Description: © The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Continental Shelf Research 78 (2014): 51–61, doi:10.1016/j.csr.2014.01.025.

Description: Properties of coastal flows of the central Red Sea are examined using 2 years of velocity data acquired off the coast of Saudi Arabia near 22 °N. The tidal flow is found to be very weak. The strongest tidal constituent, the M2 tide, has a magnitude of order 4 cm s−1. Energetic near-inertial and diurnal period motions are observed. These are surface-intensified currents, reaching magnitudes of 〉10 cm s−1. Although the diurnal currents appear to be principally wind-driven, their relationship with the surface wind stress record is complex. Less than 50% of the diurnal current variance is related to the diurnal wind stress through linear correlation. Correlation analysis reveals a classical upwelling/downwelling response to the alongshore wind stress. However, less than 30% of the overall sub-inertial variance can be accounted for by this response. The action of basin-scale eddies, impinging on the coastal zone, is implicated as a primary mechanism for driving coastal flows.

Description: This research is based on work supported by Award nos.USA 00002 and KSA 00011 made by KAUST to WHOI.

Description: This paper is not subject to U.S. copyright. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 132 (2016): 263–264, doi:10.1016/j.dsr2.2016.08.001.

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing of Environment 209 (2018): 677-699, doi:10.1016/j.rse.2018.02.075.

Description: We analyse ten years of QuikSCAT satellite surface winds to statistically characterize the spatio-temporal variability of the westward mountain-gap wind jets over the northern Red Sea. These wind jets bring relatively cold and dry air from the Arabian Desert, increasing heat loss and evaporation over the region similar to cold-air outbreaks from mid and subpolar latitudes. QuikSCAT captures the spatial structure of the wind jets and agrees well with in situ observations from a heavily instrumented mooring in the northern Red Sea. The local linear correlations between QuikSCAT and in situ winds are 0.96 (speed) and 0.85 (direction). QuikSCAT also reveals that cross-axis winds such as the mountain-gap wind jets are a major component of the regional wind variability. The cross-axis wind pattern appears as the second (or third) mode in the four vector Empirical Orthogonal Function analyses we performed, explaining between 6% to 11% of the wind variance. Westward wind jets are typical in winter, especially in December and January, but with strong interannual variability. Several jets can occur simultaneously and cover a large latitudinal range of the northern Red Sea, which we call large-scale westward events. QuikSCAT recorded 18 large-scale events over ten years, with duration between 3 to 8 days and strengths varying from 3–4 to 9–10 m/s. These events cause large changes in the wind stress curl pattern, imposing a remarkable sequence of positive and negative curl along the Red Sea main axis, which might be a wind forcing mechanism for the oceanic mesoscale circulation.

Description: This work was supported by NSF grant OCE-1435665 and NASA grant NNX14AM71G.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chelton, D. B., Schlax, M. G., Samelson, R. M., Farrar, J. T., Molemaker, M. J., McWilliams, J. C., & Gula, J. Prospects for future satellite estimation of small-scale variability of ocean surface velocity and vorticity. Progress in Oceanography, 173, (2019):256-350, doi:0.1016/j.pocean.2018.10.012.

