We read with interest Tolman's (1998, hereafter T98) analysis of the effect
of observation errors on validation of marine winds. His demonstration of
the importance of the correct treatment of the errors in comparative analys
is of wind-speed land other types of) data is welcome, as examples of inacc
urate comparisons are common, particularly for satellite data validation wh
ich is often published in non-refereed reports. Kent et ad. (1998) show tha
t apparent trends of the order reported can be directly attributed to error
s in both datasets and that the trend appears smaller and in the opposite s
ense if the satellite wind speed rather than the ship wind speed is used as
the independent variable for plotting.
T98 states that 'in special cases, where the ratio of... errors can be esti
mated, more advanced regression techniques can be used'. Our aim in this no
te is to advocate a simple, established method of data analysis which can l
ead to reliable comparisons of pairs of nearly co-located and simultaneous
observations from two sources, both containing random errors. This method e
nables the use of these advanced regression techniques since the ratio of r
andom errors in the datasets to be compared is estimated. The error estimat
es can then be verified by using the effects of errors on bin-averaged anal
yses highlighted by T98. Following T98 and Kent et al. (1998), we shall dis
cuss satellite and in situ wind-speed data comparisons, but again expect th
e results to be more widely applicable.