DOI: 10.5061/dryad.nk98sf7sk
title: Dataset: A multi-site, year-round turbulence microstructure atlas for the deep perialpine Lake Garda

description: This repository includes the dataset described in "A multi-site,
 year-round turbulence microstructure atlas for the deep perialpine Lake
 Garda", Scientific Reports, 2021, DOI:
 10.1038/s41597-021-00965-0 A multi-site, year-round dataset comprising a
 total of 606 high-resolution turbulence microstructure profiles of shear
 and temperature gradient in the upper 100 m depth is made available for
 Lake Garda (Italy). Concurrent meteorological data were measured from the
 fieldwork boat at the location of the turbulence measurements. During the
 fieldwork campaign (March 2017-June 2018), four different sites were
 sampled on a monthly basis, following a standardized protocol in terms of
 time-of-day and locations of the measurements. Additional monitoring
 activity included a 24-h campaign and sampling at other
 sites. Turbulence quantities were estimated, quality-checked, and
 merged with water quality and meteorological data to  produce a
 unique turbulence atlas for a lake. The dataset is open to a wide range of
 possible applications, including research on the variability of turbulent
 mixing across seasons and sites (demersal vs pelagic zones) and driven by
 different factors (lake-valley breezes vs buoyancy-driven convection),
 validation of hydrodynamic lake models, as well as technical studies on
 the use of shear and temperature microstructure sensors.
description: Between March 2017 and June 2018, an extensive turbulence
 monitoring campaign was carried out in Lake Garda (Italy) using a
 free-falling, internally recording microstructure profiler MicroCTD,
 specifically developed by Rockland Scientific International Inc. (RSI) for
 application in lakes, reservoirs and estuaries. Along with
 turbulence-related quantities, CTD (conductivity and temperature) and
 water quality (chlorophyll-a and turbidity) profiles, and meteorological
 data were measured. All vertical profiles were measured down to 100 m
 depth, while meteorological data were collected directly at the fieldwork
 boat (using a Davis Vantage Pro2 6152 meteorological station), providing
 representative weather conditions at the time and location of the
 turbulence measurements. The fieldwork activity was conducted from an
 inflatable rubber motorboat. A Secchi disk (black and white, 20 cm
 diameter) completed the fieldwork boat's onboard equipment, and the
 anecdotal experience of the boat captain enriched the fieldwork
 activity. Four reference sampling sites were
 established in the northern, deep and elongated part of Lake Garda: three
 along a transverse transect where the lake is about 2.5 km wide (West
 Station - WS, Central Station - CS, and East Station - ES), and one in a
 sheltered bay a few kilometers (~4 km) to the south (Limone Station - LS).
 The four sites were sampled on a monthly basis, following a standard
 procedure aimed at minimizing the differences among the monitoring days in
 terms of scheduling of the fieldwork activity (time-of-day and monitoring
 sites sequence). To achieve good statistical significance, a minimum of
 three and up to six vertical profiles were measured at each reference
 site. The monitoring campaign included also other activities, such as an
 intensive 24-hour session in May 2018 (May 7th - 8th), and the occasional
 collection of vertical profiles at additional locations. These sites
 included the deepest point of the lake (Deep Station - DS) and a shallower
 site in the southeast basin, besides occasional profiles in other points
 of the lake (Other Stations - OS). Overall, 606 profiles were
 measured. The microstructure profiler has a length of 1
 m, a maximum operational depth of 100 m and is equipped with turbulence
 and water quality sensors located at the front bulkhead, which is
 protected by a sensor guard. Turbulence properties were measured with two
 microstructure airfoil shear probes and two fast-response temperature
 sensors (type FP07), sampled at high frequency (512 Hz). Water quality
 profiles were measured with a stable and reliable conductivity/temperature
 (CT) sensor and a fluorescence/turbidity (FT) sensor (JFE-Advantech
 Sensors). The sampling rate is 64 Hz for the CT sensor and 512 Hz for the
 FT sensor. Finally, a two-axis vibration sensor (i.e., a pair of
 piezo-accelerometers) sampling at 512 Hz and a two-axis inclinometer
 (pitch and roll angles) sampling at 64 Hz monitored the dynamics of the
 profiler flight. The buoyancy of the micostructure profiler was regulated
 to achieve a downward profiling speed (W) of about 0.75 m/s (specifically,
 W=0.74 <b>±</b> 0.04 m/s, mean <b>± </b>standard
 deviation, based on the entire dataset). This profiling speed is within
 the range recommended for turbulence measurements using shear probes, but
 higher than that typically used when employing fast-response thermistors.
 Here we challenged the use of the latter type of sensors, trying to find a
 compromise to exploit the capabilities of the two types of sensors across
 the wide range of turbulence intensities observed in the lake.
