A43C-3296:
A New Lidar Data Processing Algorithm Including Full Uncertainty Budget and Standardized Vertical Resolution for use Within the NDACC and GRUAN Networks
Thursday, 18 December 2014
Thierry Leblanc, California Institute of Technology, Pasadena, CA, United States, Alexander Haefele, Federal Office of Meteorology and Climatology MeteoSwiss, Remote Sensing Group, Payerne, Switzerland, Robert J Sica, University of Western Ontario, London, ON, Canada and Anne van Gijsel, Royal Netherlands Meteorological Institute, De Bilt, Netherlands
Abstract:
A new lidar data processing algorithm for the retrieval of ozone, temperature and water vapor has been developed for centralized use within the Network for the Detection of Atmospheric Composition Change (NDACC) and the GCOS Reference Upper Air Network (GRUAN). The program is written with the objective that raw data from a large number of lidar instruments can be analyzed consistently. The uncertainty budget includes 13 sources of uncertainty that are explicitly propagated taking into account vertical and inter-channel dependencies. Several standardized definitions of vertical resolution can be used, leading to a maximum flexibility, and to the production of tropospheric ozone, stratospheric ozone, middle atmospheric temperature and tropospheric water vapor profiles optimized for multiple user needs such as long-term monitoring, process studies and model and satellite validation. A review of the program’s functionalities as well as the first retrieved products will be presented.
