Cross-Calibrated Multi-Platform Ocean Surface Wind Vector L2.5 First-Look SSM/I-F13 Microwave Analyses
(CCMP_MEASURES_ATLAS_L3_OW_L2_5_SSMI_F13_WIND_VECTORS_FLK)This dataset will be available through Earthdata Cloud only, starting September, 2022. Learn More
44 Publications Cited this Dataset
Citation metrics available for years (2014-2021)
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Publications citing Cross-Calibrated Multi-Platform Ocean Surface Wind Vector L2.5 First-Look SSM/I-F13 Microwave Analyses
Citation metrics available for years (2014-2021)
| Year | Citation |
|---|---|
| 2015 | Seasonal SSH variability of the northern South China Sea, Journal of Physical Oceanography,https://doi.org/10.1175/JPO-D-14-0193.1 |
| 2015 | Evaluation of the simulation capability of the Wavewatch III model for Pacific Ocean wave, Acta Oceanologica Sinica,https://doi.org/10.1007/s13131-015-0737-1 |
| 2015 | Features of near-inertial motions observed on the northern South China Sea shelf during the passage of two typhoons, Acta Oceanologica Sinica,https://doi.org/10.1007/s13131-015-0594-y |
| 2015 | Atlas, R., Ardizzone, J. V., Hoffman, R., Jusem, J. C., and Leidner, S. M.: Cross-calibrated, multi-platform ocean surface wind velocity product (MEaSUREs Project), Guide Document, Physical Oceanography Distributed Active Archive Center (PODAAC), JPL, Pasadena, Cali5 fornia, 18 May 2009, Version 1.0., 26 pp., 2009. Long-term variability of the South Adriatic circulation and phytoplankton biomass in relation to large-scale climatic pattern., Ocean Science Discussions,https://doi.org/10.5194/osd-12-203-2015 |
| 2015 | Low‐salinity water off West Luzon Island in summer, Journal of Geophysical Research: Oceans,https://doi.org/10.1002/2014JC010465 |
| 2015 | Natural variability of surface oceanographic conditions in the offshore Gulf of Mexico, Progress in Oceanography,https://doi.org/10.1016/j.pocean.2014.12.007 |
| 2015 | Characterization of the seascape used by juvenile and wintering adult Southern Giant Petrels from Patagonia Argentina, Estuarine, Coastal and Shelf Science,https://doi.org/10.1016/j.ecss.2014.12.007 |
| 2015 | CO2 flux variability in the Galician and Californian upwelling systems |
| 2015 | Phytoplankton phenology in the coastal upwelling region off central‐southern C hile (35° S–38° S): Time‐space variability, coupling to environmental factors, and …, Journal of Geophysical Research: Oceans,https://doi.org/10.1002/2014JC010330 |
| 2015 | Coastal circulation driven by short-period upwelling-favorable winds in the northern Baja California region, Deep Sea Research Part I: Oceanographic Research Papers,https://doi.org/10.1016/j.dsr.2014.12.003 |
| 2015 | Quantitative characterization of spurious numerical oscillations in 48 CMIP5 models, Geophysical Research Letters,https://doi.org/10.1002/2015GL063931 |
| 2015 | Detection of mesoscale thermal fronts from 4 km data using smoothing techniques: Gradient-based fronts classification and basin scale application, Remote sensing of environment,https://doi.org/10.1016/j.rse.2015.03.030 |
| 2015 | Reconstruction of super-resolution fields of ocean pCO2 and air–sea fluxes of CO2 from satellite imagery in the Southeastern Atlantic, Biogeosciences,https://doi.org/10.5194/bgd-12-1405-2015 |
| 2015 | Establishment and tests of EnOI assimilation module for WAVEWATCH III, Chinese journal of oceanology and limnology,http://dx.doi.org/10.1007/s00343-015-4282-8 |
| 2016 | Causes for intraseasonal sea surface salinity variability in the western tropical P acific O cean and its seasonality, Journal of Geophysical Research: Oceans,https://doi.org/10.1002/2015JC011413 |
