Engineering Papers

Results for “urbanization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRS2007

A Numerical Study of the Urban Heat Island in the Coastal Tropical City of San Juan, Puerto Rico: Model Validation and Impacts of LCLU Changes

Urban sprawls in tropical locations are rapidly accelerating and it is more evident in islands where a large percentage of the population resides along the coasts. This paper focuses on the analysis of the impacts of land use and land cover for urbanization in the tropical coastal city of San Juan, in the tropical island of Puerto Rico. A mesoscale numerical model, the Regional Atmospheric Modeling System (RAMS), is used to study specific characteristics and patterns of the urban heat island in the San Juan Metropolitan Area (SJMA), the most noticeable urban core of the Caribbean. The research present in this paper makes use of the observations obtained during the airborne San Juan Atlas Mission in two ways. First, surface and rawinsonde data are used to validate the atmospheric model yielding satisfactory results. Second, airborne remote sensing information is used to update the model's surface characteristics to obtain a detailed configuration of the SJMA in order to perform the LCLU changes impact analysis. This analysis showed that the presence of San Juan has an impact reflected in higher air temperatures over the area occupied by the city, with positive values of up to 2.5 C, for the simulations that have specified urban LCLU indexes in the bottom boundary. One interesting result of the impact analysis was the finding of a precipitation disturbance shown as a difference in total accumulated rainfall between simulation with the city and with a potential natural vegetation induced by the presence of the urban area. Model results indicate that the urban-induced cloud formation and precipitation development occur mainly downwind of the city, including the accumulated precipitation. This spatial pattern can be explained by the presence of a-larger urbanized area in the southwest sector of the city, and of the approaching northeasterly trade winds.

Comarazamy, Daniel E.↗

NASA NTRS2010

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship to development intensity, size, and ecological setting for more than 3000 urban settlements over the globe. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby non-urban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to insure objective inter-comparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass/shrub biomes, and only a weak UHI or sometimes an Urban Heat Sink (UHS) in cities in and and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) to the difference in vegetation density between urban and rural zones represented by MODIS Normalized Difference Vegetation Index (NDVI). Globally averaged, the daytime UHI amplitude for all settlement is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers, compared to 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variances is explained by ISA for urban settlements within forests at mid-to-high latitudes. This percentage will increase to more than 80% when only USA settlements are examined.

Zhang, Ping↗

NASA NTRS2011

Assessing the Urban Heat Island Effect Across Biomes in the Continental USA Using Landsat and MODIS

Impervious surface area (ISA) from the Landsat TM and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined across urban gradients and used to stratify sampling of LST and NDVI. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban - rural temperature difference) with the largest 8 C (average) for cities built in mixed forest biomes. For all cities ISA is the primary driver for increase in temperature explaining 70% of the total variance. Annually, urban areas are warmer than the non-urban fringe by 2.9 C, except in biomes with arid and semiarid climates. The average amplitude of the UHI is asymmetric with a 4.3 C difference in summer and 1.3 C in winter. In desert environments, UHI's point to a possible heat sink effect. Results show that the urban heat island amplitude increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.

Imhoff, Marc L.↗

NASA NTRS2014

Mapping Urban Expansion Across North America Using Multi-Temporal Landsat and Nighttime Lights Data

Urban expansion and the associated changes in land cover have important climatic, hydrologic, biophysical and ecologic and socio-economic impacts on the environment. Yet, despite todays abundance of remote sensing data, an automated characterization of large-scale historical changes in urban spatial extent remains a challenge due to the inherent complexity and variability of the urban environment, the lack of a spectral signature unique to urban land cover, and the absence of an unambiguous definition of what is urban versus non-urban.Here we present a consistent, robust, scalable, physically- based methodology for characterization of urban expansion using Landsat observations. We use atmospherically corrected Landsat Global Land Survey time series, Web-enabled Landsat data time series, DMSP-OLS and NPP-VIIRS nighttime lights, for mapping the built-up and vegetated components of urban settlements at 30m resolution through multi- temporal standardized spectral mixture analysis. The methodology is tested and validated over the North American continent where it provides a first quantification of urban expansion and vegetation abundance changes from 1990 to 2010.

