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Daan Crommelin
Daan Crommelin
CWI Amsterdam, Scientific Computing group
Verified email at cwi.nl - Homepage
Title
Cited by
Cited by
Year
Stochastic parameterization: Toward a new view of weather and climate models
J Berner, U Achatz, L Batte, L Bengtsson, A De La Camara, ...
Bulletin of the American Meteorological Society 98 (3), 565-588, 2017
3872017
Strategies for model reduction: Comparing different optimal bases
DT Crommelin, AJ Majda
Journal of the Atmospheric Sciences 61 (17), 2206-2217, 2004
1582004
Subgrid-scale parameterization with conditional Markov chains
D Crommelin, E Vanden-Eijnden
Journal of the Atmospheric Sciences 65 (8), 2661-2675, 2008
1502008
Normal forms for reduced stochastic climate models
AJ Majda, C Franzke, D Crommelin
Proceedings of the National Academy of Sciences 106 (10), 3649-3653, 2009
1282009
Stochastic parameterization of shallow cumulus convection estimated from high-resolution model data
J Dorrestijn, DT Crommelin, AP Siebesma, HJJ Jonker
Theoretical and Computational Fluid Dynamics, 1-16, 2012
942012
Distinct metastable atmospheric regimes despite nearly Gaussian statistics: A paradigm model
AJ Majda, CL Franzke, A Fischer, DT Crommelin
Proceedings of the National Academy of Sciences 103 (22), 8309-8314, 2006
932006
A hidden Markov model perspective on regimes and metastability in atmospheric flows
C Franzke, D Crommelin, A Fischer, AJ Majda
Journal of Climate 21 (8), 1740-1757, 2008
872008
Stochastic climate theory
GA Gottwald, DT Crommelin, CLE Franzke
arXiv preprint arXiv:1612.07474, 2016
822016
Regime transitions and heteroclinic connections in a barotropic atmosphere
DT Crommelin
Journal of the atmospheric sciences 60 (2), 229-246, 2003
802003
Fitting timeseries by continuous-time Markov chains: A quadratic programming approach
DT Crommelin, E Vanden-Eijnden
Journal of Computational Physics 217 (2), 782-805, 2006
792006
A mechanism for atmospheric regime behaviour
DT Crommelin, JD Opsteegh, F Verhulst
J. Atmos. Sci 61, 1406-1419, 2004
792004
The impact of uncertainty on predictions of the CovidSim epidemiological code
W Edeling, H Arabnejad, R Sinclair, D Suleimenova, K Gopalakrishnan, ...
Nature Computational Science 1 (2), 128-135, 2021
682021
Reconstruction of diffusions using spectral data from timeseries
D Crommelin, E Vanden-Eijnden
Communications in Mathematical Sciences 4 (3), 651-668, 2006
552006
Diffusion estimation from multiscale data by operator eigenpairs
D Crommelin, E Vanden-Eijnden
Multiscale Modeling & Simulation 9 (4), 1588-1623, 2011
482011
Stochastic parameterization of convective area fractions with a multicloud model inferred from observational data
J Dorrestijn, DT Crommelin, AP Siebesma, HJJ Jonker, C Jakob
Journal of the Atmospheric Sciences 72 (2), 854-869, 2015
452015
Observed nondiffusive dynamics in large-scale atmospheric flow
DT Crommelin
Journal of the atmospheric sciences 61 (19), 2384-2396, 2004
442004
Homoclinic dynamics: a scenario for atmospheric ultralow-frequency variability
DT Crommelin
Journal of the Atmospheric Sciences 59 (9), 1533-1549, 2002
442002
A data-driven multicloud model for stochastic parameterization of deep convection
J Dorrestijn, DT Crommelin, JA Biello, SJ B÷ing
422012
Stochastic convection parameterization with Markov chains in an intermediate-complexity GCM
J Dorrestijn, DT Crommelin, AP Siebesma, HJJ Jonker, F Selten
Journal of the Atmospheric Sciences 73 (3), 1367-1382, 2016
342016
Hidden Markov models for wind farm power output
D Bhaumik, D Crommelin, S Kapodistria, B Zwart
IEEE Transactions on Sustainable Energy 10 (2), 533-539, 2018
312018
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