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160 records · Page 9

Covid-19 Impact Monitoring for Climate Environment (Greenhouse Gases)

To track atmospheric CO2 changes resulting from the lockdowns, observations collected by the NASA Orbiting Carbon Observatory-2 (OCO-2) satellite and Japan’s Greenhouse gases Observing SATellite (GOSAT) in 2020 were compared to results collected in previous years. The OCO-2 results were used to search for changes on regional scales over the globe. Targeted observations from GOSAT were used to track changes in large urban areas, such as Beijing and Tokyo. Both types of observations yielded key insights into the CO2 changes accompanying the economic disruptions caused by the COVID-19 lockdowns. ESA, NASA and JAXA developed the dashboard jointly to monitor the climate impacts of COVID-19.

greenhouse gases↗

Anomalous Net Biome Exchange Over Amazonian Rainforests Induced by the 2015/16 El Niño: Temperature-dominated Total Flux but Soil Dryness-Shaped Spatial Pattern

The magnitude and spatial pattern of anomalous net biome exchange (NBE) induced by the 2015/16 El Niño over Amazonian rainforests remain uncertain. We here investigated them using multi-model posterior NBE products in the Orbiting Carbon Observatory-2 (OCO-2) version 10 modeling intercomparison project. Results suggest that relative to the annual NBE average in 2017/18, larger anomalous carbon release occurred over the eastern and northern Amazonian rainforests in 2015/16, with a total flux of approximately 0.4 PgC yr−1 after assimilating satellite-observed column CO2 concentrations (XCO2) over land. We further find that this anomalous spatial pattern was predominantly determined by soil dryness, while the total positive NBE anomaly was dominated by higher temperature with its contribution of approximately 68~70%. We believe that atmospheric inversions assimilating more satellite-observed XCO2 in future can provide us more comprehensive understanding how Amazonian rainforests cope with the abiotic stresses induced by El Niño events.

Jun Wang↗

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO 2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO 2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO 2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

54 ENVIRONMENTAL SCIENCES↗

Oco-2 Calibration Refinement Across Versions And Plans For Oco-3

The third major reprocessing campaign for the Orbiting Carbon Observatory 2 mission is underway. With each release, several aspects of instrument calibration were improved. An onboard lamp tracks relative gain degradation, but ages too quickly to track absolute scaling. The most significant changes between builds were evolving assumptions about the stability of the solar calibrator. For the newest build, the trend in lunar measurements over a 4.5-year time series was applied. Another significant change was to expand a list of detector outliers via review of dark, lamp, and science measurements. More subtle adjustments to stray light and spectral dispersion were also performed. The techniques developed for OCO-2 are being applied to the Orbiting Carbon Observatory 3, which completed in-orbit checkout in August 2019. OCO-3 does not have a solar calibrator, and will need to constrain lamp aging via secondary lamps and comparison to other satellites.

Rosenberg, Rob↗

Characteristics of Total Column CO2 Retrievals from the OCO Missions: Biases, Information Content and Implications for Flux Inversions

The Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3, launched in 2015 and 2019, respectively, are intended to collect and deliver high-resolution observations of CO2 with unprecedented space and time coverage. Observations of CO2 from these remote-sensing missions (also known as XCO2, or column-based average, dry air mole fraction of CO2) are then used by the global carbon cycle community to answer a wide range of science questions, from the distribution and quantification of global and regional CO2 source-sink patterns to quantification of anthropogenic sources at urban scales. Even though we have had the OCO-2 mission flying for a few years now, the retrieval algorithms are continuously evolving and improving to deliver XCO2 retrievals with very high precision and high accuracy (or low biases). In this presentation, we will discuss a simple yet effective quantitative framework that has been developed by the OCO-2 flux team to evaluate the information content of these XCO2 retrievals as soon as they are released, i.e., with lower latency than full-scale flux inversions. This framework serves as a precursor to advanced inverse modeling frameworks and is intended to provide an early but accurate assessment of the signal present in the satellite retrievals, the robustness of that signal, and the ability of these retrievals to resolve patterns in CO2 surface fluxes that cannot be resolved by our current network of surface sites. Specific results will tackle a tiered set of questions that are being addressed using this framework: (a) what are the distribution of retrievals in the different modes of operation and how do they vary in space and time? (b) what is the information that is being given to the inverse modeling frameworks from the space-based data, information above and beyond what is provided by the in-situ data? and (c) how do these factors influence our choices for doing flux inversions with the satellite retrievals? While the primary focus of the results will be on application of this technique to mature OCO-2 retrievals, we will show early results for a couple of months of OCO-3 retrievals. For the time-period that the retrievals from the two missions overlap, we will highlight how this framework allows us to effortlessly put the information from OCO-3 and OCO-2 on an equal footing, thus enabling easy comparison between the two pioneering missions.

Chatterjee, Abhishek↗

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↗

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.↗

The Orbiting Carbon Observatory: NASA's First Dedicated Carbon Dioxide Mission

The Orbiting Carbon Observatory is scheduled for launch from Vandenberg Air Force Base in California in January 2009. This Earth System Science Pathfinder (ESSP) mission carries and points a single instrument that incorporates 3 high-resolution grating spectrometers designed to measure the absorption of reflected sunlight by near-infrared carbon dioxide (CO2) and molecular oxygen bands. These spectra will be analyzed to retrieve estimates of the column-averaged CO2 dry air mole fraction, X(sub CO2). Pre-flight qualification and calibration tests completed in early 2008 indicate that the instrument will provide high quality X(sub CO2) data. The instrument was integrated into the spacecraft, and the completed Observatory was qualified and tested during the spring and summer of 2008, in preparation for delivery to the launch site in the fall of this year. The Observatory will initially be launched into a 635 km altitude, near-polar orbit. The on-board propulsion system will then raise the orbit to 705 km and insert OCO into the Earth Observing System Afternoon Constellation (A-Train). The first routine science observations are expected about 45 days after launch. Calibrated spectral radiances will be archived starting about 6 months later. An exploratory X(sub CO2) product will be validated and then archived starting about 3 months after that.

Carbon Cycle↗

A Preview of the OCO-2 Spatial and Temporal Sampling Strategy

For routine science observations, the OC0-2 spacecraft bus points the instrument bore sight either at the local nadir (85 < 85deg) or at the glint spot (85 < 81 deg) and collects -106 soundings/day over the sunlit hemisphere. center dot Nadir observations: expected to yield more spatially-homogeneous optical paths in partially cloudy regions and over topographically rough land regions center dot Glint observations are expected to yield (much) higher SNR over dark ocean or ice covered surfaces. center dot For both glint and nadir observations, the spacecraft performs a yaw maneuver to orient the long axis of the spectrometer slits perpendicular to the principle plane center dot The nominal plan is to alternate between glint and nadir observations on alternate 16-day ground repeat cycles, but this strategy may be modified to maximize coverage Target observations: For calibration and validation, the spacecraft bus can also point the instrument bore sight at a stationary surface target center dot Collects up to 12,000 soundings at observing zenith angles from +75deg GEO CL-

Orbiting Carbon Observatory-2↗