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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Global mapping of urban thermal anisotropy reveals substantial potential biases for remotely sensed urban climates

Urban thermal anisotropy (UTA) drastically biases satellite-derived urban surface temperatures and fluxes, and consequently inhibits a more comprehensive understanding of global urban climates. However, UTA patterns and associated biases in observed urban climate variables have not been investigated across an adequate number of global cities with diverse contexts; nor is it known whether there are globally measurable factors that are closely related to the UTA intensity (UTAI, quantified as the maximum difference between the nadir and off-nadir urban thermal radiation). Here we investigate the UTAI over more than 5500 cities worldwide using the moderate resolution imaging spectroradiometer (MODIS) multi-angle land surface temperature (LST) observations from 2003 to 2021. The results show that the global mean UTAI can reach 5.1, 2.7, 2.4, and 1.7 K during summer daytime, winter daytime, summer nighttime, and winter nighttime, respectively. Using nadir LST observations as a reference, our analysis reveals that UTA can lead to an underestimation of satellite-based urban surface sensible heat fluxes ( H ) by 45.4% and surface urban heat island intensity ( I s ) by 43.0% when using LST observations obtained from sensor viewing zenith angles (VZAs) of ±60°. However, practitioners can limit the biases of H and I s within ±10% by using LSTs from sensor VZAs within ±30°. We find that UTAI is closely related to urban impervious surface percentage and surface air temperature across global cities. In conclusion, these findings have implications for angular normalization of satellite-retrieved instantaneous LST observations across cities worldwide.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Indicators and Monitoring Systems for Urban Climate Resiliency

Cities in the USA and around the world have begun to take an active role in responding to climate change. A central requirement for effective urban climate strategies is the capacity to understand and measure how the climate is changing, the physical, environmental, and social impacts of the changes, and whether adaptation and resiliency policies and programs put in place in response are working. The objective of this paper is to review and assess how urban climate change and resiliency efforts can be measured and to define what might serve as meaningful indicator and monitoring protocols. The New York City Panel on Climate Change (NPCC) is used as a case study along with a reviews of the emerging literature of urban climate change indicators to analyze the requirements and processes needed for a successful urban climate resiliency indicator and monitoring (I and M) system. In the paper, the basic requirements of a proposed Urban Climate Resilience Indicators and Monitoring System are presented. A specific illustration of an I and M system for tracking the urban heat island highlights challenges as well as potential solutions embedded within such systems. Discussions how these protocols can be translated to other locales and settings, as well as the relationship to the US National Climate Assessment indicator process, are presented.

New York City Panel on Climate Change↗
DOE OSTI2024

Hyper‐Local Temperature Prediction Using Detailed Urban Climate Informatics

The accurate modeling of urban microclimate is a challenging task given the high surface heterogeneity of urban land cover and the vertical structure of street morphology. Recent years have witnessed significant efforts in numerical modeling and data collection of the urban environment. Nonetheless, it is difficult for the physical‐based models to fully utilize the high‐resolution data under the constraints of computing resources. The advancement in machine learning (ML) techniques offers the computational strength to handle the massive volume of data. In this study, we proposed a modeling framework that uses ML approach to estimate point‐scale street‐level air temperature from the urban‐resolving meso‐scale climate model and a suite of hyper‐resolution urban geospatial data sets, including three‐dimensional urban morphology, parcel‐level land use inventory, and weather observations from a sensor network. We implemented this approach in the City of Chicago as a case study to demonstrate the capability of the framework. The proposed approach vastly improves the resolution of temperature predictions in cities, which will help the city with walkability, drivability, and heat‐related behavioral studies. Moreover, we tested the model's reliability on out‐of‐sample locations to investigate the modeling uncertainties and the application potentials to the other areas. This study aims to gain insights into next‐gen urban climate modeling and guide the observation efforts in cities to build the strength for the holistic understanding of urban microclimate dynamics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

ARC3.2 Summary for City Leaders Climate Change and Cities: Second Assessment Report of the Urban Climate Change Research Network

ARC3.2 presents a broad synthesis of the latest scientific research on climate change and cities. Mitigation and adaptation climate actions of 100 cities are documented throughout the 16 chapters, as well as online through the ARC3.2 Case Study Docking Station. Pathways to Urban Transformation, Major Findings, and Key Messages are highlighted here in the ARC3.2 Summary for City Leaders. These sections lay out what cities need to do achieve their potential as leaders of climate change solutions. UCCRN Regional Hubs in Europe, Latin America, Africa, Australia and Asia will share ARC3.2 findings with local city leaders and researchers. The ARC3.2 Summary for City Leaders synthesizes Major Findings and Key Messages on urban climate science, disasters and risks, urban planning and design, mitigation and adaptation, equity and environmental justice, economics and finance, the private sector, urban ecosystems, urban coastal zones, public health, housing and informal settlements, energy, water, transportation, solid waste, and governance. These were based on climate trends and future projections for 100 cities around the world.

