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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Estimating Net Primary Productivity Using Satellite and Ancillary Data

The net primary productivity (C) or annual rate of carbon accumulation per unit ground area by terrestrial plant communities is the difference of the rate of gross photosynthesis (A(sub g)) and autotrophic respiration (R) per unit ground area. Although available observations show that R is a large and variable fraction of A(sub g), viz., 0.3 to 0.7, it is generally recognized that much uncertainties exist in this fraction due to difficulties associated with the needed measurements. Additional uncertainties arise when these measurements are extrapolated to regional or global land surface using empirical equations, for example, using regression equations relating C to mean annual precipitation and air temperature. Here, a process-based approach has been taken to calculate A(sub g) and R using satellite and ancillary data. A(sub g) has been expressed as a product of radiation use efficiency, magnitude of intercepted photosynthetically active radiation (PAR), and normalized by stresses due to soil water shortage and air temperature away from the optimum range. A biophysical model has been used to determine the radiation use efficiency from the maximum rate of carbon assimilation by a leaf, foliage temperature, and the fraction of diffuse PAR incident on a canopy. All meteorological data (PAR, air temperature, precipitation, etc.) needed for the calculation are derived from satellite observations, while a land use, land cover data (based on satellite and ground measurements) have been used to assess the maximum rate of carbon assimilation by a leaf of varied cover type based on field measurements. R has been calculated as the sum of maintenance and growth components. The maintenance respiration of foliage and live fine roots at a standard temperature of different land cover has been determined from their nitrogen content using field and satellite measurements, while that of living fraction of woody stem (viz., sapwood) from the seasonal maximum leaf area index as determined from satellite observations. These maintenance respiration values were then adjusted to that corresponding to air temperature according to a prescribed non-linear variation of respiration with temperature. The growth respiration has been calculated from the difference of Ag and maintenance respiration, according to the two-compartment model. The results of calculations will be reported for 36 consecutive months (1987-1989) over large contiguous areas (ca. 10(exp 5) sq km) Of agricultural land and tropical humid evergreen forests, and compared with available field data.

Choudhury, B. J.↗
DOE OSTI2024

Climate Conundrum: A Wet or Dry European and Northern African Climate During the Middle Miocene

Abstract End of 21st‐century hydroclimate projections suggest an expansion of subtropical dry zones, with Mediterranean and Sahel regions becoming much drier. However, paleobotanical assemblage evidence from the middle Miocene (17‐12 Ma), suggests both regions were instead humid environments. Here we show that by modifying regional sea surface temperatures (SST) in an Earth System Model (CESM1.2) simulation of the middle Miocene, the increased ocean evaporation and integrated water vapor flux overrides any drying effects associated with warming‐induced land‐surface evaporation driven by atmospheric CO 2 concentrations. These modifications markedly reduce the bias in the model‐data comparison for this period. A vegetation model (BIOME4) forced with simulated climatologies predicts both regions were dominated by mixed forest, which is largely consistent with the paleobotanical record. This study unveils the potential for wetter subtropical Mediterranean climates associated with warming, presenting an alternative scenario from future drying projections with localized SST warming governing regional climate change.

Acosta, R. P.↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

Christensen, Matthew [Pacific Northwest National L↗
DOE OSTI2025

Multiscale ACI Satellite Database

The SATELLITE_EAGLES_PNNL NetCDF dataset contains a suite of satellite- and reanalysis-derived atmospheric and surface parameters on a regular latitude–longitude grid. The dataset includes core geophysical fields such as land fraction, aerosol optical depth at multiple wavelengths (465, 550, 667, and 865 nm), sea surface temperature, estimated inversion strength, and various thermodynamic and dynamic quantities (e.g., relative humidity, vertical velocity, boundary-layer height, and surface fluxes) from both MERRA and ERA reanalysis products, provided as daily-mean and instantaneous values. A major component of the dataset consists of MODIS-retrieved cloud microphysical properties, including cloud droplet number concentration, cloud effective radius, optical thickness, and liquid water path, provided for three compositing regimes (“All,” “Q06,” and “G18”). Corresponding cloud-top parameters—temperature, height, and pressure—along with total and domain-mean cloud fraction fields are also included. The file further integrates additional satellite data from AMSR-E (for cloud water, rain water, and surface precipitation retrievals) and CERES (for top-of-atmosphere radiative fluxes, cloud fractions, and albedo). This dataset is designed to evaluate aerosol–cloud interactions in warm clouds, emphasizing the use of MODIS for deriving cloud droplet number concentration and liquid water path statistics. The complementary satellite and reanalysis fields are co-located and time-matched to the same instantaneous MODIS observations, enabling consistent comparisons between cloud properties, aerosol loading, and large-scale meteorological conditions. The dataset is recently featured in Christensen et al. (2025), Machine Learning Reveals Strong Grid-Scale Dependence in the Satellite Nd–LWP Relationship, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-3850, 2025.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

A global low order spectral model designed for climate sensitivity studies

A two level, global, spectral model using pressure as a vertical coordinate is developed. The system of equations describing the model is nonlinear and quasi-geostrophic. A moisture budget is calculated in the lower layer only with moist convective adjustment between the two layers. The mechanical forcing of topography is introduced as a lower boundary vertical velocity. Solar forcing is specified assuming a daily mean zenith angle. On land and sea ice surfaces a steady state thermal energy equation is solved to calculate the surface temperature. Over the oceans the sea surface temperatures are prescribed from the climatological average of January. The model is integrated to simulate the January climate.

