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A Cross-calibrated, Multiplatform Ocean Surface Wind Velocity Product for Meteorological and Oceanographic Applications
Abstract
The ocean surface wind mediates exchanges between the ocean and the atmosphere. These air–sea exchange processes are critical for understanding and predicting atmosphere, ocean, and wave phenomena on many time and space scales. A cross-calibrated multiplatform (CCMP) long-term data record of satellite ocean surface winds is available from 1987 to 2008 with planned extensions through 2012. A variational analysis method (VAM) is used to combine surface wind data derived from conventional and in situ sources and multiple satellites into a consistent nearglobal analysis at 25-km resolution, every 6 h. The input data are cross-calibrated wind speeds derived from the Special Sensor Microwave Imager (SSM/I; F08–F15), the Tropical Rainfall Measuring Mission Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), and wind vectors from SeaWinds on the NASA Quick Scatterometer (QuikSCAT) and on the second Japanese Advanced Earth Observing Satellite (ADEOS- 2; i.e., the Midori-2 satellite). These are combined with ECMWF reanalyses and operational analyses by the VAM. VAM analyses and derived data are currently available for interested investigators through the Jet Propulsion Laboratory (JPL) Physical Oceanography Distributed Active Archive Center (PO.DAAC). This paper describes the methodology used to assimilate the input data along with the validation and evaluation of the derived CCMP products. A supplement to this article is available online: DOI: 10.1175/2010BAMS2946.2
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Cited by
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Landschützer, P., Gruber, N., Bakker, D. C. E., & Schuster, U. (2014) · Global Biogeochemical Cycles · doi:10.1002/2014gb004853 · Cited by 524
Le Quéré, C., Peters, G. P., Andres, R. J., Andrew, R. M., Boden, T. A., Ciais, P., Friedlingstein, P., Houghton, R. A., Marland, G., Moriarty, R., et al. (2014) · Earth System Science Data · doi:10.5194/essd-6-235-2014 · Cited by 450
Global ocean carbon uptake: magnitude, variability and trends
Wanninkhof, R., Park, G. H., Takahashi, T., Sweeney, C., Feely, R., Nojiri, Y., Gruber, N., Doney, S. C., McKinley, G. A., Lenton, A., et al. (2013) · Biogeosciences · doi:10.5194/bg-10-1983-2013 · Cited by 382
Climate model biases in the eastern tropical oceans: causes, impacts and ways forward.
Richter, I. (2015) · WIREs Climate Change · doi:10.1002/wcc.338 · Cited by 253
Review and assessment of latent and sensible heat flux accuracy over the global oceans.
Bentamy, A., Piollé, J. F., Grouazel, A., Danielson, R., Gulev, S., Paul, F., Azelmat, H., Mathieu, P. P., von Schuckmann, K., Sathyendranath, S., et al. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.08.016 · Cited by 116
Metadata
- Authors
- Atlas, R., Hoffman, R. N., Ardizzone, J., Leidner, S. M., Jusem, J. C., Smith, D. K., & Gombos, D.
- Venue
- Bulletin of the American Meteorological Society
- Publisher
- American Meteorological Society
- Published
- 2011-02
- Volume
- 92
- Issue
- 2
- Pages
- 157-174
- ISSN
- 0003-0007 (ISSN-L)
- 1520-0477
- OpenAlex
- W2059734998
- Cited by
- 969
- References
- 0
- FWCI
- 18.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Atlas, R., Hoffman, R. N., Ardizzone, J., Leidner, S. M., Jusem, J. C., Smith, D. K., & Gombos, D. (2011). A Cross-calibrated, Multiplatform Ocean Surface Wind Velocity Product for Meteorological and Oceanographic Applications. Bulletin of the American Meteorological Society. https://doi.org/10.1175/2010bams2946.1
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