de.hamburg.icdc/amd.de.fval/kit.dlidCSM01.l2.wind-gust_1 en SAMD v2.2, https://doi.org/10.25592/uhhfdm.9902 FESSTVAL fval_kit_dlidCSM01_l2_wind-gust_1 Doppler lidar wind and gust data from FESSTVAL 2021, Level2 (uzk) at Birkholz DOI:10.25592/uhhfdm.11227 Steinheuer, Julian; Löhnert, Ulrich Institute for Geophysics and Meteorology, University of Cologne, Cologne, Germany CF-1.7 where applicable external NETCDF4 de 2.8 daily 1 This data is subject to the FESSTVaL data policy to be found at https://doi.org/10.25592/uhhfdm.9890 and in the SAMD Observation Data Product Standard https://doi.org/10.25592/uhhfdm.9902. Level 1 files have been created by Deutscher Wetterdienst, Meteorologisches Observartorium Lindenberg (info@dwd.de) Institute of Geophysics and Meteorology, University of Cologne Julian Steinheuer Julian.Steinheuer@uni-koeln.de 2021-08-10 2021-08-31 600 none 42.48 Birkholz: 52.200 °N, 14.192 °E This is the Level2uzk data at Birkholz of the data set that is described in this documentation: The data set contains two wind products: (i) vertical profiles of the mean wind vector and (ii) vertical profiles of wind gusts. The data set is based on Doppler Lidar (DL) measurements and it is available for three different supersites (Falkenberg, Lindenberg, Birkholz) operated during the Field Experiment on Sub-mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) covering the period May 17, 2021, to August 31, 2021. For quality assurance purposes, an intercomparison experiment of the eight DL systems participating in FESSTVaL was organized in Falkenberg between July 16 and August 09, 2021. This implies that no DL wind_and_gust products are available for the Lindenberg and Birkholz sites during this period. The comparison experiment in Falkenberg included operation of DLs in the system configuration applied to determine gusts (see below) – thus for this site the wind_and_gust product is available also for the period July 29 to August 09, 2021. Note that two additional wind and gust products are available for which a separate description is given: (a) profiles based on ultrasonic anemometer measurements at the 99m tower at the Grenzschichtmessfeld (GM) Falkenberg, and (b) profiles from the same lidar measurements but derived using a different retrieval algorithm (level2uzk). DL profiles extend throughout the lower atmospheric boundary layer from 90m up to a maximum height typically above 1500 m dependent on the atmospheric backscatter conditions. The DL measurements were based on a conically Doppler lidar scanning geometry with high temporal resolution (~3.4s for one full scan, azimuth resolution of approx. ~33 deg) and a constant zenith angle of 28 deg. The realization of such a scanning strategy was possible via the continuous scan mode option of the DL system with a number of accumulated pulses per beam Npa = 3000. Two different types of Halo Photonics DL systems were used at the three sites during the campaign: (i) a Halo Photonics Streamline XR with a range gate length of 48 m and Halo Photonics Streamline with a range gate length of 30 m. For the non-XR systems the focus was set to 500 m, for XR systems it is set to infinity per default. For more details concerning the scan configuration see also Steinheuer et al. ( https://doi.org/10.5194/amt-15-3243-2022). In total there are three DL data subsets provided (Level1, Level2dwd, Level2uzk): Level-2 data represent 10-min averages of the derived mean wind vector and of wind gust speeds. Usually, gusts are defined as a 3s moving average (WMO, https://library.wmo.int/doc_num.php?explnum_id=10616). We try to match this by calculating first for each scan (sampling time 3.4 s) a wind estimate and then we search for the maximum value (= gust) within a pre-defined 10min interval. The gust is provided if at least 50% of the individual scans within the 10 minutes have been processed. The Level2uzk dataset contains results based on the Uni Cologne processing (see Steinheuer et al., https://doi.org/10.5194/amt-15-3243-2022; and see https://github.com/JSteinheuer/DWL_retrieval). All data are organized in daily files. The original measurements cover the lower 2600m (non-XR systems) / 4200m (XR systems) above ground level. However, depending on the signal quality and the results of the product’s quality assurance, the availability of reliable data in this lower part of the atmospheric boundary layer may be limited to lower heights. Due to configuration changes, system updates or location changes, there are single days for which the data are either missing or not complete. Operational decisions on the measurement strategy during FESSTVaL and the availability of the instruments led to different measurement tasks of the DL systems during the experiment which implies that the data products at each site originate from different systems during sub-periods of the experiment. The quality control procedures implemented for the level2uzk product omits an assessment of the signal-to-noise ratio of the backscattered lidar signal (snr), but are instead based on statistical coherence. This involves fitting a wind vector to the radial observations and iteratively eliminating outliers that are inconsistent with the fit. The iteration stops when the fit have small uncertainties (wind is returned) or too many rejected observations (no wind is returned). The amount of included observations and the quality of the fit is combinend to a covariance matrix for the wind vector describing the uncertainty of each estimate. Please check Steinheuer et al., https://doi.org/10.5194/amt-15-3243-2022 for a detailed description. Reliability of both the derived mean wind and the gust wind speeds has been assessed by comparison with the sonic wind and gust product data at a reference level of 90 m for a several-months data set. Rmsd values are in the order of 0.3 m/s for the mean wind speed, and 0.7 m/s for the maximum gust speed, respectively. HALO Photonics Doppler lidar (system_id: 161 XR) 52.2 14.192 70 none none

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2022 Steinheuer, Julian none https://doi.org/10.5194/amt-15-3243-2022 Short term observations Local observations Supersites RAO 144 101 2 3 3 lat () latitude degrees_north lon () longitude degrees_east zsl () altitude m time ('time',) time time seconds since 1970-01-01 00:00:00 height ('height',) height vertical distance from sensor m height_corg ('height',) height mask for the center of range gates heights 1 time_bnds ('time', 'nv') time boundaries u ('time', 'height') eastward_wind eastward wind m s-1 v ('time', 'height') northward_wind northward wind m s-1 w ('time', 'height') upward_air_velocity upward air velocity m s-1 u_max ('time', 'height') eastward wind of gust m s-1 u_min ('time', 'height') eastward wind of weakest wind m s-1 v_max ('time', 'height') northward wind of gust m s-1 v_min ('time', 'height') northward wind of weakest wind m s-1 w_min ('time', 'height') upward air velocity of weakest wind m s-1 wspeed ('time', 'height') wind_speed wind speed m s-1 wspeed_max ('time', 'height') wind speed of gust m s-1 wspeed_min ('time', 'height') wind speed of weakest wind m s-1 wdir ('time', 'height') wind_from_direction wind direction ° wdir_max ('time', 'height') wind direction of wind gust ° wdir_min ('time', 'height') wind direction of weakest wind ° covariances ('time', 'height', 'row', 'col') covariances of wind m2 s-2 covariances_max ('time', 'height', 'row', 'col') covariances of gust m2 s-2 covariances_min ('time', 'height', 'row', 'col') covariances of weakest wind m2 s-2 sd_wspeed ('time', 'height') standard deviation of wind speed m s-1 sd_wspeed_max ('time', 'height') standard deviation of wind gust speed m s-1 sd_wspeed_min ('time', 'height') standard deviation of weakest wind m s-1