the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 Apr 2025
Harmonised boundary layer wind profile dataset from six ground-based doppler wind lidars in a transect across Paris, France
Abstract. Doppler wind lidars (DWL) offer high-resolution wind profile measurements that are valuable for understanding atmospheric boundary layer (ABL) dynamics. Here six ground-based DWL, deployed in a multi-institutional effort along a 40 km transect through the centre of Paris (France), are used to retrieve horizontal wind speed and direction through the ABL at 18–25 m vertical and 1–60 min temporal resolution. Data are available for June 2022 – March 2024 (three DWL) and two Intensive Observation Periods (six DWL) across 9 weeks in September 2023 – December 2023. Data from all sensors are harmonised in terms of quality control, file format, as well as temporal and vertical resolutions. The quality of this DWL dataset is evaluated against in-situ measurements at the Eiffel Tower and radiosonde profiles. This unique, spatially dense, open dataset will allow urban boundary layer dynamics to be explored in process-studies, and is further valuable for the evaluation of high-resolution weather, climate, inverse and air pollution models that resolve city-scale processes.
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RC1: 'Comment on essd-2025-167', Anonymous Referee #1, 16 Jul 2025
Review of the ESSD manuscript 2025-167 “Harmonised boundary layer wind profile dataset from six ground based doppler wind lidars in a transect across Paris, France”
The presented topic of the manuscript is very interesting and relevant for atmospheric boundary layer research in urban environments. The final harmonized and open data set of boundary layer wind profiles is quite valuable for the research community and opens new pathway for process based studies and evaluation of atmospheric models for urban applications.
Specific comments:
Line 62: “The harmonisation process involves application of wind retrievals from …” Do you refer to application of certain wind retrieval algorithms?
Line 88: “… scanning configurations with the following parameters: azimuth (θ) and zenith (φ) emission angles of the laser” is good but table 3 presents horizontal wind scan type with elevation angle e.g. VAD 75°, please add information that refers to this angle
Line 233: „Päschke et al.’s (2015) retrieval method“: Did you applied default values of configuration file or did you changed certain parameter settings e.g. for CNS_PERCENTAGE? Please provide config files if possible.
Line 322: GPS position is updated every 1s?
Figure 1: Please provide the time period of the presented wind rose measured at the Tour Eiffel
Figure 2a: The figure capture states “ordered from north-east to south-west”, this is true if we look from the bottom panel to the top panel. But not the other way around. May better: “ordered from north-east (lower panel) to south-west (upper panel).
Figure 2b: The horizontal lines for the very low altitudes are bit confusing. These lines show that below at a certain altitude e.g. 100 m are no data? This corresponds to the lowest reasonable gate?
Table 1: City centre (CC) is given as reference, please provide latitude and longitude. The abbreviation LMD means?
Table 2: No table entry means “not available” e.g. for the “Radial wind accuracy” or something else?
Citation: https://doi.org/10.5194/essd-2025-167-RC1 -
RC2: 'Comment on essd-2025-167', Anonymous Referee #2, 08 Aug 2025
The manuscript describes the development and evaluation of a harmonized multi-year, multi-instrument Doppler wind lidar (DWL) dataset from a transect of six stations across the Paris metropolitan area. The paper is generally well-structured, and the dataset is of clear value to the community. However, I have several substantive concerns and recommendations that should be addressed.
1) Section 3.6 provides some descriptions of QC procedures for each instrument model, but the rationale behind the choice of certain thresholds (e.g., SNR limits, RMSE cut-offs, range gate thresholds) is only briefly mentioned. Please elaborate on: How these thresholds were determined (empirical inspection vs. manufacturer specification vs. literature values)? Whether sensitivity tests were performed to assess the impact of varying these thresholds on data retention and accuracy?
2) Although the dataset harmonizes variables and QC flags across instruments, it is not clear whether any systematic inter-comparisons or bias corrections between different DWL models were conducted before merging. Given known differences in hardware performance (e.g., range resolution, beam configuration), the authors should add more detailed description to explain: Whether cross-calibration between collocated or overlapping instruments was attempted? How residual biases between instruments might influence the spatial gradients along the transect?
3) The transect spans sites with markedly different surface characteristics (airport, high-rise urban, low-rise suburban, rural plateau). While this diversity is a strength, it also complicates interpretation. Please provide a more systematic evaluation of how site-specific surface roughness, orography, and local obstacles might influence the retrieved wind profiles. And consider including a table or figure summarizing estimated roughness lengths or urban canopy parameters for each site, with discussion of implications for representativeness.
4) The radiosonde comparison (Section 4.1) is limited to two release days, both during IOP2. While these examples are illustrative, they are not statistically robust. If more radiosonde launches were available during the campaign (or from nearby operational soundings), please include them in the evaluation. Provide quantitative statistics (bias, RMSE, correlation) for all matched profiles, not just visual comparisons.
5) Temporal evaluation with in-situ measurements: The Eiffel Tower comparison is appropriate, but: the wind speed bias at PAROIS is noted but not fully explored—please quantify whether this is a constant offset, wind-direction-dependent, or height-dependent bias.
6) The L3 product involves resampling to common vertical and temporal grids (Section 3.7). While necessary for harmonization, these interpolations may affect fine-scale variability, particularly near the surface or in cases of sharp vertical gradients (e.g., low-level jets). Please provide a short sensitivity analysis or example quantifying the difference between original and resampled profiles for selected cases. Discuss whether interpolation across missing range gates could introduce artificial smoothing or biases.
7) The dataset has significant potential for NWP, LES, and inverse modeling communities, but guidance for optimal use is somewhat limited. Suggest adding a subsection or table outlining recommended uses and limitations of the dataset, including: Appropriate spatial/temporal scales for which the data are reliable; Known limitations (e.g., reduced accuracy under precipitation, lower data availability in low-aerosol conditions); Differences in performance between instruments and sites.
8) Figures 5 and 6: The color scales and symbols are sometimes difficult to distinguish for readers; please consider improving accessibility.
Citation: https://doi.org/10.5194/essd-2025-167-RC2
Data sets
Harmonised boundary layer wind profile dataset from six ground-based doppler wind lidars across Paris, France William Morrison https://doi.org/10.5281/zenodo.14761503
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