Stochastic model reduction: convergence and applications to climate equations
Keyword(s):
AbstractWe study stochastic model reduction for evolution equations in infinite-dimensional Hilbert spaces and show the convergence to the reduced equations via abstract results of Wong–Zakai type for stochastic equations driven by a scaled Ornstein–Uhlenbeck process. Both weak and strong convergence are investigated, depending on the presence of quadratic interactions between reduced variables and driving noise. Finally, we are able to apply our results to a class of equations used in climate modeling.
2021 ◽
Vol 23
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pp. 115-126
2015 ◽
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pp. 563-587
1985 ◽
Vol 42
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pp. 821-838
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2017 ◽
Vol 340
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pp. 46-57
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2012 ◽
Vol 81
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pp. 2175-2205
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2005 ◽
Vol 46
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pp. 102103
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