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1. Introduction Wind forces motion in the ocean and in turn the motion in the ocean determines the weather and climate in large portions of the world. Wind forcing is essential in El Niño–Southern Oscillation (ENSO) and other ocean–atmosphere interaction phenomena occurring in the tropics. As such, a homogeneous wind dataset of high quality would much advance research on the prediction and mechanisms of seasonal forecasting. Vialard (2000) emphasizes that wind stress is certainly the most
1. Introduction Wind forces motion in the ocean and in turn the motion in the ocean determines the weather and climate in large portions of the world. Wind forcing is essential in El Niño–Southern Oscillation (ENSO) and other ocean–atmosphere interaction phenomena occurring in the tropics. As such, a homogeneous wind dataset of high quality would much advance research on the prediction and mechanisms of seasonal forecasting. Vialard (2000) emphasizes that wind stress is certainly the most
1. Introduction The Reynolds stress terms and , where u ′, v ′, and w ′, respectively, represent the cross-shore, alongshore, and vertical components of turbulent velocities and the overbar is an averaging operator, play an important role in the mean momentum and turbulence dynamics of boundary layer flows. Estimating the Reynolds stress from observations is crucial in diagnosing these dynamics. Often the Reynolds decomposition between mean and turbulent velocity components and its
1. Introduction The Reynolds stress terms and , where u ′, v ′, and w ′, respectively, represent the cross-shore, alongshore, and vertical components of turbulent velocities and the overbar is an averaging operator, play an important role in the mean momentum and turbulence dynamics of boundary layer flows. Estimating the Reynolds stress from observations is crucial in diagnosing these dynamics. Often the Reynolds decomposition between mean and turbulent velocity components and its
1. Introduction Scatterometer observations of wind stress at the ocean’s surface show clear evidence of both large-scale atmospheric features and smaller-scale features resulting from interactions with the ocean ( Chelton et al. 2004 ). The small-scale oceanic features are caused by two primary mechanisms. The first mechanism is that of the ocean velocity, since stress can be approximated as a quadratic function of the relative velocity between the atmosphere and ocean ( Pacanowski 1987 ). The
1. Introduction Scatterometer observations of wind stress at the ocean’s surface show clear evidence of both large-scale atmospheric features and smaller-scale features resulting from interactions with the ocean ( Chelton et al. 2004 ). The small-scale oceanic features are caused by two primary mechanisms. The first mechanism is that of the ocean velocity, since stress can be approximated as a quadratic function of the relative velocity between the atmosphere and ocean ( Pacanowski 1987 ). The
1. Introduction Recent studies about global warming or multidecadal variability in the climate system indicate a poleward shift or long-term oscillation of the westerly wind over the Southern Ocean (e.g., Cai et al. 2003 ). The responses in the ocean to changes in wind stress over the Southern Ocean were investigated in previous studies (e.g., Oke and England 2004 ). In the latitude band containing the Drake Passage, meridional geostrophic flow zonally integrated above the sill depth must be
1. Introduction Recent studies about global warming or multidecadal variability in the climate system indicate a poleward shift or long-term oscillation of the westerly wind over the Southern Ocean (e.g., Cai et al. 2003 ). The responses in the ocean to changes in wind stress over the Southern Ocean were investigated in previous studies (e.g., Oke and England 2004 ). In the latitude band containing the Drake Passage, meridional geostrophic flow zonally integrated above the sill depth must be
drought, failed to respond quickly to drought stress on crops that were primarily responding to moisture sometimes in the first few inches of top soil. Palmer (1968) developed a shorter-term index called the crop moisture index (CMI). While the PDSI and CMI can accept higher-resolution inputs, they have primarily been driven by the National Weather Service (NWS) Cooperative Observer Program coarse-resolution data for rainfall and soil characteristics and retained the simplified evaporative loss
drought, failed to respond quickly to drought stress on crops that were primarily responding to moisture sometimes in the first few inches of top soil. Palmer (1968) developed a shorter-term index called the crop moisture index (CMI). While the PDSI and CMI can accept higher-resolution inputs, they have primarily been driven by the National Weather Service (NWS) Cooperative Observer Program coarse-resolution data for rainfall and soil characteristics and retained the simplified evaporative loss