| 2016 | Atlas, R., Ardizzone, J. V., Hoffman, R., Jusem, J. C. and Leidner, S. M.: Cross-calibrated, multiplatform ocean surface wind velocity product (MEaSUREs Project). Guide Document. Physical Oceanography Distributed Active Archive Center (PO.DAAC). JPL, Pasadena, California, 18 May 2009, Version 1.0., 26p, 2009. Mediterranean thermohaline properties and large-scale climatic patterns,https://arts.units.it/handle/11368/2908028 |
| 2016 | Seasonal cycle of nearbottom transport and currents in the northern Gulf of California, Journal of Geophysical,https://doi.org/10.1002/2016JC012063 |
| 2016 | Common characteristics of directional spreadingsteepness joint distribution in freak wave events, Ocean Science,https://doi.org/10.5194/os-12-781-2025 |
| 2016 | Anomalous Java cooling at the initiation of positive Indian Ocean Dipole events, Journal of Geophysical,https://doi.org/10.1002/2016JC011635 |
| 2016 | Impacts of reprocessed altimetry on the surface circulation and variability of the Western Alboran Gyre, Advances in Space Research,https://doi.org/10.1016/j.asr.2016.05.026 |
| 2016 | Global oceanic wind speed trends, Ocean & Coastal Management,https://doi.org/10.1016/j.ocecoaman.2016.05.001 |
| 2016 | Evaluation of Different Wind Fields for Storm surge Modeling in the Persian Gulf, core.ac.uk |
| 2016 | Comments from the editors and reviewers, researchgate.net,https://doi.org/10.1016/j.csr.2017.05.011 |
| 2016 | On the role of atmospheric forcing on upper ocean physics in the Southern Ocean and biological impacts,https://escholarship.org/uc/item/5qs1x85p |
| 2016 | Phenology of size-partitioned phytoplankton carbon-biomass from ocean color remote sensing and cmip5 models,https://doi.org/10.3389/fmars.2016.00039 |
| 2016 | Coupled patterns between the surface chlorophyll-a and the physical factors in the Pacific Ocean, International conference on Geoscience and Remote Sensig,https://doi.org/10.1109/IGARSS.2016.7730195 |
| 2016 | O Estudo da interao oceano-atmosfera em um ciclone extratropical no Atlntico Sudoeste: uma abordagem numrica em altssima resoluo |
| 2016 | Atlas, R., Ardizzone, J. V., Hoffman, R., Jusem, J. C., and Leidner, S. M.: Cross-calibrated, multi-platform ocean surface wind velocity product (MEaSUREs Project), Guide Document, Physical Oceanography Distributed Active Archive Center (PO.DAAC), JPL, Pasadena, California, 18 May 2009, Version 1.0., 26 pp., 2009. Long-term variability of the southern Adriatic circulation in relation to North Atlantic Oscillation, Ocean,https://doi.org/10.5194/os-12-233-2016 |
| 2017 | Environmental effects on the spatiotemporal patterns of abundance and distribution of Sardina pilchardus and sardinella off the Mauritanian coast (NorthWest Africa, Fisheries |
| 2017 | Factors influencing the skill of synthesized satellite wind products in the tropical Pacific, Journal of Geophysical Research: Oceans,https://doi.org/10.1002/2016JC012340 |
| 2017 | Comparison of the ocean surface vector winds from atmospheric reanalysis and scatterometerbased wind products over the Nordic Seas and the northern North, Journal of Geophysical Research: Oceans,https://doi.org/10.1002/2016JC012453 |
| 2017 | OPeNDAP link wrong Distribution of sea-air CO2 fluxes in the Patagonian Sea: seasonal, biological and thermal effects, Continental Shelf,https://doi.org/10.1016/j.csr.2017.05.011 |
| 2017 | Recent Decadal Trend in the North Atlantic Wind Energy Resources, Advances in Meteorology,https://doi.org/10.1155/2017/7257492 |
| 2017 | Trends in significant wave height and surface wind speed in the China Seas between 1988 and 2011, Journal of Ocean University of,https://doi.org/10.1007/s11802-017-3213-z |
| 2019 | Multidecadal wind variability drives temperature shifts on the Agulhas Bank, Journal of Geophysical Research: Oceans,https://doi.org/10.1029/2018JC014614 |
| 2019 | Wind and Wave Energy in the Important Waters of the South China Sea, 21st Century Maritime Silk Road: Construction of Remote Islands and Reefs,https://doi.org/10.1007/978-981-10-8114-9_5 |