 The processing of the microstructure data was based on the
 scripts provided by RSI (ODAS libraries v4.4), properly modified for the
 specific purposes of the analysis. The data processing workflow is
 described in detail in the manuscript presenting the dataset, which has
 been structured aimed at providing a self-contained, step-by-step
 reference compendium synthesizing the key procedures and the best
 practices available in the literature. For the sake of synthesis, here
 only the main steps are summarized, while we refer the interested reader
 to the manuscript for the full and detailed description of the data
 processing: shear probes and fast-response
 thermistors were converted into physical units knowing the sensitivity of
 the shear probes and the resistance of the FP07 (after calibrating each
 cast against the precise CT sensor); the vertical
 profile was partitioned into 3 m long, 50% overlapping segments. For each
 segment, the frequency spectra of shear and temperature gradient were
 derived by ensemble averaging the fast Fourier transform power spectra
 computed for 1 m long, 50% overlapping subsegments, detrended and Hanning
 tapered; the measured frequency spectrum was
 converted into the corresponding wavenumber spectrum knowing the profiling
 speed and according to the Taylor's frozen turbulence
 hypothesis; the raw microstructure shear signals were
 cleaned by despiking and high-pass filtering, corrected for the probe’s
 spatial response, and denoised removing high-frequency noise due to
 instrument vibrations using the piezo-accelerometers data. Then, the
 resulting shear signals were used to derive the shear power
 spectra; the vertical temperature gradient signals
 were calculated by applying a high-pass filter to the pre-emphasized
 temperature signals, and the corresponding temperature gradient spectra
 were derived. The spectra were then corrected for the frequency response
 of the probes; the despiked and response-corrected
 shear and temperature gradient wavenumber spectra, processed as outlined
 above, were used to calculate vertical profiles of dissipation rates of
 turbulent kinetic energy (TKE) and temperature variance using the
 (empirical) Nasmyth and (theoretical) Kraichnan spectra as reference,
 respectively; all estimates were checked based on a
 number of quality metrics, and a detailed quality screening
 and inter-sensor cross-validation was carried out. 
 The Matlab scripts for estimating TKE and temperature variance
 dissipation rates according to the procedures described in the manuscript
 are provided together with the dataset. Some steps rely on functions
 provided by RSI through the ODAS library. We provided some
 alternatives/suggestions for users not having access to this
 library.
description: The dataset is archived as a collection of raw files and
 processed files. Each file contains the set of vertical profiles measured
 in a monitoring site in a single day, and is identified by an increasing
 ID number. A .csv table summarizing the list of records with the
 associated ID number, measurement date and time, weather conditions,
 Secchi depth, and general notes is provided in the dataset for reference.
 A README file describing the structure and content of the archived files
 is provided together with the dataset. The raw files
 (.P) provided by the instrument are complemented by the instrument
 configuration file (.cfg), which contains comprehensive instrument's
 metadata and probes' calibration parameters needed for independent
 processing of the measured records.  The processed data
 are provided both as NetCDF files (a common, self-describing, portable
 format for scientific data) and as .mat files (a proprietary Matlab data
 format that can also be opened using open-source platforms such as Python,
 R, and GNU Octave). Each processed file contains the turbulence, water
 quality, and physical quantities listed in the file
 List_Variables.xlsx/List_Variables.csv provided in the dataset (same as
 Online-only Table 1 in the manuscript). The archived variables are divided
 into three groups according to their resolution: FAST for data at 512 Hz,
 SLOW for data at 64 Hz, and BINNED for quantities computed over 3 m
 segments. For a given vertical microstructure profile, each group of
 variables is saved in a separate NetCDF file (for a total of 606 profiles
 x 3 groups = 1818 NetCDF files). As for .mat files, each group of
 variables is stored as an independent structure in the same vertical
 profile file (for a total of 606 .mat files). The meteorological records
 (METEO) merge the data from the on-board thermo-hygrometer and
 meteorological station, and are also provided as NetCDF and .mat
 files. The extensive microstructure dataset collected
 in Lake Garda is open to a wide range of possible
 applications including: characterization
 of the turbulence structures driven by different external factors (typical
 alternating lake-valley breezes, strong northerly Föhn wind events, winter
 frosts due to cold atmospheric fronts); in-depth
 insights on the lateral heterogeneity of turbulence (thanks to the
 systematic sampling along a lateral transect);
 investigation of the spatial heterogeneity of weather conditions
 over the lake (thanks to spatially distributed meteorological data
 acquired at the fieldwork boat); tuning of parameters
 in turbulence closures for numerical models; better
 understanding the performance of airfoil shear probes and fast-response
 thermistors when measuring turbulence quantities varying over several
 orders of magnitude (e.g., frequency response correction of fast-response
 thermistors); advance in general open questions in
 observational turbulence estimates in natural waters: the range of
 applicability of the length-scale dissipation method as well as the
 variability of turbulent mixing in a broad range of stratification and
 energetic condition.