In search of the true wind; scatterometer calibration and error modelling

Abstract

Wind is a very important geophysical variable to accurately measure for weather forecasting and climate. However, a statistical phenomenon important for the validation or calibration of winds is the small dynamic range relative to the typical measurement uncertainty, i.e. the generally small Signal-to-Noise Ratio. In such cases pseudo biases may occur, when standard validation or calibration methods are applied, such as regression or bin-average analyses. Also, non-linear transformation, for instance between wind components and speed and direction, will generally give rise to pseudo biases. In fact, validation or calibration can only be done properly when the full error characteristics of the data are known. The problem is that in practise prior knowledge on the error characteristics is seldom available. In this paper we will show that simultaneous error modelling and calibration may be achieved only by using triple collocations. To illustrate the statistical analysis using triple collocations, in situ, ERS scatterometer, and forecast model winds are used. Wind component error analysis is shown to be more convenient than wind speed and direction error analysis. The anemometer winds from the NOAA buoys are shown to have the largest error variance, followed by the scatterometer, and the NCEP forecast model winds proved the most accurate. When using the in situ winds as a reference the scatterometer wind components were biased low by ~4%. The NCEP forecast model winds were found to be biased high by ~6%. Such corrections are relevant for the use of surface winds to compute fluxes of momentum, humidity or heat, or to drive ocean wave or circulation models.

Keywords: calibration, error modelling, scatterometer, surface wind

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry