A composite state method for ensemble data assimilation with multiple limited-area models
References
-
. An ensemble adjustment Kalman filter for data assimilation. Mon. Wea. Rev. 2001; 129: 2884– 2903. -
, . A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts. Mon. Wea. Rev. 1999; 127: 2741– 2758. -
, , . Adaptive sampling with the ensemble transform Kalman filter. Part I: theoretical aspects. Mon. Wea. Rev. 2001; 129: 420– 436. -
, , . Ensemble data assimilation with the CNMCA regional forecasting system. Q. J. Roy. Meteorol. Soc. 2010; 136: 132– 145. -
, . Ensemble transform Kalman filter perturbations for a regional ensemble prediction system. Q. J. Roy. Meteorol. Soc. 2009; 135: 757– 766. -
, , . Analysis scheme in the ensemble Kalman filter. Mon. Wea. Rev. 1998; 126: 1719– 1724. -
, . Assimilating host model information into a limited area model. Tellus. 2012; 64A: 18536. DOI: 10.3402/tellusa.v64i0.15836. -
. Limitations of some common lateral boundary schemes used in regional NWP models. Mon. Wea. Rev. 1983; 111: 1002– 1012. -
. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 1994; 99, C5: 10143– 10162. -
, . Introducing the coupling information in a limited-area variational assimilation. Q. J. Roy. Meteorol. Soc. 2008; 134: 723– 735. -
, . An idealized comparison of one-way and two-way grid nesting. Mon. Wea. Rev. 2010; 138: 2174– 2187. -
, , . Can a moderate-resolution limited-area data assimilation system add value to the global analysis of tropical cyclones?. Mon. Wea. Rev. 2013; 141: 1866– 1883. -
, . Data assimilation using an ensemble Kalman filter technique. Mon. Wea. Rev. 1998; 126: 796– 811. -
, , . Efficient data assimilation for spatiotemporal chaos: a local ensemble transform Kalman filter. Physica D. 2007; 230: 112– 126. -
, . A comparison of two numerical weather prediction methods for diagnosing fast-physics errors in climate models. Q. J. Roy. Meteorol. Soc. 2014; 140: 517– 524. -
, . The impact of data assimilation length scales on analysis and prediction of convective storms. Mon. Wea. Rev. 2014; 142: 3781– 3808. -
. Designing chaotic models. J. Atmos. Sci. 2005; 62: 1574– 1587. -
, , . Strategies for coupling global and limited-area ensemble Kalman filter assimilation. Nonlin. Proc. Geophys. 2011; 18: 415– 430. -
, , , , , co-authors. A local ensemble Kalman filter for atmospheric data assimilation. Tellus. 2004; 56A: 415– 428. -
. Mesoscale Meteorological Modeling. 2013; 98: Academic Press. -
, , . LETKF for the non-hydrostatic regional model COSMO-DE. COSMO Newsletter. 2011; 11: 27– 31. -
, , . Boundary conditions for limited-area ensemble Kalman filters. Mon. Wea. Rev. 2006; 134: 2490– 2502. -
, , . Which is better, an ensemble of positive-negative pairs or a centered spherical simplex ensemble?. Mon. Wea. Rev. 2004; 132: 1590– 1605. -
, , . A tutorial on lateral boundary conditions as a basic and potentially serious limitation to regional numerical weather prediction. Bull. Amer. Met. Soc. 1997; 78: 2599– 2617. -
, . Ensemble data assimilation without perturbed observations. Mon. Wea. Rev. 2002; 130: 1913– 1924. -
, , , . Weight interpolation for efficient data assimilation with the local ensemble transform Kalman filter. Q. J. Roy. Meteorol. Soc. 2009; 135: 251– 262. -
, , , . Simultaneous global and limited-area ensemble data assimilation using joint states. Tellus. 2012; 64A: 18407. DOI: 10.3402/tellusa.v64i0.18407. -
, , . On the propagation of information and the use of localization in ensemble Kalman filtering. J. Atmos. Sci. 2010; 67: 3823– 3834.
DOI: https://doi.org/10.3402/tellusa.v67.26495 | Journal eISSN: 3035-9554
Language: English
Page range: 26495 - 26495
Submitted on: Oct 31, 2014
Accepted on: Mar 17, 2015
Published on: Dec 1, 2015
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services
© 2015 Matthew Kretschmer, Brian R. Hunt, Edward Ott, Craig H. Bishop, Sabrina Rainwater, Istvan Szunyogh, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.