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Title: Progress report of FY 1998 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 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. The focus of this years activities has been on the intercomparison of data obtained during the Water Vapor Intensive Operating Period'97 at the SGP CART site in central Oklahoma.

Authors:
;
Publication Date:
Research Org.:
National Oceanic and Atmospheric Administration (US)
Sponsoring Org.:
US Department of Energy (US)
OSTI Identifier:
762790
DOE Contract Number:
AI03-97ER62343
Resource Type:
Technical Report
Resource Relation:
Other Information: PBD: 1 Oct 1999
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; ACOUSTIC MEASUREMENTS; MOISTURE; NIGHT SKY; OPTICAL RADAR; RADIOMETERS; WATER VAPOR; ECOLOGICAL CONCENTRATION; CALCULATION METHODS

Citation Formats

Edgeworth R. Westwater, and Yong Han. Progress report of FY 1998 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes. United States: N. p., 1999. Web. doi:10.2172/762790.
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Edgeworth R. Westwater, & Yong Han. Progress report of FY 1998 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes. United States. doi:10.2172/762790.
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Edgeworth R. Westwater, and Yong Han. Fri . "Progress report of FY 1998 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes". United States. doi:10.2172/762790. https://www.osti.gov/servlets/purl/762790.
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@article{osti_762790,
title = {Progress report of FY 1998 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes},
author = {Edgeworth R. Westwater and Yong Han},
abstractNote = {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. The focus of this years activities has been on the intercomparison of data obtained during the Water Vapor Intensive Operating Period'97 at the SGP CART site in central Oklahoma.},
doi = {10.2172/762790},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Oct 01 00:00:00 EDT 1999},
month = {Fri Oct 01 00:00:00 EDT 1999}
}
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Technical Report:
View Technical Report (0.37 MB)
DOI:  10.2172/762790
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  • ;
    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-qualitymore » 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.« less

  • ;
    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-qualitymore » 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.« less

  • ; ; ; ... - Journal of Geophysical Research
    In November to December 1991, a substantial number of remote sensors and in situ instruments were operated together in Coffeyville, Kansas, during the climate experiment FIRE II. Included in the suite of instruments were (1) the NOAA Environmental Technology Laboratory (ETL) three-channel microwave radiometer, (2) the NASA GSFC Raman lidar, (3) ETL radio acoustic sounding system (RASS), and (4) frequent, research-quality radiosondes. The Raman lidar operated only at night and the focus of this portion of the experiment concentrated on clear conditions. The lidar data, together with frequent radiosondes and measurements of temperature profiles (every 15 min) by RASS allowedmore » profiles of temperature and absolute humidity to be estimated every minute. The authors compared 2-min measurements of brightness temperature (T{sub b}) with calculations of T{sub b} that were based on the Liebe and Layton, and Liebe et al. microwave propagation models, as well as the Waters model. The comparisons showed the best agreement at 20.6 GHz with the Waters model, with the Liebe et al. model being best at 31.65 GHz. The results at 90 GHz gave about equal success with the Liebe and Layton, and Liebe et al. models. Comparisons of precipitable water vapor derived independently from the two instruments also showed excellent agreement, even for averages as short as 2 min. The rms difference between Raman and radiometric determinations of precipitable water vapor was 0.03 cm which is roughly 2%. The experiments clearly demonstrate the potentisdal of simultaneous operation of radiometers and Raman lidars for fundamental physical studies of water vapor. 31 refs., 5 figs., 5 tabs.« less

  • ; ; ; ... - IEEE Transactions on Geoscience and Remote Sensing
    Brightness temperatures computed from five absorption models and radiosonde observations were analyzed by comparing them with measurements from three microwave radiometers at 23.8 and 31.4 GHz. Data were obtained during the Cloudiness Inter-Comparison experiment at the U.S. Department of Energy's Atmospheric Radiation Measurement Program's (ARM) site in North-Central Oklahoma in 2003. The radiometers were calibrated using two procedures, the so-called instantaneous ?tipcal? method and an automatic self-calibration algorithm. Measurements from the radiometers were in agreement, with less than a 0.4-K difference during clear skies, when the instantaneous method was applied. Brightness temperatures from the radiometer and the radiosonde showed anmore » agreement of less than 0.55 K when the most recent absorption models were considered. Precipitable water vapor (PWV) computed from the radiometers were also compared to the PWV derived from a Global Positioning System station that operates at the ARM site. The instruments agree to within 0.1 cm in PWV retrieval.« less