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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

Opportunities for Coordinated Observations of CO2 with the Orbiting Carbon Observatory (OCO) and Greenhouse Gases Observing Satellite (GOSAT)

The Orbiting Carbon Observatory (OCO) and the Greenhouse Gases Observing Satellite (GOSAT) are the first two satellites designed to make global measurements of atmospheric carbon dioxide (CO2) with the precision and sampling needed identify and monitor surface sources and sinks of this important greenhouse gas. Because the operational phases of the OCO and GOSAT missions overlap in time, there are numerous opportunities for comparing and combining the data from these two satellites to improve our understanding of the natural processes and human activities that control the atmospheric CO2 and it variability over time. Opportunities for cross-calibration, cross-validation, and coordinated observations that are currently under consideration are summarized here.

climate↗

Global CO2 Distributions over Land from the Greenhouse Gases Observing Satellite (GOSAT)

January 2009 saw the successful launch of the first space-based mission specifically designed for measuring greenhouse gases, the Japanese Greenhouse gases Observing SATellite (GOSAT). We present global land maps (Level 3 data) of column-averaged CO2 concentrations (X(sub CO2)) derived using observations from the GOSAT ACOS retrieval algorithm, for July through December 2009. The applied geostatistical mapping approach makes it possible to generate maps at high spatial and temporal resolutions that include uncertainty measures and that are derived directly from the Level 2 observations, without invoking an atmospheric transport model or estimates of CO2 uptake and emissions. As such, they are particularly well suited for comparison studies. Results show that the Level 3 maps for July to December 2009 on a lO x 1.250 grid, at six-day resolution capture much of the synoptic scale and regional variability of X(sub CO2), in addition to its overall seasonality. The uncertainty estimates, which reflect local data coverage, X(sub CO2) variability, and retrieval errors, indicate that the Southern latitudes are relatively well-constrained, while the Sahara Desert and the high Northern latitudes are weakly-constrained. A probabilistic comparison to the PCTM/GEOS-5/CASA-GFED model reveals that the most statistically significant discrepancies occur in South America in July and August, and central Asia in September to December. While still preliminary, these results illustrate the usefulness of a high spatiotemporal resolution, data-driven Level 3 data product for direct interpretation and comparison of satellite observations of highly dynamic parameters such as atmospheric CO2.

Hammerling, Dorit M.↗

Space-Based Measurements of CO2 from the Japanese Greenhouse Gases Observing Satellite (GOSAT) and the NASA Orbiting Carbon Observatory-2 (OCO-2) Missions

Space-based remote sensing observations hold substantial promise for future long-term monitoring of CO2 and other greenhouse gases. The principal advantages of space based measurements include: (1) Spatial coverage (especially over oceans and tropical land) (2) Sampling density (needed to resolve CO2 weather). The principal challenge is the need for high precision To reach their full potential, space based CO2 measurements must be validated against surface measurements to ensure their accuracy. The TCCON network is providing the transfer standard There is a need for a long-term vision to establish and address community priorities (1) Must incorporate ground, air, space-based assets and models (2) Must balance calls for new observations with need to maintain climate data records.

Orbiting Carbon Observatory -↗

The earth's radiation budget and its relation to atmospheric hydrology. I - Observations of the clear sky greenhouse effect. II - Observations of cloud effects

The clear-sky components of the earth's radiation budget (ERB), the relationship of these components to the sea surface temperature (SST), and microwave-derived water-vapor amount are analyzed in an observational study along with the relationship between the cloudy-sky components of ERB and space/time coincident observations of SST, microwave-derived cloud liquid water, and cloud cover. The purpose of the study is to use these observations for establishing an understanding of the couplings between radiation and the atmosphere that are important to understanding climate feedback. A strategy for studying the greenhouse effect of earth by analyzing the emitted clear-sky longwave flux over the ocean is proposed. It is concluded that the largest observed influence of clouds on ERB is more consistent with macrophysical properties of clouds as opposed to microphysical properties. The analysis for clouds and the greenhouse effect of clouds is compared quantitatively with the clear sky results. Land-ocean differences and tropical-midlatitude differences are shown and explained in terms of the cloud macrostructure.

Stephens, Graeme L.↗

Observations of Greenhouse Gases as Climate Indicators

Humans have significantly altered the energy balance of the Earth’s climate system mainly not only by extracting and burning fossil fuels but also by altering the biosphere and using halocarbons. The 3rd US National Climate Assessment pointed to a need for a system of indicators of climate and global change based on long-term data that could be used to support assessments and this led to the development of the National Climate Indicators System (NCIS). Here we identify a representative set of key atmospheric indicators of changes in atmospheric radiative forcing due to greenhouse gases (GHGs), and we evaluate atmospheric composition measurements, including non-CO2GHGs for use as climate change indicators in support of the US National Climate Assessment. GHG abundances and their changes over time can provide valuable information on the success of climate mitigation policies, as well as insights into possible carbon-climate feedback processes that may ultimately affect the success of those policies. To ensure that reliable information for assessing GHG emission changes can be provided on policy-relevant scales, expanded observational efforts are needed. Furthermore, the ability to detect trends resulting from changing emissions requires a commitment to supporting long-term observations. Long-term measurements of greenhouse gases, aerosols, and clouds and related climate indicators used with a dimming/brightening index could provide a foundation for quantifying forcing and its attribution and reducing error in existing indicators that do not account for complicated cloud processes.

greenhouse gases↗

Detectability of anthropogenic impacts on terrestrial carbon storage through space-based greenhouse gas observations

While changes in human activity and their impact on the terrestrial biosphere may be apparent in inventory and land-surface satellite data, reliably matching these changes to signals in atmospheric greenhouse gases remains challenging. The dominant signals in atmospheric carbon dioxide (CO2) are those of the seasonal and diurnal variability of the terrestrial biosphere. As a result, the historically large short-term change in anthropogenic fossil fuel emissions due to COVID-19 produced an atmospheric CO2 signal near the threshold of detectability of the current space-based observing system. Impacts of anthropogenic activity on terrestrial carbon storage are likewise expected to be difficult, if not impossible, to detect and validate with atmospheric observations. For example, many forest management projects involve reduction of wood removals that would otherwise be taken off site and decompose years later and are thus not reflected in immediate onsite carbon fluxes. Nevertheless, changes implemented over a jurisdictional scale, as opposed to individual projects, may be detectable. This presentation will analyze to what extent NASA’s Goddard Earth Observing System (GEOS)/Orbiting Carbon Observatory 2 (OCO-2) assimilated column CO2 (XCO2) product is able to detect anthropogenic changes to terrestrial carbon storage and the results of several simulation experiments meant to represent potential forest management scenarios. As examples, we consider past and future changes due to conversion in the Tropics to agricultural land use from slash-and-burn, e.g., from Reducing emissions from deforestation and forest degradation in developing countries (REDD+) efforts. This has the potential to inform what practices may be observable with current and future technology, e.g., Europe’s upcoming CO2 monitoring mission (CO2M), and where improvement is needed.

Brad Weir↗

Capturing Complete Spatial Context in Satellite Observations of Greenhouse Gases

Scientific consensus from a 2015 pre-Decadal Survey workshop highlighted the essential need for a wide-swath (mapping) low earth orbit (LEO) instrument delivering carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) measurements with global coverage. OCO-2 pioneered space-based CO2 remote sensing, but lacks the CH4, CO and mapping capabilities required for an improved understanding of the global carbon cycle. The Carbon Balance Observatory (CARBO) advances key technologies to enable high-performance, cost-effective solutions for a space-based carbon-climate observing system. CARBO is a compact, modular, 15-30° field of view spectrometer that delivers high-precision CO2, CH4, CO and solar induced chlorophyll fluorescence (SIF) data with weekly global coverage from LEO. CARBO employs innovative immersion grating technologies to achieve diffraction-limited performance with OCO-like spatial (2 x 2 sq.km) and spectral (λ/Δλ≈ 20,000) resolution in a package that is >50% smaller, lighter and more cost-effective. CARBO delivers a 25- to 50-fold increase in spatial coverage compared to OCO-2 with no loss of detection sensitivity. Individual CARBO modules weigh < 20 kg, opening diverse new space-based platform opportunities.

Miller, Charles E.↗