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All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Central atlantic regional ecological test site: A prototype regional environmental information system, volume 1

The Central Atlantic Regional Ecological Test Site (CARETS) project was a demonstration project for introducing data from Landsat and high-altitude aircraft sensors into regional land planning and management. This report summarizes the CARETS project results and describes its output of maps, reports, computer tapes, and other products. CARETS used a geographic information system model under which land use maps were prepared from sensor data, then digitized, processed, and linked to other environmental and social data sets, and to environmental consequences such as air pollution, stream runoff, local climatic factors, and coastal erosion. Landsat data showed the test region in 1972 to be nine percent urban and built-up land, 38 percent agriculture, 50 percent forest, three percent nonforested wetlands, and less than one percent barren land, exclusive of water-covered areas. User surveys, conferences, and workshops involving 65 agencies facilitated widespread distribution of data products and produced evaluations concerning their usefulness. We found a heterogeneous user community with diverse information needs largely preferring aerial photographs rather than satellite multispectral scanner data. Among project recommendations are establishment of a network of regional land resource information centers, working toward improved compatibility of Federal, State and local information programs supportive of land use decisions.

Land use↗
DOE OSTI2020

Calculating Average Hot Water Mixes of Residential Plumbing Fittings Using the ANSI 301-2019 Hot Water Draw Model and National Residential Data to Estimate Hot Water Use in Showerheads and Lavatory Faucets

Available studies of hot water use percentages may not necessarily be generalized to a national level given regional differences, varying methodological approaches, and limited sample sizes. While some publicly available usage data, reports, and surveys estimate actual household usage, a lack of water use data specific to end uses make more precise savings calculations difficult. Additionally, most hot water draw models tend to focus on overall household use and may not readily estimate lavatory fixture use. However, reviewing more recent studies and standards enables the U.S. Environmental Protection Agency’s WaterSense program to update its estimates for hot water use and consumers’ corresponding energy and monetary savings to better reflect realworld conditions. This report specifically focuses on improving hot water use and savings estimates of lavatory faucets and showerheads. To estimate the hot water use of lavatory faucets and showerheads, we employed the 2015 Residential Energy Consumption Surveys (RECS) microdata alongside the ANSI 301-2019 Hot Water Draw Model. These estimates account for regional differences in hot water use, including regional cold water inlet temperatures. As a result, the refinements presented in this report are more robust, more recent, and better describe the geographic variation than previous inputs used by the WaterSense program. In addition, the approach described in this paper can be updated over time or tailored to regionally specific needs given available inputs. We conclude that hot water percentages for showers and faucets calculated using publicly available national data are close to the percentages found by regional studies and are consistent with household-level models of water use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

A map of roadmaps for zero and low energy and carbon buildings worldwide

Formulation of targets and establishing which factors in different contexts will achieve these targets are critical to successful decarbonization of the building sector. To contribute to this, we have performed an evidence map of roadmaps for zero and low energy and carbon buildings (ZLECB) worldwide, including a list and classification of documents in an on-line geographical map, a description of gaps, and a narrative review of the knowledge gluts. We have retrieved 1219 scientific documents from Scopus, extracted metadata from 274 documents, and identified 117 roadmaps, policies or plans from 27 countries worldwide. We find that there is a coverage bias towards more developed regions. The identified scientific studies are mostly recommendations to policy makers, different types of case studies, and demonstration projects. The geographical inequalities found in the coverage of the scientific literature are even more extreme in the coverage of the roadmaps. These underexplored world regions represent an area for further investigation and increased research/policy attention. Our review of the more substantial amount of literature and roadmaps for developed regions shows differences in target metrics and enforcement mechanisms but that all regions dedicate some efforts at national and local levels. Roadmaps generally focus more on new and public buildings than existing buildings, despite the fact that the latter are naturally larger in number and total floor area, and perform less energy efficiently. A combination of efficiency, technical upgrades, and renewable generation is generally proposed in the roadmaps, with behavioral measures only reflected in the use of information and communication technologies, and minimal focus being placed on lifecycle perspectives. We conclude that insufficient progress is being made in the implementation of ZLECB. More work is needed to couple the existing climate goals, with realistic, enforceable policies to make the carbon savings a reality for different contexts and stakeholders worldwide.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2001