| 2019 | CMIP5-based wave energy projection: case studies of the South China Sea and the East China Sea, IEEE Access,https://doi.org/10.1109/ACCESS.2019.2924197 |
| 2019 | Roles of different physical processes in upper ocean responses to Typhoon Rammasun (2008)-induced wind forcing, Science China Earth Sciences,https://doi.org/10.1007/s11430-018-9313-8 |
| 2019 | Sea surface temperature, ocean color and wind forcing patterns in the Bay of La Paz, Gulf of California: Seasonal variability, Atmósfera,http://doi.org/10.20937/atm.2019.32.01.03 |
| 2019 | Global pattern of phytoplankton diversity driven by temperature and environmental variability, Science Advances,10.1126/sciadv.aau6253 |
| 2019 | Stokes 漂流近似公式对海洋表层流场估算的影响, 海洋与湖沼,http://dx.doi.org/10.11693/hyhz20180500110 |
| 2019 | https://podaac.jpl.nasa.gov/Cross_Calibrated_Multi_ Platform_OceanSurfaceWindVectorAnalyses. Diakses bulan Januari 2016. KAJIAN INDEKS VARIABILITAS TINGGI GELOMBANG SIGNIFIKAN DI INDONESIA, Jurnal Segara,https://doi.org/10.15578/segara.v14i3.6650 |
| 2019 | Micro-scale classification of offshore wind energy resource——A case study of the New Zealand, Journal of Cleaner Production,https://doi.org/10.1016/j.jclepro.2019.04.082 |
| 2019 | Assessment of Significant Wave Height in the Taiwan Strait Measured by a Single HF Radar System, Journal of Atmospheric and Oceanic Technologies,https://doi.org/10.1175/JTECH-D-18-0146.1 |
| DOI | 10.5067/CCF25-01F13 |
| Short Name | CCMP_MEASURES_ATLAS_L3_OW_L2_5_SSMI_F13_WIND_VECTORS_FLK |
| Description | This dataset is derived under the Cross-Calibrated Multi-Platform (CCMP) project and contains value-added Special Sensor Microwave Imager (SSM/I) ocean surface winds from the Defense Meteorological Satellite Program (DMSP) F13 platform. The CCMP datasets combine cross-calibrated satellite winds obtained from Remote Sensing Systems (REMSS) using a Variational Analysis Method (VAM) to produce a high-resolution (0.25 degree) gridded analysis. Wind directions from the resulting analysis are assigned to the location and time of the satellite-derived wind speed observations to create this value added dataset. The CCMP data set includes cross-calibrated satellite winds derived from SSM/I, SSMIS, AMSR-E, TRMM TMI, QuikSCAT, SeaWinds, WindSat and other satellite instruments as they become available from REMSS. REMSS uses a cross-calibrated sea-surface emissivity model function which improves the consistency between wind speed retrievals from microwave radiometers (i.e., SSM/I, SSMIS, AMSR, TMI, and WindSat) and those from scatterometers (i.e., QuikSCAT and SeaWinds). The VAM combines these data with in situ measurements and a starting estimate (first guess) of the wind field. The European Center for Medium-Range Weather Forecasts (ECMWF) ERA-40 Reanalysis is used as the first-guess from 1987 to 1998. The ECMWF Operational analysis is used from January 1999 onward. All wind observations and analysis fields are referenced to a height of 10 meters. The ERA-40 can be obtained from the Computation and Information Systems Laboratory (CISL) at the National Center for Atmospheric Research (NCAR): http://rda.ucar.edu/datasets/ds117.0/. The ECMWF Operational analysis can also be obtained from CISL at NCAR: http://rda.ucar.edu/datasets/ds111.1/. Three products are distributed to complete the CCMP dataset series. L3.0 product contains high-resolution analyses every 6-hours. These data are then time averaged over monthly and 5-day periods to derive the L3.5 product. Directions from the L3.0 product are then assigned to the time and location of the passive microwave satellite wind speed observations to derive the L2.5 product. All datasets are distributed on a 0.25 degree cylindrical coordinate grid. This dataset is one