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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Forward Modeling of Atmospheric Carbon Dioxide in GEOS-5: Uncertainties Related to Surface Fluxes and Sub-Grid Transport

Forward GEOS-5 AGCM simulations of CO2, with transport constrained by analyzed meteorology for 2009-2010, are examined. The CO2 distributions are evaluated using AIRS upper tropospheric CO2 and ACOS-GOSAT total column CO2 observations. Different combinations of surface C02 fluxes are used to generate ensembles of runs that span some uncertainty in surface emissions and uptake. The fluxes are specified in GEOS-5 from different inventories (fossil and biofuel), different data-constrained estimates of land biological emissions, and different data-constrained ocean-biology estimates. One set of fluxes is based on the established "Transcom" database and others are constructed using contemporary satellite observations to constrain land and ocean process models. Likewise, different approximations to sub-grid transport are employed, to construct an ensemble of CO2 distributions related to transport variability. This work is part of NASA's "Carbon Monitoring System Flux Pilot Project,"

Pawson, Steven↗
NASA NTRS2015

AgMIP Climate Data and Scenarios for Integrated Assessment

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

agriculture↗
NASA NTRS2019

Progress in Atmospheric Carbon Monitoring Using NASA's GEOS Model and Data from the OCO and GOSAT Missions

NASA's Global Modeling and Assimilation Office (GMAO) produces a variety of carbon products based the synthesis of satellite remote sensing data and outputs of the Goddard Earth Observing System (GEOS). This includes bottom-up surface fluxes due to fossil fuel emissions, biomass burning, terrestrial biospheric exchange, and ocean exchangeconstrained by measurements of nighttime lights, fire radiative power, normalized difference vegetation index, and ocean color. These fluxes are the basis of top-down estimates of carbon concentrations and fluxes. In particular, the GMAO system processes retrievals of column carbon dioxide (XCO2) from GOSAT and OCO-2 to produce a high-resolution, long-term global analysis of CO2 in three dimensions every 6 hours. Here, we discuss the potential applications of such products for satellite intercomparison and evaluation against independent, non-coincident data. We also highlight the ability to provide monthly global atmospheric growth rates inferred from the assimilated CO2 concentration product. Finally, we discuss the challenges facing such products including bias correction and the estimation and analysis of model transport errors.

Weir, B.↗
NASA NTRS2019

GEOS-Carb III: Delivering Mature Carbon Flux and Concentration Datasets in Support of NASA's Carbon Monitoring System

The GEOS-Carb project seeks to make high quality, data-driven products that support NASA's Carbon Monitoring System Program. These include bottom-up land and ocean flux estimates along with fossil fuel emissions, all informed by satellite data and the MERRA-2 reanalysis. These flux data support atmospheric carbon products that include both simulations and data assimilation products. We show examples of this work and discuss applications to future mission planning.

Ott, L.↗
NASA NTRS2015

An Inversion Analysis of Recent Variability in Natural CO2 Fluxes Using GOSAT and In Situ Observations

About one-half of the global CO2 emissions from fossil fuel combustion and deforestation accumulates in the atmosphere, where it contributes to global warming. The rest is taken up by vegetation and the ocean. The precise contribution of the two sinks, and their location and year-to-year variability are, however, not well understood. We use two different approaches, batch Bayesian synthesis inversion and variational data assimilation, to deduce the global spatiotemporal distributions of CO2 fluxes during 2009-2010. One of our objectives is to assess different sources of uncertainties in inferred fluxes, including uncertainties in prior flux estimates and observations, and differences in inversion techniques. For prior constraints, we utilize fluxes and uncertainties from the CASA-GFED model of the terrestrial biosphere and biomass burning driven by satellite observations and interannually varying meteorology. We also use measurement-based ocean flux estimates and two sets of fixed fossil CO2 emissions. Here, our inversions incorporate column CO2 measurements from the GOSAT satellite (ACOS retrieval, filtered and bias-corrected) and in situ observations (individual flask and afternoon-average continuous observations) to estimate fluxes in 108 regions over 8-day intervals for the batch inversion and at 3 x 3.75 weekly for the variational system. Relationships between fluxes and atmospheric concentrations are derived consistently for the two inversion systems using the PCTM atmospheric transport model driven by meteorology from the MERRA reanalysis. We compare the posterior fluxes and uncertainties derived using different data sets and the two inversion approaches, and evaluate the posterior atmospheric concentrations against independent data including aircraft measurements. The optimized fluxes generally resemble those from other studies. For example, the results indicate that the terrestrial biosphere is a net CO2 sink, and a GOSAT-only inversion suggests a shift in the global sink from the tropics south to the north relative to the prior and to an in-situ-only inversion. We also find a smaller terrestrial sink in higher-latitude northern regions in boreal summer of 2010 relative to 2009.

