Adams, D. K., McGillicuddy, D. J. J., Zamudio, L., Thurnherr, A. M., Liang, X., Rouxel, O., et al. (2011). Surface-generated mesoscale eddies transport deep-sea products from hydrothermal vents.
Science, 332(6029), 580–583.
Abstract: Atmospheric forcing, which is known to have a strong influence on surface ocean dynamics and production, is typically not considered in studies of the deep sea. Our observations and models demonstrate an unexpected influence of surface-generated mesoscale eddies in the transport of hydrothermal vent efflux and of vent larvae away from the northern East Pacific Rise. Transport by these deep-reaching eddies provides a mechanism for spreading the hydrothermal chemical and heat flux into the deep-ocean interior and for dispersing propagules hundreds of kilometers between isolated and ephemeral communities. Because the eddies interacting with the East Pacific Rise are formed seasonally and are sensitive to phenomena such as El Nino, they have the potential to introduce seasonal to interannual atmospheric variations into the deep sea.
Ahern, K., Bourassa, M. A., Hart, R. E., Zhang, J. A., & Rogers, R. F. (2019). Observed Kinematic and Thermodynamic Structure in the Hurricane Boundary Layer During Intensity Change.
Mon. Wea. Rev., .
Abstract: The axisymmetric structure of the inner-core hurricane boundary layer (BL) during intensification [IN; intensity tendency ≥ 20 kt (24 h)−1], weakening [WE; intensity tendency < −10 kt (24 h)−1], and steady-state [SS; the remainder] periods are analyzed using composites of GPS dropwindsondes from reconnaissance missions between 1998 and 2015. A total of 3,091 dropsondes were composited for analysis below 2.5 km elevation—1,086 during IN, 1,042 during WE, and 963 during SS. In non-intensifying hurricanes, the lowlevel tangential wind is greater outside the radius of maximum wind (RMW) than for intensifying hurricanes, implying higher inertial stability (I) at those radii for non-intensifying hurricanes. Differences in tangential wind structure (and I) between the groups also imply differences in secondary circulation. The IN radial inflow layer is of nearly equal or greater thickness than nonintensifying groups, and all groups show an inflow maximum just outside the RMW. Non-intensifying hurricanes have stronger inflow outside the eyewall region, likely associated with frictionally forced ascent out of the BL and enhanced subsidence into the BL at radii outside the RMW. Equivalent potential temperatures (θe) and conditional stability are highest inside the RMW of non-intensifying storms, which is potentially related to TC intensity. At greater radii, inflow layer θe is lowest in WE hurricanes, suggesting greater subsidence or more convective downdrafts at those radii compared to IN and SS hurricanes. Comparisons of prior observational and theoretical studies are highlighted, especially those relating BL structure to large-scale vortex structure, convection, and intensity.
Ahern, K. K. (2015).
Analysis of Polar Mesocyclonic Surface Turbulent Fluxes in the Arctic System Reanalysis (ASRv1) Dataset. Master's thesis, Florida State University, Tallahassee, FL.
Ahern, K. K. (2019).
Hurricane Boundary Layer Structure during Intensity Change: An Observational and Numerical Analysis.
Ahmed, A. (2013).
Visualization of geo spatial data in real time. Master's thesis, Florida State University, Tallahassee, FL.
AjayaMohan, R. S., Jagtap, S., LaRow, T. E., Cocke, S., O'Brien, J. J., Jones, J., et al. (2004). Using climate models to generate crop yield forecasts in southeast USA. In
Research Activities in Atmospheric and Ocean Modeling, CAS/JSC Working Group on Numerical Experimentation.
Ajayi, A., Le Sommer, J., Chassignet, E., Molines, J. - M., Xu, X., Albert, A., et al. (2020). Spatial and Temporal Variability of the North Atlantic Eddy Field From Two Kilometric-Resolution Ocean Models.
J. Geophys. Res. Oceans, 125(5).
Abstract: Ocean circulation is dominated by turbulent geostrophic eddy fields with typical scales ranging from 10 to 300 km. At mesoscales (>50 km), the size of eddy structures varies regionally following the Rossby radius of deformation. The variability of the scale of smaller eddies is not well known due to the limitations in existing numerical simulations and satellite capability. Nevertheless, it is well established that oceanic flows (<50 km) generally exhibit strong seasonality. In this study, we present a basin‐scale analysis of coherent structures down to 10 km in the North Atlantic Ocean using two submesoscale‐permitting ocean models, a NEMO‐based North Atlantic simulation with a horizontal resolution of 1/60 (NATL60) and an HYCOM‐based Atlantic simulation with a horizontal resolution of 1/50 (HYCOM50). We investigate the spatial and temporal variability of the scale of eddy structures with a particular focus on eddies with scales of 10 to 100 km, and examine the impact of the seasonality of submesoscale energy on the seasonality and distribution of coherent structures in the North Atlantic. Our results show an overall good agreement between the two models in terms of surface wave number spectra and seasonal variability. The key findings of the paper are that (i) the mean size of ocean eddies show strong seasonality; (ii) this seasonality is associated with an increased population of submesoscale eddies (10�50 km) in winter; and (iii) the net release of available potential energy associated with mixed layer instability is responsible for the emergence of the increased population of submesoscale eddies in wintertime.
