Javascript must be enabled to continue!
Thermohaline response of the upper ocean to tropical cyclones. Observations and modelling.
View through CrossRef
<p><span>An</span> impact of <span>the</span> upper <span>ocean response</span> to tropical cyclones (TC) is usually <span>considered</span> <span>as</span> a negative feedback mechanism between cooling of the mixed layer (ML) and intensity of a TC. <span>Influence of</span> TCs <span>on</span> the upper ocean is manifested as <span>anomalies</span> in sea surface temperature (SST) and sea surface salinity (SSS) <span>in wakes of hurricanes, that can vary significantly along tracks of TCs (Reul et al. 2021). Proper modelling of ML dynamics is still vital to explain surface cooling observed in satellite and in situ data. Although numerous models of the ML evolution have been developed (e.g., Zilitinkevich et al. 1979, Gillian et al. 2020, and works cited therein including many schemes incorporated in numerical models), there is still a controversy as to turbulent closure schemes and simplified approaches that could allow for a quick and high quality assessment of ML parameters.</span></p><p>The purpose of the <span>this work</span> is to apply a simplified model of the upper ocean response to TCs suggested by Kudryavtsev et al. 2019 with barotropic and baroclinic modes resolved. To describe ML dynamics, <span>results of Zilitinkevich and Esau (2003) are applied.</span> The cases studied are those of hurricanes passing over the Amazon-Orinoco river plume: Igor (Reul et al. 2014), Katia (Grodsky et al. 2012) and Irma (Balaguru et al. 2020).</p><p>Best track parameters of the TCs are obtained from the IBTrACKS archive. Multi-source GHRSST data on SST as well as SMOS and SMAP satellite data on SSS are used to compare the observed ocean responses to the simulated ones. ISAS20 in situ archive data are used to provide vertical profiles of temperature and salinity as an input to the model. Precipitation and evaporation data are obtained from TRMM measurements and ERA5 reanalysis, respectively. Subsets of IBTrACKS, GHRSST, ISAS20, TRMM and ERA5 data specific to domain of a TC&#8217;s wake were produced by the Centre de Recherche et d'Exploitation Satellitaire (CERSAT), at IFREMER, Plouzane (France) for ESA funded project MAXSS (Marine Atmosphere eXtreme Satellite Synergy). Model simulations are consistent with the observations and provide a deeper insight in the physics of relationship between SST and SSS anomalies in TC wakes. On the basis of analysis of the observations and model results, a semi-empirical expressions to predict SSS and SST anomalies using TC parameters (radius, wind speed and translation velocity) and prestorm stratification are suggested.</p><p>The work was supported by the Russian Science Foundation through the Project No. 21-47-00038, by Ministry of Science and Education of the Russian Federation under State Assignment No. 0555-2021-0004 at MHI RAS, and State Assi<span>gnment No. 0763-2020-0005 at RSHU (P.P. and V.K.). T</span><span>he ESA/MAXSS project support is also gratefully acknowledged (N.R. and B.C.).</span></p>
Title: Thermohaline response of the upper ocean to tropical cyclones. Observations and modelling.
Description:
<p><span>An</span> impact of <span>the</span> upper <span>ocean response</span> to tropical cyclones (TC) is usually <span>considered</span> <span>as</span> a negative feedback mechanism between cooling of the mixed layer (ML) and intensity of a TC.
<span>Influence of</span> TCs <span>on</span> the upper ocean is manifested as <span>anomalies</span> in sea surface temperature (SST) and sea surface salinity (SSS) <span>in wakes of hurricanes, that can vary significantly along tracks of TCs (Reul et al.
2021).
Proper modelling of ML dynamics is still vital to explain surface cooling observed in satellite and in situ data.
Although numerous models of the ML evolution have been developed (e.
g.
, Zilitinkevich et al.
1979, Gillian et al.
2020, and works cited therein including many schemes incorporated in numerical models), there is still a controversy as to turbulent closure schemes and simplified approaches that could allow for a quick and high quality assessment of ML parameters.
</span></p><p>The purpose of the <span>this work</span> is to apply a simplified model of the upper ocean response to TCs suggested by Kudryavtsev et al.
