Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 14
Articles | Volume 18, issue 14
https://doi.org/10.5194/amt-18-3533-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-3533-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 14
Research article
 | 
29 Jul 2025
Research article |  | 29 Jul 2025

Propagating information content: an example with advection

David D. Turner, Maria P. Cadeddu, Julia M. Simonson, and Timothy J. Wagner

Related authors

A multi-instrument framework for boundary layer wind and turbulence profiling
Serena Lipari, Raghavendra Krishnamurthy, Bianca Adler, Laura Bianco, Nicola Bodini, Matthis Chabert d'Hières, Harindra J. S. Fernando, Robert Jackson, Michael Kieburtz, Anthony Kirincich, Stefano Letizia, Julie K. Lundquist, Paytsar Muradyan, Rob K. Newsom, Joseph O'Brien, Sujan Pal, Mikhail Pekour, David D. Turner, Sonia Wharton, and Seth Zippel
EGUsphere, https://doi.org/10.5194/egusphere-2026-5984,https://doi.org/10.5194/egusphere-2026-5984, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
The HRRR Meteorology, Energy, and Transmission (MET) Toolkit: advancing high-resolution atmospheric data for contiguous US energy applications
Nicola Bodini, Emina Maric, Ulrike Egerer, Grant Buster, Luke Lavin, Pavlo Pinchuk, Brandon Benton, and David D. Turner
Wind Energ. Sci., 11, 3919–3948, https://doi.org/10.5194/wes-11-3919-2026,https://doi.org/10.5194/wes-11-3919-2026, 2026
Short summary
Evaluating the scanning capabilities of an MWR to estimate temperature and humidity advection from a single site
Andrea Burgos-Cuevas, David D. Turner, Jan H. Schween, Tobias Marke, Tobias Böck, and Ulrich Löhnert
EGUsphere, https://doi.org/10.5194/egusphere-2026-4994,https://doi.org/10.5194/egusphere-2026-4994, 2026
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Multi-season evaluation of temperature and wind in the marine boundary layer along the United States northeast coast in the High-Resolution Rapid Refresh model
Bianca Adler, Laura Bianco, David D. Turner, Joseph Olson, Xia Sun, Joshua Gebauer, Nicola Bodini, Stefano Letizia, and James M. Wilczak
Geosci. Model Dev., 19, 8627–8649, https://doi.org/10.5194/gmd-19-8627-2026,https://doi.org/10.5194/gmd-19-8627-2026, 2026
Short summary
The Alaska Meteorology, Energy, and Transmission (MET) Toolkit dataset
Nicola Bodini, Grant Buster, and David D. Turner
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-680,https://doi.org/10.5194/essd-2026-680, 2026
Preprint under review for ESSD
Short summary
More articles (22)

Cited articles

Baidar, S., Wagner, T. J., Turner, D. D., and Brewer, W. A.: Using optimal estimation to retrieve winds from velocity-azimuth display (VAD) scans by a Doppler lidar, Atmos. Meas. Tech., 16, 3715–3726, https://doi.org/10.5194/amt-16-3715-2023, 2023. 
Bevington, P. R. and Robinson, D. K.: Data Reduction and Error Analysis for the Physical Sciences, third edition, McGraw-Hill, 320 pp., ISBN 0-07-911243-9, 2003. 
Blumberg, W. G., Wagner, T. J., Turner, D. D., and Correia Jr., J.: Quantifying the accuracy and uncertainty of diurnal thermodynamic profiles and convection indices derived from the Atmospheric Emitted Radiance Interferometer, J. Appl. Meteor. Clim., 56, 2747–2766, https://doi.org/10.1175/JAMC-D-17-0036.1, 2017. 
Browning, K. and Wexler, R.: The determination of kinematic properties of a wind field using Doppler radar, J. Appl. Meteor., 7, 105–113, 1968. 
Cadeddu, M. P., Marchand, R., Orlandi, E., Turner, D. D., and Mech, M.: Microwave passive ground-based retrievals of cloud and rain liquid water path in drizzling clouds: Challenges and possibilities, IEEE T. Geosci. Remote Sens., 55, 6468–6481, https://doi.org/10.1109/TGRS.2017.2728699, 2017. 
More articles (22)
Download
Short summary
When deriving a geophysical variable from remote sensors, the uncertainty and information content are critical. The latter quantify specifies what fraction of a real perturbation would be observed in the derived variable. This paper outlines, for the first time, a methodology for propagating the information content from multiple remote sensors into a derived product using horizontal advection as an example.
Read more
Share