Ali, A., Christensen, K. H., Breivik, Ø., Malila, M., Raj, R. P., Bertino, L., et al. (2019). A comparison of Langmuir turbulence parameterizations and key wave effects in a numerical model of the North Atlantic and Arctic Oceans.
Ocean Modelling, 137, 76–97.
Abstract: Five different parameterizations of Langmuir turbulence (LT) effect are investigated in a realistic model of the North Atlantic and Arctic using realistic wave forcing from a global wave hindcast. The parameterizations mainly apply an enhancement to the turbulence velocity scale, and/or to the entrainment buoyancy flux in the surface boundary layer. An additional run is also performed with other wave effects to assess the relative importance of Langmuir turbulence, namely the Coriolis-Stokes forcing, Stokes tracer advection and wave-modified momentum fluxes. The default model (without wave effects) underestimates the mixed layer depth in summer and overestimates it at high latitudes in the winter. The results show that adding LT mixing reduces shallow mixed layer depth (MLD) biases, particularly in the subtropics all year-around, and in the Nordic Seas in summer. There is overall a stronger relative impact on the MLD during winter than during summer. In particular, the parameterization with the most vigorous LT effect causes winter MLD increases by more than 50% relative to a control run without Langmuir mixing. On the contrary, the parameterization which assumes LT effects on the entrainment buoyancy flux and accounts for the Stokes penetration depth is able to enhance the mixing in summer more than in winter. This parametrization is also distinct from the others because it restrains the LT mixing in regions of deep MLD biases, so it is the preferred choice for our purpose. The different parameterizations do not change the amplitude or phase of the seasonal cycle of heat content but do influence its long-term trend, which means that the LT can influence the drift of ocean models. The combined impact on water mass properties from the Coriolis-Stokes force, the Stokes drift tracer advection, and the wave-dependent momentum fluxes is negligible compared to the effect from the parameterized Langmuir turbulence.
Ali, M., Singh, N., Kumar, M., Zheng, Y., Bourassa, M., Kishtawal, C., et al. (2018). Dominant Modes of Upper Ocean Heat Content in the North Indian Ocean.
Climate, 6(3), 71.
Abstract: The thermal energy needed for the development of hurricanes and monsoons as well as any prolonged marine weather event comes from layers in the upper oceans, not just from the thin layer represented by sea surface temperature alone. Ocean layers have different modes of thermal energy variability because of the different time scales of ocean-atmosphere interaction. Although many previous studies have focused on the influence of upper ocean heat content (OHC) on tropical cyclones and monsoons, no study thus farparticularly in the North Indian Ocean (NIO)has specifically concluded the types of dominant modes in different layers of the ocean. In this study, we examined the dominant modes of variability of OHC of seven layers in the NIO during 1998-2014. We conclude that the thermal variability in the top 50 m of the ocean had statistically significant semiannual and annual modes of variability, while the deeper layers had the annual mode alone. Time series of OHC for the top four layers were analyzed separately for the NIO, Arabian Sea, and Bay of Bengal. For the surface to 50 m layer, the lowest and the highest values of OHC were present in January and May every year, respectively, which was mainly caused by the solar radiation cycle.
Ali, M., Singh, N., Kumar, M., Zheng, Y., Bourassa, M., Kishtawal, C., et al. (2019). Dominant Modes of Upper Ocean Heat Content in the North Indian Ocean.
Climate, 6(71), 1–8.
Abstract: The thermal energy needed for the development of hurricanes and monsoons as well as any prolonged marine weather event comes from layers in the upper oceans, not just from the thin layer represented by sea surface temperature alone. Ocean layers have different modes of thermal energy variability because of the different time scales of ocean–atmosphere interaction. Although many previous studies have focused on the influence of upper ocean heat content (OHC) on tropical cyclones and monsoons, no study thus far—particularly in the North Indian Ocean (NIO)—has specifically concluded the types of dominant modes in different layers of the ocean. In this study, we examined the dominant modes of variability of OHC of seven layers in the NIO during 1998–2014. We conclude that the thermal variability in the top 50 m of the ocean had statistically significant semiannual and annual modes of variability, while the deeper layers had the annual mode alone. Time series of OHC for the top four layers were analyzed separately for the NIO, Arabian Sea, and Bay of Bengal. For the surface to 50 m layer, the lowest and the highest values of OHC were present in January and May every year, respectively, which was mainly caused by the solar radiation cycle.