Advanced Validation of AMSR Wind Speed Measurements
using Buoy, Scatterometer, and NWP Surface Analysis Products
PI: Michael H. Freilich
Title:
Institution: College of Oceanic and Atmospheric Sciences, Oregon State University
104 Ocean Administration Bldg
Oregon State University
Corvallis, OR 97331-5503
Phone: (541) 737-2748
Email: mhf@coas.oregonstate.edu
WWW: http://www.oce.orst.edu/po/satellite.html
EOS Team: AMSR-E
NASA EOS-PSO funding through FY02: $58,860
ABSTRACT
An investigation is proposed to conduct detailed validation of the AMSR-E and
ADEOS-AMSR wind speed data sets. The analyses will involve comparisons between
AMSR wind speed estimates and those from operational ocean moored buoys (National
Data Buoy Center and TOGA/TAO), the SeaWinds microwave scatterometer instruments
on QuikSCAT and ADEOS-II, and operational surface wind analyses produced by
ECMWF and NCEP. The random component error model of Freilich (1997) and the
statistical approach of Freilich and Vanhoff (2001) will form the basis for
the validation analysis -- although derived originally for scatterometer validation,
the approach uses only wind speed information and is thus applicable to AMSR
wind data. The formalism explicitly accounts for (and solves for the magnitudes
of) equivalent random component errors in the comparison data sets as well as
the AMSR measurements to be validated; it is thus well suited for the use of
satellite and operational surface wind analyses as comparison data. The effects
of compatibility errors between the satellite and comparison data will be quantified
and minimized for both the buoy and the ECMWF/NCEP data sets. The proposed investigation
will build on advanced validation analysis techniques, data acquisition and
reduction tools, and archives developed by the PI in previous studies of spaceborne
microwave wind data sets; complement the baseline AMSR wind validation (conducted
by the AMSR Oceans Team) by using an alternate error model and a formalism that
explicitly accounts for random errors in all data sets; extend previous studies
by using temporal averaging of buoy measurements and spatial averaging of AMSR
measurements (when compared with ECMWF/NCEP analyses) to minimize, and quantify
the effects of, resolution-induced compatibility errors; and provide regional
and global ocean estimates of systematic gain, offset, and random uncertainty
for AMSR wind speeds both at the 25 km resolution of the raw data and at the
100-400 km resolution of operational surface wind analyses. Initial analyses
and algorithm refinements will be conducted using existing available radiometer
data from SSM/I and scatterometer data from SeaWinds on QuikSCAT. AMSR Level
2 data will be used as soon as preliminary wind speed data sets become available.
Results will be made available to the AMSR Instrument Team for their use in
post-launch geophysical algorithm refinement.