MCRN Colloquium resumes

2016 Spring Schedule

Friday, January 15th, 2016, 9:30am EST: Henk Dijkstra (University of Utrecht, The Netherlands)

Title: Transitions in high-dimensional climate models  

Abstract: Climate research deals with changes in the statistics rather than in the exact state of the Earth system. Ergodic theory is aimed to relating the dynamics of a system to its statistical properties and thus particularly suitable for developing a theory of climate variability. In this presentation, concepts of ergodic theory will be used to study climate variability and response to forcing. In particular, it is shown that crucial information on the stability of the climate system can be extracted by approximations of the associated transfer operators and their ergodicity spectrum. The methodology is applied to transitions in high-dimensional models of the El Nino/Southern Oscillation, midlatitude atmospheric blocking events and transitions between a snow-free and snow-covered Earth.


Monday, February 1, 2016, 10am ESTLaura Slivinski (NOAA)

Title: An application of Lagrangian data assimilation to Katama Bay, MA  

Abstract: Data assimilation is the process of combining predictions from numerical models with observations of the system. Fully Lagrangian data assimilation seeks to directly assimilate trajectories from drifters into some circulation model. This talk will provide a brief overview of Lagrangian data assimilation, followed by tests of assimilating trajectories from surface drifters into a model of a small bay to improve the estimate of a spatially-dependent model parameter. We focus on the Manning’s n coefficient of friction, a parameter that generally must be tuned by hand, in the narrow, time-varying southern inlet of the bay. Synthetic experiments show that Lagrangian data assimilation can successfully estimate this parameter, regardless of the location of the drifters. Experiments with real data from 2013 show that assimilating drifter trajectories, released for a time period on the order of an hour, can improve upon the original tuned value of this parameter; however, this improvement seems to depend on the initial offset between modeled and observed velocities.

Joint work with: Larry Pratt, Irina Rypina, Mara Orescanin


Mondays, February 8 and 15:  No webinars for Lunar New Year and U.S. Presidents’ Day


Monday, February 22, 2016, 4pm ESTVladimir Alexeev (International Arctic Research Center, University of Alaska Fairbanks)

Title: Local and non-local mechanisms of Arctic warming 

Abstract: Polar amplification (PA) is a prominent feature of currently observed and predicted future climate change suggested by both observations and models. We will discuss several PA mechanisms and feedbacks in the ocean and the atmosphere suggested by different researchers and connect it to the real world observations. Surface albedo feedback (SAF) has been shown to contribute prominently to the currently observed PA along with other mechanisms, e.g. involving atmospheric heat transport. SAF is believed to be a strong positive local feedback, while atmospheric heat transport makes the connection between the Arctic and the low latitudes non-local. We will also discuss a more general method of feedback analysis that results in feedback and gain matrices.

Joint work with: Craig Jackson


Monday, February 29, 2016, 10am ESTMarc Kjerland (Disaster Prevention Research Institute, Kyoto University)

Title: Adaptive mesh refinement for storm surge modeling

Abstract: Coastal inundation such as storm surge is a major concern for many of the world's population centers, and recent disasters such as Hurricane Sandy and Typhoon Haiyan highlight the growing risks of climate change. Numerical simulation of storm surge can be challenging due to the large spatial scales required, but using simplified fluid equations and adaptive mesh refinement can greatly reduce computation time with minimal loss of accuracy. In this study we look at an application to Typhoon Haiyan and the potential challenges of this approach.


Monday, March 7, 2016, 4pm EST: Axel Timmermann (International Pacific Research Center, University of Hawaii)

Title: Nonlinear dynamics of the El Niño Southern Oscillation

Abstract: Currently, the strongest El Nino on record wreaks havoc across our planet, shifting global sea level and weather patterns and creating famines in South Africa and Central America. Other areas have experienced flooding which may have facilitated the outbreak of the mosquito-borne Zika virus across parts of Brazil and the Dengue virus in Hawaii. 

Even though this event has led to massive disruptions of livelihoods and economies, many of its physical aspects still remain elusive: What caused its explosive growth in summer 2015? Why did a similar initial condition in 2014 trigger only a small event? Why are La Nina events weaker than El Nino events? What processes terminate El Nino events? How long can an El Nino last? These are crucial questions that need to be resolved to improve seasonal predictions of future climate anomalies in the tropical regions. 

My talk will address how concepts of nonlinear dynamical systems’ analysis can help to elucidate the underlying processes and timing of El Nino's growth and demise. The presentation will touch upon Combination modes, Nonlinear resonances, Global Bifurcations, Mixed Mode Oscillations, Noise-induced instabilities and forbidden return times. 


