Observations during the Dynamics of the Madden–Julian Oscillation (DYNAMO) experiment focused on sensing atmospheric parameters, including vertical moisture profiles, cloud structure, precipitation processes, and planetary boundary layer properties, all of which are important for understanding and modeling the Madden–Julian Oscillation (MJO). These observations were performed using a variety of in-situ and remote sensors, including the S-band polarimetric and Ka-band (S-PolKa) radar, deployed by the National Center for Atmospheric Research (NCAR), and a colocated University of Miami microwave radiometer (UM-radiometer) operating at 23.8 and 30.0 GHz. These instruments sampled approximately the same volumes of the atmosphere at a variety of azimuth and elevation angles. The principal goal of this study is to develop a new retrieval strategy to estimate slant water vapor path (SWP) and slant liquid water (SLW) using UM-radiometer measurements from zenith to low elevation angles at a variety of azimuth angles. Retrievals of SWP along the radar signal path help to determine the error in radar reflectivity due to water vapor absorption. The retrieval algorithm has been developed using the vapor–liquid water ratio (VLWR) as well as both modeled and measured brightness temperatures for zenith to low elevation angles. Observation system simulation experiment (OSSE) results and measured radiosonde data have been used to determine that the retrieval uncertainty is less than 5% for integrated water vapor (IWV) and less than 12% for integrated liquid water (ILW). OSSE results for SWP show that the retrieval uncertainty is less than 8% at 5° elevation angle and less than 5% at 7° and 9°, while the mean difference between SWP retrieved from radiometer measurements and those retrieved from the S-PolKa radar during the DYNAMO campaign is less than 10% at 5° elevation angle and less than 7.5% at 7° and 9°. OSSE results for SLW show that the mean error is less than 24% for 5° elevation angle and less than 18% for 7° and 9°. Such retrievals of SWP and SLW help to characterize the distribution of water vapor and liquid water in the lower troposphere, which in turn may contribute to improvements in forecasting of convective initiation and precipitation.
|Original language||English (US)|
|Journal||IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing|
|State||Accepted/In press - Sep 14 2015|
ASJC Scopus subject areas
- Computers in Earth Sciences
- Atmospheric Science