Water Vapor Tracers as Diagnostics of the Regional Hydrologic Cycle

Numerous studies suggest that local feedback of surface evaporation on precipitation, or recycling, is a significant source of water for precipitation. Quantitative results on the exact amount of recycling have been difficult to obtain in view of the inherent limitations of diagnostic recycling calculations. The current study describes a calculation of the amount of local and remote geographic sources of surface evaporation for precipitation, based on the implementation of three-dimensional constituent tracers of regional water vapor sources (termed water vapor tracers, WVT) in a general circulation model. The major limitation on the accuracy of the recycling estimates is the veracity of the numerically simulated hydrological cycle, though we note that this approach can also be implemented within the context of a data assimilation system. In the WVT approach, each tracer is associated with an evaporative source region for a prognostic three-dimensional variable that represents a partial amount of the total atmospheric water vapor. The physical processes that act on a WVT are determined in proportion to those that act on the model's prognostic water vapor. In this way, the local and remote sources of water for precipitation can be predicted within the model simulation, and can be validated against the model's prognostic water vapor. As a demonstration of the method, the regional hydrologic cycles for North America and India are evaluated for six summers (June, July and August) of model simulation. More than 50% of the precipitation in the Midwestern United States came from continental regional sources, and the local source was the largest of the regional tracers (14%). The Gulf of Mexico and Atlantic regions contributed 18% of the water for Midwestern precipitation, but further analysis suggests that the greater region of the Tropical Atlantic Ocean may also contribute significantly. In most North American continental regions, the local source of precipitation is correlated with total precipitation. There is a general positive correlation between local evaporation and local precipitation, but it can be weaker because large evaporation can occur when precipitation is inhibited. In India, the local source of precipitation is a small percentage of the precipitation owing to the dominance of the atmospheric transport of oceanic water. The southern Indian Ocean provides a key source of water for both the Indian continent and the Sahelian region.

Bosilovich, Michael G.↗
DOE OSTI2023

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

Abstract Background and Objectives The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations’ heat exposure in the early (1995–2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. Research Design and Methods We estimate older adults’ heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. Results Population aging and rising temperatures are documented throughout the United States, with particular “hotspots” in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. Discussion and Implications Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Ionosphere/microwave beam interaction study

A solar power satellite microwave power density of 20mw sq cm was confirmed as the level where nonlinear interactions may occur in the ionosphere, particularly at 100 km altitude. Radio wave heating at this altitude, produced at the Arecibo Observatory, yielded negative results for radio wave heating of an underdense ionosphere. Overdense heating produced striations in the ionosphere which may cause severe radio frequency interference problems under certain conditions. The effects of thermal self-focusing are shown to be limited severely geographically. The aspect sensitivity of field-aligned striations makes interference-free regions above magnetic latitude about 60 deg. A test program is proposed to simulate the interaction of the SPS beam with the ionosphere, to measure the effects of the interaction on the ionosphere and on communication and navigation systems, and to interpret the results.

Duncan, L. M.↗
NASA NTRS1982

Major determinants of the biogeographic pattern of the shallow-sea fauna

The benthic shallow-sea is defined as the region of sea floor lying between the supralittoral zone at the shoreline and the impingement of the thermocline separating a warm shallow and variable portion of the water column from rather homogeneous and constant cooler waters beneath. Three types of shallow-sea provinces can be recognized: (1) one-dimensional, linear shelves; (2) two-dimensional shelves; and (3) scattered islands in two-dimensional arrays. Dispersal powers of marine invertebrates vary with developmental mode, and patterns of dispersal, endemism and speciation vary among the different provincial types. Invertebrate developmental modes vary systematically with geography, and presumably are adaptive to environmental conditions. Clades with only a single mode of development tend to be restricted to regions appropriate to that mode, significantly affecting their biogeographic patterns. The consequences of geographic and other environmental changes are reviewed.

Valentine, J. W.↗
NASA NTRS1986

An analysis of the high-latitude thermospheric wind pattern calculated by a thermospheric general circulation model. II - Neutral parcel transport

A diagnostic package developed to analyze runs made by the National Center for Atmospheric Research thermosphere general circulation model is used to calculate neutral parcel trajectories in the high-latitude E and F regions. Parcel trajectories are presented for a number of different cases to illustrate the main characteristics of F region parcel transport in the winter high-latitude region. Several examples of E region parcel trajectories are similarly analyzed, concentrating on both the southern (summer) and northern (winter) regions. F region parcel trajectories are calculated backward in time from passage over a given geographical location to illustrate the 'genesis' of those parcels whose velocities can be monitored from a ground-based Fabry-Perot observatory.

Killeen, T. L.↗
NASA NTRS1997

Ground Calibrations of the Clouds and the Earth's Radiant Energy System (CERES) Tropical Rainfall Measuring Mission Spacecraft Thermistor Bolometers

The Clouds and the Earth's Radiant Energy System (CERES) spacecraft scanning thermistor bolometers will measure earth-reflected solar and earth-emmitted,longwave radiances, at the top-of-the-atmosphere. The measurements are performed in the broadband shortwave (0.3-5.0 micron) and longwave (5.0 - >100 micron) spectral regions as well as in the 8 -12 micron water vapor window over geographical footprints as small as 10 kilometers at the nadir. The CERES measurements are designed to improve our knowledge of the earth's natural climate processes, in particular those related to clouds, and man's impact upon climate as indicated by atmospheric temperature. November 1997, the first set of CERES bolometers is scheduled for launch on the Tropical Rainfall Measuring Mission (TRMM) Spacecraft. The CERES bolometers were calibrated radiometrically in a vacuum ground facility using absolute reference sources, tied to the International Temperature Scale of 1990. Accurate bolometer calibrations are dependent upon the derivations of the radiances from the spectral properties [reflectance, transmittance, emittance, etc.] of both the sources and bolometers. In this paper, the overall calibration approaches are discussed for the longwave and shortwave calibrations. The spectral responses for the TRMM bolometer units are presented and applied to the bolometer ground calibrations in order to determine pre-launch calibration gains.

