A5103247350- Atmospheric and Environmental Gas Dynamics
- Atmospheric Ozone and Climate
- Atmospheric chemistry and aerosols
- Spectroscopy and Laser Applications
- Atmospheric aerosols and clouds
- Calibration and Measurement Techniques
- Geochemistry and Geologic Mapping
- Advanced Data Compression Techniques
- Speech and Audio Processing
- Geological Modeling and Analysis
- Service-Oriented Architecture and Web Services
- Distributed Sensor Networks and Detection Algorithms
- Seismology and Earthquake Studies
- Solar Radiation and Photovoltaics
- Formal Methods in Verification
- Space exploration and regulation
- Planetary Science and Exploration
- Model-Driven Software Engineering Techniques
- Biomedical and Chemical Research
- Advanced Adaptive Filtering Techniques
- Cyclone Separators and Fluid Dynamics
- Digital Filter Design and Implementation
- Gas Sensing Nanomaterials and Sensors
- Laser Design and Applications
- Seismic Imaging and Inversion Techniques
Jet Propulsion Laboratory
2010-2020
Abstract. This work describes the NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used evaluate errors in face of realistic clouds aerosols, polarized non-Lambertian surfaces, imperfect meteorology, uncorrelated instrument noise. We find that post-retrieval filters essential eliminate poorest retrievals, which arise primarily due cloud...
Abstract. Here, we report preliminary estimates of the column averaged carbon dioxide (CO2) dry air mole fraction, XCO2, retrieved from spectra recorded over land by Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for NASA Orbiting Carbon Observatory (OCO) mission. After screening clouds and other known error sources, these retrievals reproduce much expected structure in global XCO2 field, including its variation with latitude...
Abstract. The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO2) with accuracy, resolution, coverage needed quantify CO2 fluxes (sources sinks) on regional scales. OCO-2 was successfully launched 2 July 2014 has gathered more than years of observations. v7/v7r operational data products from September January 2016 are discussed here. On monthly timescales, 7 12 % these...
The accuracy of atmospheric trace gas retrievals depends directly on the molecular absorption model used within retrieval algorithm. For remote sensing well-mixed gases, such as carbon dioxide (CO2), where variability is small compared to background, quality key. Recent updates oxygen (O2) coefficients (ABSCO) for 0.76 µm A-band and water vapor (H2O) continuum 1.6 2.06 CO2 bands Orbiting Carbon Observatory (OCO-2 OCO-3) algorithm are described here. Updates in O2 involve inclusion new...
Abstract. The Orbiting Carbon Observatory-2 (OCO-2) is the first National Aeronautics and Space Administration (NASA) satellite designed to measure atmospheric carbon dioxide (CO2) with accuracy, resolution, coverage needed quantify CO2 fluxes (sources sinks) on regional scales. OCO-2 was successfully launched 2 July 2014, joined 705 km Afternoon Constellation 3 August 2014. On monthly time scales, 7 12 % of these measurements are sufficiently cloud aerosol free yield estimates...
Abstract Remote sensing of the atmosphere is typically achieved through measurements that are high‐resolution radiance spectra. In this article, our goal to characterize first‐moment and second‐moment properties errors obtained when solving regularized inverse problem associated with space‐based atmospheric CO 2 retrievals, specifically for dry air mole fraction in a column atmosphere. The estimating (or retrieving) state variables usually ill posed, leading solution based on regularization...
Abstract. Here, we report preliminary estimates of the column averaged carbon dioxide (CO2) dry air mole fraction, XCO2, retrieved from spectra recorded over land by Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for NASA Orbiting Carbon Observatory (OCO) mission. After screening clouds and other known error sources, these retrievals reproduce much expected structure in global XCO2 field, including its variation with latitude...
Abstract. Since the launch of Greenhouse Gases Observing Satellite (GOSAT) in 2009, retrieval algorithms designed to infer column-averaged dry-air mole fraction carbon dioxide (XCO2) from hyperspectral near-infrared observations reflected sunlight have been greatly improved. They now generally include scattering effects clouds and aerosols, as early work found that absorption-only retrievals, which neglected these effects, often incurred unacceptably large errors, even for scenes with...
Abstract. This work describes the NASA Atmospheric CO2 Observations from Space (ACOS) XCO2 retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used evaluate errors in face of realistic clouds aerosols, polarized non-Lambertian surfaces, imperfect meteorology, uncorrelated instrument noise. We find that post-retrieval filters essential eliminate poorest retrievals, which arise primarily due cloud...
Abstract. Since the launch of Greenhouse Gases Observing Satellite (GOSAT) in 2009, retrieval algorithms designed to infer column-averaged dry-air mole fraction carbon dioxide (XCO2) from hyperspectral near-infrared observations reflected sunlight have been greatly improved. They now generally include scattering effects clouds and aerosols, as early work found that absorption-only retrievals, which neglected these effects, often incurred unacceptably large errors, even for scenes with...
PreviousNext No AccessSEG Technical Program Expanded Abstracts 1995Neural networks and paper seismic interpretationAuthors: Miles LeggettMike SmythAlisdair ManningCliff N. PrescottHuw EdwardsMiles LeggettBritish Gas plc, U.K., Mike SmythBritish Alisdair ManningBritish Cliff PrescottBritish Huw EdwardsBritish U.K.https://doi.org/10.1190/1.1887232 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink:...
Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Why Robust Software Engineering Matters for Atmospheric Composition RetrievalsAuthorsJamesMcDuffieiDMikeSmythiDSebastianValiDVijayNatrajKevinBowmaniDJonathanHobbsSébastienRocheiDJosephMendoncaEdwinSarkissianSee all authors James McDuffieiDCorresponding Author• Submitting AuthorNASA Jet Propulsion LaboratoryiDhttps://orcid.org/0000-0002-9408-5695view email addressThe was not providedcopy...