Doug Vandemark

A unified directional spectrum for long and short wind‐driven waves

Review of several recent ocean surface wave models finds that while comprehensive in many regards, these spectral models do not satisfy certain additional, but fundamental, criteria. We propose that these criteria include the ability to properly describe diverse fetch conditions and to provide agreement with in situ observations of Cox and Munk [1954] and Jahne and Riemer [1990] and Hara et al. [1994] data in the high-wavenumber regime. Moreover, we find numerous analytically undesirable aspects such as discontinuities across wavenumber limits, nonphysical tuning or adjustment parameters, and noncentrosymmetric directional spreading functions. This paper describes a two-dimensional wavenumber spectrum valid over all wavenumbers and analytically amenable to usage in electromagnetic models. The two regime model is formulated based on the Joint North Sea Wave Project (JONSWAP) in the long-wave regime and on the work of Phillips [1985] and Kitaigorodskii [1973] at the high wavenumbers. The omnidirectional and wind-dependent spectrum is constructed to agree with past and recent observations including the criteria mentioned above. The key feature of this model is the similarity of description for the high- and low-wavenumber regimes; both forms are posed to stress that the air-sea interaction process of friction between wind and waves (i.e., generalized wave age, u/c) is occurring at all wavelengths simultaneously. This wave age parameterization is the unifying feature of the spectrum. The spectrums directional spreading function is symmetric about the wind direction and has both wavenumber and wind speed dependence. A ratio method is described that enables comparison of this spreading function with previous noncentrosymmetric forms. Radar data are purposefully excluded from this spectral development. Finally, a test of the spectrum is made by deriving roughness length using the boundary layer model of Kitaigorodskii. Our inference of drag coefficient versus wind speed and wave age shows encouraging agreement with Humidity Exchange Over the Sea (HEXOS) campaign results.

AERONET-OC: a Network for the Validation of Ocean Color Primary Products

Abstract The ocean color component of the Aerosol Robotic Network (AERONET-OC) has been implemented to support long-term satellite ocean color investigations through cross-site consistent and accurate measurements collected by autonomous radiometer systems deployed on offshore fixed platforms. The AERONET-OC data products are the normalized water-leaving radiances determined at various center wavelengths in the visible and near-infrared spectral regions. These data complement atmospheric AERONET aerosol products, such as optical thickness, size distribution, single scattering albedo, and phase function. This work describes in detail this new AERONET component and its specific elements including measurement method, instrument calibration, processing scheme, quality assurance, uncertainties, data archive, and products accessibility. Additionally, the atmospheric and bio-optical features of the sites currently included in AERONET-OC are briefly summarized. After illustrating the application of AERONET-OC dat...

The ERS Scatterometer Wind Measurement Accuracy: Evidence of Seasonal and Regional Biases

Abstract A validation of European Space Agency (ESA) remote sensing satellite (ERS) scatterometer ocean wind measurements is performed using a formalism recently proposed for and applied to NASA scatterometer (NSCAT) and Special Sensor Microwave Imager (SSM/I) measurements. This simple analytical model relates scatterometer measurements to true winds, taking into account errors in the satellite winds as well as errors in the data used for reference. In this study, National Data Buoy Center (NDBC) buoy winds are the chosen reference. In addition, ECMWF analysis winds are used as a third data source to completely determine the errors via a triple collocation analysis. According to this development, the resulting wind speed error analysis indicates that ERS scatterometer estimates are negatively biased at light winds. This result differs from recent results determined using standard regression analysis. It is also shown that ERS and NSCAT measurement accuracies are comparable in an overall sense. This error ...

SMOS satellite L-band radiometer: A new capability for ocean surface remote sensing in hurricanes

The Soil Moisture and Ocean Salinity (SMOS) mission currently provides multiangular L-band (1.4 GHz) brightness temperature images of the Earth. Because upwelling radiation at 1.4 GHz is significantly less affected by rain and atmospheric effects than at higher microwave frequencies, these new SMOS measurements offer unique opportunities to complement existing ocean satellite high wind observations that are often contaminated by heavy rain and clouds. To illustrate this new capability, we present SMOS data over hurricane Igor, a tropical storm that developed to a Saffir-Simpson category 4 hurricane from 11 to 19 September 2010. Thanks to its large spatial swath and frequent revisit time, SMOS observations intercepted the hurricane 9 times during this period. Without correcting for rain effects, L-band wind-induced ocean surface brightness temperatures (TB) were co-located and compared to H*Wind analysis. We find the L-band ocean emissivity dependence with wind speed appears less sensitive to roughness and foam changes than at the higher C-band microwave frequencies. The first Stokes parameter on a ∼50 km spatial scale nevertheless increases quasi-linearly with increasing surface wind speed at a rate of 0.3 K/m s−1 and 0.7 K/m s−1 below and above the hurricane-force wind speed threshold (∼32 m s−1), respectively. Surface wind speeds estimated from SMOS brightness temperature images agree well with the observed and modeled surface wind speed features. In particular, the evolution of the maximum surface wind speed and the radii of 34, 50 and 64 knots surface wind speeds are consistent with GFDL hurricane model solutions and H*Wind analyses. The SMOS sensor is thus closer to a true all-weather satellite ocean wind sensor with the capability to provide quantitative and complementary surface wind information of interest for operational Hurricane intensity forecasts.