Carbon dioxide↗
NASA NTRSDate not supplied

Principal Component and Machine Learning Approach to Gap Fill Hyperspectral Ocean Color Satellite Retrievals

Retrievals of ocean color properties from space are important for monitoring the health of the ocean ecosystem but such retrievals can be limited spatially due to conditions such as clouds, aerosols, and sun glint. Gap filling of ocean color retrievals is typically performed by combining retrievals from multiple satellites or temporally averaging multiple days of retrievals. Despite these techniques large gaps still exist posing challenges for near real time monitoring of events like harmful algae blooms. To address these limitations, we developed a spatial gap filling approach applying machine learning approach to hyperspectral instruments to learn how to perform an atmospheric correction under challenging retrieval conditions. In this approach a principal component analysis is used to decompose the hyperspectral measurements into spectral components that describe the scattering and absorption of the atmosphere mixed with the surface spectral signatures. The coefficients of the principal components are used to train a neural network to predict ocean color properties derived from a standard MODIS ocean color algorithm. We apply the approach to two hyperspectral UV/VIS sensors, the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can be used to estimate ocean color properties such as chlorophyll, remote sensing reflectance, and fluorescence line height. This method could be used as a gap-filling technique for the future Ocean Color Instrument (OCI) onboard upcoming NASA's Plankton, Aerosol Cloud, ocean Ecosystem (PACE) satellite to provide additional information for monitoring the health of our global oceans. Additionally, it could be applied to the first NASA and Smithsonian geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) spectrometer to better understand diurnal variability in inland and coastal ocean ecology.

Zachary Fasnacht↗
NASA NTRS1986

Diurnal variation of outgoing longwave radiation in the tropics

The diurnal harmonic in longwave emission in the tropical belt (30 deg N-30 deg S) is estimated from nine years of NOAA polar-orbiting satellite data. The results are compared successfully with Nimbus-7 ERB scanner data and with GOES-West geosynchronous satellite data. An interesting and consistent diurnal variation in longwave emission is found over the regions of intense oceanic convection, such as the ITCZ and SPCZ regions, with a peak-to-peak variation of 6-8 W/sq m and a maximum in the morning (0600-1200 LST). Histogram analysis indicates that this variation is associated with a diurnal variation in convective cloud (about 400 mb). Over regions of very intense convection, a diurnal variation of very high clouds (above 100 mb), which is out of phase with the variations at lower levels in the atmosphere, reduces the magnitude of the diurnal harmonic in longwave emission. It is interesting that histograms based on data averaged over 8-km and 250-km boxes give the same qualitative information about cloud and emission variability.

Hartmann, D. L.↗
NASA NTRSDate not supplied

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗
NASA NTRS2001

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

Ichoku, Charles↗
NASA NTRS1998

Comparison of Globally Complete Versions of GPCP and CMAP Monthly Precipitation Analyses

