Multi-Sensor Retrievals of Ozone Generated with the Tropospheric Ozone and its Precursors from Earth System Sounding (TROPESS) framework.
No abstract provided
Engineering topics
Publications and source records attributed to McDuffie, James.
No abstract provided
No abstract provided
No abstract provided
Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO 2 ( X CO 2 ) for the roughly 100 000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy,better than 0.25 %, is required in order to accurately infer carbon sources and sinks from X CO 2 , significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20 % over land and 40 % over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO 2 data record continues to expand.
No abstract available
UNKNOWN
The NASA Crew Launch Vehicle is a two-stage orbital launcher designed to meet NASA's current as well as future needs for human space flight. In order to free the designers to explore more possibilities during the design phase, a need exists for the ability to quickly perform simulation on both the baseline vehicle as well as the vehicle after proposed changes due to mission planning, vehicle configuration and avionics changes, proposed new guidance and control algorithms, and any other contingencies the designers may wish to consider. Further, after the vehicle is designed and built, the need will remain for such analysis in the event of future mission planning. An easily reconfigurable, modular, nonlinear six-degree-of-freedom simulation matching NASA Marshall's in-house high-fidelity simulator is created with the ability to quickly perform simulation and analysis of the Crew Launch Vehicle throughout the entire launch profile. Simulation results are presented and discussed, and an example comparison fly-off between two candidate controllers is presented.