Geophysical Ocean Products from AMSR-E & WindSAT

1. Geophysical Ocean Products from AMSR-E & WindSAT Chelle L. Gentemann, Frank Wentz, Thomas Meissner, Kyle Hilburn, Deborah Smith, and Marty Brewer www.remss.com • Retrieval algorithm •  Validation results •  New directions • AMSRE Science Team • Portland, OR, 2012

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

3. V07 • 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 50-60 mm by 1%increased vapor values above 60 mm by 2-3% • changed the range of cloud water values to: -0.05 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

4. Algorithm AMSR2 & AMSRE: 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.

5. AMSR-E v7 SST Buoy Validation Independent, global validation using GTS in situ SST database

6. Wind algorithm • No-rain algorithm ( 10.7 GHz: 32 km) • Physical algorithm • Trained from Monte Carlo simulated brightness temperatures (TB). • Based on radiative transfer model. • Wind speed in rain algorithms ( 6.8 GHz: 50 km) • Statistical or hybrid algorithms • Trained from match-ups between measured TB and ground truth wind speeds in rainy conditions. • Utilizes spectral difference (6.8 GHz versus 10.7 GHz) in wind/rain response of measured brightness temperatures. • Same method is used by NOAA aircraft step frequency microwave radiometers (SFMR) to measure wind speeds in hurricanes. • Global wind speed in rain algo • trained for all rain conditions • H-wind algo • trained for tropical cyclones

7. Winds • Radiometer winds in rain: • T. Meissner + F. Wentz, IEEE TGRS 47(9), 2009, 3065 - 3083

8. Performance: no-rain wind speeds 5 years of data. 2003-2008 Joint PDF: WindSat versus validation data

9. Performance: wind speeds in rain 5 years of WindSat - Buoys

10. Comparing Ground-Based GPS to SSM/I water Vapor Geologists have deployed a HUGE network of ground-based GPS stations to evaluate earth movements, etc. GPS works by measuring the amount of time the signals need to go from the GPS satellites to the ground. This time depends on the distance (obviously) but also amount of water vapor (and air) in the atmosphere above the station. This is an error source for the geologists. It is a signal for meteorologists!

11. Binned means of SSM/I v6 – GPS PW Updated and Corrected in AMSRE v7 RTM All SSMI data: (<50 mm) Mean = 0.05 mm STD = 1.79 mm # collocations = 91678 SSM/I v6 vapor appears low above 50 mm

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

13. AMSR-E Microwave SST Retrievals for Europe Standard Algorithm RFI Mitigation • Color: standard deviation of AMSR-E – Reynolds SST • RFI mitigation algorithm does not use 10.7 GHz channel, and is optimized to use the remaining channels; SST retrieval possible thanks to AMSR-E’s 6.9 GHz channel • RFI around Europe has a strong increasing trend over AMSR-E’s period of operation • Data shown: descending passes for 2011 • Red spots in North Sea are ground-based RFI (also present in ascending passes)

14. Thank you • Adaptive algorithms to minimize RFI, land contamination • AMSR2 sample data just released….