In this study two global observational precipitation products, namely the Global Precipitation Climatology Project's (GPCP) community data set and CPC's Merged Analysis of Precipitation (CMAP), are compared on global to regional scales in the context of the different satellite and gauge data inputs and merger techniques. The average annual global precipitation rates, calculated from data common in regions/times to both GPCP and CMAP, are similar for the two. However, CMAP is larger than GPCP in the tropics because: (1) CMAP values in the tropics are adjusted month-by month to atoll gauge data in the West Pacific, which are greater than any satellite observations used; and (2) CMAP is produced from a linear combination of data inputs, which tends to give higher values than the microwave emission estimates alone to which the inputs are adjusted in the GPCP merger over the ocean. The CMAP month-to-month adjustment to the atolls also appears to introduce temporal variations throughout the tropics which are not detected by satellite-only products. On the other hand, GPCP is larger than CMAP in the high-latitude oceans, where CMAP includes the scattering based microwave estimates which are consistently smaller than the emission estimates used in both techniques. Also, in the polar regions GPCP transitions from the emission microwave estimates to the larger TOVS-based estimates. Finally, in high-latitude land areas GPCP can be significantly larger than CMAP because GPCP attempts to correct the gauge estimates for errors due to wind loss effects.

Curtis, Scott↗
NASA NTRS1979

Diffuse reflectance of the ocean - The theory of its augmentation by chlorophyll a fluorescence at 685 nm

The radiative transfer equation is modified to include the effect of fluorescent substances and solved in the quasi-single scattering approximation for a homogeneous ocean containing fluorescent particles with wavelength independent quantum efficiency and a Gaussian shaped emission line. The results are applied to the in vivo fluorescence of chlorophyll a (in phytoplankton) in the ocean to determine if the observed quantum efficiencies are large enough to explain the enhancement of the ocean's diffuse reflectance near 685 nm in chlorophyll rich waters without resorting to anomalous dispersion. The computations indicate that the required efficiencies are sufficiently low to account completely for the enhanced reflectance. The validity of the theory is further demonstrated by deriving values for the upwelling irradiance attenuation coefficient at 685 nm which are in close agreement with the observations.

Gordon, H. R.↗
NASA NTRS2007

RadSTAR L-Band Imaging Scatterometer: Performance Assessment

RadSTAR is an instrument development program aimed at combining a radiometer and a scatterometer system into a highly compact configuration that uses a single, electronically scanned antenna to provide co-located and simultaneous measurements of emission and backscatter for airborne and spaceborne applications [I]. The program was designed to map soil moisture and ocean salinity, both important components of the water cycle, and to map sea ice density and thickness, an important factor in ocean-atmosphere heat exchange in Polar Regions. The accuracy in estimation of these and a number of other Earth science parameters can be greatly enhanced by providing the co-aligned radar/radiometer microwave measurements. For instance, radiometer estimates of soil moisture from soil emission are affected by emission from vegetation, and from the roughness of the surface. Complementary measurements using the scatterometer can be used to evaluate the vegetation and surface roughness effects. Hence, the combined observations can provide an improved estimate. As with soil moisture, the ocean salinity is a function of the microwave emission from the sea surface temperature (SST) and sea roughness. There, the addition of radar backscatter measurements of sea roughness enables the correction of the emissivity and provide more accurate estimates of ocean salinity. Similar arguments can be made for other important Earth science parameters. This paper discusses the RadSTAR program, the radar system design, calibration, and digital beamforming techniques, and presents preliminary analysis of the data collected during the test flights. The data sets obtained during the flights and during the radar calibration in the anechoic chamber are also employed to asses the performance of the radar. The paper also discusses the Digital Beamforming Synthetic Aperture Radar (DBSAR) processor, a real-time processor recently developed for the LIS instrument which enables beam synthesis, fine resolutions, and large swaths.

Rincon, Rafael↗
NASA NTRSDate not supplied

Applications of MERRA-2 data for avian migration, biomass burning, and dusty atmospheric rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗
NASA NTRSDate not supplied

Applications of MERRA-2 Data for Avian Migration, Biomass Burning, and Dusty Atmospheric Rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗
NASA NTRS2026

SCOAPE-II: A 2024 Multiplatform Measurement Campaign off the US Gulf Coast to Assess Oil and Gas Emissions on the Outer Continental Shelf