2019 with barotropic and baroclinic modes resolved.
To describe ML dynamics, <span>results of Zilitinkevich and Esau (2003) are applied.
</span> The cases studied are those of hurricanes passing over the Amazon-Orinoco river plume: Igor (Reul et al.
2014), Katia (Grodsky et al.
2012) and Irma (Balaguru et al.
2020).
</p><p>Best track parameters of the TCs are obtained from the IBTrACKS archive.
Multi-source GHRSST data on SST as well as SMOS and SMAP satellite data on SSS are used to compare the observed ocean responses to the simulated ones.
ISAS20 in situ archive data are used to provide vertical profiles of temperature and salinity as an input to the model.
Precipitation and evaporation data are obtained from TRMM measurements and ERA5 reanalysis, respectively.
Subsets of IBTrACKS, GHRSST, ISAS20, TRMM and ERA5 data specific to domain of a TC&#8217;s wake were produced by the Centre de Recherche et d'Exploitation Satellitaire (CERSAT), at IFREMER, Plouzane (France) for ESA funded project MAXSS (Marine Atmosphere eXtreme Satellite Synergy).
Model simulations are consistent with the observations and provide a deeper insight in the physics of relationship between SST and SSS anomalies in TC wakes.
On the basis of analysis of the observations and model results, a semi-empirical expressions to predict SSS and SST anomalies using TC parameters (radius, wind speed and translation velocity) and prestorm stratification are suggested.
</p><p>The work was supported by the Russian Science Foundation through the Project No.
21-47-00038, by Ministry of Science and Education of the Russian Federation under State Assignment No.
0555-2021-0004 at MHI RAS, and State Assi<span>gnment No.
0763-2020-0005 at RSHU (P.
P.
and V.
K.
).
T</span><span>he ESA/MAXSS project support is also gratefully acknowledged (N.
R.
and B.
C.
).
</span></p>.
Related Results
The Dynamics of Jupiter’s Polar Cyclones
The Dynamics of Jupiter’s Polar Cyclones
The poles of Jupiter are hidden from the view of Earth-orbiting and solar-plane satellites. In 2016, the arrival of the Juno spacecraft into a pole-to-pole orbit around Jupiter pro...
Access impact of observations
Access impact of observations
The accuracy of the Copernicus Marine Environment and Monitoring Service (CMEMS) ocean analysis and forecasts highly depend on the availability and quality of observations to be as...
Tropical and mediterranean cyclones in the IPSL climate model : tracking & assessment
Tropical and mediterranean cyclones in the IPSL climate model : tracking & assessment
Cyclones tropicaux et méditerranéens dans le modèle de climat de l'IPSL : détection et évaluation
Les tempêtes font partie des désastres qui font le plus de dégâts ...
Bencana Badai Siklon Tropis Di Indonesia
Bencana Badai Siklon Tropis Di Indonesia
Tropical cyclones are powerful storms. Usually the average radius is around 150-200km. This tropical cyclone is formed above the sea where the sea water temperature is warm, more t...
Impact of the Ocean-Atmosphere coupling on extratropical cyclones around the Mediterranean basin
Impact of the Ocean-Atmosphere coupling on extratropical cyclones around the Mediterranean basin
The Mediterranean basin is well recognized as one of the main climate change hotspots; besides, this region is one the most active cyclogenetic area of the Northern Hemisphere with...
Vorticity-gradient forces and a center-of-mass approach explain the mean and oscillatory motion of Jupiter's polar cyclones.
Vorticity-gradient forces and a center-of-mass approach explain the mean and oscillatory motion of Jupiter's polar cyclones.
The polar cyclones on Jupiter have been observed regularly since their discovery by the Juno mission in 2016. While the symmetrically spaced 9 and 6 cyclones at Jupiter's north and...
The effects of warm and cold core eddy processes on cyclone activity
The effects of warm and cold core eddy processes on cyclone activity
<p>It is a well-established that the Tropical Cyclones (TC) often fuel from the thermal energy stored in the ocean top layer. As the ocean mixed layer temperature is ...

