Ae. Walker et Jl. Wilkin, OPTIMAL AVERAGING OF NOAA NASA PATHFINDER SATELLITE SEA-SURFACE TEMPERATURE DATA/, J GEO RES-O, 103(C6), 1998, pp. 12869-12883
Statistical interpolation is applied to 8 years of cloud-interrupted s
atellite radiometer data to produce estimates of sea surface temperatu
re (SST) at 10-day intervals in the Indo-Australian region. The data a
re 9-km resolution daily ''best SST'' values calculated globally by th
e NOAA/NASA Pathfinder project reanalysis of advanced very high resolu
tion radiometer (AVHRR) data. The optimal averaging technique determin
es an unbiased estimate of the signal that has the minimum mean square
variance from the data, within the limits of the expected measurement
error. Previous studies have shown that the method is superior to oth
er linear averaging techniques, especially that of simple composite av
eraging. The method is applied in the time domain only, preserving the
9-km spatial resolution of the data. The signal and noise covariances
were evaluated from the data. This was done with care so that accurat
e estimates of the error bounds that bracket the optimally averaged va
lues might be obtained. These error bounds were then verified against
in situ data. A Markov function, (1 + tau/a) exp (-tau/a), where tau i
s the time lag and a is a characteristic timescale, was fitted to the
data and used for the signal correlation function. This was selected a
fter evaluation of functional forms proposed in other studies. The eff
ect on the analysis of geographical variation in the correlation funct
ion was considered. The computational demand of the repeated matrix op
erations in optimal interpolation was reduced by using a limited durat
ion data window. The complete analysis procedure for the 8-year data s
et, comprising over 10(6) time series, was tractable on a modern works
tation. The result is a set of SST maps for 1987-1994 at an interval o
f 10 days and a spatial resolution of 9 km. The analyses are suitable
for applications such as high-resolution ocean and atmosphere modeling
where the timescales and space scales of interest are comparable to t
he analysis (i.e., of the order of 10 days, 9 km) and for which the pr
esence of gaps due to clouds is problematic. Some features of Indo-Aus
tralian regional mesoscale circulation that the analysis highlights ar
e examined, including examples of detailed mesoscale SST evolution and
interannual variability.