Swen Jullien

Processes setting the characteristics of sea surface cooling induced by tropical cyclones

[1] A 1/2° resolution global ocean general circulation model is used to investigate the processes controlling sea surface cooling in the wake of tropical cyclones (TCs). Wind forcing related to more than 3000 TCs occurring during the 1978–2007 period is blended with the CORE II interannual forcing, using an idealized TC wind pattern with observed magnitude and track. The amplitude and spatial characteristics of the TC-induced cooling are consistent with satellite observations, with an average cooling of � 1°C that typically extends over 5 radii of maximum wind. A Wind power index (WPi) is used to discriminate cooling processes under TCs with high-energy transfer to the upper ocean (strong and/or slow cyclones) from the others (weak and/or fast cyclones). Surface heat fluxes contribute to � 50 to 80% of the cooling for weak WPi as well as away from the cyclone track. Within 200 km of the track, mixing-induced cooling increases linearly with WPi, explaining � 30% of the cooling for weak WPis and up to � 80% for large ones. Mixing-induced cooling is strongly modulated by pre-storm oceanic conditions. For a given WPi, vertical processes can induce up to 8 times more cooling for shallow mixed layer and steep temperature stratification than for a deep mixed layer. Vertical mixing is the main source of rightward bias of the cold wake for weak and moderate WPi, but along-track advection becomes the main contributor to the asymmetry for the largest WPis.

Observation-Based Estimates of Surface Cooling Inhibition by Heavy Rainfall under Tropical Cyclones

Tropical cyclones drive intense ocean vertical mixing that explains most of the surface cooling observed in their wake (the “cold wake”). In this paper, the authors investigate the influence of cyclonic rainfall on the cold wake at a global scale over the 2002–09 period. For each cyclone, the cold wake intensity and accumulated rainfall are obtained from satellite data and precyclone oceanic stratification from the Global Eddy-Permitting Ocean Reanalysis (GLORYS2). The impact of precipitation on the cold wake is estimated by assuming that cooling is entirely due to vertical mixing and that an extra amount of energy (corresponding to the energy used to mix the rain layer into the ocean) would be available for mixing the ocean column in the hypothetical case with no rain. The positive buoyancy flux of rainfall reduces the mixed layer depth after the cyclone passage, hence reducing cold water entrainment. The resulting reduction in cold wake amplitude is generally small (median of 0.07 K for a median 1 K cold wake) but not negligible (>19% for 10% of the cases). Despite similar cyclonic rainfall, the effect of rain on the cold wake is strongest in the Arabian Sea and weak in the Bay of Bengal. An analytical approach with a linearly stratified ocean allows attributing this difference to the presence of barrier layers in the Bay of Bengal. The authors also show that the cold wake is generally a “salty wake” because entrainment of subsurface saltier water overwhelms the dilution effect of rainfall. Finally, rainfall temperature has a negligible influence on the cold wake.

The NOW regional coupled model: Application to the tropical Indian Ocean climate and tropical cyclone activity

This paper presents the NOW regional coupled ocean-atmosphere model built from the NEMO ocean and WRF atmospheric numerical models. This model is applied to the tropical Indian Ocean, with the oceanic and atmospheric components sharing a common 1 =4 horizontal grid. Long experiments are performed over the 1990–2009 period using the Betts-Miller-Janjic (BMJ) and Kain-Fritsch (KF) cumulus parameterizations. Both simulations produce a realistic distribution of seasonal rainfall and a realistic northward seasonal migration of monsoon rainfall over the Indian subcontinent. At subseasonal time scales, the model reasonably reproduces summer monsoon active and break phases, although with underestimated rainfall and surface wind signals. Its relatively high resolution results in realistic spatial and seasonal distributions of tropical cyclones, but it fails to reproduce the strongest observed cyclone categories. At interannual time scales, the model reproduces the observed variability associated with the Indian Ocean Dipole (IOD) and the delayed basin-wide warming/cooling induced by the El Nino Southern Oscillation (ENSO). The timing of IOD occurrence in the model generally matches that of the observed events, confirming the influence of ENSO on the IOD development (through the effect of lateral boundary conditions in our simulations). Although the KF and BMJ simulations share a lot in common, KF strongly overestimates rainfall at all time scales. KF also overestimates the number of simulated cyclones by a factor two, while simulating stronger events (up to 55 m s -1 -1 ). These results could be related to an overly active cumulus parameterization in KF.

