Cross-Calibrated Multi-Platform Ocean Surface Wind Vector Analyses

Background

The Cross-Calibrated Multi-Platform (CCMP) Ocean Surface Wind Vector Analyses (Atlas et al., 2011) provide a consistent, gap-free long-term time-series of ocean surface wind vector analysis fields from July 1987 through June 2011. The CCMP datasets combine cross-calibrated satellite winds using a Variational Analysis Method (VAM) to produce a high-resolution (0.25 degree) gridded analysis. The CCMP dataset uses satellite winds derived by Remote Sensing Systems (RSS) from a number of microwave satellite instruments. RSS intercalibrates radiometers on the brightness temperature level to within 0.5 deg C and applies a highly refined sea-surface emissivity model and radiative transfer function to derive surface winds.  This results in high consistency  between wind speed retrievals from microwave radiometers (i.e., SSM/I, SSMIS, AMSR, TMI, and WindSat).  RSS also has developed a geophysical model function for deriving wind speeds and directions from microwave scatterometers (including QuikScat and SeaWinds).  Both radiometer and scatterometer data are validated against ocean moored buoys, which prove the measurements are in excellent agreement (within 0.8 m/s) despite the different instrument measurement dynamics wind retrieval methodologies. The VAM (Hoffman et al., 2003) combines the RSS 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. Three globally gridded datasets are distributed to complete the CCMP dataset series: 1) gridded swaths of ascending and descending platform-specific passive radiometer wind speeds with CCMP-derived wind directions (L2.5); 2) fully-assimilated gap-free 6-hourly surface wind fields (L3.0); and 3) monthly and 5-day averaged surface wind fields (L3.5).

RMS speed difference (top) and mean speed difference (bottom) for each analysis versus the cross-calibrated satellite surface wind datasets that were assimilated. A negative mean speed difference indicates that the analysis wind speed is less than the satellite wind speed. Statistics were calculated in 1-month bins starting in July 1987. Image from Atlas et al., 2011.
Figure Caption:
RMS speed difference (top) and mean speed difference (bottom) for each analysis versus the cross-calibrated satellite surface wind datasets that were assimilated. A negative mean speed difference indicates that the analysis wind speed is less than the satellite wind speed. Statistics were calculated in 1-month bins starting in July 1987. Image from Atlas et al., 2011.

Contents

Snapshot of CCMP 6-hourly wind fields on 1 June 2008 00Z. Typhoon 06W (Nakri) is visible in this image north east of the Philippines. Wind data during this time was assimilated from the following satellite instruments: QuikSCAT, SSM/I F13, SSM/I F14, TMI, and AMSRE
Figure Caption:
Snapshot of CCMP 6-hourly wind fields on 1 June 2008 00Z. Typhoon 06W (Nakri) is visible in this image north east of the Philippines. Wind data during this time was assimilated from the following satellite instruments: QuikSCAT, SSM/I F13, SSM/I F14, TMI, and AMSRE.

The data assimilated into the CCMP analyses span specific time periods throughout the CCMP time series. From 1987 through 1989, CCMP assimilated wind data from a single satellite source, SSM/I F08. From 1990 through most of 2009 wind data was acquired from at least 2 operational SSM/I platforms. From 2010 onward, data the  SSMIS instrument on F17 replaced data from retired SSM/I instruments. Additional radiometer wind speed data became available from TMI since 1997 and AMSRE since 2002. Due to the inherent limitations of passive radiometer wind data (Wentz et al., 1986), namely the inability to determine accurate surface wind direction, it was decided to begin assimilating scatterometer data into CCMP, from QuikSCAT, which operatedfrom 1999 through 2009 and from SeaWinds on ADEOS-II which operated for a brief 6-month period in 2003. New technology developed by the U.S. Navy provided for a polarimetric radiometer known as WindSat, which is the first passive microwave radiometer to provide directional information in the surface wind fields. Assimilation of WindSat began in 2010 after QuikSCAT data were no longer available and continues through 2011. WindSat began operating in 2003, but retrieval of accurate wind directions has proven elusive, and, to date, CCMP only assimilates WindSat wind speeds. CCMP also assimilates surface wind vector data from in situ sources, such as TAO, PIRATA, and NCEP quality-controlled GDAS1 data.

What makes this dataset unique?

For many applications and research perspectives, consistent oceanic surface wind data of high quality and high temporal and spatial resolution are required to understand and predict large scale air-sea interactions which influence both the atmosphere and ocean. The dynamic nature of wind combined with the difficulties in providing globally gridded, gap-free, and high-quality wind vector analysis fields at sub-daily temporal and sub-synoptic spatial resolution presents a challenge to both data providers and user communities alike. In weather applications, forecasters need to assess the skill of their forecast models, particularly in cases where ocean surface wind observations of hurricanes are either unavailable or unreliable. For climate applications, obtaining consistent, gap-free wind vector data of sufficient time series length is of critical importance in resolving wind-induced climate patterns such as the El Niño-Southern Oscillation (ENSO) and Madden-Julian Oscillation (MJO). Through many years of improvements to the RSS validation and cross-calibration and to the VAM data assimilation technique, CCMP has been able to achieve consistently high quality wind speeds at spatial resolutions appropriate to the satellite data sources. The grid resolution of 0.25 degree latitude by longitude significantly surpasses that of any operational analysis or reanalysis dataset that exists for surface winds. The current version of CCMP datasets are based on a heritage of decades of peer-reviewed research and development (Atlas et al. 1996).

CCMP is the first and one of the few, if any, existing surface wind analysis products that has bridged the gap between state-of-the-art data assimilation and cross-calibration of wind data from uniquely different sensors, such as scatterometers and passive microwave radiometers. CCMP has wide-ranging appeal to users in educational, operational and research environments.