2008
DOI: 10.1175/2008jpo3881.1
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A Global Climatology of Surface Wind and Wind Stress Fields from Eight Years of QuikSCAT Scatterometer Data

Abstract: Global seasonal cycles of the wind and wind stress fields estimated from the 8-yr record (September 1999–August 2007) of wind measurements by the NASA Quick Scatterometer (QuikSCAT) are presented. While this atlas, referred to here as the Scatterometer Climatology of Ocean Winds (SCOW), consists of 12 variables, the focus here is on the wind stress and wind stress derivative (curl and divergence) fields. SCOW seasonal cycles are compared with seasonal cycles estimated from NCEP–NCAR reanalysis wind fields. The… Show more

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Cited by 475 publications
(371 citation statements)
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References 90 publications
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“…Upon preliminary inspection of these products, we observe that blooms (i.e., concentrations above 10 mg/m 3 ) are not present in the climatological chlorophyll product; more importantly, climatological wind vectors are spatially smoother and have smaller magnitude than those of December 2008 and 2009. Long-term means smooth out extremes, as expected, but we suspect that in the case of winds the difference in magnitudes may originate from the additional harmonic filtering performed by Risien and Chelton (2008) and/or the data source itself (ASCAT vs. QuikSCAT; Bentamy et al, 2012). To mitigate this problem, we decrease the intercept for the climatological prediction model by 2.5 units.…”
Section: Inter-annual Variabilitymentioning
confidence: 93%
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“…Upon preliminary inspection of these products, we observe that blooms (i.e., concentrations above 10 mg/m 3 ) are not present in the climatological chlorophyll product; more importantly, climatological wind vectors are spatially smoother and have smaller magnitude than those of December 2008 and 2009. Long-term means smooth out extremes, as expected, but we suspect that in the case of winds the difference in magnitudes may originate from the additional harmonic filtering performed by Risien and Chelton (2008) and/or the data source itself (ASCAT vs. QuikSCAT; Bentamy et al, 2012). To mitigate this problem, we decrease the intercept for the climatological prediction model by 2.5 units.…”
Section: Inter-annual Variabilitymentioning
confidence: 93%
“…The New Island 2009/2010 GLM was used in this exercise. QuikSCAT wind climatology (1999QuikSCAT wind climatology ( -2008 was provided by Risien and Chelton (2008, data available at http://cioss.coas.oregonstate.edu/scow/). Upon preliminary inspection of these products, we observe that blooms (i.e., concentrations above 10 mg/m 3 ) are not present in the climatological chlorophyll product; more importantly, climatological wind vectors are spatially smoother and have smaller magnitude than those of December 2008 and 2009.…”
Section: Inter-annual Variabilitymentioning
confidence: 99%
“…Atmospheric forcing is from monthly climatologies, which simplifies our investigation of basic upwelling dynamics by removing interannual and externally-forced, intraseasonal variability. Wind stress is from the Scatterometer Climatology of Ocean Winds (SCOW, Risien and Chelton 2008) and heat and freshwater fluxes are from the International Comprehensive Ocean Atmosphere Dataset (ICOADS, Worley et al 2005) 1 .…”
Section: Regional Ocean Modelmentioning
confidence: 99%
“…OAFlux products are constructed over the ocean from an optimal blending of satellite retrievals and three atmospheric reanalyses (Yu 2007;Yu et al 2008). To assess surface wind speeds, we used the Scatterometer Climatology of Ocean Winds (SCOW) product, derived from 122 months (September 1999-October 2009) of QuikSCAT scatterometer data and available over the ocean only (Risien and Chelton 2008). SCOW monthly 0.25° gridded fields were interpolated to N96 for comparison to MetUM output.…”
Section: Observational Datasetsmentioning
confidence: 99%