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Turbulent and radiative exchanges of heat between the ocean and atmosphere (hereafter heat fluxes), ocean surface wind stress, and state variables used to estimate them, are Essential Ocean Variables (EOVs) and Essential Climate V...
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Turbulent and radiative exchanges of heat between the ocean and atmosphere (hereafter heat fluxes), ocean surface wind stress, and state variables used to estimate them, are Essential Ocean Variables (EOVs) and Essential Climate Variables (ECVs) influencing weather and climate. This paper describes an observational strategy for producing 3-hourly, 25-km (and an aspirational goal of hourly at 10-km) heat flux and wind stress fields over the global, ice-free ocean with breakthrough 1-day random uncertainty of 15 W m-2 and a bias of less than 5 W m-2. At present this accuracy target is met only at OceanSITES reference station moorings and research vessels (RVs) that follow best practices. To meet these targets globally, in the next decade, satellite-based observations must be optimized for boundary layer measurements of air temperature, humidity, sea surface temperature, and ocean wind stress. In order to tune and validate these satellite measurements, a complementary global in situ flux array, built around an expanded OceanSITES network of time series reference station moorings, is also needed. The array would include 500 - 1000 measurement platforms, including autonomous surface vehicles, moored and drifting buoys, RVs, the existing OceanSITES network of 22 flux sites, and new OceanSITES expanded in 19 key regions. This array would be globally distributed, with 1 - 3 measurement platforms in each nominal 10° by 10° boxes. These improved moisture and temperature profiles and surface data, if assimilated into Numerical Weather Prediction (NWP) models, would lead to better representation of cloud formation processes, improving state variables and surface radiative and turbulent fluxes from these models. The in situ flux array provides globally distributed measurements and metrics for satellite algorithm development, product validation, and for improving satellite-based, NWP and blended flux products. In addition, some of these flux platforms will also measure direct turbulent fluxes, which can be used to improve algorithms for computation of air-sea exchange of heat and momentum in flux products and models. With these improved air-sea fluxes, the ocean’s influence on the atmosphere will be better quantified and lead to improved long-term weather forecasts, seasonal-interannual-decadal climate predictions, and regional climate projections.
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We apply a one-dimensional mixed layer model, based on second moment closure of turbulence, to study the effects of surface gravity waves on mixing in the oceanic mixed layer. The turbulent kinetic energy injected near the surface...
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We apply a one-dimensional mixed layer model, based on second moment closure of turbulence, to study the effects of surface gravity waves on mixing in the oceanic mixed layer. The turbulent kinetic energy injected near the surface by breaking waves, and the kinetic energy input from Langmuir circulations that may exist in the presence of surface gravity waves, are both parameterized and included in the turbulence model. As expected, the wave breaking elevates both the turbulent kinetic energy and its dissipation rate in the upper few meters, well above the classical values expected from similarity theory for shear layers adjacent to a boundary. While there is a significant impact on mixed layer properties near the surface, wave breaking-induced turbulence decays rapidly with distance from the surface and hence the overall effects on the mixed layer are small. On the other hand, the energy input to turbulence from Langmuir cells elevates the turbulent kinetic energy and mixing throughout the mixed layer, and is therefore more effective in deepening the mixed layer. While the changes in sea surface temperature (SST) brought about by the inclusion of Langmuir cells are rather small on diurnal time scales, they can be appreciable over seasonal time scales. Nevertheless, these SST changes are well within the uncertainties in the modeled SST resulting from an imperfect knowledge of the air–sea fluxes used to drive the mixed layer models.
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Abstract In winter, the Northwest Tropical Atlantic Ocean can be characterized by various wave age‐based interactions among ocean current, surface wind and surface waves, which are critical for accurately describing surface wind ...
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Abstract In winter, the Northwest Tropical Atlantic Ocean can be characterized by various wave age‐based interactions among ocean current, surface wind and surface waves, which are critical for accurately describing surface wind stress. In this work, coupled wave‐ocean‐atmosphere model simulations are conducted using two different wave roughness parameterizations within COARE3.5, including one that relies solely on wind speed and another that uses wave age and wave slope as inputs. Comparisons with the directly measured momentum fluxes during the ATOMIC/EUREC4A experiments in winter 2020 show that, for sea states dominated by short wind waves under moderate to strong winds, the wave‐based formulation (WBF) increases the surface roughness length in average by 25% compared to the wind‐speed‐based approach. For sea states dominated by remotely generated swells under moderate to strong wind intensity, the WBF predicts significantly lower roughness length and surface stress (≈15%), resulting in increased near‐surface wind speed above the constant flux layer (≈5%). Further investigation of the mixed sea states in the model and data indicates that the impact of swell on wind stress is over‐emphasized in the COARE3.5 WBF, especially under moderate wind regimes. Various approaches are explored to alleviate this deficiency by either introducing directional alignment between wind and waves or using the mean wave period instead of the wave period corresponding to the spectral peak to compute the wave age. The findings of this study are likely to be site‐dependent, and mostly concern specific regimes of wind and waves where the original parameterization was deficient.
