An Optical Flow Approach to Tracking Ship Track Behavior Using GOES-R Satellite Imagery
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Ship-tracks are produced by ship-emitted aerosols interacting with low clouds. Here, we apply deep learning models on satellite data to produce the first global climatology map of ship-tracks. We show that ship-tracks are at the nexus of cloud physics, maritime shipping, and fuel regulation. Our map captures major shipping lanes while missing others because of background conditions. Ship-track frequency is more than 10 times higher than a previous survey, and its interannual fluctuations reflect variations in cross-ocean trade, shipping activity, and fuel regulations. Fuel regulation can alter both detected frequency and shipping routes due to cost. The 2020 fuel regulation, together with the coronavirus disease 2019 pandemic, reduced ship-track frequency to its lowest level in recent decades across the globe and may have ushered in an era of low frequency. The regulation reduces the aerosol indirect forcing from ship emissions by 46% or between 0.02 and 0.27 W m −2 given its current estimates.
Ship emissions are a major source of aerosols over oceans, affecting both air quality and energy balance of the climate. However, estimates of their climate forcing diverge between studies relying on visible ship-tracks and those based on models. Here we show that forcing due to visible ship-tracks accounts for just 5% of the total forcing over the southeast Atlantic shipping-lane. Most forcing from ship emissions comes from aerosols that do not form detectable ship-tracks. They are only tips of the iceberg. We make three forcing calculations, one bottom-up based on visible ship-tracks, one top-down based on spatial relationships, and a hybrid approach that combines top-down or model estimated cloud droplet number concentration changes and cloud adjustments. Although the forcing based on machine learning detected ship tracks is an order of magnitude greater than prior results using manually detected ship-tracks, it remains only 5% of that inferred by top-down or cloud adjustment based methods for pre-2020 shipping. The top-down and the combined cloud adjustments methods show similar forcing for the post-2020 reduction in ships’ sulfur emission, although the methods have important regional differences in cloud adjustments that need further investigation. Our results reconcile a long-standing discrepancy in the literature and have important implications for aerosol indirect forcing and marine cloud brightening.
Ship tracks, long thin artificial cloud features formed from the pollutants in ship exhaust, are satellite-observable examples of aerosol-cloud interactions (ACI) that can lead to increased cloud albedo and thus increased solar reflectivity, phenomena of interest in solar radiation management. In addition to ship tracks being of interest to meteorologists and policy makers, their observed cloud perturbations provide benchmark evidence of ACI that remain poorly captured by climate models. To broadly analyze the effects of ship tracks, high-resolution satellite imagery data highlighting their presence are required. To support this, we provide a hand labelled dataset to serve as a benchmark for a variety of subsequent analyses. Established from a previous dataset that identified ship track presence using NASA’s MODIS Aqua satellite imager, our first-of-its-kind dataset is comprised of image masks: capturing full ship track regions, including their contours, emission points and dispersive patterns. In total, 300 images, or around 2,500 masked ship tracks, observed under varying conditions are provided, and may facilitate training of machine learning algorithms to automate extraction.
Ship tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship tracks from satellite data on a large scale is prohibitively costly while a large number of samples are required to improve our understanding. Here we train a deep neural network to automate finding ship tracks. The neural network model generalizes well as it not only finds ship tracks labeled by human experts but also detects those that are occasionally missed by humans. It finds more ship tracks than all previous studies combined and produces a map of ship track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship tracks on a large scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.
Ship tracks represent a natural laboratory to study the effects of aerosols on clouds. A number of observations and simulations have shown that increased droplet concentrations in ship tracks increase their total cross-sectional area, thereby enhancing cloud albedo and providing a negative radiative forcing at the surface and the top of the atmosphere. In some cases, cloud water has been found to be enhanced in ship tracks, which has been attributed to suppression of drizzle and implies an enhanced susceptibility of cloud albedo to droplet concentrations. However, more recently compiled observations indicate that cloud water is instead reduced in daytime ship tracks on average. Such a response is consistent with cloud-burning due to solar absorption by soot (the semi-direct radiative forcing of aerosols), recently suggested to be suppressing trade cumulus cloud coverage over the Indian Ocean. We will summarize observational evidence and present large-eddy simulations that consider these competing mechanisms in the effects of aerosols on cloud albedo.
