{"id":92,"date":"2020-09-04T16:37:29","date_gmt":"2020-09-04T16:37:29","guid":{"rendered":"https:\/\/nike.atmos.ucla.edu\/henry\/?page_id=92"},"modified":"2025-12-11T19:20:53","modified_gmt":"2025-12-11T19:20:53","slug":"home","status":"publish","type":"page","link":"https:\/\/atmos.ucla.edu\/mchekroun\/","title":{"rendered":"Home"},"content":{"rendered":"\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-28f84493 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\">\n<div class=\"wp-block-media-text is-stacked-on-mobile\"><figure class=\"wp-block-media-text__media\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"274\" src=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/picture_chekroun2.jpg\" alt=\"\" class=\"wp-image-450 size-full\" srcset=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/picture_chekroun2.jpg 400w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/picture_chekroun2-300x206.jpg 300w\" sizes=\"auto, (max-width: 400px) 100vw, 400px\" \/><\/figure><div class=\"wp-block-media-text__content\">\n<h2 class=\"wp-block-heading\">Micka\u00ebl D. Chekroun<\/h2>\n\n\n\n<p>Researcher<\/p>\n\n\n\n<p>Ph. D in Mathematics<br>mchekroun@atmos.ucla.edu<\/p>\n<\/div><\/div>\n<\/div>\n<\/div>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Research Interests<\/h2>\n\n\n\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/www.pnas.org\/doi\/full\/10.1073\/pnas.1321816111\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"302\" src=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/sens_bis_copy.jpg\" alt=\"\" class=\"wp-image-452\" srcset=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/sens_bis_copy.jpg 400w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/sens_bis_copy-300x227.jpg 300w\" sizes=\"auto, (max-width: 400px) 100vw, 400px\" \/><\/a><\/figure>\n\n\n\n<h3 class=\"wp-block-heading has-lighter-blue-background-color has-background\"><strong>Modes of Variability:&nbsp;<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/doi.org\/10.1088\/1361-6633\/ae2206\" target=\"_blank\" rel=\"noreferrer noopener\">Kolmogorov modes of jump-diffusion models<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/aip.scitation.org\/doi\/full\/10.1063\/1.4989400\" target=\"_blank\" rel=\"noreferrer noopener\">Data-adaptive harmonic modes<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1007\/s10955-020-02535-x\" target=\"_blank\" rel=\"noreferrer noopener\">Ruelle-Pollicott resonances, correlations and power spectra<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1007\/s10955-020-02526-y\" target=\"_blank\" rel=\"noreferrer noopener\">Characterization of stochastic nonlinear oscillations<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Stochastic Non-equilibrium Systems:&nbsp;<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/doi.org\/10.1088\/1751-8121\/ada7ad\" target=\"_blank\" rel=\"noreferrer noopener\">Non-Markovian reduced models to unravel transitions<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.jde.2022.11.025\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic transitions in non-equilibrium systems<\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.springer.com\/us\/book\/9783319124957\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic invariant manifolds for SPDEs<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.jde.2015.10.022\" target=\"_blank\" rel=\"noreferrer noopener\">Stampacchia Maximum Principle for SPDEs<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Data-driven Equations Discovery:<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/doi.org\/10.1063\/5.0039496\" target=\"_blank\" rel=\"noreferrer noopener\">Data-driven stochastic models and the Koopman operator<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1063\/1.4989400\" target=\"_blank\" rel=\"noreferrer noopener\">Data-driven networks of stochastic nonlinear oscillators<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.physd.2014.12.005\" target=\"_blank\" rel=\"noreferrer noopener\">Data-driven non-Markovian closure models<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Closure of Multiscale Systems:<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/doi.org\/10.1088\/1751-8121\/ada7ad\" target=\"_blank\" rel=\"noreferrer noopener\">Non-Markovian reduced models to unravel transitions<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1063\/5.0167419\" target=\"_blank\" rel=\"noreferrer noopener\">Anticipating tipping points and higher-order critical transitions<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1007\/s10955-019-02458-2\" target=\"_blank\" rel=\"noreferrer noopener\">Variational approach to closure of nonlinear dynamics<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.compfluid.2016.07.005\" target=\"_blank\" rel=\"noreferrer noopener\">Fast oscillations and balance motions in reduced primitive