Remote sensing of tropospheric chemistry using lidars from geostationary orbit

Syed Ismail; Janette C. Gervin; H. John Wood; Frank Peri

doi:10.1117/12.578975

11 January 2005 Remote sensing of tropospheric chemistry using lidars from geostationary orbit

Syed Ismail, Janette C. Gervin, H. John Wood, Frank Peri

Proceedings Volume 5659, Enabling Sensor and Platform Technologies for Spaceborne Remote Sensing; (2005) https://doi.org/10.1117/12.578975
Event: Fourth International Asia-Pacific Environmental Remote Sensing Symposium 2004: Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2004, Honolulu, Hawai'i, United States

Abstract

Tropospheric chemistry is considered to be the next frontier of atmospheric chemistry, and understanding and predicting the global influence of natural and human-induced effects on tropospheric chemistry will be the next challenge for atmospheric research over the foreseeable future. A geostationary Earth orbit (GEO) vantage point provides an ideal location for measuring spatially and temporally resolved distributions of trace gas species. One powerful technique for making this measurement is LIght Detection And Ranging (lidar) using solid-state lasers. Presently, NASA has a notional plan for using lidars for tropospheric chemistry measurements, but from low Earth orbit (LEO). While permitting high spatially resolved measurements, LEO measurements, however, lack the temporal resolution required to monitor important atmospheric processes and transport. A GEO instrument will require a more energetic and efficient lidar system in order to permit accurate measurements. In this study, we investigated the capability of a lidar for tropospheric profiling of chemical species and we develop a roadmap for the requisite technologies.

Citation Download Citation

Syed Ismail, Janette C. Gervin, H. John Wood, and Frank Peri "Remote sensing of tropospheric chemistry using lidars from geostationary orbit", Proc. SPIE 5659, Enabling Sensor and Platform Technologies for Spaceborne Remote Sensing, (11 January 2005); https://doi.org/10.1117/12.578975

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