Progress report of FY 1997 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes

Abstract

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 proposal was 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. The algorithm will include recently-developed quality control procedures for radiometers. The focus of this years activities has been on the intercomparison of data obtained during an intensive operating period at the SGP CART site in central Oklahoma.