Articles | Volume 9, issue 12
https://doi.org/10.5194/amt-9-5965-2016
https://doi.org/10.5194/amt-9-5965-2016
Research article
 | 
13 Dec 2016
Research article |  | 13 Dec 2016

Tropospheric delay parameters from numerical weather models for multi-GNSS precise positioning

Cuixian Lu, Florian Zus, Maorong Ge, Robert Heinkelmann, Galina Dick, Jens Wickert, and Harald Schuh

Related authors

DNS (v1.0): An open source ray-tracing tool for space geodetic techniques
Florian Zus, Kyriakos Balidakis, Ali Hasan Dogan, Rohith Thundathil, Galina Dick, and Jens Wickert
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-237,https://doi.org/10.5194/gmd-2024-237, 2025
Preprint under review for GMD
Short summary
Assimilation of GNSS Zenith Delays and Tropospheric Gradients: A Sensitivity Study utilizing sparse and dense station networks
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
EGUsphere, https://doi.org/10.5194/egusphere-2025-19,https://doi.org/10.5194/egusphere-2025-19, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Determination of high-precision tropospheric delays using crowdsourced smartphone GNSS data
Yuanxin Pan, Grzegorz Kłopotek, Laura Crocetti, Rudi Weinacker, Tobias Sturn, Linda See, Galina Dick, Gregor Möller, Markus Rothacher, Ian McCallum, Vicente Navarro, and Benedikt Soja
Atmos. Meas. Tech., 17, 4303–4316, https://doi.org/10.5194/amt-17-4303-2024,https://doi.org/10.5194/amt-17-4303-2024, 2024
Short summary
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024,https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Combined GNSS reflectometry–refractometry for automated and continuous in situ surface mass balance estimation on an Antarctic ice shelf
Ladina Steiner, Holger Schmithüsen, Jens Wickert, and Olaf Eisen
The Cryosphere, 17, 4903–4916, https://doi.org/10.5194/tc-17-4903-2023,https://doi.org/10.5194/tc-17-4903-2023, 2023
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Observations of tall-building wakes using a scanning Doppler lidar
Natalie E. Theeuwes, Janet F. Barlow, Antti Mannisenaho, Denise Hertwig, Ewan O'Connor, and Alan Robins
Atmos. Meas. Tech., 18, 1355–1371, https://doi.org/10.5194/amt-18-1355-2025,https://doi.org/10.5194/amt-18-1355-2025, 2025
Short summary
Mid-Atlantic nocturnal low-level jet characteristics: a machine learning analysis of radar wind profiles
Maurice Roots, John T. Sullivan, and Belay Demoz
Atmos. Meas. Tech., 18, 1269–1282, https://doi.org/10.5194/amt-18-1269-2025,https://doi.org/10.5194/amt-18-1269-2025, 2025
Short summary
Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm
Padmanabhan Thiruvengadam, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, and Joël Van Baelen
Atmos. Meas. Tech., 18, 1185–1191, https://doi.org/10.5194/amt-18-1185-2025,https://doi.org/10.5194/amt-18-1185-2025, 2025
Short summary
GNSS-RO residual ionospheric error (RIE): a new method and assessment
Dong L. Wu, Valery A. Yudin, Kyu-Myong Kim, Mohar Chattopadhyay, Lawrence Coy, Ruth S. Lieberman, C. C. Jude H. Salinas, Jae N. Lee, Jie Gong, and Guiping Liu
Atmos. Meas. Tech., 18, 843–863, https://doi.org/10.5194/amt-18-843-2025,https://doi.org/10.5194/amt-18-843-2025, 2025
Short summary
Benchmarking KDP in rainfall: a quantitative assessment of estimation algorithms using C-band weather radar observations
Miguel Aldana, Seppo Pulkkinen, Annakaisa von Lerber, Matthew R. Kumjian, and Dmitri Moisseev
Atmos. Meas. Tech., 18, 793–816, https://doi.org/10.5194/amt-18-793-2025,https://doi.org/10.5194/amt-18-793-2025, 2025
Short summary

Cited articles

Andrei, C. and Chen, R.: Assessment of time-series of troposphere zenith delays derived from the global data assimilation system numerical weather model, GPS Solut., 13, 109–117, 2008.
Blewitt, G., Kreemer, C., Hammond, W. C., Plag, H.-P., Stein, S., and Okal, E.: Rapid determination of earthquake magnitude using GPS for tsunami warning systems, Geophys. Res. Lett., 33, L11309, https://doi.org/10.1029/2006GL026145, 2006.
Boehm, J., Niell, A., Tregoning, P., and Schuh, H.: Global Mapping Function (GMF): A new empirical mapping function based on numerical weather model data, Geophys. Res. Lett., 33, L7304, https://doi.org/10.1029/2005GL025546, 2006.
Byram, S., Hackman, C., and Tracey, J.: Computation of a High-Precision GPS-Based Troposphere Product by the USNO, Proc. ION GNSS 2011, 19–23 September 2011, Portland, Oregon, USA, 572–578, 2011.
Chen, G. and Herring, T. A.: Effects of atmospheric azimuth asymmetry on the analysis of space geodetic data, J. Geophys. Res., 102, 20489–20502, https://doi.org/10.1029/97JB01739, 1997.
Download
Short summary
The recent dramatic development of multi-GNSS constellations brings great opportunities and potential for more enhanced precise positioning, navigation, timing, and other applications. In this contribution, we develop a numerical weather model (NWM) constrained PPP processing system to improve the multi-GNSS precise positioning. Compared to the standard PPP solution, significant improvements of both convergence time and positioning accuracy are achieved with the NWM-constrained PPP solution.
Share