{"id":169,"date":"2021-06-04T11:03:35","date_gmt":"2021-06-04T10:03:35","guid":{"rendered":"https:\/\/www.iamas.org\/ecs\/?p=169"},"modified":"2021-06-04T11:03:35","modified_gmt":"2021-06-04T10:03:35","slug":"iamas-early-career-scientist-webinar-series-1-june-22nd-2021","status":"publish","type":"post","link":"https:\/\/www.iamas.org\/ecs\/2021\/06\/04\/iamas-early-career-scientist-webinar-series-1-june-22nd-2021\/","title":{"rendered":"IAMAS Early Career Scientist Webinar Series #1 June 22nd 2021"},"content":{"rendered":"\n

Tuesday June 22nd at 20:00-21:00 UTC<\/strong><\/h2>\n\n\n\n

All attendees must register through the following link:<\/strong>https:\/\/univ-lille-fr.zoom.us\/webinar\/register\/WN_RGclPVVCRWifn6NhS3lVJQ<\/a><\/p>\n\n\n\n

An Introduction to IAMAS<\/strong><\/p>\n\n\n\n

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Prof. Joyce Penner
President, International Association of Meteorology and Atmospheric Science
Distinguished Professor of Atmospheric Science, University of Michigan, USA<\/p>\n<\/div><\/div>\n\n\n\n

Professor Joyce Penner, the President of IAMAS, will first give an introductory talk about the IAMAS organization.<\/p>\n\n\n\n

South Pacific Ocean Climate Dynamics and Predictability<\/strong><\/p>\n\n\n\n

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Dr. Jiale Lou
CIRES, University of Colorado Boulder
NOAA Physical Science Laboratory<\/p>\n<\/div><\/div>\n\n\n\n

Abstract<\/strong>
The mechanisms and predictability of Pacific decadal climate variability (PDV) is an active area of research in climate science and is one of high societal importance. To date, most research into PDV has been focused on mechanisms and responses in the North Pacific. Dr Lou\u2019s PhD thesis presents a comprehensive investigation, based on the development and application of a family of hierarchical stochastically forced models, of the mechanisms underpinning PDV climate predictability and that focuses on the role of the South Pacific Ocean and coupling to the tropics.

First, a simple one-dimensional first-order autoregressive (AR1) model was used to understand the space and time variations of the South Pacific decadal oscillation (SPDO) \u2013 which represents the leading sea surface temperature (SST) mode in the South Pacific. The analysis revealed that the first Pacific-South American (PSA1) pattern is the key atmospheric driver of the SPDO. Further, the leading mode of integrated subsurface upper ocean temperature variability was shown to match expectations from the propagation of oceanic Rossby waves across the extratropical South Pacific, with the atmospheric PSA variability providing the high-frequency \u2018noise\u2019 source of the observed low-frequency (\u2018reddened\u2019) SST SPDO response.

Second, the stochastically forced AR1 model was generalised to higher-dimensional fields with the inclusion of spatial features using a linear inverse model (LIM) approach. The deterministic dynamics underpinning the combined tropical and South Pacific system was investigated, with the seasonal predictive skill of the SPDO and El Ni\u00f1o\u2013Southern Oscillation (ENSO) quantified under the LIM framework. It was found that, although the oscillatory periods of ENSO and the SPDO are distinct \u2013 the former oscillating on interannual timescales and the latter oscillating on (inter-)decadal timescales \u2013 their damping time scales were very similar, and their predictive skill comparable. With the inclusion of subsurface processes in the extratropical South Pacific, the linear predictive skill of both ENSO and the SPDO was found to be enhanced. Overall, the study showed that Pacific SST variability forecast skill from the computationally cheap LIMs was competitive with state-of-the-art operational seasonal forecast systems that employ sophisticated initialisation schemes and general circulation models, thus providing a useful benchmark for these operational systems.

Third, the LIM framework was applied to gain a deeper understanding of the role of stochastic forcing from the atmospheric PSA variability and to determine the optimal structures for initialised forecasts of the tropical and South Pacific climate system and its variability. This analysis revealed the spatial imprint of atmospheric PSA variability combined with temporal stochastic forcing that acts to drive the low frequency oceanic SST variability across the tropical and South Pacific, and excites optimal initial perturbations for the prediction of ENSO and the SPDO.

Finally, informed by the aforementioned hierarchy of stochastically forced linear reduced space models, Jiale\u2019s PhD thesis culminates with an overarching framework that links the atmosphere to the surface and subsurface oceans across a range of time scales from (intra-)seasonal to (inter-)decadal. Hence, the thesis provides, for the first time, a mechanistic framework and integrated understanding of the drivers of large-scale South Pacific climate variability and predictability.<\/p>\n\n\n\n

Dr Jiale Lou<\/strong> is now a postdoctoral researcher at the CIRES, University of Colorado Boulder and the NOAA Physical Science Laboratory. He is working on seasonal to decadal climate predictions and predictability of some environmental conditions by using a series of empirical climate models. His research interests include large-scale climate variability, climate dynamics, and climate predictions and predictability studies.<\/em> Prior to working with NOAA, he obtained his PhD degree in quantitative marine science at University of Tasmania, Australia. His PhD thesis is about the South Pacific Ocean climate dynamics and predictability.<\/em><\/td><\/tr><\/tbody><\/table><\/figure>\n","protected":false},"excerpt":{"rendered":"

Tuesday June 22nd at 20:00-21:00 UTC All attendees must register through the following link:https:\/\/univ-lille-fr.zoom.us\/webinar\/register\/WN_RGclPVVCRWifn6NhS3lVJQ An Introduction to IAMAS Prof. Joyce PennerPresident, International Association of Meteorology and Atmospheric ScienceDistinguished Professor of Atmospheric Science, University of Michigan, USA Professor Joyce Penner, the President of IAMAS, will first give an introductory talk about the IAMAS organization. South Pacific […]<\/p>\n","protected":false},"author":28,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"cybocfi_hide_featured_image":"","footnotes":""},"categories":[4],"tags":[6],"class_list":["post-169","post","type-post","status-publish","format-standard","hentry","category-events","tag-webinar"],"_links":{"self":[{"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/posts\/169","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/comments?post=169"}],"version-history":[{"count":2,"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/posts\/169\/revisions"}],"predecessor-version":[{"id":171,"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/posts\/169\/revisions\/171"}],"wp:attachment":[{"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/media?parent=169"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/categories?post=169"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.iamas.org\/ecs\/wp-json\/wp\/v2\/tags?post=169"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}