Stochastic methods are an interesting tool for the representation of subgrid-scale dynamics in weather and climate models. Our interest is in the derivation of corresponding approaches with minimal tuning, thereby hopefully most robust under external modifications, e.g. climate change.

Publications

2017

Berner J., Achatz U., Batte L., Bengtsson L., de la Cámara A., Christensen H., Colangeli M, Coleman D., Crommelin D., Dolaptchiev S.I., Franzke C., Friederichs P., Imkeller P., Järvinen H., Juricke S., Kitsios V., Lott F., Lucarini V.; Mahajan S., Palmer T., Penland C.,  Sakradzija M., von Storch J.-S., Weisheimer A., Weniger M., Williams P.,  and J.-I. Yano 2017: Stochastic parameterization: Towards a new view of weather and climate models. Bull. Am. Met. Soc., 98, 565 – 587

2016

Wouters, J., Dolaptchiev, S.I., Lucarini. V., and U. Achatz 2016: Parametrization of stochastic multiscale triads. Nonlin. Processes Geophys., 23, 435–445

2013

Dolaptchiev, S.I., Achatz U. and I. Timofeyev , Stochastic closure for local averages in the finite-difference discretization of the forced Burgers equation. Theor. Comput. Fluid Dyn. 27, 297-317

Dolaptchiev, S.~I., Timofeyev, I. and Achatz, U., Subgrid-scale closure for the inviscid Burgers-Hopf equation, Commun. Math. Sci., 11, 757–777

Achatz, U., U. Löbl, S. Dolaptchiev and A. Gritsun, Fluctuation-Dissipation Supplemented by Nonlinearity: A Climate-Dependent Sub-Grid-Scale Parameterization in Low-Order Climate Models. J. Atmos Sci., 70, 1833-1846