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49 pages, 10129 KiB

Open AccessArticle

A Coupled Evaluation of Operational MODIS and Model Aerosol Products for Maritime Environments Using Sun Photometry: Evaluation of the Fine and Coarse Mode

by Jeffrey S. Reid, Amanda Gumber, Jianglong Zhang, Robert E. Holz, Juli I. Rubin, Peng Xian, Alexander Smirnov, Thomas F. Eck, Norman T. O’Neill, Robert C. Levy, Elizabeth A. Reid, Peter R. Colarco, Angela Benedetti and Taichu Tanaka

Remote Sens. 2022, 14(13), 2978; https://doi.org/10.3390/rs14132978 - 22 Jun 2022

Cited by 10 | Viewed by 2927

Abstract

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments [...] Read more.

Although satellite retrievals and data assimilation have progressed to where there is a good skill for monitoring maritime Aerosol Optical Depth (AOD), there remains uncertainty in achieving further degrees of freedom, such as distinguishing fine and coarse mode dominated species in maritime environments (e.g., coarse mode sea salt and dust versus fine mode terrestrial anthropogenic emissions, biomass burning, and maritime secondary production). For the years 2016 through 2019, we performed an analysis of 550 nm total AOD₅₅₀, fine mode AOD (FAOD₅₅₀; also known as FM AOD in the literature), coarse mode AOD (CAOD₅₅₀), and fine mode fraction (η₅₅₀) between Moderate Resolution Spectral Imaging Radiometer (MODIS) V6.1 MOD/MYD04 dark target aerosol retrievals and the International Cooperative for Aerosol Prediction (ICAP) core four multi-model consensus (C4C) of analyses/short term forecasts that assimilate total MODIS AOD₅₅₀. Differences were adjudicated by the global shipboard Maritime Aerosol Network (MAN) and selected island AERONET sun photometer observations with the application of the spectral deconvolution algorithm (SDA). Through a series of conditional and regional analyses, we found divergence included regions of terrestrial influence and latitudinal dependencies in the remote oceans. Notably, MODIS and the C4C and its members, while having good correlations overall, have a persistent +0.04 to +0.02 biases relative to MAN and AERONET for typical AOD₅₅₀ values (84th% < 0.28), with the C4C underestimating significant events thereafter. Second, high biases in AOD₅₅₀ are largely associated with the attribution of the fine mode in satellites and models alike. Thus, both MODIS and C4C members are systematically overestimating AOD₅₅₀ and FAOD₅₅₀ but perform better in characterizing the CAOD₅₅₀. Third, for MODIS, findings are consistent with previous reports of a high bias in the retrieved Ångström Exponent, and we diagnosed both the optical model and cloud masking as likely causal factors for the AOD₅₅₀ and FAOD₅₅₀ high bias, whereas for the C4C, it is likely from secondary overproduction and perhaps numerical diffusion. Fourth, while there is no wind-speed-dependent bias for surface winds <12 m s⁻¹, the C4C and MODIS AOD₅₅₀s also overestimate CAOD₅₅₀ and FAOD₅₅₀, respectively, for wind speeds above 12 m/s. Finally, sampling bias inherent in MAN, as well as other circumstantial evidence, suggests biases in MODIS are likely even larger than what was diagnosed here. We conclude with a discussion on how MODIS and the C4C products have their own strengths and challenges for a given climate application and discuss needed research. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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15 pages, 4404 KiB

Open AccessArticle

Laboratory Heat Flux Estimates of Seawater Foam for Low Wind Speeds

by C. Chris Chickadel, Ruth Branch, William E. Asher and Andrew T. Jessup

Remote Sens. 2022, 14(8), 1925; https://doi.org/10.3390/rs14081925 - 15 Apr 2022

Cited by 1 | Viewed by 2059

Abstract

Laboratory experiments were conducted to measure the heat flux from seafoam continuously generated in natural seawater. Using a control volume technique, heat flux was calculated from foam and foam-free surfaces as a function of ambient humidity (ranged from 40% to 78%), air–water temperature [...] Read more.

Laboratory experiments were conducted to measure the heat flux from seafoam continuously generated in natural seawater. Using a control volume technique, heat flux was calculated from foam and foam-free surfaces as a function of ambient humidity (ranged from 40% to 78%), air–water temperature difference (ranged from −9 °C to 0 °C), and wind speed (variable up to 3 m s⁻¹). Water-surface skin temperature was imaged with a calibrated thermal infrared camera, and near-surface temperature profiles in the air, water, and foam were recorded. Net heat flux from foam surfaces increased with increasing wind speed and was shown to be up to four times greater than a foam-free surface. The fraction of the total heat flux due to the latent heat flux was observed for foam to be 0.75, with this value being relatively constant with wind speed. In contrast, for a foam-free surface the fraction of the total heat flux due to the latent heat flux decreased at higher wind speeds. Temperature profiles through foam are linear and have larger gradients, which increased with wind speed, while foam free surfaces show the expected logarithmic profile and show no variation with temperature. The radiometric surface temperatures show that foam is cooler and more variable than a foam-free surface, and bubble-resolving thermal images show that radiometrically transparent bubble caps and burst bubbles reveal warm foam below the cool surface layer, contributing to the enhanced variability. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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22 pages, 5691 KiB