Mondays, March 13, 27 and April 3:  No webinars during various Daylight Saving Time changes throughout the world and U.S. Spring Breaks 


Monday, April 11, 2016, 4pm EDT: Juan Durazo (Arizona State University)

Title: Data assimilation for extreme ionospheric events: observing system experiments of the September 26, 2011 geomagnetic storm  

Abstract: As increasingly sophisticated ground- and space-based technological systems that depend on the near-Earth space environment are being built, vulnerabilities to variations in the ionosphere are also increasing. These vulnerabilities are especially prominent during extreme space-weather events, where satellite communication systems or terrestrial power grid are at risk of being disrupted. Data assimilation has become an essential tool for the specification of ionospheric space-weather, in particular the evolution of its electron density distribution. In this study, we use the Local Ensemble Transform Kalman Filter (LETKF) data assimilation scheme and the Thermosphere-Ionosphere-Electrodynamics Global Circulation Model (TIEGCM) to track and forecast the global electron density distribution during a recent geomagnetic storm in September 26, 2011. Synthetic observations are generated and are assimilated into the ensemble forecast at every hour, using observations available within 30 minutes of analysis time. As a system that is strongly driven by external influences, the quality ionospheric forecasts depends on the estimation of these drivers, which include solar conditions, geomagnetic activity, and the state of the charge-neutral thermosphere, which is intimately coupled with the ionosphere. Thus the data assimilation system employed is extended to estimate these drivers in addition to the electron density state. Results show that the LETKF can adequately handle the inverse problem of using the available observations to estimate the ionospheric drivers that generated them, in addition to estimating the global distribution of electron density during this extreme space-weather event.


Monday, April 18, 2016, 10am EDT: Mary Silber (University of Chicago) and Karna Gowda (Northwestern University)

Title: Vegetation patterns in mathematical models, and vegetation patterns in Somalia

Abstract:  Visually striking large-scale spatial patterns of vegetation have been observed in semi-arid regions in the Americas, Africa and Australia. These have led to suggestions by theoretical ecologists that certain characteristics of the patterns may serve as early-warning signs of desertification. This is an attractive idea since these patterns can be monitored through satellite imaging of the globe.

A number of conceptual mathematical models of water-vegetation interactions, of advection-reaction-diffusion type, have been developed to explore the process of vegetation collapse as annual mean precipitation decreases. We probe one of these early warning sign proposals, within the context of varying parameters of a mathematical model of vegetation patterns, to assess its robustness. This leads to the identification of the key modeling assumptions that support the early warning sign scenario within this mathematical model. At the same time, we have become very interested in the potential of the satellite data to identify directly possible early warning signs, and towards this end, we are focusing on images of Somalia vegetation patterns, over many decades, to assess changes. The first part of this talk, presented by Mary Silber, will highlight the results of our PDE model analysis, and the second part of this talk, presented by Karna Gowda, will describe our proposed and preliminary investigations of satellite image data of Somalia.


Monday, April 25, 2016, 4pm EDT: Erik Van Vleck (University of Kansas)

Title: Hybrid Data Assimilation Techniques and Applications

Abstract: Data assimilation provides a framework for incorporating data or observations into models for both state space and parameter estimation. In this talk we discuss the development of some hybrid data assimilation techniques based upon shadowing refinement. These techniques employ dimension reduction motivated by time dependent stability theory and are designed in an equation free form for application from conceptual to large stand-alone models. We discuss some of the applications we are investigating using these techniques and illustrate their effectiveness on some model problems.


Monday, May 2, 2016, 10am EDT: Amit Apte (International Centre for Theoretical Sciences of the Tata Institute of Fundamental Research, India)

Title:  Simple models of the Indian summer monsoon

Abstract:  The Indian summer monsoon is a dramatic multiscale, multiphysics event that has a profound impact on the food security of more than a billion people. Predictions for the monsoon rainfall using present-day general circulation models are often wide of the mark, with serious consequences for the economy of the countries of the Indian subcontinent. An understanding of the basic dynamical features of the monsoon system is an important open problem.

In this talk, I will try to review "my" current understanding (to be distinguished from "our" current understanding) of the salient features of the dynamics of the monsoon. I will also present some of the past attempts at modelling some features of the monsoon using simple models. In particular, I will discuss the PDE models related to the work of Gill (doi:10.1002/qj.49710644905) and ODE models related to the work of Zickfeld et al. (doi:10.1029/2005GL022771). This is an ongoing work in collaboration with Raj Saha, Rama Govindarajan, Vishal Vasan, SajiniAnand, Vijay Prakash.


* For current information, see the latest MCRN Newsletter.  


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