Ecosystems↗
DOE OSTI2023

DownScaleBench for developing and applying a deep learning based urban climate downscaling- first results for high-resolution urban precipitation climatology over Austin, Texas

Abstract Cities need climate information to develop resilient infrastructure and for adaptation decisions. The information desired is at the order of magnitudes finer scales relative to what is typically available from climate analysis and future projections. Urban downscaling refers to developing such climate information at the city (order of 1 – 10 km) and neighborhood (order of 0.1 – 1 km) resolutions from coarser climate products. Developing these higher resolution (finer grid spacing) data needed for assessments typically covering multiyear climatology of past data and future projections is complex and computationally expensive for traditional physics-based dynamical models. In this study, we develop and adopt a novel approach for urban downscaling by generating a general-purpose operator using deep learning. This ‘DownScaleBench’ tool can aid the process of downscaling to any location. The DownScaleBench has been generalized for both in situ (ground- based) and satellite or reanalysis gridded data. The algorithm employs an iterative super-resolution convolutional neural network (Iterative SRCNN) over the city. We apply this for the development of a high-resolution gridded precipitation product (300 m) from a relatively coarse (10 km) satellite-based product (JAXA GsMAP). The high-resolution gridded precipitation datasets is compared against insitu observations for past heavy rain events over Austin, Texas, and shows marked improvement relative to the coarser datasets relative to cubic interpolation as a baseline. The creation of this Downscaling Bench has implications for generating high-resolution gridded urban meteorological datasets and aiding the planning process for climate-ready cities.

Singh, Manmeet (ORCID:0000000233747149)↗
NASA NTRS1981

A study of model parameters associated with the urban climate using HCMM data

Progress in the study of the intensity of the urban heat island is reported. The intensity of the heat island is commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions. The intensity is considered as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. Twelve case studies were selected and CCT's were ordered. In situ data was obtained from sixteen stations scattered about the city of St. Louis. Upper-air meteorological data were obtained and the water vapor and the temperature data were processed. Atmospheric transmissivities were computed for each of the case studies.

Source record↗
DOE OSTI2023

Integration of urban science and urban climate adaptation research: opportunities to advance climate action

There is a growing recognition that responding to climate change necessitates urban adaptation. We sketch a transdisciplinary research effort, arguing that actionable research on urban adaptation needs to recognize the nature of cities as social networks embedded in physical space. Given the pace, scale and socioeconomic outcomes of urbanization in the Global South, the specificities and history of its cities must be central to the study of how well-known agglomeration effects can facilitate adaptation. The proposed effort calls for the co-creation of knowledge involving scientists and stakeholders, especially those historically excluded from the design and implementation of urban development policies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Reply to Comment by Velasco on “High-Resolution, Multilayer Modeling of Singapore’s Urban Climate Incorporating Local Climate Zones”

In response to the comment on our paper “High-resolution, multilayer modeling of Singapore's urban climate incorporating local climate zones,” we provide detailed response to each of the incorrect accusations with scientifically based evidence. We have evaluated our model using all the available observational data, and the results showed good agreement. Our modeling study includes assumptions, as all modeling work does, and we have discussed their rationales and possible implications.

M. O. Mughal↗
NASA NTRS1981

A study of model parameters associated with the urban climate using HCMM data

Infrared and visible data from the Heat Capacity Mapping Mission (HCMM) satellite were used to study the intensity of the urban heat island, commonly defined as the temperature difference between the center of the city and the surrounding suburban and rural regions, as a function of changes in the season and changes in meteorological conditions in order to derive various parameters which may be used in numerical models for urban climate. The analysis was focused on the city of St. Louis; and in situ data from St. Louis was combined with HCMM data in order to derive the various parameters. The HCMM data were mapped onto a Mercator projection map of the city and ground temperatures were established using data corrected for the effects of atmospheric absorption. The corrected and uncorrected HCMM data were compared to determine the magnitude of the error induced by atmospheric effects.

