Cal/Val Discussion

Summary

• No large errors in rain, freshening observed by Aquarius can be significant and real (up to about 3 hours on average after rain)– Incorporation of CMORPH rain will improve time co-incident observations in rain– Rain roughness signature appears to be absorbed into roughness correction

• SST correlated bias appears to also have a wind speed dependence– Both oxygen absorption model and dielectric model can create bias structure similar

to that observed– An SST dependence of the wind/roughness correction likely also a factor

• The ancillary SST accuracy is very important and significant biases between products have been shown– A systematic comparison is needed

• A drift in the scatterometer produces a ~0.2 m/s drift in the windspeed over the first ~3months of the mission– Will have some impact on Aquarius calibration

• An instrument only based calibration removes the quasi-monthly wiggles, but long term drift may still be an issue

V4 and Beyond• Decide on approach address apparent SST dependence of retrievals• Determine best ancillary SST product to use in the retrieval algorithm• Create instrument only wiggle corrected product then assess different

techniques for long term drift removal by validating independently against ARGO– e.g Cold sky calibrations, Antarctica

• Include RIM product to identify observations with surface freshening– Useful for cal/val and science applications

• Incorporate tuned RFI filters for high-level RFI and incorporate correction for low-level RFI

• Incorporate real Aquarius or SMAP land TB maps into land correction algorithm

• Evaluate nature of residual inter-beam biases and determine cause