DECIPHER-Monte Baldo dataset
Published 2026 | Version v01
Dataset Open

TEAMx DECIPHER Monte Baldo WindLidar WINDCUBE 100s, Raw Data (University of Trento)

Authors/Creators

  • 1. ROR icon University of Trento

Description

1. Short Description of the Sensor

The scanning WINDCUBE family uses the same pulsed Doppler technology as the well-known and widely used WINDCUBE vertical profiler. Fiber technology used in all WINDCUBE Lidars is designed to meet strong operational requirements and optimal instrument compactness.

The modularity allows the use of the WINDCUBE 100S/200S/400S with different scanning scenarios (PPI, RHI, LOS, DBS) adapted to multiple applications. 

WINDCUBE 100S/200S/400S offer the most advanced technique to measure the wind components on a large scale for short-term campaigns or long-term operations to reduce uncertainties, understand physical phenomena (such as wakes), or improve forecasting.

Dimension (L-W-H) (mm): 1008x814x1365 with scanning head and minimum feet extension
Weight 232 kg without options
Outdoor conditions

ambient temperature: -25°C - +45°C

Permeability: IP65

Humidity: 10% - 100%

Resistant to salty environment: ISO 9227
power consumption 500 W - 1600 W (range includes use of coolers and heaters)

Scanning modes

  • PPI: The lidar emits pulses of light and measures the backscattered light from atmospheric particles (aerosols, cloud droplets, etc.). By rotating its beam at a constant elevation angle, the lidar creates a "slice" of the atmosphere at that height. Scanning by varying the azimuth at a constant elevation.

  • RHI: RHI scans involve varying the elevation angle while keeping the azimuth angle constant, creating a vertical slice of the atmosphere.

  • DBS: scanning technique used in Doppler wind lidar for measuring wind velocity profiles. It involves directing the lidar beam at different angles (including a vertical beam) to collect radial velocity measurements, which are then used to calculate the horizontal and vertical wind components.

  • LOS: Stare or step-stare scanning mode to measure the radial wind along a fixed line of view.

1.2 Specification

Accumulation time 0.5 to 10 s (1s is standard)
Max. typical range up to 3000 m
Maximum range 14300 m
Physical range resolution 25, 50, 75, 100 m
Distance between two range gates Down to 1 m with gate overlapping
Number of range gates up to 320, depending on the range gate length used
First range of measurement More than twice the range gate length
Scanner rotation speed Up to 30°/s
Azimuth angle Between 0° and 360° (with 0.1° increment)
Elevation angle Between -19° and 199° (with 0.1° increment)

 

2. Measurement Strategy during the Campaign

2.1 Description of data collection

The data collection comprises the following consecutive scanning modes run in a loop.

PPI

  • Range (Distance along the line of sight, between the instrument and the center of each range gate): 50 - 1300 m  🡨 range = range gate length*2 x ((gate index) + 1)
  • Range gate length: 25 m
  • Gate index: 0 – 25
  • Elevations (fix): 15 – 45° in 5° steps
  • Azimuth (swinging): 251 – 310° in 1° step (corrected from 261 – 320 to compass alignment)
  • PPI sequence: 7 scans
  • Single PPI duration: 59 s
  • PPI sequence duration: 413 s

RHI

  • Range (Distance along the line of sight, between the instrument and the center of each range gate): 50 - 1300 m  🡨 range = range gate length*2 x ((gate index) + 1)
  • Range gate length: 25 m
  • Gate index: 0 – 25
  • Elevations (swinging): 6 – 45° in 1° steps
  • Azimuth (fix): 250 – 310° in 5° step (corrected from 261 – 320 to compass alignment)
  • RHI sequence: 13 scans
  • Single RHI duration: 39 s
  • RHI sequence duration: 507 s

DBS

  • Range (Distance along the line of sight, between the instrument and the center of each range gate): 52 - 1708 m 
  • Range gate length: 25 m
  • Gate index: 0 – 32
  • Measurement height: 1650 m 🡨 measurement height = range gate length*2 x ((gate index) + 1)
  • Elevations (fix): 75° + 90°
  • Azimuth (fix): cardinal points
  • Single DBS duration: 10 s

The entire scan cycle (PPI+RHI+DBS) lasts approximately 16-17 minutes

2.2 Time period covered by the data

12 July 2025 - 22 October 2025

2.3 Time zone

UTC

2.4 Physical location

Latitude 45.6654264; Longitude 10.82369476; Altitude 1316 m

 

3. Data Processing

3.1 Description of derived parameters and processing techniques used

Original data files are provided

3.2 Description of quality assurance and control procedures

This dataset was not subject to any quality control or processing. It is provided in its original form.

