Version 7 SST from AMSR-E & WindSAT

Transcription

1 Version 7 SST from AMSR-E & WindSAT Chelle L. Gentemann, Thomas Meissner, Lucrezia Ricciardulli & Frank Wentz Retrieval algorithm Validation results RFI THE 44th International Liege Colloquium on Ocean Dynamics Liege, Belgium, 2012

2 Wind Speed AMSRE & WindSAT v7 Ocean Products L2, L3, and L4 Data produced in NRT at GHRSST format SST L2P and L2P_gridded at PO.DAAC Climate quality satellite inter-calibration and re-processing Geophysical data freely available via FTP Browse images, movies, sub-setting at SST Rain Rate Water Vapor Cloud

3 AMSR-E SST 2PM/AM Sunglint missing data in daytime

4 WindSAT 6AM/6PM Gap due to footprint matching With forward/back looks Sunglint missing data in daytime

5 V6 to V07 WindSAT v07 is first public release. V07 refers to the algorithm used to process all RSS passive MW instruments. SSMI is to be released in V07 any day now and TMI will follow in ~July There are 3 major V7 algorithm changes: the water vapor continuum absorption model was re-derived the clear-sky bias in cloud water was removed (cloud data format has changed) the beamfilling correction in the rain algorithm was modified The effects of V7 changes relative to V6: increased vapor values in the range of mm by 1% increased vapor values above 60 mm by 2-3% changed the range of cloud water values to: to 2.45 mm (cloud data format has changed) increased the global mean rain rates by about 16% (mostly due to changes in the extratropical values) New emissivity model (Meissner & Wentz) Improved diurnal cycle added to Reynolds during development Improved RFI detection (space and ground-based)

6 Algorithm EIA = Earth Incidence Angles WDIR = Wind Direction Future work: develop methodology to utilize adaptive algorithms, when channel is identified as RFI or side lobe (land) contaminated, will rely on other channels for retrieval where possible. Testing with AMSR-E.

7 Adaptive algorithms In region affected by side-lobe contamination (near land or sea ice) or RFI, switch algorithms to utilize nonaffected channels if possible Develop automated way to flag data affected by RFI at L2B level

8 SST v7 Buoy Validation Independent, global validation using GTS in situ SST database. Only additional QC of data was to remove daytime collocations at winds < 4m/s

9 Moored buoy validation

10 V7 SST - Reynolds Data from entire mission AMSR 2PM - Reynolds AMSR 2AM - Reynolds WSAT 6AM - Reynolds WSAT 6PM - Reynolds Δ SST ( C)

11 SST compared to drifting buoys AMSR 2PM - Reynolds AMSR 2AM - Reynolds WSAT 6AM - Reynolds WSAT 6PM - Reynolds Data from entire mission

12 Δ SST ( C) AMSR v7 diurnal Day Night For all panels the color of the lines Indicates SST Wind (m/s) Wind (m/s) Left = Day Right = Night Cloud (mm) Cloud (mm) From top to bottom is wind, cloud, and vapor Vapor (mm) Vapor (mm)

13 V7 versus V5 Day Night Version 7 Version 5 Wind (m/s) Wind (m/s) Version 5 low wind bias due to SST/wind algorithm development. In Version 7 we used an improved diurnal SST representation both in our RTM simulations that are used to develop the SST algorithm and final post-hoc analysis.

14 V5 to V7 The version 7 Has larger amplitude Diurnal warming than Version 5, additionally You can also see that The low winds are Decreased and high Winds are increased slightly Version 7 Version 5 Day SST Day Wind

15 ground / ship based RFI over ocean Ascension Island, Hawaii, North Sea, Gulf of Mexico, Mumbai GeoStationary Satellites Media Broadcasts *Glint Angle*

16 RFI How to identify? use orbital data, prior to any geophysical quality controls (SST out of bounds, etc) Geophysical retrieval algorithms that use different channels 2 SST algorithms SST 7GHz = all channels SST 11GHz = channels 11 GHz 3 Wind algorithms Wind 7GHz = all channels Wind 11GHz = channels 11 GHz Wind 718GHz = channels 18 GHz Compare different algorithms to each other as well as independent (SST Reynolds, Wind NCEP) Save maximum difference over entire dataset to identify hot spots. Do time series analysis to identify whether affecting ascending, descending, or both, and for what time periods

17 Ground-based RFI around Hawaii Ground-based RFI around Hawaii occurred: 7GHz: before 2003 Jan 27 11GHz: after 2007 Apr 10 Version 5 Version 7 SST 7GHz - Rey SST 7GHz - Rey Left column: Version 5 SSTs. This is the maxium difference, the RFI is causing biases ~20K. Right column: Version 7 SSTs with new RFI filtering. SST 11GHz - Rey SST 11GHz - Rey

18 Some RFI WSAT SST 7GHz - Rey AMSRE SST 7GHz - Rey This shows RFI in the 6 GHz channel, the 10 GHz and 18 GHz also have different sources that need to be considered. The different channel bandwidths result in WSAT being more affected near Europe than AMSR. Some RFI filtering down at L1 level for WSAT, so not all sources apparent in this image.

19 Identifying ground-based RFI RFI affecting ascending Could use 11 GHz algo Instead here

20 RFI impact Most RFI is geostationary satellite transmissions reflection and can therefore only affect either ascending or descending parts of the orbit, so while that region may not be measured in one look direction, it will be fine in the other Ground based is difficult to identify, monitor, and flag appropriately. Maximum difference method provides good mask for flagging RFI Bottom line most data is fine, the more difficult ground-based RFI is mostly intermittent with a minimal impact on the overall quality of the data, but version 7 has significantly more RFI flagging than version 5 and is a better dataset.

21 Thank you WSAT and AMSR are both available in v7 Data quality of WSAT is similar to that of AMSR Current NRT is ~12 hours, will improve in future WSAT data access issues were a problem through 2/2012 and have not been resolved so more data consistently availalbe