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SUMMARY:Stochastic Downscaling for Convective Regimes with Gaussian Random
  Fields - Rachel Prudden | Met Office
DTSTART:20210302T110000Z
DTEND:20210302T123000Z
UID:TALK155395@talks.cam.ac.uk
CONTACT:Tudor Suciu
DESCRIPTION:Downscaling aims to link the behaviour of the atmosphere at fi
 ne scales to properties measurable at coarser scales\, and has the potenti
 al to provide high resolution information at a lower computational and sto
 rage cost than numerical simulation alone. This is especially appealing fo
 r targeting convective scales\, which are at the edge of what is possible 
 to simulate operationally. Since convective scale weather has a high degre
 e of independence from larger scales\, a generative approach is essential.
  I will describe a statistical method for downscaling moist variables to c
 onvective scales using conditional Gaussian random fields\, with an applic
 ation to wet bulb potential temperature (WBPT) data over the UK. This mode
 l uses an adaptive covariance estimation to capture the variable spatial p
 roperties at convective scales.
LOCATION:https://zoom.us/j/6708259482?pwd=Qk03U3hxZWNJZUZpT2pVZnFtU2RRUT09
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