Lee, Robert B., III↗
NASA NTRS2001

Interfaces For Planning Vehicle Routes

A system for producing vehicle routes such as aircraft flight plans in the presence of weather and other hazards defines static and moving hazards with polygons drawn on a display containing graphic hazard regions. Different hazard types and intensities are displayed differently. Both lateral and vertical geographic depictions are displayed, and hazards can be displayed temporally as well. Users input information and thresholds for hazards.

Thea Lynn Feyereisen↗
NASA NTRS2004

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Olson, William S.↗
NASA NTRS2006

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Improved Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5 -resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%-80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5deg resolution is relatively small (less than 6% at 5 mm day.1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%-35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%-15% at 5 mm day.1, with proportionate reductions in latent heating sampling errors.

Olson, William S.↗
NASA NTRS2015

Vegetation Cover Change in the Upper Kings River Basin of the Sierra Nevada Detected Using Landsat Satellite Image Analysis

The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.

normalized difference vegetation index (NDVI)↗
NASA NTRS2016

Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

geographic barriers↗
NASA NTRS2012

Human Settlements in the South-Central U.S., Viewed at Night from the International Space Station

A recent innovation of astronauts observing Earth from the International Space Station (ISS) is documenting human footprints by photographing city lights at night time. One of the earliest night-time images from the ISS was the US-Mexico border at El Paso-Ciudad Juarez. The colors, patterns and density of city lights document the differences in the cultural settlement patterns across the border region, as well as within the urban areas themselves. City lights help outline the most populated areas in settlements around the world, and can be used to explore relative population densities, changing patterns of urban/suburban development, transportation networks, spatial relationship to geographic features, and more. The data also provides insight into parameters such as surface roughness for input into local and regional climate modeling and studies of light pollution. The ground resolution of night-time astronaut photography from the ISS is typically an order of magnitude greater than current Defense Meteorological Satellite Program (DMSP) data, and therefore can serve as a "zoom lens" for selected urban areas. Current handheld digital cameras in use on the ISS, optimized for greater light sensitivity, provide opportunities to obtain new detailed imagery of atmospheric phenomena such as airglow, aurora, and noctilucent clouds in addition to documenting urban patterns. ISS astronauts have taken advantage of increasingly sensitive digital cameras to document the world at night in unprecedented detail. In addition, the capability to obtain time-lapse imagery from fixed cameras has been exploited to produce dynamic videos of both changing surface patterns around the world and atmospheric phenomena. We will profile some spectacular images of human settlements over the South-Central U.S., and contrast with other images from around the world. More data can be viewed at http://eol.jsc.nasa.gov/Videos/CrewEarthObservationsVideos/. US-Mexico border is obvious by the different lighting pattern. Not surprisingly, the densely illuminated city of Juarez indicates a higher population; El Paso's smaller population is spread out over a larger area.

Dawson, Melissa↗
DOE OSTI2021

Multiscale influenza forecasting

Abstract Influenza forecasting in the United States (US) is complex and challenging due to spatial and temporal variability, nested geographic scales of interest, and heterogeneous surveillance participation. Here we present Dante, a multiscale influenza forecasting model that learns rather than prescribes spatial, temporal, and surveillance data structure and generates coherent forecasts across state, regional, and national scales. We retrospectively compare Dante’s short-term and seasonal forecasts for previous flu seasons to the Dynamic Bayesian Model (DBM), a leading competitor. Dante outperformed DBM for nearly all spatial units, flu seasons, geographic scales, and forecasting targets. Dante’s sharper and more accurate forecasts also suggest greater public health utility. Dante placed 1st in the Centers for Disease Control and Prevention’s prospective 2018/19 FluSight challenge in both the national and regional competition and the state competition. The methodology underpinning Dante can be used in other seasonal disease forecasting contexts having nested geographic scales of interest.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Overview of US AID-World Bank-NASA Collaboration to Address Water Management Issues in the MENA Region

The World Bank, USAID and NASA have recently established a joint project to study multiple issues pertaining to water related applications in the Middle East North Africa (MENA) region. The main concentration of the project is on utilization of remote sensing data and hydrological models to address crop irrigation and mapping, flood mapping and forecasting, evapotranspiration and drought problems prevalent in this large geographic area. Additional emphases are placed on understanding the climate impact on these areas as well. Per IPCC 2007 report, by the end of this century MENA region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. These observations generate multiple products such as soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gases, ice and snow measurements, and many more. All of the data products, models and research results are distributed-via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, droUght assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Finally, capacity building is a critical part of this project and NASA will assist in this effort as well.

Habib, Shahid↗