A network for standardized ocean color validation measurements

The Aerosol Robotic Network (AERONET), originally developed to evaluate aerosol optical properties and validate satellite retrievals of those properties at various scales with measurements from worldwidedistributed autonomous Sun photometers [Holben et al., 1998],since January 2006 has been extended to support marine remote sensing and monitoring applications. This new network component, called AERONETOcean Color (AERONET-OC), provides the additional capability of measuring the radiance emerging from the sea—the ‘water-leaving radiance’—with modified Sun photometers installed on offshore platforms such as lighthouses, oceanographic towers, and derricks. AERONET-OC is proving to be instrumental in supporting satellite ocean color validation activities through standardized measurements performed at different sites with identical measuring systems and protocols, calibrated using a single reference source and method, and processed with the same code. Recent investigations [Zibordi et al., 2006] suggest that in order to generate accurate climate data records from remote sensing data, time series of in situ measurements from a cadre of AERONET-OC sites could play a major role in the assessment and merging of radiometric products from different ocean color missions.

Improved electromagnetic bias theory

In this paper we describe modifications to a previous theory for the altimeter electromagnetic bias (EM bias) of Srokosz [1986]. A major correction introduces a scaling of Srokoszs model by nonnegligible dimensionless ratios that depend on the slope variance of both long and short waves. With these modifications the EM bias is no longer simply a function of the cross skewness between surface elevation and slope but now depends on the variance ratios that represent the modulation between short and long waves. Inclusion of these ratios can reduce previous EM bias estimates by as much as 50%. Different directions for the longwave and shortwave field are also accounted for in the two-dimensional development of our approach. A radar frequency dependence consistent with observation is also predicted by the new model. Derivation extending our development to the next higher order in wave statistics is also presented and discussed.

Importance of peakedness in sea surface slope measurements and applications

We recall the simple statistical concept that non-Gaussian distribution peakedness results from the compounding of random processes. This idea is applied to observations and analysis of sea surface slopes as inferred using optical and microwave-scattering measurements. Our study emphasizes the importance of identifying and quantifying the distribution variance and kurtosis from observations. Data are shown to indicate consistently non-Gaussian peakedness, to indicate the need to report at least two parameters in an even order analysis, and to indicate near equivalence between radar and optical data. Physical interpretation for observed infrequent steep slopes is given via compounding statistical processes where normally distributed short-scale waves are modulated because of random fluctuations mainly associated with the underlying long wave field. Implications of non-Gaussian peakedness are provided for altimeter backscatter theory and for modeling wave-breaking probability.

Demonstration of ocean surface salinity microwave measurements from space using AMSR-E data over the Amazon plume

Microwave Sea Surface Salinity (SSS) measurements can be performed by isolating the emissivity response to salinity changes from numerous geophysical effects, including surface temperature and wind waves. At L-band frequencies (1 to 2 GHz), the sensitivity to SSS is sufficient but it falls off quickly as frequency is increased. Nevertheless, methods using higher microwave frequencies with much lower SSS sensitivity than at L band, can already be tested. In particular, combining 6 and 10 GHz data in vertical polarization efficiently minimizes sea surface roughness and thermal impacts. Using AMSR-E data, the retrieved bi-monthly maps of SSS at 0.5 degrees resolution over the region of the Amazon plume show relative accuracy in-line with the future L-band dedicated mission objectives. Citation: Reul, N., S. Saux-Picart, B. Chapron, D. Vandemark, J. Tournadre, and J. Salisbury (2009), Demonstration of ocean surface salinity microwave measurements from space using AMSR-E data over the Amazon plume, Geophys. Res. Lett., 36, L13607, doi:10.1029/2009GL038860.

Improved electromagnetic bias theory: Inclusion of hydrodynamic modulations

The modulation of short ocean waves by longer ones is a likely contributor to the radar altimeters electromagnetic ranging bias (EM bias). An analytic model to account for this component of the EM bias is developed here under a two-scale two-dimensional hydrodynamic assumption. Following the principle of wave action balance, a standard hydrodynamic modulation transfer function is used to establish that the longer modulating waves enter the EM bias formulation not only through their elevation and slope variables but also through their quadratures. These latter contributions help to explain the role of long-wave slope and orbital velocity fields within the EM bias problem. Simplified analytical expressions are derived using linear Gaussian statistics for both modulating and modulated waves. For the sake of completeness an outline of the possible extension to nonlinear interacting waves is provided.

One- and Two-Dimensional Wind Speed Models for Ka-Band Altimetry

abstractSARAL—the Satellite with ARgos and ALtiKa—is the first satellite radar altimetry mission to fly a Ka-band instrument (AltiKa). Ocean backscatter measurements in the Ka band suffer larger signal attenuation due to water vapor and atmospheric liquid water than those from Ku-band altimeters. An attenuation algorithm is provided, based on radar propagation theory, which is a function of atmospheric pressure, temperature, water vapor, and liquid water content. Because of the nature of the air–sea interactions between wind and surface gravity waves, the shorter wavelength Ka-band backscatter exhibits a different relationship with wind speed than at Ku band, particularly at moderate to high wind speeds. This paper presents a new one-dimensional wind speed model, as a function of backscatter only, and a two-dimensional model, as a function of backscatter and significant wave height, tuned to AltiKa’s backscatter measurements. The performance of these new Ka-band altimeter wind speed models is assessed thr...