 

4. Data Format

4.1 Data file structure

NetCDF files with metadata (WindLidar native), zipped. One file per single scan. Data are within the wind_and_aerosols_data folder within the zip file

4.2 File naming convention

WLS100s-173_YYYY-MM-DD_HH-mm-SS_[scan type]_[scan_id]_[range gate in meter].nc

4.3 List of relevant parameters and units

All the scans provide measurements of the radial speed (m/s) as a function of time (s) and along the scan beam (range, m), defined by the azimuth and elevation angles, together with the carrier-to-noise ratio (CNR) and the radial speed confidence index for quality checking the measurements. The DBS scans also provide horizontal wind speed, wind direction and vertical wind speed computed using the last four inclined scans; given that each DBS scan consists of 4 inclined scans plus a vertical one and that each scan cycle (PPI+RHI+DBS) for the current dataset lasts approximately 16-17 minutes, only the last of the inclined DBS scan allows to compute the instantaneous speed. The previous 3 rely on a mix between the current and the previous inclined scans, with approximately 16-17 minutes of time lag.

 

5. Data Remarks

5.1 Known missing data periods

Missing the whole 29-08-2025 due to insufficient power supply

5.2 Software compatibility

All software that can read and process NetCDF files

 

 

Technical info

1. Data Sharing Policy within DECIPHER

1.1 Data Types

Two data types are envisioned, namely Raw Data and Processed Data. The submission of both data types is not mandatory.

  • "Raw Data" consists of the dataset as measured by the sensor. Data manipulation by the curators must be kept to a minimum, i.e., converting the file format and including metadata. Curators must include the tag "Raw Data" in the title of the dataset to refer to this data type.

  • "Processed Data" consists of the dataset after manipulation through a documented, literature-compliant procedure of data processing, including data cleaning, quality control, and averaging. The procedure must be documented in the dataset description page. Curators must include the tag "Processed Data" in the title of the dataset to refer to this data type. 

1.2 Internal Use

Datasets will be initially accessible only to the partners who contributed measurements on Monte Baldo. The agreement between partners for the usage of others’ datasets is to propose coauthorship to the respective owners. 

The requirements for public data use depend on the level of data processing, whether raw or processed:

  • The use of "Raw Data" by the project consortium is bound to a proper crediting of the dataset, using the reference reported on the dataset page. For the first 6 months after the dataset's publication, co-authorship proposals must be made to the data owners. Beyond this initial period, co-authorship is no longer mandatory, but users are encouraged to offer it to the curators.
  • The use of "Processed Data" by the project consortium is bound to a proper crediting of the dataset, using the reference reported on the dataset page. Users of the processed data must offer co-authorship to the data curators. 

 

2. Data Sharing and Public Data Use within TEAMx

Complying with the TEAMx data management plan: 

“Any use of TEAMx data products, during or after the embargo period, must include an acknowledgement (i.e., citation) of the source and the data provider. 

Data users must inform the respective data providers if a data product is to be shared with other parties via journal articles, presentations, and research proposals. If the data product constitutes a substantial part of the work, the data provider should be offered co-authorship and the opportunity to collaborate (both during and after the embargo period). In the case of co-authorship, an additional acknowledgement of the data provider is not required.”

 

3. Acknowledgement

The recommended formula for the attribution of the dataset is the following, and is mandatory in all cases: 

The [description of the data product] was collected/produced as part of the TEAMx programme and provided by [name of the data provider, institution of data provider]. [name of the data provider]’s contribution to TEAMx was supported by: (i) the PRIN2022 - DECIPHER project, funded by the European Union - Next Generation EU, Mission 4 Component 2, Prot. n. 2022NEWP4J - CUP: E53D23004450006, J53D23002810006 and B53D23007350006; (ii) the strategic partnership SPACE IT UP!, funded by the Italian Space Agency and the Ministry of University and Research, Contract n. 2024-5-E.0 - CUP: I53D24000060005; (iii) the consortium iNEST-Interconnected Nord-Est Innovation Ecosystem, funded by the European Union - Next Generation EU (PNRR, Mission 4.2, Investment 1.5, project no. ECS00000043, CUP: E63C22001030007) [add any project funding personal research within teamx]. The data are archived at [name of data repository] and are accessible at [URL/DOI of data product].

 

Files

Lidar_RawData.zip

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Additional details

Related works

Is described by
Other: https://sites.google.com/unitn.it/decipherproject/home-page (URL)

Funding

Ministero dell'università e della ricerca
PRIN2022 - DECIPHER 2022NEWP4J
Agenzia Spaziale Italiana
SPACE IT UP I53D24000060005
Ministero dell'università e della ricerca
iNest - Interconnected Nord-Est Innovation Ecosystem ECS00000043

References

  • Doglioni G, Barbano F, Barbaro E, Bracci A, Brun C, Cairns WRL, Carpentari S, Cassiani M, Conen F, Cozzi G, Di Felice Fabrizi C, Di Liberto L, Di Girolamo P, Dionisi D, Di Paolantonio M, Di Sabatino S, Einbock A, Finco A, Gerosa G, Giovannini L, Marzuoli R, Nardon C, Njimongbet A, Pasqualini F, Philippot N, Plebani D, Poggi D, Porcù F, Rajput A, Rossetti C, Sankar MS, Summa D, Dallo F, Biasuzzi B, Gianessi S, Vendrame N, Zardi D. Disentangling mechanisms controlling atmospheric transport and mixing processes over mountain areas at different space- and timescales - the field campaign of the project DECIPHER. Submitted to BAMS