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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.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Estimation of intensity, footprint, and capacity of surface urban heat islands using a direction-enhanced adaptive synchronous extraction (DEASE) method

Here, the surface urban heat island (SUHI) effect, assessed through remotely sensed land surface temperature (LST), remains a focal point in urban climate research. Conventional indicators like SUHI intensity (SUHII) and footprint (SUHIF) capture peak values and spatial extent but fail to account for the cumulative thermal load—a critical dimension reflecting the total heat exposure imposed by spatially continuous warming, which directly limits a holistic assessment of ecological and societal impacts of the SUHI effect. Therefore, this study introduces an indicator termed SUHI capacity (SUHIC), designed to quantify the aggregated SUHI effect by integrating the magnitude of the warming signal across all affected areas, thereby enabling a more comprehensive evaluation of urban thermal environments. Furthermore, a direction-enhanced adaptive synchronous extraction (DEASE) method is proposed for the quantification of SUHIC. This method can dynamically identify the optimal background reference area based on the urban-rural LST gradients in various directions within the city, without relying on predefined mathematical models as previously. The results from 102 European cities first confirm that the directional variations in urban-rural LST gradients, and the DEASE method can effectively capture these distinctions for the simultaneous estimation of SUHII, SUHIF, and SUHIC. Secondly, the spatial patterns of absolute SUHIC values show strong associations with those of SUHIF (R2>0.86), while its relative values (normalized by the area of urban) align more closely with SUHII (R2 > 0.64). More importantly, SUHIC can serve as a crucial reference for assessing the urban thermal signal when SUHII and SUHIF diverge. The proposed method and framework contribute to standardizing the quantification of the SUHI effect.

Indicator↗
NASA NTRS1999

Fractal Characterization of Hyperspectral Imagery

Two Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.

Qiu, Hon-Iie↗
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 NTRS2024

San José Urban Development: Quantifying Canopy Cover and Land Surface Temperature in San José to Identify Future Tree Planting Sites

The urban heat island effect refers to the phenomenon of substantially increased temperatures in urban areas compared to their surrounding suburban or rural counterparts. The City of San José’s Department of Parks, Recreation and Neighborhood Services (PRNS) and Department of Transportation (DOT) work to mitigate the UHI effect through urban forestry initiatives. The PRNS and DOT partnered with NASA DEVELOP to identify areas in need of tree plantings. We examined land surface temperature (LST) throughout the city using data from the Thermal Infrared Sensor (TIRS) and TIRS-2 on NASA’s Landsat 8 and 9 satellites from 2013 to 2024. We also assessed canopy cover in parks using LiDAR data collected in 2020 for the United States Geological Survey’s 3D Elevation Program, and measured vegetation greenness using the Normalized Difference Vegetation Index (NDVI) with PlanetScope imagery from 2018 to 2024. We evaluated social and environmental factors that influence the distribution of heat event impacts by creating a heat vulnerability index. We found that heat is concentrated in urban areas and that poor vegetation health is associated with high LST. We also found that socially vulnerable communities are disproportionately located in areas of high environmental risk. These analyses allow the partners to prioritize tree plantings in parks near areas of high social and environmental risk. We determined that Earth observations can be used to inform urban forestry decision making, but because methodologies for using LiDAR to assess canopy cover vary greatly, it is difficult to make comparisons across different canopy cover assessments.

land surface temperature↗
DOE OSTI2023

Geographic disparities of cardiovascular and cancer mortality in the USA: 1981–2019

Background: Cardiovascular and cancer mortality are the two leading causes of death in the developed world including the USA. However, mortality trends for these diseases are highly dynamic, and the geographic landscape is in transition. We analyze patterns of mortality improvement at county level during recent decades focusing on mortality decline and geographic diversity. Methods: We grouped age-adjusted mortality rates of cardiovascular and cancer diseases from CDC WONDER for 2959 US counties into 3-year time periods to improve reliability. We calculated percent mortality decrease between 1981–83 and 2016–19 for both causes to quantify mortality improvements for counties. Results: Using standard deviation as an index of disparities, place-based cancer mortalities were 68% larger than cardiovascular disparities. Significantly, 566 US counties had same or higher rates of cancer mortality in 2019 as in 1981. The geographic distribution of mortality improvement in either cause tends to favor largely populated areas along coasts. Less-populated, rural places in the interior and southeastern regions were experiencing less improvement. Conclusions: At the county level, large place-based disparities exist for both causes of death with the magnitude of disparities being substantially larger for the reduction in cancer deaths. Put differently, place matters, more for cancer than cardiovascular mortality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Urbanization-induced land and aerosol impacts on storm propagation and hail characteristics

