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Title:   Author  item
                                            MOGHADDAM, M. - University Of Michiganitem
                                            CHAPIN, ELAINE - Jet Propulsion Laboratoryitem
                                            Crow, Wadeitem
                                            CUENCA, W.T. - Oregon State Universityitem
                                            ENTEKHABI, DARA - Collaboratoritem
                                            HENLSEY, S. - Collaboratoritem
                                            LOU, Y. - Collaboratoritem
                                            MOORCROFT, P. - Harvard Universityitem
                                            SAATCHI, S. - Collaboratoritem
                                            SHEPSON, P. - Collaborator
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 7/1/2015
                                    Publication  Date: N/A
                                    Citation: N/AInterpretive Summary:
                                Technical Abstract: Active microwave remote sensing has long been recognized as a key component of an effective environmental observing strategy, due to the strong relationships of radar measurements with geometric and compositional properties of the Earth’s landscape. The Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) Earth Venture Suborbital 1 (EV-S1) mission was selected by NASA in 2010 to build and utilize a P-band synthetic aperture radar (SAR) to observe root-zone soil moisture (RZSM) distributions at representative north American biomes, and use such distributions to provide a new estimate of net ecosystem exchange (NEE) for North America. North American ecosystems are critical components of the global carbon cycle, exchanging large amounts of carbon dioxide and other gases with the atmosphere. These fluxes are quantified through NEE, but current continental-scale estimates of NEE contain high levels of uncertainty. As much as 60–80% of the uncertainty can be attributed to and its spatial and temporal heterogeneity [1]; mapping spatial and temporal variations of RZSM therefore has a key role in addressing a major challenge of climate research. This talk will describe the AirMOSS mission, its instrument and flight platform, timeline, mission success Criteria, data products, and the latest science results. The retrieval algorithms for RZSM will be discussed, and the accuracy of derived products will be presented.


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