Open AccessArticle

Improving the Representation of Whitecap Fraction and Sea Salt Aerosol Emissions in the ECMWF IFS-AER

by Samuel Rémy and Magdalena D. Anguelova

Remote Sens. 2021, 13(23), 4856; https://doi.org/10.3390/rs13234856 - 30 Nov 2021

Cited by 6 | Viewed by 2250 | Correction

Abstract

The European Centre for Medium-Range Weather Forecasts (ECMWF) operates the Integrated Forecasting System aerosol module (IFS-AER) to provide daily global analysis and forecast of aerosols for the Copernicus Atmosphere Monitoring Service (CAMS). New estimates of sea salt aerosol emissions have been implemented in [...] Read more.

The European Centre for Medium-Range Weather Forecasts (ECMWF) operates the Integrated Forecasting System aerosol module (IFS-AER) to provide daily global analysis and forecast of aerosols for the Copernicus Atmosphere Monitoring Service (CAMS). New estimates of sea salt aerosol emissions have been implemented in the IFS-AER using a new parameterization of whitecap fraction as a function of wind speed and sea surface temperature. The effect of whitecap fraction simulated by old and new parameterizations has been evaluated by comparing the IFS-AER new sea salt aerosol characteristics to those of aerosol retrievals. The new parameterization brought a significant improvement as compared to the two parameterizations of sea salt aerosol emissions previously implemented in the IFS-AER. Likewise, the simulated sea salt aerosol optical depth and surface concentration are significantly improved, as compared against ground and remote sensing products. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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13 pages, 3463 KiB

Open AccessArticle

A Novel Method to Discriminate Active from Residual Whitecaps Using Particle Image Velocimetry

by Xin Yang and Henry Potter

Remote Sens. 2021, 13(20), 4051; https://doi.org/10.3390/rs13204051 - 11 Oct 2021

Cited by 3 | Viewed by 1854

Abstract

Whitecap foam generated by wind-driven wave breaking is distinguished as either active (stage A) or residual (stage B). Discrimination of whitecap stages is essential to quantify the influence of whitecaps on the physical and chemical processes at the marine boundary layer. This study [...] Read more.

Whitecap foam generated by wind-driven wave breaking is distinguished as either active (stage A) or residual (stage B). Discrimination of whitecap stages is essential to quantify the influence of whitecaps on the physical and chemical processes at the marine boundary layer. This study provides a novel method to identify whitecap stages based on visible imagery using particle image velocimetry (PIV). Data used are from a Gulf of Mexico cruise where collocated infrared (IR) and visible cameras simultaneously recorded whitecaps. IR images were processed by an established thresholding method to determine stage A lifetime from brightness temperature. The visible images were also filtered using a thresholding method and then processed using PIV to estimate the average whitecap velocity. A linear relationship was established between the lifetime of stage A and the timescale of averaged velocity. This novel method allows stage A whitecap lifetime to be determined using whitecap velocity and provides an objective approach to separate whitecap stages. This method paves the way for future research to easily quantify whitecap stages using affordable off-the-shelf video cameras. Results, which include evidence that whitecaps stop advancing before stage A ends and may be an indication of bubble plume degassing, are discussed. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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23 pages, 5572 KiB

Open AccessArticle

Field Observations of Breaking of Dominant Surface Waves

by Pavel D. Pivaev, Vladimir N. Kudryavtsev, Aleksandr E. Korinenko and Vladimir V. Malinovsky

Remote Sens. 2021, 13(16), 3321; https://doi.org/10.3390/rs13163321 - 22 Aug 2021

Cited by 8 | Viewed by 2574

Abstract

The results of field observations of breaking of surface spectral peak waves, taken from an oceanographic research platform, are presented. Whitecaps generated by breaking surface waves were detected using video recordings of the sea surface, accompanied by co-located measurements of waves and wind [...] Read more.

