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<p>Hello everyone,</p>
<p><br>
</p>
<p>Aviatar Bach (<a class="moz-txt-link-freetext" href="https://eviatarbach.com/cv/">https://eviatarbach.com/cv/</a>) will be visiting the
Department of Scientific Computing March 1st and 2nd. <br>
</p>
<p>He will a talk <b> </b>at the colloquium of SC with the title <b>Towards
the combination of physical and data-driven forecasts for Earth
system prediction</b> today Wednesday March 1st starting at
3:30 in 499DSL. <br>
</p>
<p><br>
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<p>If you would like to join by zoom:
<a class="moz-txt-link-freetext" href="https://fsu.zoom.us/j/94273595552">https://fsu.zoom.us/j/94273595552</a><br>
</p>
<p><br>
</p>
<p>He is also available to talk with other scientist during his
visit. If you are interested please contact Olmo Zavala
<a class="moz-txt-link-abbreviated" href="mailto:osz09@fsu.edu">osz09@fsu.edu</a> ASAP.</p>
<p><br>
<b>Abstract:</b><br>
<br>
Due to the recent success of machine learning (ML) in many
prediction problems, there is a high degree of interest in
applying ML to Earth system prediction. However, because of the
high dimensionality of the system, it is critical to use hybrid
methods which combine data-driven models, physical models, and
observations. I will present two such hybrid methods: Ensemble
Oscillation Correction (EnOC) and the multi-model ensemble Kalman
filter (MM-EnKF).<br>
<br>
<br>
Oscillatory modes of the climate system are one of its most
predictable features, especially at intraseasonal timescales. It
has previously been shown that these oscillations can be predicted
well with statistical methods, often with better skill than
dynamical models. However, they only represent a portion of the
signal, and a method for beneficially combining them with
dynamical forecasts of the full system has not previously been
developed. Ensemble Oscillation Correction (EnOC) is a method
which corrects oscillatory modes in ensemble forecasts from
dynamical models. I will show results of EnOC applied to forecasts
of South Asian monsoon rainfall, outperforming the
state-of-the-art forecasts on subseasonal-to-seasonal timescales.<br>
<br>
<br>
A more general method for combining multiple models and
observations is multi-model data assimilation (MM-DA). MM-DA
generalizes the variational, Bayesian, and minimum variance
formulation of the Kalman filter. Here, I will show how multiple
model ensembles can be combined for both DA and forecasting in a
flow-dependent manner using a multi-model ensemble Kalman filter
(MM-EnKF). This methodology is applied to multiscale chaotic
models and results in significant error reductions compared to the
best model and to an unweighted multi-model ensemble. Lastly, I
will discuss the prospects of using the MM-EnKF for hybrid
forecasting.<br>
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<p>Thanks,</p>
<p>Olmo<br>
</p>
<p><br>
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<p style="margin-bottom: 0in; line-height: 100%"><font style="font-size: 10pt" color="#212529"><i><b>Olmo
Zavala-Romero</b></i></font></p>
<p><font color="#212529"><font face="Calibri, sans-serif"><font style="font-size: 9pt" size="2"><b>Assistant Professor</b></font></font></font>
</p>
<p><font style="font-size: 9pt" size="1"><b><a href="http://olmozavala.com" class="moz-txt-link-freetext">http://olmozavala.com</a></b></font>
</p>
<p><font color="#212529"><font face="Century Gothic, sans-serif"><font style="font-size: 8pt" size="2"><b>Department of
Scientific Computing</b></font></font></font></p>
<p><font color="#212529"><font face="Century Gothic, sans-serif"><font style="font-size: 8pt" size="2"><b>Florida State
University</b></font></font></font></p>
<p><font color="#212529"><font face="Century Gothic, sans-serif"><font style="font-size: 8pt" size="2">400 Dirac Science Library</font></font></font></p>
<p><font color="#212529"><font face="Century Gothic, sans-serif"><font style="font-size: 8pt" size="2">Tallahassee, FL 32306-4120</font></font></font></p>
<p><font face="Garamond, serif"><font style="font-size: 8pt" size="2"><b>Tel: 850-346-9101</b></font></font></p>
<p><font face="Garamond, serif"><font style="font-size: 8pt" size="2"><b>Email: <a class="moz-txt-link-abbreviated" href="mailto:osz09@fsu.edu">osz09@fsu.edu</a></b></font></font></p>
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