Changes in land surface and aerosol characteristics from urbanization can affect dynamic and microphysical properties of severe storms, thus affecting hazardous weather events resulting from such storms such as hail and tornado. We examine the joint and individual effects of urban land and anthropogenic aerosols of Kansas City on a severe convective storm observed during the 2015 Plains Elevated Convection At Night (PECAN) field campaign, focusing on storm evolution, convective intensity, and hail characteristics. The simulations are carried out at the cloud-resolving scale (1 km) using a version of WRF-Chem in which the spectral-bin microphysics (SBM) is coupled with the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC). It is found that the urban land effect of Kansas City initiated a much stronger convective cell and the storm got further intensified when interacting with stronger turbulence induced by the urban land. The urban land effect also changed the storm path by diverting the storm toward the city mainly resulting from enhanced urban land-induced convergence in the urban area and around the urban-rural boundaries. The joint effect of urban land and anthropogenic aerosols enhances occurrences of both severe hail and significant severe hail by ~ 20% by enhancing hail formation and growth from riming. Overall the urban land effect on convective intensity and hail is relatively larger than the anthropogenic aerosol effect, but the joint effect is much notable than either of the individual effects, emphasizing the importance to consider both effects in evaluating urbanization effects.

Lin, Yun↗
DOE OSTI2026

Measurements of TRACER pre-convective conditions and mesoscale circulations using small unmanned aircraft systems (sUAS)

Improved comprehension of the physical processes governing convective cloud formation and lifecycle are of critical importance for understanding and predicting future climate states. The influence of these clouds on the planetary energy budget, including on precipitation, is significant. Things are particularly complex in coastal regimes, where gradients in aerosol particle properties, localized circulations such as sea breezes, and large population centers are found. To date, numerical models struggle to accurately represent these critical clouds and are therefore challenged to provide a realistic view on the planetary energy budget. Through the proposed research, we deployed two uncrewed aircraft systems (UAS) equipped with a variety of instruments alongside sensors deployed by the US Department of Energy Atmospheric Radiation Measurement (ARM) program for the TRACER (Tracking Aerosol Convection Interactions Experiment) field campaign. The two small UAS platforms consisted of a CU RAAVEN fixed-wing airplane and an OU CopterSonde system, with the copter collecting frequent vertical profiles of thermodynamic and kinematic variables such as temperature, pressure, wind and humidity. At the same time, the fixed-wing captured horizontal gradients of these quantities and aerosol size distribution. These systems were deployed south of the Houston metro area, in an area that is impacted by the Gulf of Mexico sea breeze on a daily basis. These observations offer enhanced and complementary perspectives to those provided by the DOE ARM Mobile Facility (AMF) which is was deployed in southeast Houston, and an ancillary site in a more rural location west of the urban Houston area. Quality-controlled versions of the UAS data were collected and posted on the DOE ARM data archive after the conclusion of the campaign where they are accessible by the research community and general public. The UAS perspective offers revolutionary insight into key spatial and temporal effects that have not been evaluated previously.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Urban Forests as Main Regulator of the Evaporative Cooling Effect in Cities

Abstract Higher temperatures in urban areas expose a large fraction of the human population to potentially dangerous heat stress. Green spaces are promoted worldwide as local and city‐scale cooling strategies but the amount, type, and functioning of vegetation in cities lack quantification and their interaction with urban climate in different settings remains a matter of debate. Here we use state‐of‐the‐art remote sensing data from 145 city clusters to disentangle the drivers of surface urban heat islands (SUHI) intensity and quantify urban‐rural differences in vegetation cover, species composition, and evaporative cooling. We show that nighttime SUHIs are affected mostly by abiotic factors, while daytime SUHIs are highly correlated with vegetation characteristics and the wetness of the background climate. Magnitude and seasonality of daytime SUHIs are controlled by urban‐rural differences in plant transpiration and leaf area, which explain the dependence of SUHIs on wetness conditions. Leaf area differences are caused primarily by changes in vegetation type and a loss of in‐city forested areas, highlighting the importance of maintaining “natural reserves” as a sustainable heat mitigation policy.