equations<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.pnas.org\/doi\/full\/10.1073\/pnas.2113650118\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic rectification of slow manifold closures<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.3390\/fluids3010021\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic nonlinear oscillator models of&nbsp; jet-eddy interactions<\/a>&nbsp;<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Response Theory\/Optimal Control:&nbsp;<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/arxiv.org\/abs\/2411.14769\" target=\"_blank\" rel=\"noreferrer noopener\">Linear response of jump-diffusion models<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.science.org\/doi\/10.1126\/sciadv.abq7137\" target=\"_blank\" rel=\"noreferrer noopener\">Jump-diffusion induced chaos in high-dimension<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/arxiv.org\/abs\/2212.02628\" target=\"_blank\" rel=\"noreferrer noopener\">Detecting and attributing change in climate and complex systems<\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.pnas.org\/content\/111\/5\/1684.full\" target=\"_blank\" rel=\"noreferrer noopener\">Rough parameter dependence and Ruelle-Pollicott resonances<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1007\/s10440-014-9949-1\" target=\"_blank\" rel=\"noreferrer noopener\">Finite-horizon parametrizing manifolds for optimal control reduction<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Time-Delay Systems:&nbsp;<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/www.science.org\/doi\/10.1126\/sciadv.abq7137\" target=\"_blank\" rel=\"noreferrer noopener\">Shear-induced chaos and model&#8217;s variability enhancement<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.physd.2024.134058\" target=\"_blank\" rel=\"noreferrer noopener\">SNO bifurcation, tipping solution paths, and ENSO variability<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/drive.google.com\/file\/d\/12iNibnogzCRcRnOYakCRHVMROu0X9HgE\/view\" target=\"_blank\" rel=\"noreferrer noopener\">Hopf bifurcations in cloud-rain delay models<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.aimsciences.org\/article\/doi\/10.3934\/dcds.2016.36.4133\" target=\"_blank\" rel=\"noreferrer noopener\">Galerkin-Koornwinder approximations<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1515\/9783110543599-004\" target=\"_blank\" rel=\"noreferrer noopener\">Optimal control of delay equations<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Machine Learning for Complex Systems:<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/doi.org\/10.1029\/2023MS003795\" target=\"_blank\" rel=\"noreferrer noopener\">Turbulence closure with small, local neural networks<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/iopscience.iop.org\/article\/10.1088\/2632-072X\/ad3e59\" target=\"_blank\" rel=\"noreferrer noopener\">The high-frequency and rare events barriers to neural closures<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Critical Transitions:<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/doi.org\/10.1088\/1751-8121\/ada7ad\" target=\"_blank\" rel=\"noreferrer noopener\">Non-Markovian reduced models to unravel transitions<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.jde.2022.11.025\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic transitions in non-equilibrium systems<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1063\/5.0167419\" target=\"_blank\" rel=\"noreferrer noopener\">Anticipating tipping points and higher-order critical transitions<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1007\/978-3-319-58895-7_1\" target=\"_blank\" rel=\"noreferrer noopener\">Pullback Attractor Crisis<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>Applications to Earth Science (selected):&nbsp;<\/strong><\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/arxiv.org\/abs\/2212.02628\" target=\"_blank\" rel=\"noreferrer noopener\">Detecting and attributing change in climate and complex systems<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/www.science.org\/doi\/10.1126\/sciadv.adq7518\" target=\"_blank\" rel=\"noreferrer noopener\">Gibbs states and Brownian models for haze and cloud droplets<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1038\/s42254-023-00650-8\" target=\"_blank\" rel=\"noreferrer noopener\">Theoretical tools for climate crisis and Hasselmann&#8217;s program revisited<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.5194\/acp-23-6559-2023\" target=\"_blank\" rel=\"noreferrer noopener\">Opposing trends of cloud coverage over land and ocean<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1073\/pnas.1015753108\" target=\"_blank\" rel=\"noreferrer noopener\">Past-noise forecasting of ENSO<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/link.springer.com\/chapter\/10.1007%2F978-3-319-58895-7_10\" target=\"_blank\" rel=\"noreferrer noopener\">Data-driven