Kyla Drushka

Vertical Structure of Kelvin Waves in the Indonesian Throughflow Exit Passages

Abstract The subsurface structure of intraseasonal Kelvin waves in two Indonesian Throughflow (ITF) exit passages is observed and characterized using velocity and temperature data from the 2004–06 International Nusantara Stratification and Transport (INSTANT) project. Scatterometer winds are used to characterize forcing, and altimetric sea level anomaly (SLA) data are used to trace the pathways of Kelvin waves east from their generation region in the equatorial Indian Ocean to Sumatra, south along the Indonesian coast, and into the ITF region. During the 3-yr INSTANT period, 40 intraseasonal Kelvin waves forced by winds over the central equatorial Indian Ocean caused strong transport anomalies in the ITF outflow passages. Of these events, 21 are classed as “downwelling” Kelvin waves, forced by westerly winds and linked to depressions in the thermocline and warm temperature anomalies in the ITF outflow passages; 19 were “upwelling” Kelvin waves, generated by easterly wind events and linked to shoaling of t...

In Situ Observations of Madden–Julian Oscillation Mixed Layer Dynamics in the Indian and Western Pacific Oceans

AbstractThe boreal winter response of the ocean mixed layer to the Madden–Julian oscillation (MJO) in the Indo-Pacific region is determined using in situ observations from the Argo profiling float dataset. Composite averages over numerous events reveal that the MJO forces systematic variations in mixed layer depth and temperature throughout the domain. Strong MJO mixed layer depth anomalies (>15 m peak to peak) are observed in the central Indian Ocean and in the far western Pacific Ocean. The strongest mixed layer temperature variations (>0.6°C peak to peak) are found in the central Indian Ocean and in the region between northwest Australia and Java. A heat budget analysis is used to evaluate which processes are responsible for mixed layer temperature variations at MJO time scales. Though uncertainties in the heat budget are on the same order as the temperature trend, the analysis nonetheless demonstrates that mixed layer temperature variations associated with the canonical MJO are driven largely by anoma...

Satellite and In Situ Salinity: Understanding Near-Surface Stratification and Subfootprint Variability

Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km 2 . In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.

Subseasonal variations in salinity and barrier-layer thickness in the eastern equatorial Indian Ocean

The barrier layer, the layer between the bottom of the density-defined mixed layer and the isothermal layer in the upper ocean, may play a role in air-sea dynamics. In the present study, data from Argo profiling floats in the tropical Indian Ocean and a mooring at 90°E, 0°N are used to examine subseasonal variations in upper ocean salinity and barrier-layer thickness (BLT) during boreal winter. In the eastern equatorial Indian Ocean, subseasonal variations in BLT are energetic. However, composites used to isolate the Madden-Julian Oscillation (MJO) component of the subseasonal signal reveal that, on average, the MJO anomaly in BLT is negligible despite large swings in both the mixed-layer depth and the isothermal-layer depth. This discrepancy is likely due to (a) noise from other subseasonal processes; and (b) the diversity of individual MJO events: the thickness of the mixed layer and the isothermal layer are sensitive to wind and rain forcing, so even subtle differences in the phasing and strength of MJO-related atmospheric anomalies can produce a very different effect on upper ocean stratification and hence on the thickness of the barrier layer. The effect of the barrier layer on the upper ocean response to MJO forcing is also evaluated. When the barrier layer is thick, entrainment cooling during the MJO is reduced, so the MJO drives a weaker sea surface temperature anomaly. This suggests that modulation of BLT can have significant consequences for the response of the upper ocean to the MJO, and hence, potentially, for feedbacks of the ocean onto the atmosphere on MJO time scales.

Defining Mediterranean and Black Sea biogeochemical subprovinces and synthetic ocean indicators using mesoscale oceanographic features.

The Mediterranean and Black Seas are semi-enclosed basins characterized by high environmental variability and growing anthropogenic pressure. This has led to an increasing need for a bioregionalization of the oceanic environment at local and regional scales that can be used for managerial applications as a geographical reference. We aim to identify biogeochemical subprovinces within this domain, and develop synthetic indices of the key oceanographic dynamics of each subprovince to quantify baselines from which to assess variability and change. To do this, we compile a data set of 101 months (2002–2010) of a variety of both “classical” (i.e., sea surface temperature, surface chlorophyll-a, and bathymetry) and “mesoscale” (i.e., eddy kinetic energy, finite-size Lyapunov exponents, and surface frontal gradients) ocean features that we use to characterize the surface ocean variability. We employ a k-means clustering algorithm to objectively define biogeochemical subprovinces based on classical features, and, for the first time, on mesoscale features, and on a combination of both classical and mesoscale features. Principal components analysis is then performed on the oceanographic variables to define integrative indices to monitor the environmental changes within each resultant subprovince at monthly resolutions. Using both the classical and mesoscale features, we find five biogeochemical subprovinces for the Mediterranean and Black Seas. Interestingly, the use of mesoscale variables contributes highly in the delineation of the open ocean. The first axis of the principal component analysis is explained primarily by classical ocean features and the second axis is explained by mesoscale features. Biogeochemical subprovinces identified by the present study can be useful within the European management framework as an objective geographical framework of the Mediterranean and Black Seas, and the synthetic ocean indicators developed here can be used to monitor variability and long-term change.

