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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt"> </span></b><u></u><u></u></p>
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<p class="MsoNormal" style="text-align:center" align="center"><b><span style="font-size:36.0pt;font-family:"Cambria","serif";color:#6c3fb5">JCSDA
Seminar</span></b><u></u><u></u></p>
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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt">Title</span></b><u></u><u></u></p>
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<p class="MsoNormal"><b><span style="font-size:18.0pt;font-family:"Arial","sans-serif"">Hidden
Error Variance Theory and its use in Hybrid Data
Assimilation</span></b><b><span style="font-size:18.0pt;font-family:"Arial","sans-serif""><u></u><u></u></span></b></p>
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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt">Speaker</span></b><u></u><u></u></p>
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<p class="MsoNormal"><b><span style="font-size:14.0pt;font-family:"Arial","sans-serif"">Craig
Bishop<br>
Naval Research Laboratory </span></b><b><span style="font-size:16.0pt;font-family:"Arial","sans-serif""><u></u><u></u></span></b></p>
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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt">Date,
Time & Place</span></b><u></u><u></u></p>
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<p class="MsoNormal"><b><span style="font-size:14.0pt;font-family:"Arial","sans-serif"">Friday,
<span> </span>November 2,
2012<br>
</span></b><b><span style="font-family:"Arial","sans-serif";color:red">2:00
– 3:00 PM, Conference Center</span></b><span style="font-family:"Arial","sans-serif"">,
NOAA Center for Weather and Climate Prediction, <span>5830 University
Research Court, College Park, MD </span><u></u><u></u></span></p>
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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt">Abstract</span></b><u></u><u></u></p>
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<p class="MsoNormal" style="text-align:justify;text-justify:inter-ideograph"><span style="font-size:11.0pt;font-family:"Arial","sans-serif"">A
conundrum of predictability research is that while the
prediction of flow dependent error distributions is one
of its main foci, chaos fundamentally hides flow
dependent forecast error distributions from empirical
observation. Empirical estimation of such error
distributions requires that one obtain a large sample of
error realizations given the same flow and the same
observational network.<span> </span>However,
chaotic elements of the flow and the observing network
make it practically impossible to observe and collect
the conditioned sample of errors required to empirically
define such distributions and their variance. These
variances are “hidden”. Here, an exposition of the
problem is developed from an ensemble Kalman filter data
assimilation system applied to a 10 variable non-linear
chaotic model and 25,000 replicate models. The output
from this system motivates a new analytical model for
the distribution of true error variances given an
imperfect ensemble variance. This model is defined by 6
parameters that also determine the optimal weights for
the static and flow dependent parts of Hybrid error
variance models.<span> </span>Six
new equations enable these hidden parameters to be
accurately estimated from a long time series of
(innovation, ensemble variance) data pairs.<span> </span>This new-found
ability to estimate hidden parameters provides new tools
for assessing the quality of ensemble forecasts, tuning
Hybrid error variance models and for post-processing
ensemble forecasts. Preliminary results from attempts to
use the theory to speed the tuning of Hybrid data
assimilation schemes will also be presented.<u></u><u></u></span></p>
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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt">Remote
Access</span></b><u></u><u></u></p>
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<p class="MsoNormal"><b><span style="font-size:10.0pt;font-family:"Arial","sans-serif"">Video:</span></b><span style="font-size:10.0pt;font-family:"Arial","sans-serif""> 1.</span><span style="font-size:10.0pt"> </span><span style="font-size:10.0pt;font-family:"Arial","sans-serif"">Go to </span><a href="https://star-nesdis-noaa.webex.com/" target="_blank"><span style="font-size:10.0pt;font-family:"Arial","sans-serif"">JCSDA Seminar</span></a><span style="font-size:10.0pt"> and click on the seminar title</span><span><br>
2. Enter your name and email address. <br>
3. Enter the meeting password: JCSDAseminars707<br>
4. Click "Join Now". <br>
5. Follow the instructions that appear on your screen. <br>
<b>Audio: </b>USA
participants: <a href="tel:1-866-715-2479" value="+18667152479" target="_blank">1-866-715-2479</a>, Passcode: 9457557<br>
International: <a href="tel:1-517-345-5260" value="+15173455260" target="_blank">1-517-345-5260</a><u></u><u></u></span></p>
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<p class="MsoNormal" style="text-align:right" align="right"><b><span style="font-size:14.0pt">Contact</span></b><u></u><u></u></p>
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<p class="MsoNormal"><span style="font-size:10.0pt">If you would like to present a
seminar contact </span><a href="mailto:George.Ohring@noaa.gov" target="_blank"><span style="font-size:10.0pt">George.Ohring@noaa.gov</span></a><span style="font-size:10.0pt"><u></u><u></u></span></p>
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