The results of field observations of breaking of surface spectral peak waves, taken from an oceanographic research platform, are presented. Whitecaps generated by breaking surface waves were detected using video recordings of the sea surface, accompanied by co-located measurements of waves and wind velocity. Whitecaps were separated according to the speed of their movement, c, and then described in terms of spectral distributions of their areas and lengths over c. The contribution of dominant waves to the whitecap coverage varies with the wave age and attains more than 50% when seas are young. As found, the whitecap coverage and the total length of whitecaps generated by dominant waves exhibit strong dependence on the dominant wave steepness,

ϵ_{p}

, the former being proportional to

ϵ_{p}^{6}

. This result supports a parameterization of the dissipation term, used in the WAM model. A semi-empirical model of the whitecap coverage, where contributions of breaking of dominant and equilibrium range waves are separated, is suggested. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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15 pages, 3347 KiB

Open AccessArticle

Modulation of Wind-Wave Breaking by Long Surface Waves

by Vladimir A. Dulov, Aleksandr E. Korinenko, Vladimir N. Kudryavtsev and Vladimir V. Malinovsky

Remote Sens. 2021, 13(14), 2825; https://doi.org/10.3390/rs13142825 - 18 Jul 2021

Cited by 9 | Viewed by 2638

Abstract

This paper reports the results of field measurements of wave breaking modulations by dominant surface waves, taken from the Black Sea research platform at wind speeds ranging from 10 to 20 m/s. Wave breaking events were detected by video recordings of the sea [...] Read more.

This paper reports the results of field measurements of wave breaking modulations by dominant surface waves, taken from the Black Sea research platform at wind speeds ranging from 10 to 20 m/s. Wave breaking events were detected by video recordings of the sea surface synchronized and collocated with the wave gauge measurements. As observed, the main contribution to the fraction of the sea surface covered by whitecaps comes from the breaking of short gravity waves, with phase velocities exceeding 1.25 m/s. Averaging of the wave breaking over the same phases of the dominant long surface waves (LWs, with wavelengths in the range from 32 to 69 m) revealed strong modulation of whitecaps. Wave breaking occurs mainly on the crests of LWs and disappears in their troughs. Data analysis in terms of the modulation transfer function (MTF) shows that the magnitude of the MTF is about 20, it is weakly wind-dependent, and the maximum of whitecapping is windward-shifted from the LW-crest by 15 deg. A simple model of whitecaps modulations by the long waves is suggested. This model is in quantitative agreement with the measurements and correctly reproduces the modulations’ magnitude, phase, and non-sinusoidal shape. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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12 pages, 3726 KiB

Open AccessTechnical Note

An Experimental Study on Measuring Breaking-Wave Bubbles with LiDAR Remote Sensing

by David Wang, Damien Josset, Ivan Savelyev, Magdalena Anguelova, Stephanie Cayula and Anna Abelev

Remote Sens. 2022, 14(7), 1680; https://doi.org/10.3390/rs14071680 - 31 Mar 2022

Cited by 6 | Viewed by 2334

Abstract

Laboratory experiments were conducted to evaluate the feasibility of profiling and characterizing subsurface bubble plumes following a breaking wave event from an above-water Light Detection and Ranging (LiDAR) system. Measurements of LiDAR backscatter profiles of bubble plumes under mechanically generated breaking waves in [...] Read more.

Laboratory experiments were conducted to evaluate the feasibility of profiling and characterizing subsurface bubble plumes following a breaking wave event from an above-water Light Detection and Ranging (LiDAR) system. Measurements of LiDAR backscatter profiles of bubble plumes under mechanically generated breaking waves in a wave tank were collected and analyzed. After onset of wave breaking, the LiDAR backscatter increases rapidly by injected bubble plumes of active wave breaking. This intensification reaches a depth of one wave height within one wave period. After active wave breaking, the LiDAR backscatter from dissipated bubble plumes in the upper layer of water column decreases very slowly. The temporal variations of LiDAR backscatter are comparable to the collocated in-water measurements of optical backscatter at 850 nm wavelength and acoustic backscatter at 2000 kHz frequency. The decay rate of LiDAR backscatter of dissipated bubble plumes follows a power-law function consistent with decay rate of void fraction measurements in previous studies. This study demonstrates the viability and potential of using above-water LiDAR remote sensing to characterize subsurface bubble plumes. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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9 pages, 2590 KiB

Open AccessTechnical Note

Whitecap Observations by Microwave Radiometers: With Discussion on Surface Roughness and Foam Contributions

by Paul A. Hwang

Remote Sens. 2020, 12(14), 2277; https://doi.org/10.3390/rs12142277 - 15 Jul 2020

Cited by 3 | Viewed by 2125

Abstract

Ocean surface whitecaps manifest surface wave breaking. Most of the whitecap data reported in the literature are based on optical observations through photographic or video recording. The air in whitecaps modifies the dielectric properties of microwave emissions and scattering. Therefore, whitecap information is [...] Read more.

Ocean surface whitecaps manifest surface wave breaking. Most of the whitecap data reported in the literature are based on optical observations through photographic or video recording. The air in whitecaps modifies the dielectric properties of microwave emissions and scattering. Therefore, whitecap information is intrinsic to microwave signals. This paper discusses a method to retrieve the ocean surface whitecap coverage from microwave radiometer signals. Full article

(This article belongs to the Special Issue Passive Remote Sensing of Oceanic Whitecaps)

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