Understanding the formation and evolution of rain‐formed fresh lenses at the ocean surface

Rain falling on the ocean produces a layer of buoyant fresher surface water, or ‘‘fresh lens.’’ Fresh lenses can have significant impacts on satellite-in situ salinity comparisons and on exchanges between the surface and the bulk mixed layer. However, because these are small, transient features, relatively few observations of fresh lenses have been made. Here the Generalized Ocean Turbulence Model (GOTM) is used to explore the response of the upper few meters of the ocean to rain events. Comparisons with observations from several platforms demonstrate that GOTM can reproduce the main characteristics of rain-formed fresh lenses. Idealized sensitivity tests show that the near-surface vertical salinity gradient within fresh lenses has a linear dependence on rain rate and an inverse dependence on wind speed. Yearlong simulations forced with satellite rainfall and reanalysis atmospheric parameters demonstrate that the mean salinity difference between 0.01 and 5 m, equivalent to the measurement depths of satellite radiometers and Argo floats, is 20.04 psu when averaged over the 208S–208N tropical band. However, when averaged regionally, the mean vertical salinity difference exceeds 20.15 psu in the Indo-Pacific warm pool, in the Pacific and Atlantic intertropical convergence zone, and in the South Pacific convergence zone. In most of these regions, salinities measured by the Aquarius satellite instrument have a fresh bias relative to Argo measurements at 5 m depth. These results demonstrate that the fresh bias in Aquarius salinities in rainy, low-wind regions may be caused by the presence of rain-produced fresh lenses.

The diurnal salinity cycle in the tropics

Observations from 35 tropical moorings are used to characterize the diurnal cycle in salinity at 1 m depth. The amplitude of diurnal salinity anomalies is up to 0.01 psu and more typically ∼0.005 psu. Diurnal variations in precipitation and vertical entrainment appear to be the dominant drivers of diurnal salinity variability, with evaporation also contributing. Areas where these processes are strong are expected to have relatively strong salinity cycles: the eastern Atlantic and Pacific equatorial regions, the southwestern Bay of Bengal, the Amazon outflow region, and the Indo-Pacific warm pool. We hypothesize that salinity anomalies resulting from precipitation and evaporation are initially trapped very near the surface and may not be observed at the 1 m instrument depths until they are mixed downward. As a result, the pattern of diurnal salinity variations is not only dependent on the strength of the forcing terms, but also on the phasing of winds and convective overturning. A comparison of mixed-layer depth computed with hourly and with daily averaged salinity reveals that diurnal salinity variability can have a significant effect on upper ocean stratification, suggesting that representing diurnal salinity variability could potentially improve air-sea interaction in climate models. Comparisons between salinity observations from moorings and from the Aquarius satellite (level 2 version 3.0 data) reveal that the typical difference between ascending-node and descending-node Aquarius salinity is an order of magnitude greater than the observed diurnal salinity anomalies at 1 m depth.

Impact of slowdown of Atlantic overturning circulation on heat and freshwater transports

Recent measurements of the strength of the Atlantic overturning circulation at 26°N show a 1 year drop and partial recovery amid a gradual weakening. To examine the extent and impact of the slowdown on basin wide heat and freshwater transports for 2004–2012, a box model that assimilates hydrographic and satellite observations is used to estimate heat transport and freshwater convergence as residuals of the heat and freshwater budgets. Using an independent transport estimate, convergences are converted to transports, which show a high level of spatial coherence. The similarity between Atlantic heat transport and the Agulhas Leakage suggests that it is the source of the surface heat transport anomalies. The freshwater budget in the North Atlantic is dominated by a decrease in freshwater flux. The increasing salinity during the slowdown supports modeling studies that show that heat, not freshwater, drives trends in the overturning circulation in a warming climate.

Extension of the prognostic model of sea surface temperature to rain‐induced cool and fresh lenses

The Zeng and Beljaars (2005) sea surface temperature prognostic scheme, developed to represent diurnal warming, is extended to represent rain-induced freshening and cooling. Effects of rain on salinity and temperature in the molecular skin layer (first few hundred micrometers) and the near-surface turbulent layer (first few meters) are separately parameterized by taking into account rain-induced fluxes of sensible heat and freshwater, surface stress, and mixing induced by droplets penetrating the water surface. Numerical results from this scheme are compared to observational data from two field studies of near-surface ocean stratifications caused by rain, to surface drifter observations and to previous computations with an idealized ocean mixed layer model, demonstrating that the scheme produces temperature variations consistent with in situ observations and model results. It reproduces the dependency of salinity on wind and rainfall rate and the lifetime of fresh lenses. In addition, the scheme reproduces the observed lag between temperature and salinity minimum at low wind speed and is sensitive to the peak rain rate for a given amount of rain. Finally, a first assessment of the impact of these fresh lenses on ocean surface variability is given for the near-equatorial western Pacific. In particular, the variability due to the mean rain-induced cooling is comparable to the variability due to the diurnal warming so that they both impact large-scale horizontal surface temperature gradients. The present parameterization can be used in a variety of models to study the impact of rain-induced fresh and cool lenses at different spatial and temporal scales.

Salinity rain impact model (RIM) optimization: Preliminary results

Based upon research with the Aquarius (AQ) satellite remote sensor, a rain impact model (RIM) has been developed which estimates the occurrence of sea surface salinity (SSS) stratification. RIM uses global salinity (HYCOM) and rainfall (CMORPH) products to estimate the transient change in SSS due to rainfall. Previously SSS predicted by RIM have exhibited good correlations with AQ, but the choice for the duration window (24 h) was arbitrary. In this paper, we examine the effect on RIM of different time duration windows.