Building a Climate Data Record for Ocean Vector Winds

Abstract:

Scatterometers such as QuikSCAT and ASCAT are in principle well suited for providing climate-quality wind observations. They are very stable sensors, usually unaffected by satellite drifts or other issues that might affect the temporal stability of the wind time series. However, combining data from multiple scatterometers with the accuracy required for climate studies is a major challenge. Here we will review the challenges and progress made towards producing high-quality and consistent time series of ocean vector winds from past, current, and future scatterometer missions. We will describe the development of consistent Geophysical Model Functions (GMF) at the Ku-, C, and L-band frequencies, and the efforts in understanding and removing sources of bias among different scatterometer winds (i.e., atmospheric/ocean surface effects, rain impact, imperfect calibration of the GMF, etc..) . An additional and important source of inter-satellite bias at a regional level is due to the diurnal variability in the ocean surface winds. We will present an analysis aimed at estimating the amplitude and phase of wind diurnal variability. We will show how global time series of ocean winds from different scatterometer missions do overlap within the accuracy required for climate studies, when processed in a consistent manner and with proper quality control,.