It has long been known that cloud droplet concentrations are strongly influenced by cloud condensation nuclei (CCN) and that anthropogenic sources of pollution can affect CCN concentrations. More recently it has been suggested that CCN may play an important role in climate through their effect on cloud albedo. A interesting example of the effect of anthropogenic CCN on cloud albedo is the so-called 'ship track' phenomenon. Ship tracks were first observed in satellite imagery when the ship's emissions were evidently needed for the formation of a visible cloud. However, they appear more frequently in satellite imagery as modifications to existing stratus and stratocumulus clouds. The tracks are seen most clearly in satellite imagery by comparing the radiance at 3.7 microns with that at 0.63 and 11 microns. To account for the observed change in radiance, droplet concentrations must be high, and the mean size of the droplets small, in ship tracks. Researchers describe what they believe to be the first in situ measurements in what appears to have been a ship track.
The angular distribution of scattered radiation deep within a cloud layer was measured in marine stratocumulus clouds modified by the emissions from ships. These observations, obtained at thirteen discrete wavelengths between 0.5 and 2.3 microns, were obtained as the University of Washington Convair C-131A aircraft flew through a pair of roughly parallel ship tracks off the coast of southern California on 10 July 1987. In the first of these ship tracks, the cloud droplet concentration increased from 40 to 107/cu cm (125/cu cm in the second ship track). Simultaneous to this spectacular change, the aircraft measured interstitial aerosol (Aitken nucleus) concentration that increased from 400 to 1000/cu cm and cloud liquid water content that increased from 0.03 to 0.75 g/cu m. Broadband pyranometer measurements showed that the upwelling flux density increased from 150 to 280 W/sq m. These in-situ microphysics and broadband pyranometer results, together with AVHRR satellite images obtained with the NOAA-10 satellite, are described in detail by Radke et al., (1989). Internal scattered radiation measurements at selected wavelengths obtained with the cloud absorption radiometer (King et al., 1986) for a 100 km section of marine stratocumulus clouds containing these two ship track features are presented.
Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses. Increased aerosol concentrations due to human activity affect droplet number concentration, liquid water and cloud fraction, but these changes are subject to large uncertainties. Ship tracks, long lines of polluted clouds that are visible in satellite images, are one of the main tools for quantifying aerosol–cloud interactions. However, only a small fraction of the clouds polluted by shipping show ship tracks. Here we show that even when no ship tracks are visible in satellite images, aerosol emissions change cloud properties substantially. We develop a new method to quantify the effect of shipping on all clouds, showing a cloud droplet number increase and a more positive liquid water response when there are no visible tracks. We directly detect shipping-induced cloud property changes in the trade cumulus regions of the Atlantic, which are known to display almost no visible tracks. Our results indicate that previous studies of ship tracks were suffering from selection biases by focusing only on visible tracks from satellite imagery. The strong liquid water path response we find translates to a larger aerosol cooling effect on the climate, potentially masking a higher climate sensitivity than observed temperature trends would otherwise suggest.
Radar tracking ship performance during Faith 7 - Mercury /MA-9/ flight and evaluation for critical reentry tracking and manned space flight applications
The effect of anthropogenic aerosol on the reflectivity of stratocumulus cloud decks through changes in cloud amount is a major uncertainty in climate projections. In frequently occurring nonprecipitating stratocumulus, cloud amount can decrease through aerosol-enhanced cloud-top mixing. The climatological relevance of this effect is debated because ship exhaust only marginally reduces stratocumulus amount. By comparing detailed numerical simulations with satellite analyses, we show that ship-track studies cannot be generalized to estimate the climatological forcing of anthropogenic aerosol. The ship track–derived sensitivity of the radiative effect of nonprecipitating stratocumulus to aerosol overestimates their cooling effect by up to 200%. Further, the offsetting warming effect of decreasing stratocumulus amount needs to be taken into account if we are to constrain the cloud-mediated radiative forcing of anthropogenic aerosol.