Mesoscale SST – Wind Stress coupling in the Peru–Chile Current System: Which mechanisms drive its seasonal variability?

Abstract Satellite observations and a high-resolution regional ocean–atmosphere coupled model are used to study the air/sea interactions at the oceanic mesoscale in the Peru–Chile upwelling current system. Coupling between mesoscale sea surface temperature (SST) and wind stress (WS) intensity is evidenced and characterized by correlations and regression coefficients. Both the model and the observations display similar spatial and seasonal variability of the coupling characteristics that are stronger off Peru than off Northern Chile, in relation with stronger wind mean speed and steadiness. The coupling is also more intense during winter than during summer in both regions. It is shown that WS intensity anomalies due to SST anomalies are mainly forced by mixing coefficient anomalies and partially compensated by wind shear anomalies. A momentum balance analysis shows that wind speed anomalies are created by stress shear anomalies. Near-surface pressure gradient anomalies have a negligible contribution because of the back-pressure effect related to the air temperature inversion. As mixing coefficients are mainly unchanged between summer and winter, the stronger coupling in winter is due to the enhanced large-scale wind shear that enables a more efficient action of the turbulent stress perturbations. This mechanism is robust as it does not depend on the choice of planetary boundary layer parameterization.

Global impact of tropical cyclones on primary production

In this paper, we explore the global responses of surface temperature, chlorophyll, and primary production to tropical cyclones (TCs). Those ocean responses are first characterized from the statistical analysis of satellite data under ~1000 TCs over the 1998–2007 period. Besides the cold wake, the vast majority of TCs induce a weak chlorophyll response, with only ~10% of induced blooms exceeding 0.1 mg m . The largest chlorophyll responses mostly occur within coastal regions, in contrast to the strongest cold wakes that generally occur farther offshore. To understand this decoupling, we analyze a coupled dynamical-biogeochemical oceanic simulation forced by realistic wind vortices applied along observed TC tracks. The simulation displays a realistic spatial structure of TC-induced blooms and its observed decoupling with TC cold wakes. In regions of strong TC energy input, the strongest cold wakes occur in regions of shallow thermocline (<60 m) and the strongest blooms in regions of shallow nitracline and/or subsurface chlorophyll maximum (<60 m). Shallow thermoclines are found over many open ocean regions, while regions of shallow nitracline and/or subsurface chlorophyll maximum are most prominent in near-coastal areas, explaining the spatial decoupling between the cold and bloom wakes. The overall TC contribution to annual primary production is weak and amounts to ~1%, except in a few limited areas (east Eurasian coast, South tropical Indian Ocean, Northern Australian coast, and Eastern Pacific Ocean in the TC-prone region) where it can locally reach up to 20–30%. Nearly 80% of this TC-induced annual primary production is the result of the biogeochemical response to the 30% strongest TCs.

A New Coupled Ocean‐Waves‐Atmosphere Model Designed for Tropical Storm Studies: Example of Tropical Cyclone Bejisa (2013–2014) in the South‐West Indian Ocean

Ocean-Waves-Atmosphere (OWA) exchanges are not well represented in current Numerical Weather Prediction (NWP) systems, which can lead to large uncertainties in tropical cyclone track and intensity forecasts. In order to explore and better understand the impact of OWA interactions on tropical cyclone modeling, a fully coupled OWA system based on the atmospheric model Meso-NH, the oceanic model CROCO, and the wave model WW3 and called MSWC was designed and applied to the case of tropical cyclone Bejisa (2013–2014). The fully coupled OWA simulation shows good agreement with the literature and available observations. In particular, simulated significant wave height is within 30 cm of measurements made with buoys and altimeters. Short-term (< 2 days) sensitivity experiments used to highlight the effect of oceanic waves coupling show limited impact on the track, the intensity evolution, and the turbulent surface fluxes of the tropical cyclone. However, it is also shown that using a fully coupled OWA system is essential to obtain consistent sea salt emissions. Spatial and temporal coherence of the sea state with the 10 m wind speed are necessary to produce sea salt aerosol emissions in the right place (in the eyewall of the tropical cyclone) and with the right size distribution, which is critical for cloud microphysics.