Sea Turtles for Ocean Research and Monitoring: Overview and Initial Results of the STORM Project in the Southwest Indian Ocean

Abstract

Surface and sub-surface ocean temperature observations collected by sea turtles (ST) during the first phase (Jan 2019-April 2020) of the Sea Turtle for Ocean Research and Monitoring (STORM) project are compared against in-situ and satellite temperature measurements, and later relied upon to assess the performance of the Glo12 operational ocean model over the west tropical Indian Ocean. The evaluation of temperature profiles collected by STs against collocated ARGO drifter measurements show good agreement at all sample depths (0-250 m). Comparisons against various operational satellite sea surface temperature (SST) products indicate a slight overestimation of ST-borne temperature observations of ∼0.1 • ± • 0.6 • that is nevertheless consistent with expected uncertainties on satellite-derived SST data. Comparisons of ST-borne surface and subsurface temperature observations against Glo12 temperature forecasts demonstrate the good performance of the model surface and subsurface (<50 m) temperature predictions in the West tropical Indian Ocean, with mean bias (resp. RMS) in the range of 0.2 • (resp. 0.5-1.5 • ). At deeper depths (>50 m), the model is, however, shown to significantly underestimate ocean temperatures as already noticed from global evaluation scores performed operationally at the basin scale. The distribution of model errors also shows significant spatial and temporal variability in the first 50 m of the ocean, which will be further investigated in the next phases of the STORM project.

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 1: Overview and Observing Component of the Research Project RENOVRISK-CYCLONE

“…STs released from Réunion Island principally swam at (or slightly below) the surface (~50% of the time) and near the bottom of the ocean mixed layer (OML, ~25% of the time). They were found to dive up to 100 times a day, sometimes up to 350 m, allowing the collection of numerous hydrographic profiles within and far below the OML [9]. The analysis of data collected during the first year of this experiment has confirmed the great potential of this approach for sampling the vertical structure of the ocean, validating ocean models and spaceborne sensors, as well as to investigate the intra-seasonal variability of the tropical Indian Ocean [9].…”

“…Despite these important advances, additional efforts are still needed to accurately predict and characterize the potential impacts of tropical cyclones on a given territory, especially during landfall. Such efforts include, for instance, the collection of novel atmospheric and oceanic observations, to better constrain (and verify) the performance of coupled NWP systems [9,10], as well as the implementation of wave models and specific microphysical parameterizations to improve roughness, swell, wind speed, and momentum flux representation in TC forecasting systems [11][12][13].…”

Impact of Tropical Cyclones on Inhabited Areas of the SWIO Basin at Present and Future Horizons. Part 2: Modeling Component of the Research Program RENOVRISK-CYCLONE

“…For the atmosphere, the Meso-NH research model (http://mesonh.aero.obs-mip.fr/, accessed on 27 May 2021) [37] or the AROME French operational model [38,39] can be used. Meso-NH is the non-hydrostatic mesoscale atmospheric model of the French research community.…”

“…Over the SWIO, AROME operates with a 2.5 km grid mesh over a 1600 × 900 points domain and 90 stretched vertical levels. In its operational version, it is coupled to a 1D ocean mixed layer model [41], and at initialization, an Analysis Incremental Update (IUA) scheme [42] is used to combine ECMWF large-scale analysis and AROME-OI forecast in order to reduce spin up time [39]. In its research version, it can be equipped with a 3D-Var assimilation scheme and it has the capability to be coupled to a full 3D ocean.…”

“…NEMO temperature profiles forecasted from the three model runs encompassing this 4-day period (HR1-3) were extracted at the same time at the grid point closest to the observations. Knowing that sea turtles move at most 2 to 3 km per hour [39], one can thus consider that all sea turtles data used to reconstruct a given vertical profile are collected within the same NEMO column (1/12 • horizontal resolution). As expected, the SST in the vicinity of the TC core is found to decrease significantly during the investigated 72-h intensification period of the storm.…”