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.

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 ± 0.04 m/s, mean ± 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.

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.