Milesi, Cristina↗

NASA NTRS2019

Investigating Sources of Variability and Error in Simulations of Carbon Dioxide in an Urban Region

Greenhouse gas (GHG) emissions estimation methods that use atmospheric trace gas observations, including inverse modeling techniques, perform better when carbon dioxide (CO2) fluxes are more accurately transported and dispersed in the atmosphere by a numerical model. In urban areas, transport and dispersion is particularly difficult to simulate using current mesoscale meteorological models due, in part, to added complexity from surface heterogeneity and fine spatial/temporal scales. It is generally assumed that the errors in GHG estimation methods in urban areas are dominated by errors in transport and dispersion. Other significant errors include, but are not limited to, those from assumed emissions magnitude and spatial distribution. To assess the predictability of simulated trace gas mole fractions in urban observing systems using a numerical weather prediction model, we employ an Eulerian model that combines traditional meteorological variables with multiple passive tracers of atmospheric CO2 from anthropogenic inventories and a biospheric model. The predictability of the Eulerian model is assessed by comparing simulated atmospheric CO2 mole fractions to observations from four in situ tower sites (three urban and one rural) in the Washington DC/Baltimore, MD area for February 2016. Four different gridded fossil fuel emissions inventories along with a biospheric flux model are used to create an ensemble of simulated atmospheric CO2 observations within the model. These ensembles help to evaluate whether the modeled observations are impacted more by the underlying emissions or transport. The spread of modeled observations using the four emission fields indicates the model's ability to distinguish between the different inventories under various meteorological conditions. Overall, the Eulerian model performs well; simulated and observed average CO2 mole fractions agree within 1% when averaged at the three urban sites across the month. However, there can be differences greater than 10% at any given hour, which are attributed to complex meteorological conditions rather than differences in the inventories themselves. On average, the mean absolute error of the simulated compared to actual observations is generally twice as large as the standard deviation of the modeled mole fractions across the four emission inventories. This result supports the assumption, in urban domains, that the predicted mole fraction error relative to observations is dominated by errors in model meteorology rather than errors in the underlying fluxes in winter months. As such, minimizing errors associated with atmospheric transport and dispersion may help improve the performance of GHG estimation models more so than improving flux priors in the winter months. We also find that the errors associated with atmospheric transport in urban domains are not restricted to certain times of day. This suggests that atmospheric inversions should use CO2 observations that have been filtered using meteorological observations rather than assuming that meteorological modeling is most accurate at certain times of day (such as using only mid-afternoon observations).

CO2↗

NASA NTRS2023

Sustainable Development in Algeria’s Urban Areas: Population Growth and Land Consumption

We analyzed the urban development sustainability in five major urban areas of Algeria by the standard of the UN Sustainability Development Goal indicator SDG 11.3.1, which focuses on the ratio of land consumption rate to population growth rate. We utilized the annual global artificial impervious area (GAIA) dataset to characterize land-use and population data from the two censuses carried out by the National Office of Statistics (ONS) for 2008 and 2018. We discuss the prevailing relationship between urban land consumption rate and population growth rate at the smallest territorial and population census unit scale. We confirm that the indicator SDG 11.3.1 is nonlinear and that while, for example, the wilaya of Tlemcen as a whole appears to be on a sustainable path, twenty-one of its communes are not. We found that overall, and for most of its communes, the wilaya of Oran seems to have an urban land use commensurable to its population growth, but in the wilaya of Algiers, out of fifty-seven communes, only fourteen have a tendency towards sustain-able development. However, the latter wilaya hosts the country’s capital and includes government buildings that are uninhabited but are accounted for as land consumed, and as such, the relationship between urban land consumption and population growth is biased. The wilaya of Annaba showed large discrepancies in terms of land use and population growth rates, and the evolution of these quantities is not homogenous across communes and not sustainable. In the Saharan wilaya of Ghardaia, the development is not homogeneous in all communes, with smaller communes undergoing buildup increases of more than 150% over the decade. Finally, in all communes where population growth exceeded urban land growth, there will be overcrowding, an aspect neither the SDG 11.3.1 nor the impervious surface per capita indicator captures. This result, in addition to other limitations, makes SDG 11.3.1 incomplete for the determination of the sustainable development in urban areas.

Algeria↗

NASA NTRS1984

Methane concentrations and source strengths in urban locations

The results of a six year measurement of trace gases in 18 different urban and remote areas throughout the Northern and Southern Hemispheres are reported. It is found that the measurements are consistent with a yearly atmospheric release of 30 to 60 megatons of CH4 in urban environments. Concentrations of CCl3F, CCl2F2, and CH3CCl3 were also found to be higher in the same urban samples than in corresponding samples from remote areas. The 'urban excess' (urban concentration minus remote concentration) was generally 1000 to 2000 times larger on a molar basis for CH4 than for CCl3F. The fraction of world-wide methane release occurring in the urban environment is estimated from the concentration ratios for CH4 vs CCl3F. It is shown that about 8 to 15 percent of atmospheric methane release occurs in urban areas.