Nine years ago, the Department of Interior’s Bureau of Ocean Energy Management (BOEM), the Agency with Air Quality (AQ) jurisdiction over the Outer Continental Shelf (OCS) of the US Gulf Coast west of 87.5° W longitude, asked NASA to determine the feasibility of using satellite data to measure offshore emissions in a region of concentrated oil and natural gas (ONG) operations. To study this issue NASA and BOEM conducted the May 2019 Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE) cruise in the Gulf. SCOAPE addressed both technological and scientific issues related to measuring nitrogen dioxide (NO 2 , a common air pollutant), including contrasting near-shore and deepwater regimes. Given the April 2023 launch of the geostationary Tropospheric Emissions: Monitoring of Pollution (TEMPO) AQ satellite, a 2024 SCOAPE-II was conducted in the Gulf with both ship and aircraft measurements. We present an overview of the SCOAPE-II campaign, analysis and validation of satellite-observed NO 2 , and evaluate measurements of methane from ship, aircraft, and satellite near ONG platforms. Our SCOAPE-II results are as follows: 1) Satellite NO 2 measurements (∼13:30 local time) from the TROPOspheric Monitoring Instrument (TROPOMI) are more accurate than TEMPO’s hourly scans (8.6% vs. 23.6% mean absolute bias); a new version of TEMPO data is currently being processed; 2) ship and aircraft measurements captured dozens of NO 2 and methane plumes from ONG operations, showing that they are persistent emitters; 3) satellite measurements of methane failed to replicate ship and aircraft measurements, presenting ongoing challenges for operational emissions monitoring over the Gulf.

satellite validation↗
NASA NTRS1976

Meteorological interpretations of the images from the Nimbus 5 electrically scanned microwave radiometer

The Nimbus 5 Electrically Scanned Microwave Radiometer (ESMR) is useful in determining the extent, structure, and intensity of rainfall over oceans. It is possible on the basis of rainfall maps to determine the location of frontal rain, rain/snow boundaries, and the structure of tropical storms. ESMR data on rainfall over the east coast of the United States and the Gulf of Mexico, on snowfall over the northeast coast of the United States, on frontal zones in the northwestern Pacific and on the tropical storm Leila in the South Indian Ocean are examined. Because of the generally high emissivities of land surfaces, interpretation of meteorological parameters over land is not yet possible.

Wilheit, T. T.↗
NASA NTRS2005

Understanding What's Critical in Protecting Our Society: Can Satellite Observations Help?

There are many vital issues which are impacting our daily lives and will continue to haunt us as long as we live on this planet of ours. These issues range from food supply availability, drought, coastal zone erosion, volcanoes, hurricanes, terrorism, global warming, earthquakes, water resources, air quality, public health, and agriculture production. Such societal needs are directly linked to our geometric population growth, and abundance of automobiles, industrial emissions, industrial waste and extensive fishing of our oceans and elimination of our ecology. The questions which require serious thoughts, research, coordination, and resources to understand, plan and strike a sensible balance in our daily lives and the above issues are tough to deal with. However, with the advent of remote sensing technologies, tremendous progress has been made in applying space-based and airborne data and products in solving real societal problems. Several of these problems, such as coastal zone erosion, air quality, severe weather, water availability and quality, public health, fires, land slides and others are intricately related; and in the long run can have serious consequences if not properly addressed by scientists, regulatory bodies and policy makers. Although it is a much involved and tangled web to unravel, nevertheless we have an excellent start in understanding some of the phenomena and hopefully can mitigate some of the severe effects by advancing our scientific knowledge. This paper briefly discusses the applications of remote sensing data from Terra, Aqua, and other NASA satellites how to deal with such complex problems; it provides an excellent start.

Habib, Shahid↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2.5 Longwave cloud props 3 hourly Data in Native Format (SRB_REL2.5_LW_CLDPROPS_3HRLY)

The Surface Radiation Budget (SRB) data set contain 47 surface and cloud properties including cloud fraction, cloud visible optical depth, cloud top temperature, cloud top pressure, cloud base pressure, and cloud water and ice content for each of 5 cloud types and in total. In addition to these cloud properties, the parameters also include surface pressure, total column ozone, day/night flag, and precipitable water. All perameters were measured at three hourly intervals for each day for the entire globe between 07/01/1983 and 06/30/2005 and serve as inputs to the Global Energy and Water-Cycle Experiment (GEWEX) longwave algorithm (GLW). [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3 hourly; Temporal_Resolution_Range=3 hourly].

CLOUD TOP TEMPERATURE↗