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Recent observations in the Sea of Japan show evidence of convection to a depth of roughly 1000 m in the winter of 2000, situated along the polar front. Numerical simulations have shown that this deep mixing is associated with both...
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Recent observations in the Sea of Japan show evidence of convection to a depth of roughly 1000 m in the winter of 2000, situated along the polar front. Numerical simulations have shown that this deep mixing is associated with both ageostrophic frontal circulations and pre-existing larger-scale downwelling regimes. The downwelling regimes appear to be a result of interactions between frontal meandering and deep circulation in this basin over bottom topography anomalies. The coupling between the frontal dynamics and the deep circulation are explored by analogy to atmospheric frontal circulations through the semigeostrophic Sawyer-Eliassen equation, solved numerically for the case of the Sea of Japan. As in the atmospheric case, a vertical coupling between the upper and lower circulations can produce a localized region of downwelling that can be conducive to deeper mixing than that forced solely from surface fluxes.
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A dataset consisting of daily diurnal warming values from 1996 through 2000 covering the global Tropics (30 deg N through 30 deg S) at 0.25 deg X 0.25 deg resolution has been created using a parameterization for the diurnal warmin...
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A dataset consisting of daily diurnal warming values from 1996 through 2000 covering the global Tropics (30 deg N through 30 deg S) at 0.25 deg X 0.25 deg resolution has been created using a parameterization for the diurnal warming developed previously. The inputs to the parameterization are the peak shortwave solar radiation [determined from International Satellite Cloud Climatology Project (ISCCP) data] and daily averaged wind speed [determined from Special Sensor Microwave Imager (SSM/I) data].Comparisons with Tropical Ocean Global Atmosphere (TOGA) Tropical Atmosphere Ocean (TAO) and Pilot Research Moored Array in the Tropical Atlantic (PIRATA) buoys show that the biases are small (mean bias is 0.0012 deg C; the standard deviation and correlation are 0.26 deg C and 0.74) and show no discernable geographic bias. The 5-yr average shows that throughout most regions the values are small, with higher values (approaching 1 deg C) in the northern Indian Ocean, the western equatorial Pacific, the equatorial eastern Pacific, and several coastal regions. An EOF analysis of the variability indicates that seasonal variability is the most dominant form for each of the basins; in the Atlantic and Pacific basins it is north-south following the solar cycle. In the Indian Ocean the seasonal cycle is dominated by monsoonal variability; both the northern and southern portions of the basin have above-mean or below-mean values at the same times. Seasonal shortwave variability is responsible for the second modein the Indian Ocean. East-west dipole weight structures appear in the spatial patterns for mode 2 in the Pacific and mode 3 for the Atlantic and Indian Oceans. These modes also display seasonally varying characteristics, with late 1997 and early 1998 being somewhat anomalous in the Pacific and Indian Oceans.
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The Maritime Continent (MC) is a region with enhanced tidal mixing and ocean cooling, which influences regional-scale sea surface temperatures (SSTs). We examine the coupled impacts of tidal mixing on near-surface stratification, ...
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The Maritime Continent (MC) is a region with enhanced tidal mixing and ocean cooling, which influences regional-scale sea surface temperatures (SSTs). We examine the coupled impacts of tidal mixing on near-surface stratification, SST, and deep convection on diurnal and intraseasonal time-scales, using ensembles of high-resolution, coupled ocean-atmosphere regional model simulations, with and without tidal forcing. Results show that the area-averaged SST in the eastern MC is reduced by 0.20 ℃ due to tidal forcing, with cooling exceeding 1 ℃ in the nearshore zones of shallow and complex bathymetry. The reduced SSTs decrease surface heat fluxes, leading to tropospheric drying and reduced precipitation, which are most pronounced in the near-shore zones. The results show that the magnitude of tidally-induced SST cooling is phase-dependent during the passage of the Madden Julian Oscillation (MJO). Strong westerly winds enhance entrainment cooling through wind-driven mixing and upwelling during the active phase. Conversely, the upper-ocean stratification is enhanced during the suppressed phase, and SSTs are less sensitive to subsurface cooling. Such spatio-temporal variability in the SST response to tides is accompanied by consistent changes to deep convection and atmospheric circulation. On the diurnal time-scale, nearshore cooling weakens the early-morning convection when the land-based convection propagates offshore and interacts with the cooler SST. On intraseasonal time-scales, the coupling between SST and precipitation is strengthened because of the asymmetric impacts of tide-induced mixing on SST and MJO-induced winds. The robust SST and precipitation responses demonstrated in this study suggest the need for an accurate representation of tidal forcing and vertical mixing processes in local MJO prediction models for the MC.