Blake, D. R.↗

NASA NTRS1992

AVIRIS data and neural networks applied to an urban ecosystem

Urbanization is expanding on every continent. Although urban/industrial areas occupy a small percentage of the total landscape of the earth, their influence extends far beyond their borders, affecting terrestrial, aquatic, and atmospheric systems globally. Yet little has been done to characterize urban ecosystems of their linkages to other systems horizontally or vertically. With remote sensing we now have the tools to characterize, monitor, and model urban landscapes world-wide. However, the remote sensing performed on cities so far has concentrated on land-use patterns as distinct from land-cover or composition. The popular Anderson system is entirely land-use oriented in urban areas. This paper begins with the premise that characterizing the biophysical composition of urban environments is fundamental to understanding urban/industrial ecosystems, and, in turn, supports the modeling of other systems interfacing with urban systems. Further, it is contended that remote sensing is a tool poised to provide the biophysical composition data to characterize urban landscapes.

Ridd, Merrill K.↗

NASA NTRS1998

Urban Environment Initiative

The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.

Source record↗

NASA NTRS2001

Remote Sensing of the Urban Heat Island Effect: Assessment of Risks to Human Health and Development of Mitigation Strategies for Sustainable Cities

The growth of cities, both in population and in areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 80% of the world's population will live in cities. One of the more egregious side effects of urbanization is the deterioration in air quality as a result of increased vehicular traffic, industrialization and related activities. In the United States alone, under the more stringent air quality guidelines established by the U.S. Environmental Protection Agency (EPA) in 1997, nearly 300 counties in 34 states will not meet the new air quality standards for ground level ozone. The mitigation of one the physical/environmental characteristics of urbanization known as the urban heat island (UHI) effect, is now being looked at more closely as a possible way to bring down ground level ozone levels in cities and assist states in improving air quality. The UHI results from the replacement of "natural" land covers (e.g., trees, grass) with urban land surface types, such as pavement and buildings. Heat stored in these surfaces is released into the air and results in a "dome" of elevated air temperatures that presides over cities. The effect of this dome of elevated air temperatures is known as the UHI, which is most prevalent about 2-3 hours after sunset on days with intense solar radiation and calm winds. Given the local and regional impacts of the UHI, there are significant potential affects on human health, particularly as related to heat stress and ozone on body temperature regulation and on the cardiovascular and respiratory systems. In this study we are using airborne and satellite remote sensing data to analyze how differences in the urban landscape influence or drive the development of the UHI over four U.S. cities. Additionally, we are assessing what the potential impact is on risks to human health, and developing mitigation strategies to make urban areas more environmentally sustainable.

Quattrochi, Dale A.↗

NASA NTRS2001

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and the TRMM Satellite

A recent paper by Shepherd and Pierce (conditionally accepted to Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. A convective-mesoscale model with extensive land-surface processes is employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. Early analysis suggests that urban surface roughness (through turbulence and low-level convergence) may control timing and initial location of UHI-induced convection. The magnitude of the heat island appears to be closely linked to the total rainfall amount with minor impact on timing and location. The physical size of the city may predominantly impact on the location of UHI-induced rainfall anomaly. The UHI factor parameter space will be thoroughly investigated with respect to their effects on rainfall amount, location, and timing. This study extends prior numerical investigations of the impact of urban surfaces on meteorological processes, particularly rainfall development. The work also contains several novel aspects, including the application of a high-resolution (less than I km) cloud-mesoscale model to investigate urban-induce rainfall process; investigation of thermal magnitude of the UHI on rainfall process; and investigation of UHI physical size on rainfall processes.

Shepherd, J. Marshall↗

NASA NTRS2001

Spectral Dimensionality and Scale of Urban Radiance

Characterization of urban radiance and reflectance is important for understanding the effects of solar energy flux on the urban environment as well as for satellite mapping of urban settlement patterns. Spectral mixture analyses of Landsat and Ikonos imagery suggest that the urban radiance field can very often be described with combinations of three or four spectral endmembers. Dimensionality estimates of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) radiance measurements of urban areas reveal the existence of 30 to 60 spectral dimensions. The extent to which broadband imagery collected by operational satellites can represent the higher dimensional mixing space is a function of both the spatial and spectral resolution of the sensor. AVIRIS imagery offers the spatial and spectral resolution necessary to investigate the scale dependence of the spectral dimensionality. Dimensionality estimates derived from Minimum Noise Fraction (MNF) eigenvalue distributions show a distinct scale dependence for AVIRIS radiance measurements of Milpitas, California. Apparent dimensionality diminishes from almost 40 to less than 10 spectral dimensions between scales of 8000 m and 300 m. The 10 to 30 m scale of most features in urban mosaics results in substantial spectral mixing at the 20 m scale of high altitude AVIRIS pixels. Much of the variance at pixel scales is therefore likely to result from actual differences in surface reflectance at pixel scales. Spatial smoothing and spectral subsampling of AVIRIS spectra both result in substantial loss of information and reduction of apparent dimensionality, but the primary spectral endmembers in all cases are analogous to those found in global analyses of Landsat and Ikonos imagery of other urban areas.