Hanna, A. F.↗
NASA NTRS1990

The extent of the unstable Monin-Obukhov layer for temperature and humidity above complex hilly grassland

An analysis is given of radiosonde measurements of the potential temperature, specific humidity, and wind profiles under unstable windy conditions during the First International Satellite Land Surface Climatology Project Field Experiment in Kansas. It is found that about 86 percent of the profiles have a height range over which the Monin-Obukhov (1954) similarity is valid. It is shown that the Businger-Dyer version of the similarity functions (Businger, 1988) is satisfactory for analyzing radiosonde profiles.

Brutsaert, Wilfried↗
NASA NTRS2001

E-Theatre

Mesoscale/severe storms and results from Terra Fritz Hasler (NASA/Goddard) will show the latest spectacular animations of the hurricanes and tropical storms: Floyd, Georges, Mitch, Bonnie etc. from Geostationary Operational Environmental Satellites (GOES) and Tropical Rain Measuring Mission (TRMM) supported by MMS 3D nested numerical model results. See dust storms in Africa and smoke plumes from fires in Mexico. See how High-Definition Television (HDTV) is revolutionizing entertainment and the way we communicate scientific results. Fly in from space and take a tour of Africa. Drop in on Albuquerque using 1-m Ikonos 'Spy Satellite' technology. See data from the new Earth Observing System (EOS) Terra satellite as well as Landsat 7, and SeaWiFS. See climate change in action with Global Land and Ocean productivity changes over the last 20 years. Remote sensing observations of Sea Surface Temperature (SST), El Nino, height, winds and ocean color from GOES, National Oceanic and Atmosphere Administration Advanced Very High Resolution Radiometer (AVHRR), Special Sensor Microwave Imager (SSMI), and SeaWiFS put in context with ten year LANL global ocean model. Compare the Gulf Stream observed by Terra with the simulations. Additional information is contained in the original extended abstract.

Hasler, Arthur F.↗
NASA NTRS2001

Assimilation of GOES Land Surface Data Within a Rapid Update Cycle Format: Impact on MM5 Warm Season QPF

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The focus of this paper is to examine how the satellite assimilation technique impacts simulations of near-surface meteorology on the 0-to 12-hour time scale when implemented within a local rapid update cycle (LRUC) format. The PSU/NCAR MM5 V34 is used and configured with a 36-km CONUS domain and a 12-km nest centered over the southeastern US. The LRUC format consists of a sequence of 12-hour forecasts initialized every hour between 12 and 18 UTC seven days a week. GOES skin temperature tendencies and solar insolation are assimilated in a 1-hour period prior to the start of each twelve-hour forecast. A unique aspect of the LRUC is the satellite assimilation and the continuous recycling of the adjusted moisture availability field from one forecast cycle to the next. Preliminary results for a seven-day trial period indicate that hourly LST tendencies assimilated in a 1 hour LRUC showed improved simulated air and dewpoint temperatures for all cycles on each day. The LRUC will be used during the 2001 summer months to identify the impact of the assimilation on warm season QPF Results will be presented at the meeting.

Lapenta, William M.↗
NASA NTRS2010

Evaluation and Application of Remotely Sensed Soil Moisture Products

Whereas in-situ measurements of soil moisture are very accurate, achieving accurate regional soil moisture estimates derived solely from point measurements is difficult because of the dependence upon the density of the gauge network and the proper upkeep of these instruments, which can be costly. Microwave remote sensing is the only technology capable of providing timely direct measurements of regional soil moisture in areas that are lacking in-situ networks. Soil moisture remote sensing technology is well established has been successfully applied in many fashions to Earth Science applications. Since the microwave emission from the soil surface has such a high dependency upon the moisture content within the soil, we can take advantage of this relationship and combined with physically-based models of the land surface, derive accurate regional estimates of the soil column water content from the microwave brightness temperature observed from satellite-based remote sensing instruments. However, there still remain many questions regarding the most efficient methodology for evaluating and applying satellite-based soil moisture estimates. As discussed below, we to use satellite-based estimates of soil moisture dynamics to improve the predictive capability of an optimized hydrologic model giving more accurate root-zone soil moisture estimates.