Source record↗
DOE OSTI2023

An Urban Climate Archipelago in the Southeastern U.S.

Urban boundary layers (UBLs; Barlow, 2014) are the most populous microclimate in the world but are still a challenge to represent physically due to the lack of frequent observations within most urban centers. We examine a set of inland urban regions of different sizes within the Southeast U.S.: Atlanta, GA; Athens, GA; Augusta, GA; and Columbia, SC. We compare Weather Research and Forecasting (WRF; Skamarock et al., 2019) simulation output of Atlanta to hourly-averaged Aircraft Meteorological Data Relay (AMDAR) temperature profiles within the warm season in the ATL airport. The scaling of the simulated UBL by size of the urban region is assessed by comparing the UBL dynamics of the three smaller cities (Athens, Augusta, and Columbia) to Atlanta.

Wermter, Jospeh↗
NASA NTRS2014

Chapter 11: City-Wide Collaborations for Urban Climate Education

Although cities cover only 2 percent of the Earth's surface, more than 50 percent of the world's people live in urban environments, collectively consuming 75 percent of the Earth's resources. Because of their population densities, reliance on infrastructure, and role as centers of industry, cities will be greatly impacted by, and will play a large role in, the reduction or exacerbation of climate change. However, although urban dwellers are becoming more aware of the need to reduce their carbon usage and to implement adaptation strategies, education efforts on these strategies have not been comprehensive. To meet the needs of an informed and engaged urban population, a more systemic, multiplatform and coordinated approach is necessary. The Climate and Urban Systems Partnership (CUSP) is designed to explore and address this challenge. Spanning four cities-Philadelphia, New York, Pittsburgh, and Washington, DC-the project is a partnership between the Franklin Institute, the Columbia University Center for Climate Systems Research, the University of Pittsburgh Learning Research and Development Center, Carnegie Museum of Natural History, New York Hall of Science, and the Marian Koshland Science Museum of the National Academy of Sciences. The partnership is developing a comprehensive, interdisciplinary network to educate urban residents about climate science and the urban impacts of climate change.

Climate change↗
NASA NTRS2012

Urban Climate Station Site Selection Through Combined Digital Surface Model and Sun Angle Calculations

Meteorological measurements within urban areas are becoming increasingly important due to the accentuating effects of climate change upon the Urban Heat Island (UHI). However, ensuring that such measurements are representative of the local area is often difficult due to the diversity of the urban environment. The evaluation of sites is important for both new sites and for the relocation of established sites to ensure that long term changes in the meteorological and climatological conditions continue to be faithfully recorded. Site selection is traditionally carried out in the field using both local knowledge and visual inspection. This paper exploits and assesses the use of lidar-derived digital surface models (DSMs) to quantitatively aid the site selection process. This is acheived by combining the DSM with a solar model, first to generate spatial maps of sky view factors and sun-hour potential and second, to generate site-specific views of the horizon. The results show that such a technique is a useful first-step approach to identify key sites that may be further evaluated for the location of meteorological stations within urban areas.

digital surface model↗
DOE OSTI2018

Systematic Comparison of the Influence of Cool Wall versus Cool Roof Adoption on Urban Climate in the Los Angeles Basin

This study for the first time assesses the influence of employing solar reflective “cool” walls on the urban energy budget and summertime climate of the Los Angeles basin. Here, we systematically compare the effects of cool walls to cool roofs, a heat mitigation strategy that has been widely studied and employed, using a consistent modeling framework (the Weather Research and Forecasting model). Adoption of cool walls leads to increases in urban grid cell albedo that peak in the early morning and late afternoon, when the ratio of solar radiation onto vertical walls versus horizontal surfaces is at a maximum. In Los Angeles County, daily average increase in grid cell reflected solar radiation from increasing wall albedo by 0.80 is 9.1 W m –2 , 43% of that for increasing roof albedo. Cool walls reduce canyon air temperatures in Los Angeles by 0.43 K (daily average), with the peak reduction (0.64 K) occurring at 09:00 LST and a secondary peak (0.53 K) at 18:00 LST. Per 0.10 wall (roof) albedo increase, cool walls (roofs) can reduce summertime daily average canyon air temperature by 0.05 K (0.06 K). Results reported here can be used to inform policies on urban heat island mitigation or climate change adaptation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Gray Wave of the Great Transformation: A Satellite View of Urbanization, Climate Change, and Food Security

