Toward data assimilation of ship-induced aerosol–cloud interactions

Patel, Lekha; Shand, Lyndsay

doi:10.1017/eds.2022.21

Toward data assimilation of ship-induced aerosol–cloud interactions

Journal Article · Fri Dec 23 00:00:00 EST 2022 · Environmental Data Science

DOI:https://doi.org/10.1017/eds.2022.21· OSTI ID:2311708

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Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Satellite imagery can detect temporary cloud trails or ship tracks formed from aerosols emitted from large ships traversing our oceans, a phenomenon that global climate models cannot directly reproduce. Ship tracks are observable examples of marine cloud brightening, a potential solar climate intervention that shows promise in helping combat climate change. In this paper, we demonstrate a simulation-based approach in learning the behavior of ship tracks based upon a novel stochastic emulation mechanism. Our method uses wind fields to determine the movement of aerosol–cloud tracks and uses a stochastic partial differential equation (SPDE) to model their persistence behavior. This SPDE incorporates both a drift and diffusion term which describes the movement of aerosol particles via wind and their diffusivity through the atmosphere, respectively. We first present our proposed approach with examples using simulated wind fields and ship paths. We then successfully demonstrate our tool by applying the approximate Bayesian computation method-sequential Monte Carlo for data assimilation.

View Accepted Manuscript (DOE)

Research Organization:: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: NA0003525

OSTI ID:: 2311708

Report Number(s):: SAND--2023-11630J

Journal Information:: Environmental Data Science, Journal Name: Environmental Data Science Vol. 1; ISSN 2634-4602

Publisher:: Cambridge University PressCopyright Statement

Country of Publication:: United States

Language:: English

References (19)

Transport impacts on atmosphere and climate: Shipping Eyring, Veronika; Isaksen, Ivar S. A.; Berntsen, Terje Atmospheric Environment, Vol. 44, Issue 37 https://doi.org/10.1016/j.atmosenv.2009.04.059	journal	December 2010
Turbulent diffusion and turbulent thermal diffusion of aerosols in stratified atmospheric flows Sofiev, M.; Sofieva, V.; Elperin, T. Journal of Geophysical Research: Atmospheres, Vol. 114, Issue D18 https://doi.org/10.1029/2009JD011765	journal	September 2009
Locally Enhanced Aerosols Over a Shipping Lane Produce Convective Invigoration but Weak Overall Indirect Effects in Cloud-Resolving Simulations Blossey, Peter N.; Bretherton, Christopher S.; Thornton, Joel A. Geophysical Research Letters, Vol. 45, Issue 17 https://doi.org/10.1029/2018GL078682	journal	September 2018
Substantial Cloud Brightening From Shipping in Subtropical Low Clouds Diamond, Michael S.; Director, Hannah M.; Eastman, Ryan AGU Advances, Vol. 1, Issue 1 https://doi.org/10.1029/2019AV000111	journal	March 2020
Automatically Finding Ship Tracks to Enable Large‐Scale Analysis of Aerosol‐Cloud Interactions Yuan, Tianle; Wang, Chenxi; Song, Hua Geophysical Research Letters, Vol. 46, Issue 13 https://doi.org/10.1029/2019GL083441	journal	July 2019
Aerosols in the E3SM Version 1: New Developments and Their Impacts on Radiative Forcing Wang, Hailong; Easter, Richard C.; Zhang, Rudong Journal of Advances in Modeling Earth Systems, Vol. 12, Issue 1 https://doi.org/10.1029/2019MS001851	journal	January 2020
Effects of ship emissions on sulphur cycling and radiative climate forcing over the ocean Capaldo, Kevin; Corbett, James J.; Kasibhatla, Prasad Nature, Vol. 400, Issue 6746 https://doi.org/10.1038/23438	journal	August 1999
Control of global warming? Latham, John Nature, Vol. 347, Issue 6291 https://doi.org/10.1038/347339b0	journal	September 1990
Large contribution of natural aerosols to uncertainty in indirect forcing Carslaw, K. S.; Lee, L. A.; Reddington, C. L. Nature, Vol. 503, Issue 7474 https://doi.org/10.1038/nature12674	journal	November 2013
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems Toni, Tina; Welch, David; Strelkowa, Natalja Journal of The Royal Society Interface, Vol. 6, Issue 31 https://doi.org/10.1098/rsif.2008.0172	journal	July 2008
Bayesian Tracking and Parameter Learning for Non-Linear Multiple Target Tracking Models No authors listed IEEE Transactions on Signal Processing, Vol. 63, Issue 21 https://doi.org/10.1109/TSP.2015.2454474	journal	November 2015
A New Approach to Linear Filtering and Prediction Problems Kalman, R. E. Journal of Basic Engineering, Vol. 82, Issue 1 https://doi.org/10.1115/1.3662552	journal	March 1960
Anomalous Cloud Lines Conover, John H. Journal of the Atmospheric Sciences, Vol. 23, Issue 6 https://doi.org/10.1175/1520-0469(1966)023<0778:ACL>2.0.CO;2	journal	November 1966
Comments on “Anomalous Cloud Lines” Twomey, S.; Howell, H. B.; Wojciechowski, T. A. Journal of the Atmospheric Sciences, Vol. 25, Issue 2 https://doi.org/10.1175/1520-0469(1968)025<0333:COCL>2.0.CO;2	journal	March 1968
NOAA’s HYSPLIT Atmospheric Transport and Dispersion Modeling System Stein, A. F.; Draxler, R. R.; Rolph, G. D. Bulletin of the American Meteorological Society, Vol. 96, Issue 12 https://doi.org/10.1175/BAMS-D-14-00110.1	journal	December 2015
On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo Filippi, Sarah; Barnes, Chris P.; Cornebise, Julien Statistical Applications in Genetics and Molecular Biology, Vol. 12, Issue 1 https://doi.org/10.1515/sagmb-2012-0069	journal	January 2013
Manipulating marine stratocumulus cloud amount and albedo: a process-modelling study of aerosol-cloud-precipitation interactions in response to injection of cloud condensation nuclei Wang, H.; Rasch, P. J.; Feingold, G. Atmospheric Chemistry and Physics, Vol. 11, Issue 9 https://doi.org/10.5194/acp-11-4237-2011	journal	January 2011
Large eddy simulation of ship tracks in the collapsed marine boundary layer: a case study from the Monterey area ship track experiment Berner, A. H.; Bretherton, C. S.; Wood, R. Atmospheric Chemistry and Physics, Vol. 15, Issue 10 https://doi.org/10.5194/acp-15-5851-2015	journal	January 2015
The efficacy of aerosol–cloud radiative perturbations from near-surface emissions in deep open-cell stratocumuli Possner, Anna; Wang, Hailong; Wood, Robert Atmospheric Chemistry and Physics, Vol. 18, Issue 23 https://doi.org/10.5194/acp-18-17475-2018	journal	January 2018

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