Study area

With a surface area of 368 km2 and a water volume of 49 km3, Lake Garda is one of the largest lakes of the Alpine region and the largest in Italy. It is located in the northern part of the country (center at 45° 40′N and 10° 40′E), at the foot of the Alps (Fig. 1a). Its bathymetry is heterogeneous, being characterized by a narrow (average width 4 km) and deep (maximum depth 350 m) northern trunk enclosed between steep mountains, connected to a southern larger (maximum width 18 km) and shallower (average depth 65 m) basin lying in a flat plain. The lake has one main tributary, the Sarca River at the northernmost edge, and one emissary, the Mincio River at the southern shore. Owing to its large volume and relatively small inflow and outflow rates, the residence time is about 27 years, which is long compared to the other large sub-alpine lakes50.

Figure 1 (a) Bathymetry of Lake Garda and topography of the surrounding region, with the location of Lake Garda in Northern Italy (inset), the reference transect with the monitoring stations (zoom-in view), and the meteorological (M1 and M2) and ARPAV monitoring (L) stations used in the analysis (black triangles and square, respectively). Vertical profiles of temperature (b) and conductivity at 20 °C (c) measured at the L station by ARPAV between March and April 2017 using a SBE-19plus SEACAT profiler. Full size image

The typical winds are characterized by coupled lake-valley breezes especially during warm-season clear-sky days51, while one-directional synoptic flows are frequent in wintertime often generating intense and long-lasting north-Föhn events52. In both seasons, winds in the northern part are predominantly directed along the major axis of the lake, due to the steep surrounding topography53.

The knowledge of the circulation in the lake is still at a first stage and current measurements are not available, but a preliminary modeling exercise54 provided a first description of the lake’s seasonal response to typical winds and suggested that Earth’s rotation could possibly affect transport processes in the lake.

The mixing regime of Lake Garda is classified as oligomictic with prolonged periods of incomplete mixing interspersed with occasional complete DMEs that involve the entire water column20,55. The temperature of the water is always above the temperature of maximum density, so that thermobaric effects56 do not affect the mixing regime of the lake. Salinity is low and its vertical gradients are small, thus playing secondary effects on the stability of the water column. A climate-induced change on DMEs has already been detected in the lake57. Complete (i.e., down to the bottom) buoyancy-driven convective DMEs were typically observed following particularly harsh winters causing surface cooling, the last event dating back to 2006. Since then, water temperature underwent a progressive increase along the whole water column, preventing the occurrence of significant convective DMEs.

However, the full (i.e., down to the bottom) vertical profiles measured by the Environmental Protection Agency of the Veneto Region (ARPAV) between March and April 2017 (Fig. 1b,c) suggest the existence of wind-driven flows as an additional, previously not recognized, ventilation mechanism. Visible warming of deep water down to 250 m depth accompanied by decrease in conductivity indicates that DMEs occurred after March 2017 and were most likely driven by the wind. In fact, the formation of progressively steeper profiles is not compatible with diffusive processes alone, while positive net heat flux to the lake after March (see Fig. S1 in the Supplementary Information) excludes the occurrence of buoyancy-driven DMEs. Building on this premise and expanding on the mentioned preliminary modeling analysis54, in the ensuing sections we provide evidence that wind-driven DMEs occur in Lake Garda and that these flows are modified by Earth’s rotation.

Field campaign

Beginning in March 2017, a two-year monitoring program was established in Lake Garda58. As part of the monitoring activity, monthly high-resolution profiles of temperature and chlorophyll-a (besides other physical and turbulence related quantities) were measured with a loosely tethered, free-falling turbulence and CTD microprofiler (MicroCTD, Rockland Scientific International, RSI, Canada). The instrument is configured with a downward profiling speed of 0.7 ms−1 and has a maximum operational depth of 100 m. The thermistor and chlorophyll-a fluorometer (JFE-Advantech Sensors) have an accuracy of 0.01 °C and <1 ppb, a resolution of 0.001 °C and 0.01 ppb, and a sampling rate of 64 Hz and 512 Hz, respectively.

Three reference stations were selected during the monitoring campaign: Central Station (CS), located in the center of the narrow trunk at about 4 km from the northern edge of the lake, and two additional reference stations on the east (East Station, ES) and west (West Station, WS) sides of the CS. The three stations are aligned along a transect where the lake is ~2.5 km wide (Fig. 1a). Here we analyze the vertical profiles measured at the three monitoring sites after three significant synoptic northerly wind events on 10 March, 21 April, and 7 August 2017. All downcast profiles were taken at the same time of day, between 10:00 and 13:00 CET.

Wind speed and direction data were obtained from the meteorological stations operated by the Regional Meteorological Service of the Environmental Protection Agency of the Lombardia Region (ARPA Lombardia, Fig. 2). We analyzed the time series of wind speed measured at Limone del Garda and Toscolano-Maderno, respectively site M1 and M2 in Fig. 1a. Specifically, Limone del Garda (M1) was chosen as reference station, as it is located ~6 km south of the reference transect and 200 m from the shore.

