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Results for “orbiting carbon observatory”

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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Space-Based Near-Infrared CO2 Measurements: Testing the Orbiting Carbon Observatory Retrieval Algorithm and Validation Concept Using SCIAMACHY Observations over Park Falls, Wisconsin

Space-based measurements of reflected sunlight in the near-infrared (NIR) region promise to yield accurate and precise observations of the global distribution of atmospheric CO2. The Orbiting Carbon Observatory (OCO) is a future NASA mission, which will use this technique to measure the column-averaged dry air mole fraction of CO2 (XCO2) with the precision and accuracy needed to quantify CO2 sources and sinks on regional scales (approx.1000 x 1000 sq km and to characterize their variability on seasonal timescales. Here, we have used the OCO retrieval algorithm to retrieve XCO2 and surface pressure from space-based Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) measurements and from coincident ground-based Fourier transform spectrometer (FTS) measurements of the O2 A band at 0.76 mm and the 1.58 mm CO2 band for Park Falls,Wisconsin. Even after accounting for a systematic error in our representation of the O2 absorption cross sections, we still obtained a positive bias between SCIAMACHY and FTS XCO2 retrievals of approx.3.5%. Additionally, the retrieved surface pressures from SCIAMACHY systematically underestimate measurements of a calibrated pressure sensor at the FTS site. These findings lead us to speculate about inadequacies in the forward model of our retrieval algorithm. By assuming a 1% intensity offset in the O2 A band region for the SCIAMACHY XCO2 retrieval, we significantly improved the spectral fit and achieved better consistency between SCIAMACHY and FTS XCO2 retrievals. We compared the seasonal cycle of XCO2 at Park Falls from SCIAMACHY and FTS retrievals with calculations of the Model of Atmospheric Transport and Chemistry/Carnegie-Ames-Stanford Approach (MATCH/CASA) and found a good qualitative agreement but with MATCH/CASA underestimating the measured seasonal amplitude. Furthermore, since SCIAMACHY observations are similar in viewing geometry and spectral range to those of OCO, this study represents an important test of the OCO retrieval algorithm and validation concept using NIR spectra measured from space. Finally, we argue that significant improvements in precision and accuracy could be obtained from a dedicated CO2 instrument such as OCO, which has much higher spectral and spatial resolutions than SCIAMACHY. These measurements would then provide critical data for improving our understanding of the carbon cycle and carbon sources and sinks.

carbon dioxide↗
NASA NTRS2018

Context Cameras for the Orbiting Carbon Observatory 3 (OCO-3) Instrument

We have developed an adaptable camera platform that takes advantage of screened and qualified commercial off the shelf (COTS) components (CMOS sensor, rad-tolerant microcircuits, lenses) to significantly shorten development time of space-borne visible imaging systems while reducing the overall cost and risk of the development. This modular camera platform is implemented as a suite of two visible-light cameras for the Orbiting Carbon Observatory 3 (OCO-3) instrument at NASA’s Jet Propulsion Laboratory (JPL). The Internal Context Camera (ICC) and External Context Camera (ECC) provide contextual engineering imaging support for the calibration of the OCO-3 instrument, intended to significantly reduce the duration of the mission’s calibration campaign. The OCO-3 mission has taken advantage of the design and qualification work performed by JPL’s Mars 2020 Enhanced Engineering Camera (EECam) team in reusing the qualified COTS CMOS imaging sensor, proven electronic designs, and scalable field-programmable gate array (FPGA) firmware to meet OCO-3’s mission requirements and resource availability. We will be presenting the steps taken by JPL to design, build, and test the Context Cameras for the OCO-3 mission. We will highlight the design deviations from the Mars2020 EECams and discuss the methodology of tailoring the EECam design for the OCO-3 requirements. Camera imaging capabilities, including focal plane and optical performance, will be presented, as well as a summary of the calibration and environmental test results. Finally, we will discuss the potential for future applications for the Context Cameras.

Moore, Douglas↗
DOE OSTI2025

Quantification of regional net CO 2 flux errors in the Orbiting Carbon Observatory-2 (OCO-2) v10 model intercomparison project (MIP) ensemble using airborne measurements

Inverse model intercomparison projects (MIPs) provide a chance to assess the uncertainties in inversion estimates arising from various sources. However, accurately quantifying ensemble CO 2 flux errors remains challenging and often relies on the ensemble spread. This study proposes a method for quantifying the errors in regional net surface–atmosphere CO 2 flux estimates from models taken from the Orbiting Carbon Observatory-2 (OCO-2) v10 MIP by using independent airborne CO 2 measurements for the period 2015–2017. We first calculate the root mean square error (RMSE) between the ensemble mean of posterior CO 2 concentrations and airborne observations and then isolate the CO 2 concentration errors caused solely by the ensemble mean of posterior net fluxes by subtracting the observation, representation, and transport errors from seven regions. Our analysis reveals that the flux errors projected onto CO 2 space account for 55 %–85 % of the regional average RMSE over the 3 years, ranging from 0.88 to 1.91 ppm. In five regions, the error estimates based on observations exceed those computed from the ensemble spread of posterior fluxes by a factor of 1.33–1.93, implying an underestimation of the actual flux errors, while their magnitudes are comparable in two regions. The adjoint sensitivity analysis identifies that the underestimation of flux errors is prominent where the magnitudes of fossil fuel emissions exceed those of terrestrial-biosphere fluxes by a factor of 3–31 over the 3 years. This suggests the presence of systematic biases in the inversion estimates associated with errors in the prescribed fossil fuel emissions common to all models. Our study emphasizes the value of airborne measurements for quantifying regional errors in ensemble net CO 2 flux estimates.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Measuring Atmospheric Carbon Dioxide from the NASA Orbiting Carbon Observatory-2 (OCO-2)

