Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling

Bourassa, Mark A.

doi:10.5270/oceanobs09.cwp.08

Cited by 52 publications

(47 citation statements)

References 66 publications

(82 reference statements)

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“…[2] Ocean surface wind vectors are important in many applications, including weather prediction, understanding dynamical forcing of the ocean, and studying air-sea interactions and climate [Huddleston and Spencer, 2001;Liu, 2002;Bourassa et al, 2010b]. Scatterometers, radar altimeters, synthetic aperture radars (SAR), microwave radiometers, and in situ observations provide different methods of obtaining wind speeds, and in some cases directions, globally over the ocean; however, scatterometers have proven to be the most effective instrument for retrieving ocean surface vector winds [Liu and Xie, 2006].…”

Section: Introductionmentioning

confidence: 99%

Quantifying variance due to temporal and spatial difference between ship and satellite winds

May

Bourassa

2011

J. Geophys. Res.

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[1] Ocean vector winds measured by SeaWinds can be validated with comparison in situ data that are within a certain time and space range to the satellite overpass. The total amount of random observational error is composed of two primary components, which are quantified in this study: the uncertainty associated with the data sets and the uncertainty associated with the temporal and/or spatial difference between two observations. The variance associated with a temporal difference, which can be translated into a spatial difference using Taylor's hypothesis, between two observations is initially examined in an idealized case that includes only Shipboard Automated Meteorological and Oceanographic System (SAMOS) 1 min data. The results show that the amount of variance in wind speed and direction increases as the time difference increases, while the amount of variance in wind speed increases and direction decreases with larger wind speeds. Collocated SeaWinds and SAMOS observations are used to determine the total amount of variance associated with a temporal (equivalent) difference from 0 to 60 min. For combined differences less than 25 min (equivalent) and the selected wind speed bins, the variance associated with the temporal and spatial difference is dominated by small changes in the wind speed distribution, and the sum of the observational errors is approximately 1.0 m 2 s −2 (12 deg 2 ) and 1.5 m 2 s −2 (10 deg 2 ) for wind speeds between 4 and 7 m s −1 and 7-12 m s −1 . For larger combined differences, the observational error variance is no longer the dominant term; therefore, the total variance is seen to gradually increase with increasing time differences.Citation: May, J. C., and M. A. Bourassa (2011), Quantifying variance due to temporal and spatial difference between ship and satellite winds,

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Section: Introductionmentioning

confidence: 99%

Quantifying variance due to temporal and spatial difference between ship and satellite winds

May

Bourassa

2011

J. Geophys. Res.

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“…The main advantages of point (1) are related to the excellent spatial and temporal coverage of the wind speed owing to the large swaths of scatterometers and microwave radiometers, and to the mature algorithms for retrieving wind speed from satellite measurements (the rms difference of satellite wind speed with respect to buoy neutral wind speeds being on the order of 1 m s -1 (Bourassa et al 2010)), while field measurements almost always provide k w and U simultaneously, but not always surface stress. Although satellite wind speeds are expressed as neutral wind speeds to facilitate the comparison with in situ measurements, a scatterometer measures a backscatter coefficient that is related to resonant Bragg scattering by centimetric waves.…”

Section: Remote Sensingmentioning

confidence: 99%

Transfer Across the Air-Sea Interface

Garbe

Rutgersson

Boutin

et al. 2013

Springer Earth System Sciences

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The efficiency of transfer of gases and particles across the air-sea interface is controlled by several physical, biological and chemical processes in the atmosphere and water which are described here (including waves, large-and small-scale turbulence, bubbles, sea spray, rain and surface films). For a deeper understanding of relevant transport mechanisms, several models have been developed, ranging from conceptual models to numerical models. Most frequently the transfer is described by various functional dependencies of the wind speed, but more detailed descriptions need additional information. The study of gas transfer mechanisms uses a variety of experimental methods ranging from laboratory studies to carbon budgets, mass balance methods, micrometeorological techniques and thermographic techniques. Different methods resolve the transfer at different scales of time and space; this is important to take into account when comparing different results. Air-sea transfer is relevant in a wide range of applications, for example, local and regional fluxes, global models, remote sensing and computations of global inventories. The sensitivity of global models to the description of transfer velocity is limited; it is however likely that the formulations are more important when the resolution increases and other processes in models are improved. For global flux estimates using inventories or remote sensing products the accuracy of the transfer formulation as well as the accuracy of the wind field is crucial. IntroductionThe transfer of gases and particles across the air-sea interface depends not only on the concentration difference between the water and the air, but also on the efficiency of the transfer process. The efficiency of the transfer is controlled by complex interaction of a variety of processes in the air and in the water near the interface. Here we treat both gases and particles since the transfer, to some extent, is governed by similar mechanisms. Studies of transfer across the air-sea interface include a variety of methods and techniques ranging from laboratory studies, modeling and large-scale field studies. Various methods reach somewhat different conclusions, due to representation of different

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“…Several reviews of space-based wind measurements and applications have been published (i.e. Liu 2002;Liu et al 2008;Bourassa et al 2010). The challenge is to continuously improve the present ocean wind system by means of better bias removal and calibration for low and very high wind speeds, increased temporal sampling using a constellation of instruments, finer spatial resolution and improved methods of fusing observations from multiple platforms.…”

Section: Altimetry Sst Winds Sea Statementioning

confidence: 99%

Ocean-Atmosphere Interactions of Gases and Particles

2014

Springer Earth System Sciences

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Why a chapter on Perspectives and Integration in SOLAS Science in this book? SOLAS science by its nature deals with interactions that occur: across a wide spectrum of time and space scales, involve gases and particles, between the ocean and the atmosphere, across many disciplines including chemistry, biology, optics, physics, mathematics, computing, socio-economics and consequently interactions between many different scientists and across scientific generations. This chapter provides a guide through the remarkable diversity of cross-cutting approaches and tools in the gigantic puzzle of the SOLAS realm.Here we overview the existing prime components of atmospheric and oceanic observing systems, with the acquisition of ocean-atmosphere observables either from in situ or from satellites, the rich hierarchy of models to test our knowledge of Earth System functioning, and the tremendous efforts accomplished over the last decade within the COST Action 735 and SOLAS Integration project frameworks to understand, as best we can, the current physical and biogeochemical state of the atmosphere and ocean commons. A few SOLAS integrative studies illustrate the full meaning of interactions, paving the way for even tighter connections between thematic fields. Ultimately, SOLAS research will also develop with an enhanced consideration of societal demand while preserving fundamental research coherency.

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Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling

Cited by 52 publications

References 66 publications

Quantifying variance due to temporal and spatial difference between ship and satellite winds

Quantifying variance due to temporal and spatial difference between ship and satellite winds

Transfer Across the Air-Sea Interface

Ocean-Atmosphere Interactions of Gases and Particles

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