Insertion ship tracking errors effect on Apollo Go, No-Go decision making
The ship position and attitude measurement system that was installed aboard the tracking ship Vanguard is described. An overview of the entire system is given along with a description of how precise time and frequency is utilized. The instrumentation is broken down into its basic components. Particular emphasis is given to the inertial navigation system. Each navigation system used, a mariner star tracker, navigation satellite system, Loran C and OMEGA in conjunction with the inertial system is described. The accuracy of each system is compared along with their limitations.
Results are presented from multispectral radiation measurements made within a marine stratocumulus cloud layer modified by ship-track effluents. The measurements showed that, compared with nearby noncontaminated clouds not affected by pollution, the upwelling intensity field of the modified stratocumulus clouds increased at a nonabsorbing wavelength in the visible region and decreased in the NIR, where absorption by liquid water is significant. The observations are consistent with an increased optical thickness, a reduced effective radius of the cloud droplets, and a reduced absorption in the contaminated cloud layer compared to a noncontaminated cloud.
Clouds adjust their albedo, amount and liquid water path to anthropogenic aerosols, and produce a climate forcing. Such cloud adjustments are complex functions of both environmental conditions and interaction time. However, direct observations of temporal changes in cloud adjustments are limited. Here, we develop a method to show observational evidence of substantial diel changes in cloud adjustments within ship-tracks. Polluted clouds experiencing extended nighttime exposure exhibit higher increases in cloud fraction while liquid-water path adjustments follow a non-monotonic evolution. The higher cloud fraction increase persists through daytime. Such diel variations likely stem from diel changes in solar heating and background cloud precipitation, and are important because nighttime changes persist and affect solar radiation during the day. Accounting for diel variations produces a stronger aerosol forcing, by −0.1 ∼−0.4 Wm −2 . Our approach reveals how the temporal evolution of cloud adjustments can have important implications for aerosol-cloud interactions.
Error analyses were performed to examine the height error in a relative sea-surface profile as determined by a combination of land-based multistation C-band radars and optical lasers and one ship-based radar tracking the GEOS 2 satellite. It was shown that two relative profiles can be obtained: one using available south-to-north passes of the satellite and one using available north-to-south type passes. An analysis of multi-station tracking capability determined that only Antigua and Grand Turk radars are required to provide satisfactory orbits for south-to-north type satellite passes, while a combination of Merritt Island, Bermuda, and Wallops radars provide secondary orbits for north-to-south passes. Analysis of ship tracking capabilities shows that high elevation single pass range-only solutions are necessary to give only moderate sensitivity to systematic error effects.
Abstract. The rate at which aerosols spread from a point source injection, such as from a ship or other stationary pollution source, is critical for accurately representing subgrid plume spreading in a climate model. Such climate model results will guide future decisions regarding the feasibility and application of large-scale intentional marine cloud brightening (MCB). Prior modeling studies have shown that the rate at which ship plumes spread may be strongly dependent on meteorological conditions, such as precipitating versus non-precipitating boundary layers and shear. In this study, we apply a Lagrangian particle model (PM-ABL v1.0), governed by a Langevin stochastic differential equation, to create a simplified framework for predicting the rate of spreading from a ship-injected aerosol plume in sheared, precipitating, and non-precipitating boundary layers. The velocity and position of each stochastic particle is predicted with the acceleration of each particle being driven by the turbulent kinetic energy, dissipation rate, momentum variance, and mean wind. These inputs to the stochastic particle velocity equation are derived from high-fidelity large-eddy simulations (LES) equipped with a prognostic aerosol–cloud microphysics scheme (UW-SAM) to simulate an aerosol injection from a ship into a cloud-topped marine boundary layer. The resulting spreading rate from the reduced-order stochastic model is then compared to the spreading rate in the LES. The stochastic particle velocity representation is shown to reasonably reproduce spreading rates in sheared, precipitating, and non-precipitating cases using domain-averaged turbulent statistics from the LES.
Support provided by USAS American Mariner, USNS Watertown, and USNS Huntsville for Mercury MA-8 mission