Abstract
Scatterometers provide very stable ocean vector wind data records. This is because they measure the ratio of backscattered to incident microwave signal over the ocean surface as opposed to an absolute quantity (e.g., emitted microwave signal). They provide an optimal source of observations for building a long ocean vector wind Climate Data Record (CDR). With this objective in mind, observations from different satellite platforms need to be assessed for high absolute accuracy versus a common ground truth and for fine cross-calibration during overlapping periods. Here we describe the methodology for developing a CDR of ocean surface winds from the C-band ASCAT scatterometers onboard MetOp-A, -B, and -C. This methodology is based on the following principles: a common Geophysical Model Function (GMF) and wind algorithm developed at Remote Sensing Systems (RSS) and the use of in situ and satellite winds to cross-calibrate the three scatterometers within the accuracy required for CDRs, about 0.1 m/s at the global monthly scale. Using multiple scatterometers and radiometers for comparison allows for the opportunity to isolate sensors that are drifting or experiencing step-changes as small as 0.05 m/s. We detected and corrected a couple of such changes in the ASCAT-A wind record. The ASCAT winds are now very stable over time and well cross-calibrated with each other. The full C-band wind CDR now covers 2007-present and can be easily extended in the next decade with the launch of the MetOp Second Generation scatterometers.
Highlights
The World Meteorological Organization (WMO) Global Climate Observing System (GCOS) identified ocean surface winds as one of the Essential Climate Variables [1].Changes in the surface wind patterns and intensity affect surface heat and moisture fluxes, impact the redistribution of heat and moisture by shifting convective regions, and affect the transfer of momentum to the ocean circulation
We explored the SST impact at C-band by using 10 years of ASCAT-A σ0 observations collocated with GMI wind speeds, NCEP wind directions, and SST from the Reynolds OISST dataset [58] interpolated to the ASCAT time/location
We document our efforts at Remote Sensing Systems (RSS) in making these observations consistent across different sensors, with different operating frequencies and viewing geometry, and meeting stringent accuracy requirements such that they can be combined into a Climate Data Record (CDR)
Summary
The World Meteorological Organization (WMO) Global Climate Observing System (GCOS) identified ocean surface winds as one of the Essential Climate Variables [1]. In terms of calibration targets for a given GMF, there are many options as the ground truth can be represented by in situ observations such as ocean buoys or airborne sensors, winds from numerical weather prediction models, wind retrievals from other space-based sensors, or a combination of these. For this reason, different GMFs are developed at different processing centers/institutions with assumptions that better fit their needs, whether it be processing winds for operational purposes in near-real-time, data assimilation, keeping the methodology consistent with previous versions/additional sensors, or using the retrievals to develop a CDR.
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