The development of a processing environment for time-series analysis of SeaWinds scatterometer data

The analysis of Earth observation data is normally undertaken within the spatial, or image, domain. With sensors obtaining highly frequent observations it is sometimes difficult to understand the temporal evolution and specific characteristics of the data if the analysis of the data is performed solely in the spatial domain. This paper provides an overview of the processing chain that has been developed to extract time series data sets consisting of backscattering coefficient σ⁰ measurements from the SeaWinds sensor on NASA´s QuikSCAT platform. The current global, operational, solution for land surfaces is outlined along with some typical processing times. Due to the volume of the orbital data sets from the SeaWinds sensor, emphasis is drawn upon the fact that within the operational processing chain robustness and stability of the processing environment is critical. The time series data sets are used to analyse the dynamics of freeze-thaw events across the Siberian biome. This work has been undertaken within the framework of the SIBERIA II project.