Fossil fuel combustion, deforestation, and other human activities are now adding almost 40 billion tons of carbon dioxide (CO2) to the atmosphere each year. These emissions are superimposed on an active natural carbon cycle that adds about 20 times as much CO2 to the atmosphere annually, and then reabsorbs a comparable amount, along with over half of the CO2 contributed by human activities. Interestingly, the identity and location of the natural “sinks” in the land biosphere and ocean that are responsible for absorbing this anthropogenic CO2 are still poorly understood. Because of this, it is impossible to accurately predict how these sinks will respond to a warming climate. Space based remote sensing provides new tools for studying the sources and sinks of CO2. The NASA Orbiting Carbon Observatory-2 (OCO-2) was launched in July 2014 and was inserted at the head of the 705-km Afternoon Constellation (A-Train) a month later.

Crisp, David↗
NASA NTRS2023

Using Orbiting Carbon Observatory-2 (OCO-2) column CO2 retrievals to rapidly detect and estimate biospheric surface carbon flux anomalies

The global carbon cycle is experiencing continued perturbations via increases in atmospheric carbon concentrations, which are partly reduced by terrestrial biosphere and ocean carbon uptake. Greenhouse gas satellites have been shown to be useful in retrieving atmospheric carbon concentrations and observing surface and atmospheric CO2 seasonal-to-interannual variations. However, limited attention has been placed on using satellite column CO2 retrievals to evaluate surface CO2 fluxes from the terrestrial biosphere without advanced inversion models at low latency. Such applications could be useful to monitor, in near real time, biosphere carbon fluxes during climatic anomalies like drought, heatwaves, and floods, before more complex terrestrial biosphere model outputs and/or advanced inversion modelling estimates become available. Here, we explore the ability of Orbiting Carbon Observatory-2 (OCO-2) column-averaged dry air CO2 (XCO2) retrievals to directly detect and estimate terrestrial biosphere CO2 flux anomalies using a simple mass-balance approach. An initial global analysis of surface–atmospheric CO2 coupling and transport conditions reveals that the western US, among a handful of other regions, is a feasible candidate for using XCO2 for detecting terrestrial biosphere CO2 flux anomalies. Using the CarbonTracker model reanalysis as a test bed, we first demonstrate that a well-established mass-balance approach can estimate monthly surface CO2 flux anomalies from XCO2 enhancements in the western United States. The method is optimal when the study domain is spatially extensive enough to account for atmospheric mixing and has favorable advection conditions with contributions primarily from one background region. We find that errors in individual soundings reduce the ability of OCO-2 XCO2 to estimate more frequent, smaller surface CO2 flux anomalies. However, we find that OCO-2 XCO2 can often detect and estimate large surface flux anomalies that leave an imprint on the atmospheric CO2 concentration anomalies beyond the retrieval error/uncertainty associated with the observations. OCO-2 can thus be useful for low-latency monitoring of the monthly timing and magnitude of extreme regional terrestrial biosphere carbon anomalies.

Andrew F. Feldman↗
NASA NTRS2007

The Orbiting Carbon Observatory Mission: Watching the Earth Breathe Mapping CO2 from Space

Approach: Collect spatially resolved, high resolution spectroscopic observations of CO2 and O2 absorption in reflected sunlight. Use these data to resolve spatial and temporal variations in the column averaged CO2 dry air mole fraction, X(sub CO2) over the sunlit hemisphere. Employ independent calibration and validation approaches to produce X(sub CO2) estimates with random errors and biases no larger than 1-2 ppm (0.3-0.5%) on regional scales at monthly intervals.

three channel grating spectrometry↗
NASA NTRS2011

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 -↗
NASA NTRS2006

The Orbiting Carbon Observatory (OCO) Mission

Science objectives include: Collect the first space-based measurements of atmospheric CO2 with the precision, resolution, and coverage needed to characterize its sources and sinks on regional scales and quantify their variability over the seasonal cycle. Use independent data validation approaches to ensure high accuracy (1-2 ppm, 0.3% - 0.5%). Reliable climate predictions require an improved understanding of CO2 sinks. What human and natural processes are controlling atmospheric CO2? What are the relative roles of the oceans and land ecosystems in absorbing CO2?

carbon dioxide↗
NASA NTRS2006

The Orbiting Carbon Observatory: Mission Overview

OCO will acquire the space-based data needed to identify CO2 sources and sinks and quantify their variability over the seasonal cycle. Approach: a) Collect spatially resolved, high resolution spectroscopic observations of CO2 and O2 absorption in reflected sunlight; b) Use these data to resolve spatial and temporal variations in the column averaged CO2 dry air mole fraction, X cub CO2) over the sunlit hemisphere; and c) Employ independent calibration and validation approaches to produce X(sub CO2) estimates with random errors and biases no larger than 1-2 ppm (0.3-0.5%) on regional scales at monthly intervals.

CO2↗
NASA NTRS2006

The NASA Orbiting Carbon Observatory

Accurate forecasting of future climate requires an improved understanding of the global carbon cycle and its interaction with the Earth System OCO and GOSAT will make the first space-based measurements of CO2 with the accuracy needed to quantify sources and sinks of this important greenhouse gas. Continuing Cooperation between the OCO and GOSAT teams will improve the value of both missions to the science community.

Orbiting Carbon Obervatory (OCO) mission↗