Bolten, J.↗
NASA NTRS2019

Flash Drought as Captured by Reanalysis Data: Disentangling the Contributions of Precipitation Deficit and Excess Evapotranspiration

Flash droughts – uncharacteristically rapid dryings of the land system – are naturally associated with extreme precipitation deficits. Such precipitation deficits, however, do not tell the whole story, for land surface drying can be exacerbated by anomalously high evapotranspiration (ET) rates driven by anomalously high temperatures (e.g., during heatwaves), anomalously high incoming radiation (e.g., from reduced cloudiness), and other meteorological anomalies. In this study, the relative contributions of precipitation and ET anomalies to flash drought generation in the Northern Hemisphere are quantified through the analysis of diagnostic fields contained within the MERRA-2 reanalysis product. Unique to the approach is the explicit treatment of soil moisture impacts on ET through relationships diagnosed from the reanalysis data; under this treatment, an ET anomaly that is negative relative to the local long-term climatological mean is still considered positive in terms of its contribution to a flash drought if it is high for the concurrent value of soil moisture. Maps produced in the analysis show the fraction of flash drought production stemming specifically from ET anomalies and illustrate how ET anomalies for some droughts are related to temperature and radiation anomalies. While ET is found to have an important impact on flash drought production in the central US and in parts of Russia known from past studies to be prone to heatwave-related drought, and while this impact does appear stronger during the onset (first several days) of flash droughts, overall the contribution of ET to these droughts is small relative to the contribution of precipitation deficit.

R D Koster↗
NASA NTRSDate not supplied

Cryogenic Insulation Solutions for the Surface of Mars with Its Unique Environments

The surface of Mars provides unique challenges for cryogenic insulation systems and for cryogenic spacecraft traveling there. In order to store cryogenic fluids for propulsion, life support, and other applications on the surface of Mars one must protect the insulation from the array of unique environmental factors that are present. Travel to Mars is a very energy intensive endeavor and landing on the surface requires launching over 200 kg of propellant and spacecraft per kilogram landed. As such, high performance, lightweight insulations are needed for cryogenic systems to be used on the surface. Traditional spacecraft use multilayer insulation that works well in a vacuum, but Mars has an atmospheric of pressure approximately 7 torr, consisting of approximately 95 % carbon dioxide. Based on analysis and trade studies NASA has shown that the mass savings from the higher performance of multilayer insulation with a vacuum jacket saved several hundred kilograms of mass for a typical human Mars ascent stage. Thus NASA, along with several contractors, have been developing a lightweight vacuum jacketed system for the 7 torr environment. This lightweight vacuum jacketed system must survive launch from earth, travel to Mars, and on the surface for several years. On the surface, it must be able to survive landing, natural environmental occurrences such as dust storms, and temperature cycling with minimal if any human maintenance. The insulation systems under development have been exposed to an array of tests to demonstrate their capability to survive these environments while still providing the high performance required to meet mission needs.

Cryogenic Fluid Management↗
NASA NTRS2022

Asymmetric Warming/Cooling Response to CO2 Increase/Decrease Mainly Due to Non-Logarithmic Forcing, not Feedbacks

We explore the CO2 dependence of effective climate sensitivity (SG) with symmetric abrupt and transient CO2 forcing, spanning the range 1/8×, 1/4×, 1/2×, 2×, 4×, and 8×CO2, using two state-of-the-art fully coupled atmosphere-ocean-sea-ice-land models. In both models, under abrupt CO2 forcing, we find an asymmetric response in surface temperature and SG. The surface global warming at 8×CO2 is more than one third larger than the corresponding cooling at 1/8×CO2, and SG is CO2 dependent, increasing non-monotonically from 1/8×CO2 to 8×CO2. We find similar CO2 dependence in the transient runs, forced with -1%yr−1CO2 and +1%yr−1CO2 up to 1/8×CO2 and 8×CO2, respectively. The non-logarithmic radiative forcing – not the changing feedbacks – primarily explains the dependence of SG on CO2, particularly at low CO2 levels. The changing feedbacks, however, explain SG’s non-monotonic behavior.

climate sensitivity↗
NASA NTRS2022

Planetary protection assessment of radioisotope thermoelectric generator (RTG)-powered landed missions to ocean worlds: application to Enceladus

Landed missions to icy worlds with a subsurface liquid water ocean must meet planetary protection requirements, and ensure a sufficiently small likelihood of any microorganism-bearing part of the landed element reaching the ocean. A higher bound on this likelihood is set by the potential for radioisotope thermoelectric generator (RTG) power sources, the hottest possible landed element, to melt through the ice shell and reach the ocean. Here, we quantify this potential as a function of three key parameters: surface temperature, ice shell thickness (i.e., heat flux through the shell), and thickness of a porous (insulating) snow or regolith cover. Although the model we describe can be applied to any ocean world, we present results in the context of a landed mission concept to the south polar terrain of Saturn’s moon Enceladus. In this particular context, we discuss planetary protection considerations for landing site selection. The likelihood of forward microbial contamination of Enceladus’ ocean by an RTG-powered landed mission can be made sufficiently low to not undermine compliance with planetary protection policy.