Land cover change driven by human activity is profoundly affecting Earth's natural systems with impacts ranging from a loss of biological diversity to changes in regional and global climate. This change has been so pervasive and progressed so rapidly, compared to natural processes, scientists refer to it as "the great transformation". Urbanization or the 'gray wave' of land transformation is being increasingly recognized as an important process in global climate change. A hallmark of our success as a species, large urban conglomerates do in fact alter the land surface so profoundly that both local climate and the basic ecology of the landscape are affected in ways that have consequences to human health and economic well-being. Fortunately we have incredible new tools for planning and developing urban places that are both enjoyable and sustainable. A suite of Earth observing satellites is making it possible to study the interactions between urbanization, biological processes, and weather and climate. Using these Earth Observatories we are learning how urban heat islands form and potentially ameliorate them, how urbanization can affect rainfall, pollution, and surface water recharge at the local level and climate and food security globally.

Imhoff, Marc Lee↗
NASA NTRS2007

Gray Wave of the Great Transformation: A Satellite View of Urbanization, Climate, and Food Security

Land cover change driven by human activity is profoundly affecting Earth's natural systems with impacts ranging from a loss of biological productivity to changes in atmospheric chemistry and regional and global climate. This change has been so pervasive and progressed so rapidly, compared to natural processes, scientists refer to it as 'the great transformation'. Urbanization or the 'gray wave' of this transformation is being increasingly recognized as an important process in global climate change. A hallmark of our success as a species, large urban conglomerates do in fact alter their environments so profoundly that the local climate, atmospheric composition, and the basic ecology of the landscape are affected in ways that have consequences to human health and economic well-being. Fortunately we have incredible new tools to observe and understand these processes in ways that can be used to plan and develop enjoyable and sustainable urban places. A suite of Earth observing satellites is making it possible to study the interactions between urbanization, biological processes, and the atmosphere including weather and climate. Using these Earth Observatories we are learning how urban heat islands form and potentially ameliorate them, how urbanization can affect rainfall, pollution, surface water recharge at the local level, and climate and food security globally.

Imhoff, Marc L.↗
NASA NTRS2012

Bright is the New Black - Multi-Year Performance of Generic High-Albedo Roofs in an Urban Climate

High-albedo white and cool roofing membranes are recognized as a fundamental strategy that dense urban areas can deploy on a large scale, at low cost, to mitigate the urban heat island effect. We are monitoring three generic white membranes within New York City that represent a cross-section of the dominant white membrane options for U.S. flat roofs: (1) an ethylene propylene diene monomer (EPDM) rubber membrane; (2) a thermoplastic polyolefin (TPO) membrane and; (3) an asphaltic multi-ply built-up membrane coated with white elastomeric acrylic paint. The paint product is being used by New York City s government for the first major urban albedo enhancement program in its history. We report on the temperature and related albedo performance of these three membranes at three different sites over a multi-year period. The results indicate that the professionally installed white membranes are maintaining their temperature control effectively and are meeting the Energy Star Cool Roofing performance standards requiring a three-year aged albedo above 0.50. The EPDM membrane however shows evidence of low emissivity. The painted asphaltic surface shows high emissivity but lost about half of its initial albedo within two years after installation. Given that the acrylic approach is an important "do-it-yourself," low-cost, retrofit technique, and, as such, offers the most rapid technique for increasing urban albedo, further product performance research is recommended to identify conditions that optimize its long-term albedo control. Even so, its current multi-year performance still represents a significant albedo enhancement for urban heat island mitigation.

Gaffin, S. R.↗
NASA NTRS1981

A study of model parameters associated with the urban climate using HCMM data

The use of infrared and visible data from the Heat Capacity Mapping Mission (HCMM) and in situ data to study the intensity of the urban heat island of Saint Louis is described. Analysis of HCMM data shows that an urban heat island exists day and night in all seasons when clear skies prevail. The lower albedo value of the urban region during the day suggests that the higher temperatures are due to more absorption of solar radiation. Preliminary analysis of in situ meteorological data was performed after merging with HCMM data, and surface roughness, the exchange coefficient, and the soil moisture were calculated.

Source record↗