Sea surface wind speed estimation from space-based lidar measurements

Hu, Yongxiang; Stamnes, Knut; Vaughan, Mark; Pelon, Jacques; Weimer, Carl; Wu, Deliang; Cisewski, Michael S.; Sun, Wenbo; Yang, Ping; Lin, Bing; Omar, Ali; Flittner, D.; Hostetler, C. A.; Trepte, Charles R.; Winker, David M.; Gibson, Gary G.; Santamaría, Mariana

doi:10.5194/acp-8-3593-2008

Cited by 104 publications

(83 citation statements)

References 25 publications

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“…Specular reflection decreases as wave steepness increases and is extremely large in very calm waters. Hu et al [24], citing Platt [26], Menzies et al [27], and Tratt et al [28], modeled the specular surface reflection as:…”

Section: Specular Surface Reflectionmentioning

confidence: 99%

“…Lancaster et al [23] used the GLAS (Geoscience Laser Altimeter System) lidar on the ICESat (Ice, Cloud, and land Elevation Satellite) platform to detect water surface reflectance and compared that with the predicted theoretical reflectance from QuikSCAT (Quick Scatterometer) wind speeds. Hu et al [24] used the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) lidar on the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite to measure wind speed, and compared the results to AMSR-E (Advanced Microwave Scanning Radiometer-EOS) wind speed measurements. They used the depolarization ratio available from CALIOP to remove the sea foam effect from the surface measurement.…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

Barton

Jasinski

2011

Remote Sensing

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Abstract:A method is presented for estimating subaqueous integrated backscatter using near-nadir viewing satellite lidar. The algorithm takes into account specular reflection of laser light, laser scattering by wind-generated foam as well as sun glint and solar scattering from foam. The formulation is insensitive to the estimate of wind speed but sensitive to the estimate of transmittance used in the atmospheric correction. As a case study, CALIOP data over Tampa Bay were compared to MODIS 645 nm remote sensing reflectance, which previously has been shown to be nearly linearly related to turbidity. The results indicate good correlation on nearly all CALIOP cloud-free dates during the period 2006 through 2007, particularly those with relatively high atmospheric transmittance. The correlation decreases when data are composited over all dates but is still statistically significant, a possible indication of variability in the biogeochemical composition in the water. Overall, the favorable results show promise for the application of satellite lidar integrated backscatter in providing information about subsurface backscatter properties, which can be extracted using appropriate models.

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Section: Specular Surface Reflectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

Barton

Jasinski

2011

Remote Sensing

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“…radiometer (MODIS) satellite reflectance over land or glint backscatter using 10 m analyzed wind speeds (Hu et al, 2008) interpolated to the sample locations over oceans. Samples with total column cloud plus aerosol OD > 0.7 are rejected.…”

Section: Observational Sampling and Simulated Measurement Uncertaintiesmentioning

confidence: 99%

A regional CO<sub>2</sub> observing system simulation experiment for the ASCENDS satellite mission

et al. 2014

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Abstract. Top-down estimates of the spatiotemporal variations in emissions and uptake of CO 2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO 2 measurement platforms. In particular, the planned NASA Active Sensing of CO 2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO 2 fluxes, we use a portable library of footprints (surface influence functions) generated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in combination with the Weather Research and Forecasting (WRF) model in a regional Bayesian synthesis inversion. The regional Lagrangian particle dispersion model framework is well suited to make use of ASCENDS observations to constrain weekly fluxes in North America at a high resolution, in this case at 1 • latitude × 1 • longitude. We consider random measurement errors only, modeled as a function of the mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the grid scale and weekly resolution, the largest uncertainty reductions, on the order of 50 %, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large.Uncertainty reductions are smaller for a 1.57 µm candidate wavelength than for a 2.05 µm wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual biome scale range from ∼ 40 % to ∼ 75% across our four instrument design cases and from ∼ 65% to ∼ 85 % for the continent as a whole. Tests suggest that the quantitative results are moderately sensitive to assumptions regarding a priori uncertainties and boundary conditions. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr −1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.

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“…Though originally designed for retrieving spatial and optical properties of clouds and aerosols, new applications of CALIOP measurements suggest that space-based lidars can provide physical properties of ocean surface [1] and subsurface [2] [3]. Lidars can be used for retrievals of particulate backscattering, diffuse attenuation coefficients, the size spectrum and vertical distribution of ocean particles.…”

Section: Introduction Of the Conceptmentioning

confidence: 99%

Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

Behrenfeld

Hostetler

et al. 2016

EPJ Web of Conferences

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Beam attenuation coefficient, c, provides an important optical index of plankton standing stocks, such as phytoplankton biomass and total particulate carbon concentration. Unfortunately, c has proven difficult to quantify through remote sensing. Here, we introduce an innovative approach for estimating c using lidar depolarization measurements and diffuse attenuation coefficients from ocean color products or lidar measurements of Brillouin scattering. The new approach is based on a theoretical formula established from Monte Carlo simulations that links the depolarization ratio of sea water to the ratio of diffuse attenuation Kd and beam attenuation C (i.e., a multiple scattering factor).On July 17, 2014, the CALIPSO satellite was tilted 30° off-nadir for one nighttime orbit in order to minimize ocean surface backscatter and demonstrate the lidar ocean subsurface measurement concept from space. Depolarization ratios of ocean subsurface backscatter are measured accurately. Beam attenuation coefficients computed from the depolarization ratio measurements compare well with empirical estimates from ocean color measurements. We further verify the beam attenuation coefficient retrievals using aircraftbased high spectral resolution lidar (HSRL) data that are collocated with in-water optical measurements.

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Sea surface wind speed estimation from space-based lidar measurements

Cited by 104 publications

References 25 publications

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

A regional CO<sub>2</sub> observing system simulation experiment for the ASCENDS satellite mission

Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

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Sea surface wind speed estimation from space-based lidar measurements

Cited by 104 publications

References 25 publications

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

Sensitivity of Depth-Integrated Satellite Lidar to Subaqueous Scattering

A regional CO&lt;sub&gt;2&lt;/sub&gt; observing system simulation experiment for the ASCENDS satellite mission

Ocean Lidar Measurements of Beam Attenuation and a Roadmap to Accurate Phytoplankton Biomass Estimates

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A regional CO<sub>2</sub> observing system simulation experiment for the ASCENDS satellite mission