Marc Neveu↗
NASA NTRS2023

Lake Anna Water Resources: Using NASA Earth Observations to Identify Algal Event Risk Factors in Lake Anna and Help Inform Future Management Practices

Lake Anna is a man-made reservoir and popular recreation destination that spans over 13,000 acres-9,600 public and 3,400 private-in the Piedmont region of Virginia. The Lake has recently seen a rise in documented harmful algal blooms (HABs), which pose a variety of community and ecological concerns and are often exacerbated by anthropogenic factors, such as excess nutrient loads from agricultural runoff. NASA DEVELOP has partnered with the Virginia Department of Environmental Quality (DEQ) to help monitor cyanobacteria and nutrient pollution indicators across Lake Anna. The team utilized Earth observations (EO) and in situ ancillary data to identify and monitor algal bloom trends. The team used Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-2 Multispectral Instrument (MSI), and Sentinel-3 Ocean and Land Color Instrument (OLCI) to analyze water quality variables such as chlorophyll-a, turbidity, surface temperature, and cyanobacteria. Due to the lack of comprehensive in situ data and historic HAB event records, our ability to compare and validate EOs was limited. Additionally, deficient spatial resolutions, along with a geographically complicated shoreline, accentuated the spatial constraints we faced in our analysis. After examining EOs, our results indicated conditions conducive to the formation of HABs within the upper reaches of Lake Anna. Yet, spatially dependent limiting factors may have also influenced where these phenomena developed. When used in concert with existing in situ datasets, NASA EOs provide relevant stakeholders with more comprehensive analyses with which to engage in enhanced monitoring and watershed management.

cyanobacteria↗
NASA NTRS1989

Modeling surface temperature distributions in forest landscapes

A model of the frequency distributions of the spatial variability in surface temperature is presented. Surface temperature data are obtained from two daytime and two nighttime flights of the Thermal IR Multispectral Scanner (TIMS) over forest land in western Oregon in August, 1985. The temperature values are corrected for atmospheric attenuation and thermal radiation emission with the LOWTRAN-6 algorithm. The temperature distributions were modeled with a two-parameter beta probability density distribution and the fit of the model was evaluated by comparison with the TIMS data set. Use of the model's parameters to identify and classify surface types shows good discrimination among various surfaces for the daytime images, with less distinct discrimination for the nighttime images.

Holbo, H. R.↗
NASA NTRS2017

Temperature Changes in the United States

Temperature is among the most important climatic elements used in decision-making. For example, builders and insurers use temperature data for planning and risk management while energy companies and regulators use temperature data to predict demand and set utility rates. Temperature is also a key indicator of climate change: recent increases are apparent over the land, ocean, and troposphere, and substantial changes are expected for this century. This chapter summarizes the major observed and projected changes in near-surface air temperature over the United States, emphasizing new data sets and model projections since the Third National Climate Assessment (NCA3). Changes are depicted using a spectrum of observations, including surface weather stations, moored ocean buoys, polar-orbiting satellites, and temperature-sensitive proxies. Projections are based on global models and downscaled products from CMIP5 (Coupled Model Intercomparison Project Phase 5) using a suite of Representative Concentration Pathways (RCPs; see Ch. 4: Projections for more on RCPs and future scenarios).

Vose, R. S.↗
DOE OSTI2021

Cutting out the middleman: calibrating and validating a dynamic vegetation model (ED2-PROSPECT5) using remotely sensed surface reflectance

Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to the surface energy balance, which is important to light- and temperature-sensitive plant processes as well as understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on vegetation model behavior can be constrained by observations of shortwave reflectance, thus reducing model predictive uncertainty. Importantly, calibrating against radiative transfer outputs allows models to directly use remote sensing reflectance products without relying on highly derived products (such as MODIS leaf area index) whose assumptions may be incompatible with the target vegetation model and whose uncertainties are usually not well quantified. Here, we created the EDR model by coupling the two-stream representation of canopy radiative transfer in the Ecosystem Demography model version 2 (ED2) with a leaf radiative transfer model (PROSPECT-5) and a simple soil reflectance model to predict full-range, high-spectral-resolution surface reflectance that is dependent on the underlying ED2 model state. We then calibrated this model against estimates of hemispherical reflectance (corrected for directional effects) from the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and survey data from 54 temperate forest plots in the northeastern United States. The calibration significantly reduced uncertainty in model parameters related to leaf biochemistry and morphology and canopy structure for five plant functional types.

54 ENVIRONMENTAL SCIENCES↗