Affiliation:
1. Naval Research Laboratory, Marine Meteorology Division CA Monterey USA
2. Joint Center for Satellite Data Assimilation (JCSDA) at the University Corporation Atmospheric Research (UCAR) Boulder CO USA
Abstract
AbstractA new data source from ground‐based stations that track global navigation satellite system (GNSS) transmitters has been implemented in the Navy Global Environmental Model (NAVGEM) with the NRL Atmospheric Variational Data Assimilation System‐Accelerated Representer. The observable is the ground‐based zenith total delay (ZTD) at each ground station. This ground‐based GNSS ZTD represents the tropospheric delay of the propagation of GNSS radio L‐band signal between the transmitters and the ground stations after correcting for ionospheric effects. Here, we present the implementation procedure, quality control, single observation test, bias correction scheme, and data impact assessment. One of the critical elements in the quality control scheme is to correct for the difference between the observing ground station elevation and the numerical model terrain. A single observation test shows comparable impact from this new data source to a single radiosonde observation at a single level. The ZTD biases estimated from a 6‐month experiment run are generally small, but have a dependency on the processing center and are computed separately for each station. The forecast sensitivity to observation impact diagnosis from a 3‐month experiment demonstrates that a single ZTD observation shows similar impact as the average impact from a single tangent point of a GNSS Radio Occultation profile. The assimilation of ZTD observations also significantly improves the forecast skill by 0.25%–0.75% for wind, temperature, and precipitable water and by 1%–2% for geopotential height in the Southern Hemisphere beyond 3 days.
Publisher
American Geophysical Union (AGU)
Subject
Space and Planetary Science,Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Geophysics
Reference52 articles.
1. Baker N. L. Hoppel K. Rosmond T. Pauley P. M. Ruston B. &Swadley S.(2017).The assimilation of water vapor information from satellite observations and the choice of the analysis variable. Paper presented at 17th Conference on Satellite Meteorology and Oceanography Annapolis MD.
2. Interpretation of Forecast Sensitivity Observation Impact in Data Denial Experiments
3. Bender M. Stephan K. Schraff C. &Potthast R.(2018).GPS slant delay assimilation in COSMO‐DE. Paper presented at the International Symposium on Data Assimilation Munich Germany.
4. An Hourly Assimilation–Forecast Cycle: The RUC
5. Operational Assimilation of GPS Zenith Total Delay Observations into the Met Office Numerical Weather Prediction Models