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Ilya Rivin
and
Eli Tziperman

Abstract

The sensitivity of long-term averaged air–sea fluxes calculated by a 3D atmospheric general circulation model to SST perturbations of an idealized spatial structure is investigated as a function of the SST perturbation amplitude, spatial scale, latitude, and season. This sensitivity is a dominant, yet largely unknown, parameter determining the stability and variability behavior of ocean-only model studies of decadal climate variability.

The air–sea heat-flux anomaly induced by the SST perturbation varies linearly with respect to the SST perturbation amplitude in a wide range of perturbation amplitudes (±3°C). The implied restoring time of the nonglobal SST perturbations by the air–sea fluxes is found to vary from 1.5 to 3 months (for a 50-m oceanic mixed layer and perturbation scale of less than 3.4 × 106 m) depending on the spatial scale, latitude, and season of the SST anomaly. The calculated restoring time for global perturbation is of the order of two years, and the latent heat flux is found to be the air–sea heat-flux component most sensitive to SST perturbations. Both longwave and shortwave radiative fluxes are much less sensitive than latent and sensible turbulent fluxes for nonglobal SST anomalies.

The restoring time is found to be significantly longer for large-scale anomalies than for the small-scale ones, because of the dominant effect of the heat advection by wind over small perturbations. No significant difference is found between the restoring times for SST perturbations in midlatitudes and in the Tropics. SST perturbations are dissipated faster by the air–sea fluxes during the winter than during the summer. The air–sea freshwater flux anomaly is also found to strongly depend on the SST perturbation amplitude, and to vary almost linearly with the SST perturbation in the midlatitudes, but in a nonlinear way in the Tropics. The possible model dependence of the calculated restoring times is analyzed.

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Ilya Rivin
and
Eli Tziperman

Abstract

Recent studies of decadal/interdecadal climate variability suggested two main classes of mechanisms: self-sustained (supercritical) oscillations due to the internal nonlinearity of the ocean and linear (subcritical) thermohaline oscillations driven by stochastic atmospheric forcing. The authors use a coupled ocean–atmosphere meridional box model to carefully examine these two alternatives. It is shown that a weakly nonlinear relation between the north–south density gradient in the ocean and the meridional ocean transport can lead to self-sustained oscillations. A nonlinear relation between the SST and the air–sea heat flux can also lead to self-sustained oscillations, although indications are given that the air–sea heat flux depends linearly on the SST for a wide range of SST perturbations. It is thus concluded that, if interdecadal climate variability is due to self-sustained oscillations, the necessary nonlinearity must be related to internal ocean dynamics rather than to the air–sea interaction or to nonlinear atmospheric dynamics. The box model results are used to discuss a simple criterion, based on the probability distribution function of the meridional circulation time series, for differentiating between self-sustained and linear variability. This criterion could not rule out either the linear or nonlinear hypotheses for the thermohaline variability in the GFDL coupled general circulation model run of Delworth, Manabe, and Stouffer. This may indicate that the variability in the coupled general circulation model is near critical.

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Zulema D. Garraffo
,
Hae-Cheol Kim
,
Avichal Mehra
,
Todd Spindler
,
Ilya Rivin
, and
Hendrik L. Tolman

Abstract

In this study, results are presented from the first operational ocean tracer dispersion model operated by the National Oceanic and Atmospheric Administration/National Weather Service/National Centers for Environmental Prediction (NOAA/NWS/NCEP). This study addresses the dispersion of radionuclide contaminants after the Fukushima–Daiichi nuclear accident that was triggered by the 11 March 2011 earthquake and tsunami. The tracer capabilities of the Hybrid Coordinate Ocean Model (HYCOM) were used in a regional domain for the northwestern Pacific, with nesting lateral boundary conditions using daily nowcast–forecast fields from the global operational Real-Time Ocean Forecast System (RTOFS-Global), a ° HYCOM global forecast from NCEP, based on data-assimilative ° HYCOM Global Ocean Forecast System (GOFS) analyses from the Naval Research Laboratory/Naval Oceanographic Office (NRL/NAVOCEANO). This regional model, RTOFS Episodic Tracers for a region of the North West Pacific (RTOFS-ET_WPA), was in operation until the beginning of 2014, when the simulated 137Cs concentration was very close to the background level in the Pacific before the accident, which was about 2 Becquerel m−3 [Bq; 1 Becquerel = 1 (nuclear decay) s−1].

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Ling Liu
,
Avichal Mehra
,
Daryl Kleist
,
Guillaume Vernieres
,
Travis Sluka
,
Kriti Bhargava
,
Patrick Stegmann
,
Hyun-Sook Kim
,
Shastri Paturi
,
Jiangtao Xu
, and
Ilya Rivin

Abstract

Realistic ocean initial conditions are essential for coupled hurricane forecasts. This study focuses on the impact of assimilating high-resolution ocean observations for initialization of the Modular Ocean Model (MOM6) in a coupled configuration with the Hurricane Analysis and Forecast System (HAFS). Based on the Joint Effort for Data Assimilation Integration (JEDI) framework, numerical experiments were performed for the Hurricane Isaias (2020) case, a category-1 hurricane, with use of underwater glider datasets and satellite observations. Assimilation of ocean glider data together with satellite observations provides opportunity to further advance understanding of ocean conditions and air–sea interactions in coupled model initialization and hurricane forecast systems. This comprehensive data assimilation approach has led to a more accurate prediction of the salinity-induced barrier layer thickness that suppresses vertical mixing and sea surface temperature cooling during the storm. Increased barrier layer thickness enhances ocean enthalpy flux into the lower atmosphere and potentially increases tropical cyclone intensity. Assimilation of satellite observations demonstrates improvement in Hurricane Isaias’s intensity forecast. Assimilating glider observations with broad spatial and temporal coverage along Isaias’s track in addition to satellite observations further increase Isaias’s intensity forecast. Overall, this case study demonstrates the importance of assimilating comprehensive marine observations to a more robust ocean and hurricane forecast under a unified JEDI–HAFS hurricane forecast system.

Significance Statement

This is the first comprehensive study of marine observations’ impact on hurricane forecast using marine JEDI. This study found that assimilating satellite observations increases upper-ocean stratification during the prestorm period of Isaias. Assimilating preprocessed observations from six gliders increases salinity-induced upper ocean barrier layer thickness, which reduces sea surface temperature cooling and increases enthalpy flux during the storm. This mechanism eventually enhances hurricane intensity forecast. Overall, this study demonstrates a positive impact of assimilating comprehensive marine observations to a successful ocean and hurricane forecast under a unified JEDI–HAFS hurricane forecast system.

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