An ocean calibration tool is developed for the calibration of the forthcoming ASCAT scatterometer on board of the METOP satellite. Besides handling ASCAT data the tool is also capable of handling scatterometer data from the ERS satellite, the predecessor of METOP. In this report the ocean calibration method is described and the results from ERS runs and error simulation are presented.
The calibration method is based on Fourier analysis of the data and has also been used by [STOFFELEN 1998] and [HERSCHBACH 2003]. The aim of ocean calibration is, by comparing the average measured backscatter from the antennae to the simulated backscatter from collocated NWP winds, to assess the absolute values of the measurements and the GMF and to show that there is no interbeam bias. The calibration software is used with existing ERS data and with simulated ASCAT data. The method will be applied for ASCAT as soon as real ASCAT data becomes available.
First the calibration is described from a theoretical point of view, deriving the calculation of Fourier coefficients out of a measurement set. Then the calibration software itself and the way this method is implemented is described in more detail. Then examples of a typical ocean calibration are shown using a standard input data set from ERS, July 1999. The backscatter differences are in the order of a few tenth of a dB.
In the next section the input parameters, especially the wind distribution and the backscatter distribution are examined in more detail. Calibration results for different weighting method, different input data period, and different GMF are presented. Good agreement between the different weighting methods is found.
A simulation tool which produces BUFR data files with errors added to wind speed or to the backscatter is described. These errors are random but have a well defined probability distribution. Subsequently these BUFR files are used in a simulation run of the ocean calibration in order to assess the influence of the errors in the calibration process. A simulation run with realistic values for the instrument noise and the geophysical noise, and for the NWP wind component errors is performed. The results show that the impact of the wind component errors on the calibration is the largest, as compared to the impact of the instrument noise and the geophysical noise. The ocean calibration differences between real and simulated data need to be further investigated.
The output from the ocean calibration over a certain period can be used to correct biases in the ocean calibration over another period. The impact of such a correction is examined, and it is shown that for ERS the calibration results are stable over a longer period of time.
JA Verspeek. Scatterometer calibration tool development