Paschalis, Athanasios↗
NASA NTRS2004

Tropospheric Ozone Climatology over Irene, South Africa, From 1990-1994 and 1998-2002

This paper describes ozone profiles from sonde data during the period of NASA s TRACE-A and the more recent SHADOZ (Southern Hemisphere Additional Ozonesondes) period. The data were taken by the South African Weather Service at the Irene (25 deg.54 min S; 28 deg. 13 min. E) station near Pretoria, South Africa, an area that is a unique mixture of local industry, heavy biofuels use and importation of biomass burning ozone from neighboring countries to the north. The main findings are: (1) With its geographical position at the edge of the subtropical transition zone, mid- latitude dynamical influences are evident at Irene, predominantly in winter when upper tropospheric ozone is enhanced as a result of stratospheric-tropospheric exchange. (2) There has been an increase in the near-surface ozone amount between the early 1990s and a decade later, presumably due to an influx of rural population toward the Johannesburg-Pretoria area, as well as with industrial growth and development. (3) Most significant for developing approaches for satellite ozone profile climatologies, cluster analysis has enabled the delineation of a background and "most polluted" profile. Enhancements of at least 30% occur throughout the troposphere in spring and in certain layers increases of 100 % are observed.

Diab, R. D.↗
DOE OSTI2026

Phase 1 Engagement Summary: Rural Alabama

An Alabama community coalition received technical assistance through the U.S. Department of Energy's Communities Local Energy Action Program (LEAP) to expand awareness of alternative transportation fuels through stakeholder engagement efforts. Phase 1 of the project centered on outreach, relationship-building, and the identification of community priorities. Through two workshops held in October and December 2024, the coalition engaged over 120 stakeholders - including county commissioners, school district representatives, and public and private fleet operators. These sessions included presentations from technical experts and industry partners, as well as a vehicle showcase and structured discussions to assess stakeholder needs and concerns. This report summarizes these efforts and identifies three key priority areas for Phase 2 of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Will cities keep getting hotter? The interplay of urban expansion and greening reshapes future urban heat trajectories

Urban heat islands (UHIs) pose growing risks to public health, infrastructure, and resilience. While often assumed to intensify with urban growth, dynamic changes in urban expansion and vegetation greenness complicate UHI trajectories, which remain poorly understood. This study investigated the interplay of urban expansion and greenness change on UHI spatial profile across 36 Chinese megacities during 2003–2018 using multiple satellite products. We introduce a framework that classifies urban areas into four dynamic development pathways based on impervious surface area (ISA) and enhanced vegetation index (EVI) trends: urbanized-greening, urbanized-browning, urbanizing-greening (UingG), and urbanizing-browning (UingB). While most urbanized centers exhibited greening driven by targeted initiatives and urbanizing suburbs showed browning due to vegetation loss, about 30% urban areas showed the reverse pattern, revealing overlooked complexity in urban development. Urban expansion and browning strengthened UHI in suburban areas, whereas greening initiatives mitigated UHI in urban center and mitigated UHI enhancement in suburban areas. Slowed warming in urban centers together with accelerated warming in suburban areas flattened the temperature gradient between urban centers and suburbs. This dynamic expanded the spatial extent of elevated temperatures and reshaped the classic urban-to-rural UHI profile into a flatter form. In UingB areas, UHI intensification was jointly driven by increase in ISA, vegetation loss, and their interaction, while in UingG areas, EVI increases and a negative interaction together offset over half of the warming driven by urban expansion. These findings reveal that UHI evolution is not unidirectional but depends on localized urbanization and greening dynamics, offering pathways for strategic heat mitigation.

greening initiative↗
DOE OSTI2026

Differences in urban plant community compositions across an urban-rural gradient in Knoxville, TN