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Improved seasonal prediction of sea surface temperature (SST) anomalies over the global oceans is the theme of this paper. Using 13 state-of-the-art coupled global atmosphere-ocean models and 13 yr of seasonal forecasts, the perfo...
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Improved seasonal prediction of sea surface temperature (SST) anomalies over the global oceans is the theme of this paper. Using 13 state-of-the-art coupled global atmosphere-ocean models and 13 yr of seasonal forecasts, the performance of individualmodels, the ensemble mean, the bias-removed ensemble mean, and the Florida State University (FSU) superensemble are compared. A total of 23 400 seasonal forecasts based on 1-month lead times were available for this study. Evaluation metrics include bothdeterministic and probabilistic skill measures, such as verification of anomalies based on model and observed climatology, time series of specific climate indices, standard deterministic ensemble mean scores including anomaly correlations, root-mean-square (RMS) errors, and probabilistic skill measures such as equitable threat scores for seasonal SST forecasts. This study also illustrates the Niantilde;o-3.4 SST forecast skill for the equatorial Pacific Ocean and for the dipole index for the Indian Ocean. The relative skills of total SST fields and of the SST anomalies from the 13 coupled atmosphere-ocean models are presented. Comparisons of superensemble-based seasonal forecasts with recent studies on SST anomaly forecasts are also shown. Overall it is found that the multimodel superensemble forecasts are characterized by considerable RMS error reductions and increased accuracy in the spatial distribution of SST. Superensemble SST skill also persists for El Niantilde;o and La Niantilde;a forecasts since the large comparative skill of the superensemble is retained across such years. Real-time forecasts of seasonal sea surface temperature anomalies appear to be possible.
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The turbulent heat fluxes play a pivotal role in the exchange of energy between the atmosphere and ocean. The calculation of these fluxes over the global oceans requires the use of bulk aerodynamic or flux-gradient methods that re...
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The turbulent heat fluxes play a pivotal role in the exchange of energy between the atmosphere and ocean. The calculation of these fluxes over the global oceans requires the use of bulk aerodynamic or flux-gradient methods that rely on estimates of the sea surface temperature (SST), near-surface wind speed, air temperature, and specific humidity. Errors in current methodologies of satellite retrievals of near-surface properties have been shown to be the main sources of error for calculation of the fluxes. A new neural network technique is presented here that significantly improves the error characteristics of the air temperature and specific humidity compared to previous methods. Improvements in predicting near-surface wind speed and SST are also seen. Additional improvements are also made by accounting for the effects of high cloud liquid water contents, the effects of which can be mitigated through the use of regime-specific linear and nonlinear retrieval methods. The use of a first-guess SST is shown to result in significant improvement in retrieval accuracy.
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An analysis of a satellite ocean surface turbulent flux product demonstrated that, as expected, the western boundary current regions dominate the seasonal cycle amplitude. Surprisingly, our analysis of the global ocean diurnal flu...
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An analysis of a satellite ocean surface turbulent flux product demonstrated that, as expected, the western boundary current regions dominate the seasonal cycle amplitude. Surprisingly, our analysis of the global ocean diurnal flux variability also demonstrated a regional maximum in the winter over the western boundary current regions. We conducted comparisons with in situ data from several buoys located in these regions. The buoy data were in general agreement with the relative magnitude, timing, and importance of each of the bulk parameters driving the latent and sensible heat fluxes. Further analysis demonstrated that the strength and timing of the diurnal signal is related to the location of the buoy relative to the region of maximum heat flux and sea surface temperature gradient. In both regions, the timing of the higher winds coincides with the moistest surface layer, indicating that surface fluxes rather than entrainment mixing play a key role in this phenomenon.
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In this paper, we address the question of energy leakage from turbulence to internal waves (IWs) in the oceanic mixed layer (OML). If this leakage is substantial, then not only does this have profound implications as far as the dy...
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In this paper, we address the question of energy leakage from turbulence to internal waves (IWs) in the oceanic mixed layer (OML). If this leakage is substantial, then not only does this have profound implications as far as the dynamics of the OML is concerned, but it also means that the equation for the turbulence kinetic energy (TKE) used in OML models must include an appropriate sink term, and traditional models must be modified accordingly. Through comparison with the experimental data on grid-generated turbulence in a stably stratified fluid, we show that a conventional two-equation turbulence model without any IW sink term can explain these observations quite well, provided that the fluctuating motions that persist long after the decay of grid-generated turbulence are interpreted as being due to IW motions generated by the initial passage of the grid through the stably stratified fluid and not during turbulence decay. We conclude that there is no need to postulate an IW sink term in the TKE equation, and conventional models suffice to model mixing in the OML.
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