Articles | Volume 16, issue 8
https://doi.org/10.5194/gmd-16-2077-2023
https://doi.org/10.5194/gmd-16-2077-2023
Model evaluation paper
 | 
18 Apr 2023
Model evaluation paper |  | 18 Apr 2023

Evaluating wind profiles in a numerical weather prediction model with Doppler lidar

Pyry Pentikäinen, Ewan J. O'Connor, and Pablo Ortiz-Amezcua

Related authors

Methodology for deriving the telescope focus function and its uncertainty for a heterodyne pulsed Doppler lidar
Pyry Pentikäinen, Ewan James O'Connor, Antti Juhani Manninen, and Pablo Ortiz-Amezcua
Atmos. Meas. Tech., 13, 2849–2863, https://doi.org/10.5194/amt-13-2849-2020,https://doi.org/10.5194/amt-13-2849-2020, 2020
Short summary

Related subject area

Climate and Earth system modeling
Correction of sea surface biases in the NEMO ocean general circulation model using neural networks
Andrea Storto, Sergey Frolov, Laura Slivinski, and Chunxue Yang
Geosci. Model Dev., 18, 4789–4804, https://doi.org/10.5194/gmd-18-4789-2025,https://doi.org/10.5194/gmd-18-4789-2025, 2025
Short summary
Representing lateral groundwater flow from land to river in Earth system models
Chang Liao, L. Ruby Leung, Yilin Fang, Teklu Tesfa, and Robinson Negron-Juarez
Geosci. Model Dev., 18, 4601–4624, https://doi.org/10.5194/gmd-18-4601-2025,https://doi.org/10.5194/gmd-18-4601-2025, 2025
Short summary
FINAM is not a model (v1.0): a new Python-based model coupling framework
Sebastian Müller, Martin Lange, Thomas Fischer, Sara König, Matthias Kelbling, Jeisson Javier Leal Rojas, and Stephan Thober
Geosci. Model Dev., 18, 4483–4498, https://doi.org/10.5194/gmd-18-4483-2025,https://doi.org/10.5194/gmd-18-4483-2025, 2025
Short summary
The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
Geosci. Model Dev., 18, 4399–4416, https://doi.org/10.5194/gmd-18-4399-2025,https://doi.org/10.5194/gmd-18-4399-2025, 2025
Short summary
Enhancing winter climate simulations of the Great Lakes: insights from a new coupled lake–ice–atmosphere (CLIAv1) system on the importance of integrating 3D hydrodynamics with a regional climate model
Pengfei Xue, Chenfu Huang, Yafang Zhong, Michael Notaro, Miraj B. Kayastha, Xing Zhou, Chuyan Zhao, Christa Peters-Lidard, Carlos Cruz, and Eric Kemp
Geosci. Model Dev., 18, 4293–4316, https://doi.org/10.5194/gmd-18-4293-2025,https://doi.org/10.5194/gmd-18-4293-2025, 2025
Short summary

Cited articles

Accadia, C., Zecchetto, S., Lavagnini, A., and Speranza, A.: Comparison of 10-m wind forecasts from a Regional Area Model and QuikSCAT Scatterometer wind observations over the Mediterranean Sea, Mon. Weather Rev., 135, 1945– 1960, https://doi.org/10.1175/MWR3370.1, 2007. a, b
Andersson, E.: How to evolve global observing systems, ECMWF Newsletter, 153, 37–40, https://doi.org/10.21957/9fxea2, 2017. a
Atmospheric Radiation Measurement (ARM) user facility: Balloon-Borne Sounding System (SONDEWNPN), 2013-09-28 to 2022-05-29, ARM Mobile Facility (PVC) Highland Center, Cape Cod MA; AMF1 (M1), Eastern North Atlantic (ENA) Graciosa Island, Azores, Portugal (C1), Southern Great Plains (SGP) Central Facility, Lamont, OK (C1), Tropical Western Pacific (TWP) Central Facility, Darwin, Australia (C3), compiled by: Keeler, E., Coulter, R., Kyrouac, J., and Holdridge, D., ARM Data Center [data set], https://doi.org/10.5439/1021460, 2013. a
Atmospheric Radiation Measurement (ARM) user facility: Doppler Lidar Horizontal Wind Profiles (DLPROFWIND4NEWS), 2014-10-21 to 2022-03-20, ARM Mobile Facility (PVC) Highland Center, Cape Cod MA; AMF1 (M1), Eastern North Atlantic (ENA) Graciosa Island, Azores, Portugal (C1), Southern Great Plains (SGP) Central Facility, Lamont, OK (C1), Tropical Western Pacific (TWP) Central Facility, Darwin, Australia (C3), compiled by: Shippert, T., Newsom, R., and Riihimaki, L., ARM Data Center [data set], https://doi.org/10.5439/1178582, 2014. a
Beck, J., Nuret, M., and Bousquet, O.: Model wind field forecast verification using multiple-Doppler syntheses from a national radar network, Weather Forecast., 29, 331–348, https://doi.org/10.1175/WAF-D-13-00068.1, 2014. a
Download
Short summary
We used Doppler lidar to evaluate the wind profiles generated by a weather forecast model. We first compared the Doppler lidar observations with co-located radiosonde profiles, and they agree well. The model performs best over marine and coastal locations. Larger errors were seen in locations where the surface was more complex, especially in the wind direction. Our results show that Doppler lidar is a suitable instrument for evaluating the boundary layer wind profiles in atmospheric models.
Share