Figure 2 (a,b) Time series of wind speed component along the major axis of the lake (oriented about 30°E) measured at the meteorological stations in Limone del Garda-M1 (a) and Toscolano-Maderno-M2 (b, see Fig. 1a for M1 ans M2 stations location). Vertical continuous lines indicate fieldwork days, while vertical dashed lines indicate ARPAV monitoring days. (c–e) Wind roses for the three analyzed periods based on measurements collected at station M1 relative to a three-day period, including the fieldwork day and the two preceding days. Full size image

Numerical modeling

As a complement to in-situ measurements, numerical simulations of atmospheric and lake conditions were performed for the periods 3–11 March, 18–21 April, 1–15 August 2017, according to the field campaign dates (10 March, 21 April, and 7 August 2017).

Meteorological model

High-resolution fields of meteorological data were provided by the Weather Research and Forecasting (WRF) Model59, which was used to prescribe the surface forcing. The event-based simulations were performed according to the meteorological model setup used by60,61 to reproduce thermally-driven circulations in the lake area. The spatial domain covered the whole Lake Garda region and was composed of three two-way nested domains with 94 × 90, 112 × 97, and 73 × 106 cells, and grid spacing of 9, 3, and 1 km, respectively; 30 levels were used along the vertical. Initial and boundary conditions were provided by the 6-hourly National Centers for Environmental Prediction (NCEP) Final Operational Global Analysis data on 1-degree grids. The land use was defined from the Corine Land Cover dataset, having a spatial resolution of 100 m (provided by the European Environment Agency, http://www.eea.europa.eu). Spatial and temporal fields of the meteorological of the main variables simulated for the last domain (1 km spatial resolution) were saved at a temporal resolution of 15 minutes.

Hydrodynamic model

Lake thermo-hydrodynamics were simulated using the open-source modeling suite Delft3D62. The domain was discretized by a non-uniform, locally-orthogonal curvilinear grid staggered in space with 126 × 446 cells with average resolution of ~10 m, and 100 vertical layers with increasing thickness from 1 m at the surface to 25 m at the bottom. Initial conditions for DELFT3D were set as water at rest, horizontal water level, and spatially uniform vertical temperature profile according to the temporally closest profile measured at CS by the Environmental Protection Agency of the Province of Trento (APPA) (21 March and 5 July 2017, for April and August simulations respectively) or reconstructed from field campaign data (for March simulation). A 2-day spin-up period was shown to be long enough to reasonably remove the influence of initial conditions from hydrodynamic simulations of Lake Garda54, supporting the representativeness of the numerical results. Vertical eddy diffusivity and viscosity of the model were calculated with the k − ε turbulence model. The values of the horizontal viscosities and diffusivities where both set as 0.2 m2 s−1 according to the grid size63 and a preliminary sensitivity analysis. A computational time step of 60 s was used for March and April simulations, and 30 s for August simulation. The value of the main parameters of the model are summarized in Table 1.

Table 1 Hydrodynamic model set-up. Full size table

Tracer experiment

The hydrodynamic simulations described above included numerical tracer experiments. We quantified wind-induced ventilation by analyzing the evolution of a passive tracer initially distributed with constant concentration C surf in the upper 50 m (based on the profiles in Fig. 3), while it was set to 0 mg/l along the remaining of the water column. We instantaneously released the tracer at the beginning of the wind event (t 1 ) and let it be transported by the flow up to time t 2 (see Table 1).

Figure 3 (a–c) Vertical profiles of temperature measured at the three sampling stations (ES, CS, and WS) in the three analyzed periods. (d–f) As in panels (a–c) but for chlorophyll-a. We notice that the depth of vertical profiles here and in Fig. 1 are different. Full size image

The volume V vent (i, t) of surface water ventilated in the deep lake from the beginning of the tracer experiment (time t 1 ) until time t was estimated based on the mass balance of the tracer at each transverse model cross-section i (similar to37)

$${V}_{vent}(i,t)=\frac{{V}_{isopy}(i,t){C}_{isopy}(i,t)}{{C}_{surf}},$$ (1)

where V isopy (i, t) is the volume of water below a reference isopycnal surface at model cross-section i at time t, and C isopy (i, t) is its average tracer concentration. The above mass balance assumes that the tracer concentration of downwelled water is time-invariant and equal to C surf . The isopycnal surface was chosen such that the overall V isopy was relatively small compared to the lake volume in order to be representative of the deep layer when the lake is calm and the isopycnals are horizontal. We chose the isopycnal such that V isopy was about 18% of the lake volume (corresponding to the lake volume below nearly 200 m depth). V isopy showed limited variability during the tracer experiment (±1% of lake volume), thus making it well delimited throughout the simulation.

In order to quantify the wind-induced ventilation in the lake, we calculated the ratio η between the ventilation volume reaching depths below the reference isopycnal surface and V isopy :

$$\eta (i,t)=\frac{{V}_{vent}(i,t)}{{V}_{isopy}(t)},$$ (2)

the sum of which over index i at a given time t can be interpreted as the efficiency of wind-driven ventilation of V isopy at that time.

The tracer experiment was not performed for the wind event on August 2017 since it was not significant for the analysis of deep ventilation due to the strong thermal stratification of the lake in that period.