Urban forests, or vegetation in areas under heavy human influence, provide many ecosystem services to urban residents such as localized cooling via evapotranspiration, shade, filtering of air pollution, and the associated health benefits of natural spaces. In order to quantify the magnitude of localized cooling by trees growing in varying levels of urbanization (based on % impervious surfaces, e.g., buildings, pavement), urban forest species composition, tree size, and tree density must be characterized. As a part of Oak Ridge National Laboratory’s (ORNL) urban forest temperature study, we conducted tree censuses in five Knoxville city parks where ORNL meteorological stations are deployed. Moreover, we measured every woody plant ≥ 5 cm diameter at breast height (DBH) within a 50 m radius of each site’s meteorological station for its DBH and species identification. When possible, individuals were identified down to species. Certain genera (Quercus spp., Carya spp., Pinus spp.) were identified down to genera in interest of time. Individual and total site basal area were calculated from measured DBH data. Results show notable differences in urban plant community compositions and total woody plant basal area across sites, with more urban sites closer to downtown (West View and SEEED) having lower tree basal area than the more suburban sites (West Hills, Cumberland Estates, and Victor Ashe). We identified 54 species across all sites, with West Hills and Victor Ashe having the highest species diversity. Our results show differences in forest compositions and sizes across Knoxville, which are currently informing ORNL’s evapotranspiration estimates for each site. Data Summary: Census data for West Hills (WH), Cumberland Estates (CE), Victor Ashe (VA), West View (WV), and Socially Equal Energy Efficient Development or SEEED (SD) urban forests in Knoxville, TN, USA, including tree size based on diameter at breast height (DBH; 1.3 m), species identification (Latin and common names), and basal area per stem (BA=π×[.5*DBH]^2). Field data are summarized in this file: “Community_Composition_Data.CSV”. Site-specific data detailing each site’s coordinates, number of stems measured at DBH, average tree DBH, α-diversity (number of species present), and total site basal area (sum of individual basal areas per site) are in this file: “Site_Comparisons.CSV”.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
NASA NTRS2013

Evaluation of Aerosol Mixing State Classes in the GISS Modele-matrix Climate Model Using Single-particle Mass Spectrometry Measurements

Aerosol particles in the atmosphere are composed of multiple chemical species. The aerosol mixing state, which describes how chemical species are mixed at the single-particle level, provides critical information on microphysical characteristics that determine the interaction of aerosols with the climate system. The evaluation of mixing state has become the next challenge. This study uses aerosol time-of-flight mass spectrometry (ATOFMS) data and compares the results to those of the Goddard Institute for Space Studies modelE-MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) model, a global climate model that includes a detailed aerosol microphysical scheme. We use data from field campaigns that examine a variety of air mass regimens (urban, rural, and maritime). At all locations, polluted areas in California (Riverside, La Jolla, and Long Beach), a remote location in the Sierra Nevada Mountains (Sugar Pine) and observations from Jeju (South Korea), the majority of aerosol species are internally mixed. Coarse aerosol particles, those above 1 micron, are typically aged, such as coated dust or reacted sea-salt particles. Particles below 1 micron contain large fractions of organic material, internally-mixed with sulfate and black carbon, and few external mixtures. We conclude that observations taken over multiple weeks characterize typical air mass types at a given location well; however, due to the instrumentation, we could not evaluate mass budgets. These results represent the first detailed comparison of single-particle mixing states in a global climate model with real-time single-particle mass spectrometry data, an important step in improving the representation of mixing state in global climate models.

climate models↗
NASA NTRS1977

Remote-area health care delivery through space technology - STARPAHC

A joint NASA/HEW project called Space Technology Applied to Rural Papage Advanced Health Care (STARPAHC) has been developed to deliver quality health care to inhabitants of remote geographical areas. The system consists of a hospital-based support control center, a fixed clinic, a mobile clinic, and a referral center with access to specialists via television links to the control center. A strategically located relay station routes television, voice, and data transmissions between system elements. A model system has been installed on the Papage Indian Reservation in Arizona, and is undergoing a 2-year evaluation. The system has been shown to be both effective and cost-efficient, and applications of the concept are planned for future manned spacecraft flights.