optimal sizes of errors are sought by minimizing a cost function that requires knowledge of the statistical properties of those errors. Generally, estimating an adequate structure for the statistical properties is not a trivial task and we need to model them with certain assumptions. In this study, we investigate the impact of the assumptions we make for the wind stress error covariance function in estimating wind-driven basin-scale ocean circulation. The statistical properties of the wind stress
optimal sizes of errors are sought by minimizing a cost function that requires knowledge of the statistical properties of those errors. Generally, estimating an adequate structure for the statistical properties is not a trivial task and we need to model them with certain assumptions. In this study, we investigate the impact of the assumptions we make for the wind stress error covariance function in estimating wind-driven basin-scale ocean circulation. The statistical properties of the wind stress
1. Introduction Wind stress at the sea surface is the main driver of global ocean circulation, redistributing mass, momentum, and energy in the ocean (e.g., Gill 1982 ; Wunsch and Ferrari 2004 ). Moreover, representing the momentum flux between the atmosphere and the ocean, surface wind stress is one of the key factors controlling oceanic turbulent mixing and therefore exerts significant impacts on ocean temperature and salinity (e.g., Ouni et al. 2021 ; Zhou et al. 2018 ). Due to the
1. Introduction Wind stress at the sea surface is the main driver of global ocean circulation, redistributing mass, momentum, and energy in the ocean (e.g., Gill 1982 ; Wunsch and Ferrari 2004 ). Moreover, representing the momentum flux between the atmosphere and the ocean, surface wind stress is one of the key factors controlling oceanic turbulent mixing and therefore exerts significant impacts on ocean temperature and salinity (e.g., Ouni et al. 2021 ; Zhou et al. 2018 ). Due to the
for June, July, and August (JJA) from 46 yr of International Comprehensive Ocean–Atmosphere Dataset (ICOADS) release 2.1 ( Worley et al. 2005 ). These ship-based observations are heavily biased in favor of the Northern Hemisphere and along major shipping routes. This is particularly true for the austral winter months (JJA) when the sampling of the Southern Ocean is reduced to almost zero. HR presented the first ship-based monthly climatology of wind stress and wind stress curl fields on a global
for June, July, and August (JJA) from 46 yr of International Comprehensive Ocean–Atmosphere Dataset (ICOADS) release 2.1 ( Worley et al. 2005 ). These ship-based observations are heavily biased in favor of the Northern Hemisphere and along major shipping routes. This is particularly true for the austral winter months (JJA) when the sampling of the Southern Ocean is reduced to almost zero. HR presented the first ship-based monthly climatology of wind stress and wind stress curl fields on a global
under heat stress, 35% of workers experience occupational heat strain, while 30% of workers report productivity losses ( Flouris et al. 2018a ). However, occupational heat stress has been mainly studied to date in jobs associated with the military, construction, mining, agricultural, and metal industries ( Brake and Bates 2002 ; Hunt et al. 2016 ; Jay and Brotherhood 2016 ; Krishnamurthy et al. 2017 ; Ryan and Euler 2017 ), as they include intense physical activity, wearing of protective
under heat stress, 35% of workers experience occupational heat strain, while 30% of workers report productivity losses ( Flouris et al. 2018a ). However, occupational heat stress has been mainly studied to date in jobs associated with the military, construction, mining, agricultural, and metal industries ( Brake and Bates 2002 ; Hunt et al. 2016 ; Jay and Brotherhood 2016 ; Krishnamurthy et al. 2017 ; Ryan and Euler 2017 ), as they include intense physical activity, wearing of protective
1. Introduction and motivation The momentum exchange between the atmosphere and ocean through wind stress is of importance for many purposes, including air–sea interaction studies, climate studies, ocean modeling, and ocean prediction. Wind stress is typically obtained from bulk parameterizations that estimate turbulent fluxes using standard meteorological data (e.g., Fairall et al. 2003 ). In particular, the total wind stress magnitude ( τ ) at the ocean surface can be calculated from the
1. Introduction and motivation The momentum exchange between the atmosphere and ocean through wind stress is of importance for many purposes, including air–sea interaction studies, climate studies, ocean modeling, and ocean prediction. Wind stress is typically obtained from bulk parameterizations that estimate turbulent fluxes using standard meteorological data (e.g., Fairall et al. 2003 ). In particular, the total wind stress magnitude ( τ ) at the ocean surface can be calculated from the