Description: Recent technological developments have resulted in two techniques for estimating surface velocity with higher resolution than can be achieved from presently available nadir altimeter data: (1) Geostrophically computed estimates from high-resolution sea surface height (SSH) measured interferometrically by the wide-swath altimeter on the Surface Water and Ocean Topography (SWOT) Mission with a planned launch in 2021; and (2) Measurements of ocean surface velocity from a Doppler scatterometer mission that is in the early planning stages, referred to here as a Winds and Currents Mission (WaCM). In this study, we conduct an analysis of the effects of uncorrelated measurement errors and sampling errors on the errors of the measured and derived variables of interest (SSH and geostrophically computed velocity and vorticity for SWOT, and surface velocity and vorticity for WaCM). Our analysis includes derivations of analytical expressions for the variances and wavenumber spectra of the errors of the derived variables, which will be useful to other studies based on simulated SWOT and WaCM estimates of velocity and vorticity. We also discuss limitations of the geostrophic approximation that must be used for SWOT estimates of velocity. The errors of SWOT and WaCM estimates of velocity and vorticity at the full resolutions of the measured variables are too large for the unsmoothed estimates to be scientifically useful. It will be necessary to smooth the data to reduce the noise variance. We assess the resolution capabilities of smoothed estimates of velocity and vorticity from simulated noisy SWOT and WaCM data based on a high-resolution model of the California Current System (CCS). By our suggested minimum threshold signal-to-noise (S/N) variance ratio of 10 (a standard deviation ratio of 3.16), we conclude that the wavelength resolution capabilities of maps of velocity and vorticity constructed from WaCM data with a swath width of 1200 km are, respectively, about 60 km and 90 km in 4-day averages. For context, the radii of resolvable features are about four times smaller than these mesoscale wavelength resolutions. If the swath width can be increased to 1800 km, the wavelength resolution capabilities of 4-day average maps of surface velocity and vorticity would improve to about 45 km and 70 km, respectively. Reducing the standard deviation of the uncorrelated measurement errors from the baseline value of m s−1 to a value of 0.25 m s−1 would further improve these resolution capabilities to about 20 km and 45 km. SWOT data will allow mapping of the SSH field with far greater accuracy and space–time resolution than are presently achieved by merging the data from multiple nadir altimeter missions. However, because of its much narrower 120-km measurement swath compared with WaCM and the nature of the space–time evolution of the sampling pattern during each 21-day repeat of the SWOT orbit, maps of geostrophically computed velocity and vorticity averaged over the 14-day period that is required for SWOT to observe the full CCS model domain are contaminated by sampling errors that are too large for the estimates to be useful for any amount of smoothing considered here. Reducing the SSH measurement errors would do little to improve SWOT maps of velocity and vorticity. SWOT estimates of these variables are likely to be useful only within individual measurement swaths or with the help of dynamic interpolation from a data assimilation model. By our criterion, in-swath SWOT estimates of velocity and vorticity have wavelength resolution capabilities of about 30 km and 55 km, respectively. In comparison, in-swath estimates of velocity and vorticity from WaCM data with m s−1 have a wavelength resolution capability of about 130 km for both variables. Reducing the WaCM measurement errors to m s−1 would improve the resolution capabilities to about 50 km and 75 km for velocity and vorticity, respectively. These resolutions are somewhat coarser than the in-swath estimates from SWOT data, but the swath width is more than an order of magnitude wider for WaCM. Instantaneous maps of velocity and vorticity constructed in-swath from WaCM data will therefore be much less prone to edge effect problems in the spatially smoothed fields. Depending on the precise value of the threshold adopted for the minimum S/N ratio and on the details of the filter used to smooth the SWOT and WaCM data, the resolution capabilities summarized above may be somewhat pessimistic. On the other hand, aspects of measurement errors and sampling errors that have not been accounted for in this study will worsen the resolution capabilities presented here. Another caveat to keep in mind is that the resolution capabilities deduced here from simulations of the CCS region during summertime may differ somewhat at other times of year and in other geographical regions where the signal variances and wavenumber spectra of the variables of interest differ from the CCS model used in this study. Our analysis nonetheless provides useful guidelines for the resolutions that can be expected from SWOT and WaCM.

Description: We thank Ralph Milliff, Bo Qiu, Ernesto Rodríguez and Lee-Lueng Fu for many helpful editorial comments and suggestions that improved the manuscript. This research was funded by NASA Grants NNX13AD78G, NNX14AM72G, NNX13AE32G, NNX14AM66G, NNX16AH76G,NNX14AM71G and NNX17AH54G. The two North Atlantic Ocean simulations in this study were performed using HPC resources from GENCI-TGCC with support from Grant 2017-A0010107638 for Jonathan Gula.

Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kantha, L., Weller, R. A., Farrar, J. T., Rahaman, H., & Jampana, V. A note on modeling mixing in the upper layers of the Bay of Bengal: importance of water type, water column structure and precipitation. Deep-Sea Research Part II-Topical Studies in Oceanography, 168, (2019): 104643. doi: 10.1016/j.dsr2.2019.104643.

Description: Turbulent mixing in the upper layers of the northern Bay of Bengal is affected by a shallow layer overlying the saline waters of the Bay, which results from the huge influx of freshwater from major rivers draining the Indian subcontinent and from rainfall over the Bay during the summer monsoon. The resulting halocline inhibits wind-driven mixing in the upper layers. The brackish layer also alters the optical properties of the water column. Air-sea interaction in the Bay is expected to play a significant role in the intraseasonal variability of summer monsoons over the Indian subcontinent, and as such the sea surface temperature (SST) changes during the summer monsoon are of considerable scientific and societal importance. In this study, data from the heavily instrumented Woods Hole Oceanographic Institution (WHOI) mooring, deployed at 18oN, 89.5oE in the northern Bay from December 2014 to January 2016, are used to drive a one-dimensional mixing model, based on second moment closure model of turbulence, to explore the intra-annual variability in the upper layers. The model results highlight the importance of the optical properties of the upper layers (and hence the penetration of solar insolation in the water column), as well as the temperature and salinity in the upper layers prescribed at the start of the model simulation, in determining the SST in the Bay during the summer monsoon. The heavy rainfall during the summer monsoon also plays an important role. The interseasonal and intraseasonal variability in the upper layers of the Bay are contrasted with those in the Arabian Sea, by the use of the same model but driven by data from an earlier deployment of a WHOI mooring in the Arabian Sea at 15.5 oN, 61.5 oE from December 1994 to December 1995.

Description: LK was supported by U.S. Office of Naval Research (ONR) MISO/BoB DRI under grant number N00014-17-1-2716. RW and JTF were supported by ONR Grants N00014-13-1-0453 and N00014-17-1-2880, and the WHOI mooring was funded by Grant N00014-13-1-0453. RW was supported by ONR for the 1994–1995 deployment of the surface mooring in the Arabian Sea. HR and VJ wish to thank Dr. SSC Shenoi, the Director of INCOIS and Dr. M Ravichandran, Director, NCPOR for the encouragement and support to carry out this study. This work was supported by the Ministry of Earth Sciences (MoES), Govt. of India. This is also INCOIS Contribution number 349.