An empirical model to retrieving ocean wave period from nadir altimeter data

Abstract

Accurate measurement of the ocean wave period is of much scientific interest both operationally and for research. Shipping and offshore industries are keen to obtain real-time and climatological information on wave period in the open ocean to assist the design of sea-going structures and maximise safety at sea. Similarly, wave period is relevant for short-to-medium term ocean and weather forecasting, and more broadly, to ocean circulation and climate research, given the reported dependence of atmosphere-ocean momentum transfer on some measure of sea state development. In principle, full ocean wave spectra can be obtained from satellite synthetic aperture radars (SAR), yet the systematic extraction of wave period information from SAR has so far not been pursued. Hence, global wave period information is presently available only through numerical wave models, and there remain concerns about the lack of large scale validation of the geographical distribution and temporal variability of the modelled ocean waves. Here, we propose that ocean wave period information can be retrieved with adequate accuracy using satellite altimeters. There is evidence that satellite altimeter data contain wave period information, in addition to that on wave height. The existence of sea state development effects on the retrieval of altimeter wind speed is well documented and a few earlier studies have already considered the development of altimeter wave period models. However, the sea state dependence in these semi-empirical models is complex, and in both cases, the datasets of collocated altimeter/buoy measurements used to develop the models spanned only a small range of environmental conditions. In this paper, we present preliminary results of a new, purely empirical, wave period algorithm developed on the basis of the largest to-date dataset of collocated altimeter/buoy spectra measurements. The empirical wave period model is validated using independent collocated altimeter/buoy data, and by computing global monthly wave climatology. These are compared with existing wave period climatologies derived from numerical wave models.