in a series of First-Look (FLK) CCMP datasets and is a continuation and expansion of the SSM/I surface wind velocity project that began under the NASA Pathfinder Program. Refinements and upgrades to the FLK version will be incorporated under a new release (date to be determined) known as Late-look (LLK) and may include additional satellite datasets. All satellite surface wind data are obtained from REMSS under the DISCOVER project: Distributed Information Services: Climate/Ocean Products and Visualizations for Earth Research (http://www.discover-earth.org/index.html). The CCMP project is the result of an investigation funded by the NASA Making Earth Science data records for Use in Research Environments (MEaSUREs) program (http://community.eosdis.nasa.gov/measures/). In accordance with the MEaSUREs program, the CCMP datasets are also known as Earth System Data Records (ESDRs). In collaboration with private and government institutions, a team led by Dr. Robert Atlas (PI; proposal originally solicited by REASoN, and currently funded by MEaSURES) has created the CCMP project to provide multi-instrument ocean surface wind velocity ESDRs, with wide ranging research applications in meteorology and oceanography. |
| Version | 1 |
| Dataset Type | COMPLETE |
| Measurement | OCEANS > OCEAN WINDS > SURFACE WINDS |
| Processing Level | 3 |
| Coverage | Region: GLOBAL North Bounding Coordinate: 89.875 degrees South Bounding Coordinate: -89.875 degrees West Bounding Coordinate: -180 degrees East Bounding Coordinate: 180 degrees Time Span: 1995-May-03 to 2009-Nov-18 |
| Resolution | Spatial Resolution: 0.25 Decimal Degrees x 0.25 Decimal Degrees Temporal Resolution: 12 Hour |
| Projection | Projection Type: Gridded Ellipsoid: WGS 84 |
| Platform/Sensor | DMSP 5D-2/F13 / Platform Name: Defense Meteorological Satellite Program-F13 (DMSP 5D-2/F13) Orbit Period: 102.0 minutes Inclination Angle: 98.8 degrees SSM/I SENSOR Name: Special Sensor Microwave Imager (SSM/I) Swath Width: 1394.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. |
| Project | Making Earth Science Data Records for Use in Research Environments (MEaSUREs) |
| Data Provider | Publisher: PO.DAAC Creator: NASA/GSFC/NOAA Release Place: PO.DAAC Release Date: 2009-May-08 Resource: https://podaac-tools.jpl.nasa.gov/drive/files/allData/ccmp/L2.5/docs/ccmp_users_guide.pdf |
| Keyword(s) | wind data, wind, ocean wind, wind speed, vector, vectors, ocean wind vector, ocean wind vectors, cross-calibrated, multi-platform, ccmp, analysis, analyses, gridded, ssm/i, ssmi, dmsp, f13, assimilated, measures, ecmwf |
Questions related to this dataset? Contact podaac@podaac.jpl.nasa.gov
| DIRECT ACCESS | |
| PO.DAAC DRIVE | https://podaac-tools.jpl.nasa.gov/drive/files/allData/ccmp/L2.5/flk |
| Web Service | https://podaac.jpl.nasa.gov/ws/search/granule/?datasetId=PODAAC-CCF25-01F13&apidoc |
| Format | BINARY |
| DATA CITATION POLICY | |
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Citation is critically important for dataset documentation and discovery. Please cite the data as follows, and cite the reference papers when it is appropriate.
| Citation | NASA/GSFC/NOAA. 2009. Cross-Calibrated Multi-Platform Ocean Surface Wind Vector L2.5 First-Look SSM/I-F13 Microwave Analyses. Ver. 1. PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5067/CCF25-01F13
For more information see Data Citations and Acknowledgments.
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| Journal Reference | Atlas, R., R. N. Hoffman, J. Ardizzone, S. M. Leidner, J. C. Jusem, D. K. Smith, D. Gombos, 2011: A cross-calibrated, multiplatform ocean surface wind velocity product for meteorological and oceanographic applications. Bull. Amer. Meteor. Soc., 92, 157-174. doi: 10.1175/2010BAMS2946.1 . |
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