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2.1. Remote Sensing |
The dataset of the satellite observations, used in the study, includes Sea Surface |
Temperature (SST), distributed by the E.U. Copernicus Marine Service (https://www. |
copernicus.eu/, accessed on 5 August 2022), covering the entire study period from 1982 to |
2021 (Table 1). The SST dataset is the Operational SST and Ice Analysis (OSTIA; [44]) global |
SST reprocessed product at 0.05◦ horizontal grid resolution, using in situ and satellite data. |
The satellite-derived data consist of the daily mean gap-free (L4) horizontal fields over the |
South Florida region (Figure 1). The South Florida SST data were used to analyze the SST |
Water 2022, 14, 3840 5 of 28 |
temporal and spatial variability, and to detect the MHWs. Extensive validation of the OSTIA |
product, based on comparisons with ARGO and drifter data, confirmed the good quality |
of the SST fields at the global scale (Quality Information Document (https://catalogue. |
marine.copernicus.eu/documents/QUID/CMEMS-SST-QUID-010-011.pdf, accessed on |
1 October 2022). The performance of the product was also tested in the South Florida |
coastal region with the use of in situ measurements collected by the National Data Buoy |
Center (NDBC; Section 2.2) and is discussed in Section 3.1. |
2.2. Field Observations |
Hourly measurements of SST were derived from three NDBC buoys (Figure 1; Table 1), |
located south of Key West (Buoy SANF1), at a Key Largo coastal region (Buoy MLRF1), and |
at the entrance of Biscayne Bay (Buoy FWYF1). The field observations of SST were used |
to evaluate the performance of the satellite-derived SST fields over different periods and |
coastal areas of South Florida. Air temperature hourly data were also collected at Buoy |
FWYF1 to evaluate the relation between SST and atmospheric temperature anomalies in |
Biscayne Bay and Miami Beach. |
2.3. Meteorological Data |
The meteorological conditions for the study domain and period were derived from |
the ERA5 hourly data on single levels, distributed by the Copernicus Marine Service |
(Table 1). The ERA5 dataset is a fifth-generation European Centre for Medium-Range |
Weather Forecasts (ECMWF) reanalysis that combines model data with observations (data |
assimilation), providing hourly estimates for a large number of atmospheric quantities. |
Herein, we used the meridional and zonal components of the wind at a height of 10 m |
above the sea surface to estimate the variability of the wind speed over the ocean waters of |
South Florida (land values excluded) during the 1982–2021 period. In addition, we also |
used the air temperature at 2 m above the surface, which is produced by the interpolation |
between the lowest model level and the Earth’s surface, taking into account the atmospheric |
conditions. The hourly surface net shortwave solar radiation (QS), the surface net longave |
backcatter radiation (Qb), the surface sensible heat flux (Qh), and the surface latent heat |
flux (Qe) were also collected by the ERA5 dataset to estimate the interannual variability of |
the surface net heat flux (QT; Equation (1)) over the 1982–2021 period. |
QT = QS + Qb + Qe + Qh (1) |
where QS and Qb represent the radiative terms, while the Qh and Qe represent the turbulent |
terms. The ERA5 radiation fields are suitable to evaluate the long-term interannual variability of the heat fluxes over regional basins [45]. The spatial resolution of the atmospheric |
hourly fields is 0.25◦ |
. |
2.4. Hydrodynamic Simulations |
The hydrodynamic simulations are based on the Florida Straits, South Florida, and |
Florida Keys Hybrid Coordinate Ocean Model (FKEYS-HYCOM; Kourafalou and Kang, |
2012) and cover a 9-year period (2012–2020). HYCOM (http://hycom.org, accessed on |
10 October 2022; [46–48]) is a state-of-the-art, three-dimensional hydrodynamic model |
with advanced mixing schemes and employs a flexible (hybrid) vertical coordinate system |
(isopycnal, Cartesian, and sigma discretizations) that is advantageous for the topographically complex study area (Figure 1). FKEYS-HYCOM employs 26 hybrid vertical layers and |
significantly high horizontal resolution of 1/100◦ |
, or 900 m as compared to 1/25◦ |
, 3.6 km |
in the GoM-HYCOM outer model that provides the boundary conditions [49]. The model |
domain covers the area from 78.08◦ W to 84.528◦ W and 22.188◦ N to 27.58◦ N (Figure 1). |
The topography was derived from a high-resolution (1/100◦ |
) regional Gulf of Mexico |
bathymetry developed at the Florida State University/COAPS with a minimum depth of |
1 m. The FKEYS-HYCOM vertical coordinates are maintained in isopycnic mode in the |
“open sea” domain (e.g., Straits of Florida), they smoothly transform to bottom following |
Water 2022, 14, 3840 6 of 28 |
(sigma) and/or Cartesian (fixed z-level) coordinates in the mixed layer, and in the coastal |
and shelf areas (e.g., Florida shelves, northern Cuban coast and shallow banks). Atmospheric forcing is provided by the Navy Global Environmental Model (NAVGEM, [50]). |
The FKEYS-HYCOM has been validated with satellite [26,27] and in situ [51] data, showing |
additional skill in reproducing the circulation patterns and capturing the FC evolution in |
the Straits of Florida. We used the model outputs to derive the FC location in the Straits of |
Florida and evaluate its impact on the coastal SST variability. |
2.5. Detection of Marine Heat Waves |
The study adopts the definition proposed by Hobday et al. [1] to determine the |
MHW events, based on abrupt SST increases above a “climatologic” value (the baseline |
temperature) for a certain time period. This approach has been broadly used to evaluate the |
MHW variability in both global ocean (i.e., [14,52]) and regional basins (i.e., [9,10,12,44,53]). |
To define a baseline temperature, Hobday et al. [1] proposed a period of 30 years, which is |
associated with the time scale variability of ocean drives (e.g., El Nino). Herein, we use a |
longer dataset of 40 years with satellite-derived SST fields (see Section 2.1). According to |
this definition, a MHW is defined as a discrete and prolonged anomalously warm oceanbased event. Hobday et al. [1] also pointed out that a MHW should be defined relative |
to a baseline period and a particular time of the year from which the intensity, duration |
and spatial extent of the MHW could be defined. This also means that a MHW is not just |
limited to the warmer months, since for some biological applications the consideration of |
heatwaves in colder months is essential. The term ‘discrete’ implies that the MHW is an |
identifiable event with clear start and end dates; ‘prolonged’ means that it has a duration |
of at least 5 days. Gaps, between events of two days or less with subsequent five days or |
more, will be considered as a continuous event. ‘Anomalously warm’ means that the water |
temperature is warm compared to the baseline temperature. The baseline temperature |
used in the present study is defined by the seasonal (monthly) varying 90th percentile, |
derived from the 1982–2021 SST data in the resolution (0.05◦ |
) of the South Florida domain. |
Moreover, the duration (the time between the start and end dates; ≥5 days) was also |
computed for all detected MHW events. The intensity of the MHWs was examined based |
on the methodology introduced by Hobday et al. [2]. The goal is to set categories of MHWs |
on multiples of the value represented by the local difference between the climatological |
mean and the 90th percentile baseline, which is the threshold used to identify MHWs. |
Multiples of this local difference will describe different categories of MHWs. Magnitude |
of scale descriptors, defined as moderate (1–2× times, Category 1), strong (2–3× times, |
Category 2), and severe (>3× times, Category 3), can be allocated at each point in space |
and time of an MHW event. |
3. Results |
3.1. Evaluation of Satellite-Derived SST at Coastal Areas |
The quality of the SST fields at coastal areas is tested, based on the comparison with |
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