Small, Christopher↗

NASA NTRS2002

High Spatial Resolution Thermal Remote Sensing of the Urban Heat Island Effect: Assessment of Risks to Human Health and Development of Mitigation Strategies for Sustainable Cities

Quattrochi, Dale A.↗

NASA NTRS2002

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Shepherd, J. Marshall↗

NASA NTRS2004

Status of NASA Satellite, Field Observations, and Numerical Modeling Addressing the Impact of Urbanization on Short and Long Term Precipitation Variability

Howard (1833a) made the first documented observation of a temperature difference between an urban area and its rural environment. Manley (1958) termed this contrast the "urban heat island (UHI)". The UHI has now become a widely acknowledged, observed, and researched phenomenon because of its broad implications. It is estimated that by the year 2025, 60% of the world's population will live in cities (UNFP, 1999). In the United States, the current urban growth rate is approximately 12.5%, with 80% currently living in urban areas. As cities continue to grow, urban sprawl creates unique problems related to land use, transportation, agriculture, housing, pollution, and development for policymakers. Urban expansion and its associated urban heat islands also have measurable impacts on weather and climate processes.

Shepherd, J. Marshall↗

NASA NTRS2005

A Multi-scale Approach to Urban Thermal Analysis

An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.

Gluch, Renne↗

NASA NTRS2006

The Use of ATLAS Data to Quantify Surface Radiative Budget Alteration Through Urbanization for San Juan, Puerto Rico.

The additional heating of the air over the city is the result of the replacement of naturally vegetated surfaces with those composed of asphalt, concrete, rooftops and other manmade materials. The temperatures of these artificial surfaces can be 20 to 40 0 C higher than vegetated surfaces. Materials such as asphalt store much of the sun s energy and remains hot long after sunset. This produces a dome of elevated air temperatures 5 to 8 C greater over the city, compared to the air temperatures over adjacent rural areas. This effect is called the "urban heat island". Urban landscapes are a complex mixture of vegetated and nonvegetated surfaces. It is difficult to take enough temperature measurements over a large city area to characterize the complexity of urban radiant surface temperature variability. However, the use of remotely sensed thermal data from airborne scanners are ideal for the task. The NASA Airborne Thermal and Land Applications Sensor (ATLAS) operates in the visual and IR bands was used in February 2004 to collect data from San Juan, Puerto Rico with the main objective of investigating the Urban Heat Island (UHI) in tropical cities. In this presentation we will examine the techniques of analyzing remotely sensed data for measuring the effect of various urban surfaces on their contribution to the urban heat island effect. Results from data collected from other US cities of Sacramento, Salt Lake City and Baton Rouge will be used to compare the "urban fabric" among the cities.

Luvall, Jeffrey C.↗

NASA NTRS2006

Simulation of Urban Heat Island Mitigation Strategies in Atlanta, GA Using High-Resolution Land Use/Land Cover Data Set to Enhance Meteorological Modeling

The specification of land use/land cover (LULC) and associated land surface parameters in meteorological models at all scales has a major influence on modeled surface energy fluxes and boundary layer states. In urban areas, accurate representation of the land surface may be even more important than in undeveloped regions due to the large heterogeneity within the urban area. Deficiencies in the characterization of the land surface related to the spatial or temporal resolution of the data, the number of LULC classes defined, the accuracy with which they are defined, or the degree of heterogeneity of the land surface properties within each class may degrade the performance of the models. In this study, an experiment was conducted to test a new high-resolution LULC data set for meteorological simulations for the Atlanta, Georgia metropolitan area using a mesoscale meteorological model and to evaluate the effects of urban heat island (UHI) mitigation strategies on modeled meteorology for 2030. Simulation results showed that use of the new LULC data set reduced a major deficiency of the land use data used previously, specifically the poor representation of urban and suburban land use. Performance of the meteorological model improved substantially, with the overall daytime cold bias reduced by over 30%. UHI mitigation strategies were projected to offset much of a predicted urban warming between 2000 and 2030. In fact, for the urban core, the cooling due to UHI mitigation strategies was slightly greater than the warming associated with urbanization over this period. For the larger metropolitan area, cooling only partially offset the projected warming trend.

Crosson, William L.↗