New Version 3.0 Cross-Calibrated Multi-Platform (CCMP) ocean vector wind analysis available now
Global, complete wind vector maps every 6 hours for 26+ years
A new version of the CCMP wind analysis (CCMP V3.0) is now available. CCMP is a level 4 wind product that uses a variational analysis method to combine satellite observations with a background field from weather model output to produce a globally complete wind product that closely follows satellite observations where and when they are available.
This new version is more accurate, particularly at winds above 15 m/s. The long-term trends are also more reliable and agree better with other long-term records of wind speed.
For now, the new version is available for 1993-2019. We are working to update it to the current date and put a system in place to update it with a latency of a few weeks.
The development of V3.0 was driven by several goals:
- Use a more up-to-date and regularly updated reanalysis product for the background wind field. Production of the ERA-Interim reanalysis ceased in July, 2019, forcing us to adopt a new background if we wanted to be able to extend CCMP beyond this time. We chose to move to ERA5 because it is available hourly, facilitating a future enhancement to CCMP for higher frequency analysis.
- Improve performance and agreement with satellite winds at high wind speed.
- Minimize spurious trends caused by satellite/background biases. As the amount of satellite data available changes over time, we take care to prevent biases from aliasing into long-term trends
The development philosophy we adopted assumes that the RSS-produced wind datasets from scatterometers (QuikSCAT and ASCAT) are accurate at all wind speeds. These winds have been validated via comparison with winds from moored buoys at low and moderate wind speeds. Above ~20 m/s buoy winds become increasingly less reliable because of wave-shadowing, tilting of the buoys, and the effects of spray in various types of anemometers. RSS scatterometer winds are validated at high winds by:
- Comparison with airborne Stepped Frequency Microwave Radiometer (SFMR) measurements flown in tropical cyclones, which are, in turn, anchored by wind speeds from dropsondes [Meissner et al 2017]. The SMAP winds validated in [Meissner et al 2017] are compared to ASCAT winds in [Ricciardulli et al. 2021].
- Comparison with winds measured by Saildrones in tropical cyclones [Ricciardulli et al. 2022].
- Comparison with winds from oil platforms in the North Sea [Manaster et al 2019].
What's new in V3.0?
- V3.0 uses ERA5 Neutral Stability (NS) winds as a background field. V2.0 used unadjusted ERA-Interim 10m winds as its background field.
- ERA5 NS winds are adjusted to account for ocean surface currents using the Ocean Surface Current Analysis Real-time (OSCAR) dataset. Satellite winds are measured relative to the moving ocean surface so the background fields need to be adjusted to this frame of reference before combining.
- A speed adjustment was applied to match the distribution of wind speeds in the ERA5 background to QuikSCAT and ASCAT measurements. The adjustment depends on time of year and latitude, but does not change from year to year, so it has no direct effect on long-term trends.
- A small seasonally dependent regional vector adjustment was applied to improve agreement between the adjusted ERA5 NS winds and scatterometers.
- Small regional adjustments were applied to radiometer winds before they are included. These adjustments are the largest for the "medium frequency" radiometers whose lowest frequency channel is 19 GHz (e.g., SSM/I and SSMIS). The 19 GHz winds are more strongly affected by anomalous atmospheric conditions than wind retrievals that use the lower 11 GHz channel. These adjustments were not used in CCMP V2.0.
- Because of the dependence on OSCAR ocean currents, CCMP 3.0 starts in 1993 when the OSCAR dataset begins.
These changes improve the accuracy of CCMP, particularly at winds above 15 m/s. The long-term trends are also more reliable and agree better with other long-term records of wind speed. Earlier versions of CCMP likely included spurious wind trends due to the mismatch between the satellite and background winds.
Mears, C.; Lee, T.; Ricciardulli, L.; Wang, X.; Wentz, F. Improving the Accuracy of the Cross-Calibrated Multi-Platform (CCMP) Ocean Vector Winds. Remote Sens. 2022, 14, 4230. https://doi.org/10.3390/rs14174230Meissner, T., L. Ricciardulli, and F.J. Wentz, 2017, Capability of the SMAP Mission to Measure Ocean Surface Winds in Storms, Bulletin of the American Meteorological Society 98(8), 1660-1677, https://doi.org/10.1175/BAMS-D-16-0052.1
Ricciardulli, L.; Foltz, G.R.; Manaster, A.; Meissner, T. Assessment of Saildrone Extreme Wind Measurements in Hurricane Sam Using MW Satellite Sensors. Remote Sens. 2022, 14, 2726. https://doi.org/10.3390/rs14122726
Ricciardulli L., Manaster A., 2021: Intercalibration of ASCAT Scatterometer Winds from MetOp-A, -B, and -C, for a Stable Climate Data Record. Remote Sensing, 13(18), 3678. https://doi.org/10.3390/rs13183678
Manaster, A., L. Ricciardulli, and T. Meissner, 2019: Validation of High Ocean Surface Winds from Satellites Using Oil Platform Anemometers. J. Atmos. Oceanic Technol., 36, 803–818, https://doi.org/10.1175/JTECH-D-18-0116.1