Ocean-atmosphere water flux and evaporation

Abstract

There have been continuous endeavors to estimate E and LH over global oceans using satellite data and based on bulk parameterization of turbulence transport, since Liu and Niiler (1984) successfully estimated the flux by introducing an empirical relation between monthlyWand q.With some improvement in this supply side approach, a number of data sets have been operationally produced in the past two decades, but large differences among these data sets and between products from satellite data and from reanalysis of operational weather prediction remain (e.g., Curry et al., 2004). We have introduced a new method of direct retrieval of E and LH from the radiances measured by microwave radiometers, which improves the random error of the daily value of LH to 10 % of the dynamic range, as compared with the 19 % error using the methods we pioneered 30 years ago of computing the fluxes from bulk parameters derived from the same radiances. Evaluations to find the optimal flux product are difficult because of the lack of credible standards (e.g., extensive direct flux measurement). One good constraint to the uncertainties is the closure of the atmospheric water budget, which dictates that E-P should balance ∇ Θ. The “demand side” approach of estimating Θ and ∇ Θ from satellite data serves not only as a credible way to evaluate traditional “supply side” flux products but also to provide the ocean freshwater exchange as a whole, without the need of securing precipitation data separately. The Q data have been extensively tested in comparison with all available rawinsonde data and products of numerical models. The water flux data, as ∇ Θ, are also validated through mass conservation using data from GRACE and river discharge climatology; the validation study shows 20 % uncertainties of the seasonal water balance. The feasibility of using upper ocean heat and salinity conservations is also demonstrated with very preliminary results. There is still much room left for improvement in estimating water flux over global ocean. The new space-based data products, with better spatial and temporal resolution, have many ongoing scientific applications.