Belasco, N.↗
NASA NTRS1974

Photointerpretation of ERTS-A multispectral images analysis of vegetation and land use for the Valencia Lake Basin region

The area of investigation includes part of the Central and Capital Region of Venezuela. Climatic conditions define the existence of different ecological associations with biological forms well defined in their physiognomic complexity as they reach complete development in environments related to gross geomorphic units: coastal area, northern mountain range, fluvio-lacustrines plains, southern mountain range, southern ridges and parts of Venezuelan central plains. In this area, rainfall varies from 600 mm to 2000 mm and evapotranspiration indexes indicate the existence of vegetation for semiarid conditions ( tropical very dry forest) as well as vegetation for very humid conditions (very humid premontane forest). This project was designed for: (1) Location of areas with representative ecosystems for the purpose of managing planning. (2) Identification of structural and physiognomic characteristics of vegetation. (3) Assessment of human activity effects on environmental debasement. (4) Definition of the content and possibilities of orbital ERTS images for the study of urban and rural land use. (5) Setting photointerpretation patterns applicable to areas of similar gross environmental conditions.

Salas, F.↗
NASA NTRS2014

Column Aerosol Optical Properties and Aerosol Radiative Forcing During a Serious Haze-Fog Month over North China Plain in 2013 Based on Ground-Based Sunphotometer Measurements

In January 2013, North China Plain experienced several serious haze events. Cimel sunphotometer measurements at seven sites over rural, suburban and urban regions of North China Plain from 1 to 30 January 2013 were used to further our understanding of spatial-temporal variation of aerosol optical parameters and aerosol radiative forcing (ARF). It was found that Aerosol Optical Depth at 500 nm (AOD500nm) during non-pollution periods at all stations was lower than 0.30 and increased significantly to greater than 1.00 as pollution events developed. The Angstrom exponent (Alpha) was larger than 0.80 for all stations most of the time. AOD500nm averages increased from north to south during both polluted and non-polluted periods on the three urban sites in Beijing. The fine mode AOD during pollution periods is about a factor of 2.5 times larger than that during the non-pollution period at urban sites but a factor of 5.0 at suburban and rural sites. The fine mode fraction of AOD675nm was higher than 80% for all sites during January 2013. The absorption AOD675nm at rural sites was only about 0.01 during pollution periods, while 0.03-0.07 and 0.01-0.03 during pollution and non-pollution periods at other sites, respectively. Single scattering albedo varied between 0.87 and 0.95 during January 2013 over North China Plain. The size distribution showed an obvious tri-peak pattern during the most serious period. The fine mode effective radius in the pollution period was about 0.01-0.08 microns larger than during nonpollution periods, while the coarse mode radius in pollution periods was about 0.06-0.38 microns less than that during nonpollution periods. The total, fine and coarse mode particle volumes varied by about 0.06-0.34 cu microns, 0.03-0.23 cu microns, and 0.03-0.10 cu microns, respectively, throughout January 2013. During the most intense period (1-16 January), ARF at the surface exceeded −50W/sq m, −180W/sq m, and −200W/sq m at rural, suburban, and urban sites, respectively. The ARF readings at the top of the atmosphere were approximately −30W/sq m in rural and −40-60W/sq m in urban areas.

Atmosphere↗
DOE OSTI2024

2022 Component Innovation Awardee: Pecos Wind Power

Distributed wind energy systems supply electricity for nearby homes and businesses, often in remote and rural regions. Systems capable of capturing energy in areas with low wind speeds make it possible to deploy these clean energy systems in many geographic locations. Pecos Wind Power's 85-kilowatt (kW) horizontal-axis PW85 wind turbine shows potential to reduce the levelized cost of energy by approximately 55% when compared to typical small wind systems while achieving utility-scale capacity factors of more than 40% in areas with lower wind speeds. To maximize cost competitiveness, the Pecos Wind Power turbine needs a blade optimized for low wind speeds. Through its 2022 Competitiveness Improvement Project (CIP) award, Pecos Wind Power and partner Wetzel Wind Energy Services will model, optimize, fabricate, and validate a 14.5-meter wind turbine blade made specifically for these applications. Three prior CIP awards supported Pecos Wind Power's initial development of the PW85 turbine.

CIP↗
NASA NTRS1995

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Epperson, David L.↗