Progress report of FY 1999 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes

摘要

Previously, the proposers have delivered to ARM a documented algorithm, that is now applied operationally, and which derives water vapor profiles from combined remote sensor measurements of water vapor radiometers, cloud-base ceilometers, and radio acoustic sounding systems (RASS). With the expanded deployment of a Raman lidar at the CART Central Facility, high quality, high vertical-resolution, water vapor profiles will be provided during nighttime clear conditions, and during clear daytime conditions, to somewhat lower altitudes. The object of this effort is to use Kalman Filtering, previously applied to the combination of nighttime Raman lidar and microwave radiometer data, to derive high-quality water vapor profiles, during non-precipitating conditions, from data routinely available at the CART site. Input data to the algorithm would include: Raman lidar data, highly quality-controlled data of integrated moisture from microwave radiometers and GPS, RASS, and radiosondes. While analyzing data obtained during the Water Vapor Intensive Operating Period'97 at the SGP CART site in central Oklahoma, several questions arose about the calibration of the ARM microwave radiometers (MWR). A large portion of this years effort was a thorough analysis of the many factors that are important for the calibration of this instrument through the tip calibration method and the development of algorithms to correct this procedure. An open literature publication describing this analysis has been accepted.