Review and assessment of latent and sensible heat flux accuracy over the global oceans

For over a decade, several research groups have been developing air-sea heat flux information over the global ocean, including latent (LHF) and sensible (SHF) heat fluxes over the global ocean. This paper aims to provide new insight into the quality and error characteristics of turbulent heat flux estimates at various spatial and temporal scales (from daily upwards). The study is performed within the European Space Agency (ESA) Ocean Heat Flux (OHF) project. One of the main objectives of the OHF project is to meet the recommendations and requirements expressed by various international programs such as the World Research Climate Program (WCRP) and Climate and Ocean Variability, Predictability, and Change (CLIVAR), recognizing the need for better characterization of existing flux errors with respect to the input bulk variables (e.g. surface wind, air and sea surface temperatures, air and surface specific humidities), and to the atmospheric and oceanic conditions (e.g. wind conditions and sea state). The analysis is based on the use of daily averaged LHF and SHF and the asso- ciated bulk variables derived from major satellite-based and atmospheric reanalysis products. Inter-comparisons of heat flux products indicate that all of them exhibit similar space and time patterns. However, they also reveal significant differences in magnitude in some specific regions such as the western ocean boundaries during the Northern Hemisphere winter season, and the high southern latitudes. The differences tend to be closely related to large differences in surface wind speed and/or specific air humidity (for LHF) and to air and sea temperature differences (for SHF). Further quality investigations are performed through comprehensive comparisons with daily-averaged LHF and SHF estimated from moorings. The resulting statistics are used to assess the error of each OHF product. Consideration of error correlation between products and observations (e.g., by their assimilation) is also given. This reveals generally high noise variance in all products and a weak signal in common with in situ observations, with some products only slightly better than others. The OHF LHF and SHF products, and their associated error characteristics, are used to compute daily OHF multiproduct-ensemble (OHF/MPE) estimates of LHF and SHF over the ice-free global ocean on a 0.25° × 0.25° grid. The accuracy of this heat multiproduct, determined from comparisons with mooring data, is greater than for any individual product. It is used as a reference for the anomaly characterization of each individual OHF product

Probability Distribution Characteristics for Surface Air–Sea Turbulent Heat Fluxes over the Global Ocean

To analyze the probability density distributions of surface turbulent heat fluxes, the authors apply the twoparametric modified Fisher–Tippett (MFT) distribution to the sensible and latent turbulent heat fluxes recomputed from 6-hourly NCEP–NCAR reanalysis state variables for the period from 1948 to 2008. They derived the mean climatology and seasonal cycle of the location and scale parameters of the MFT distribution. Analysis of the parameters of probability distributions identified the areas where similar surface turbulent fluxes are determined by the very different shape of probability density functions. Estimated extreme turbulent heat fluxes amount to 1500–2000 W m22 (for the 99th percentile) and can exceed 2000 W m22 for higher percentiles in the subpolar latitudes and western boundary current regions. Analysis of linear trends and interannual variability in the mean and extreme fluxes shows that the strongest trends in extreme fluxes (more than 15 W m22 decade21) in the western boundary current regions are associated with the changes in the shape of distribution. In many regions changes in extreme fluxes may be different from those for the mean fluxes at interannual and decadal time scales. The correlation between interannual variability of themean and extreme fluxes is relatively low in the tropics, the SouthernOcean, and the Kuroshio Extension region.Analysis of probability distributions in turbulent fluxes has also been used in assessing the impact of sampling errors in theVoluntaryObserving Ship (VOS)-based surface flux climatologies, allowed for the estimation of the impact of sampling in extreme fluxes. Although sampling does not have a visible systematic effect onmean fluxes, sampling uncertainties result in the underestimation of extreme flux values exceeding 100 W m22 in poorly sampled regions

Estimating air-sea fluxes of heat, freshwater and momentum through global ocean data assimilation

Spectral properties of whitecaps are of importance for color ocean remote sensing and aerosol optical thickness probing from satellite-based instruments. They also influence planetary albedo and climate. In particular, whitecaps may affect the response of the climate system to changes in greenhouse gases and other atmospheric constituents. Several experimental measurements of whitecap spectral reflectance have been performed both in the surf zone and in the open ocean, which indicate that oceanic foam cannot be considered as a gray body (e.g., for satellite remote sensing techniques). This paper is devoted to the interpretation of experiments performed in terms of the radiative transfer theory. Only the case of a semi-infinite foam is studied in detail. However, results can be easily extended to the case of finite foamed media having large optical thickness. The model introduced is capable of explaining main features observed, like a sharp decrease of the foam spectral reflectance in the infrared as compared with the visible part of the electromagnetic spectrum and a high correlation of the foam reflectance R and the water absorption coefficient a. A simple method to retrieve the spectral dependence of a from the spectral foam reflectance R is proposed

Air–Sea fluxes from ICOADS: the construction of a new gridded dataset with uncertainty estimates

The methods used to calculate a new in situ global dataset of air–sea exchanges, called the NOCS Flux Dataset v2.0, are described. The fluxes have been derived from in situ weather reports from Voluntary Observing Ships (VOS) covering the period 1973–2006. The reports have been adjusted for known biases and residual uncertainties estimated. The dataset is constructed using Optimal Interpolation (OI) using new estimates of random uncertainty in the observations. Daily fields have been calculated on a 1° latitude by 1° longitude grid, each grid box and time step have an associated uncertainty estimate. Monthly fields have been calculated from simple averages of the daily fields and monthly uncertainty estimates from the daily uncertainties, using estimates of the autocorrelation between the daily uncertainty estimates. The uncertainties due to the choice of flux parameterisation have not been accounted for. Bias adjustments applied to the data are shown to reduce trends in the data and to improve the consistency of estimates of air temperature, sea surface temperature (SST) and specific humidity. The bias adjustments also improve the agreement of NOCS v2.0 with independent data from research moorings. Cross-validation of the dataset suggests that the uncertainty estimates are realistic, but that the uncertainties are probably underestimated in high variability regions and overestimated in regions with lower variability