stochastic modeling of Arctic sea ice<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1175\/JCLI-D-15-0372.1\" target=\"_blank\" rel=\"noreferrer noopener\">Low-order reduced models of GCM datasets<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1002\/grl.50991\" target=\"_blank\" rel=\"noreferrer noopener\">Low-order reduced models of Madden-Julian oscillation<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.5194\/esd-8-1171-2017\" target=\"_blank\" rel=\"noreferrer noopener\">Paleoclimate stochastic models<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/doi.org\/10.1016\/j.physd.2011.06.005\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic climate dynamics and random attractors<\/a><\/li>\n<\/ul>\n\n\n\n<p><\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-align-center\"><a href=\"https:\/\/doi.org\/10.1029\/2023MS003795\" target=\"_blank\" rel=\"noreferrer noopener\">Turbulence Closure with Small, Neural Networks:<\/a><\/h3>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"800\" height=\"268\" src=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/jets.png\" alt=\"\" class=\"wp-image-458\" srcset=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/jets.png 800w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/jets-300x101.png 300w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/jets-768x257.png 768w\" sizes=\"auto, (max-width: 800px) 100vw, 800px\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\"><strong>Vimeo movie<\/strong>:&nbsp;<strong><a href=\"https:\/\/vimeo.com\/824681438\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/vimeo.com\/824681438<\/a><\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-align-center\"><strong><a href=\"http:\/\/www.sciencedirect.com\/science\/article\/pii\/S016727891100145X\" target=\"_blank\" rel=\"noreferrer noopener\">Stochastic Strange Attractor (Chekroun et al. (2011), Physica D, 240):<\/a><\/strong><\/h3>\n\n\n\n<figure class=\"wp-block-image aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"395\" height=\"400\" src=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/lora_0_3_bis_copy.jpg\" alt=\"\" class=\"wp-image-460\" srcset=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/lora_0_3_bis_copy.jpg 395w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/lora_0_3_bis_copy-296x300.jpg 296w\" sizes=\"auto, (max-width: 395px) 100vw, 395px\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\"><strong>Vimeo movie<\/strong>:&nbsp;<strong><a href=\"https:\/\/vimeo.com\/240039610\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/vimeo.com\/240039610<\/a><\/strong><\/p>\n\n\n\n<h3 class=\"wp-block-heading has-text-align-center\"><a href=\"https:\/\/www.science.org\/doi\/10.1126\/sciadv.abq7137\" target=\"_blank\" rel=\"noreferrer noopener\">Cloud Physics and Stochastic Strange Attractors (Chekroun&nbsp;<em>et al.<\/em>&nbsp;(2022), Science Advances, 8 (46)):<\/a><\/h3>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"800\" height=\"519\" src=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/toto_snap.png\" alt=\"\" class=\"wp-image-461\" srcset=\"https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/toto_snap.png 800w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/toto_snap-300x195.png 300w, https:\/\/atmos.ucla.edu\/mchekroun\/wp-content\/uploads\/sites\/25\/2025\/12\/toto_snap-768x498.png 768w\" sizes=\"auto, (max-width: 800px) 100vw, 800px\" \/><\/figure>\n\n\n\n<p class=\"has-text-align-center\"><strong>Vimeo movie<\/strong>:&nbsp;<strong><a href=\"https:\/\/vimeo.com\/773696444\" target=\"_blank\" rel=\"noreferrer noopener\">https:\/\/vimeo.com\/773696444<\/a><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Micka\u00ebl D. Chekroun Researcher Ph. D in Mathematicsmchekroun@atmos.ucla.edu Research Interests Modes of Variability:&nbsp; Stochastic Non-equilibrium Systems:&nbsp; Data-driven Equations Discovery: Closure of Multiscale Systems: Response Theory\/Optimal Control:&nbsp; Time-Delay Systems:&nbsp; Machine Learning for Complex Systems: Critical Transitions: Applications to Earth Science (selected):&nbsp; Turbulence Closure with Small, Neural Networks: Vimeo movie:&nbsp;https:\/\/vimeo.com\/824681438 Stochastic Strange Attractor (Chekroun et al. (2011),&#8230;<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-landing.php","meta":{"footnotes":""},"class_list":["post-92","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/pages\/92","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/comments?post=92"}],"version-history":[{"count":17,"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/pages\/92\/revisions"}],"predecessor-version":[{"id":467,"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/pages\/92\/revisions\/467"}],"wp:attachment":[{"href":"https:\/\/atmos.ucla.edu\/mchekroun\/wp-json\/wp\/v2\/media?parent=92"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}