Search Results

You are looking at 1 - 10 of 14 items for :

  • Review Articles in Monthly Weather Review x
  • All content x
Clear All
P. L. Houtekamer and Fuqing Zhang

comprehensive description of the then already rapidly developing field with references to many applications in the earth sciences. An excellent review by Hamill (2006) relates the EnKF to Bayesian methods, to the Kalman filter, and to the extended Kalman filter. It also discusses different properties of stochastic and deterministic update algorithms, and stresses the need for model error parameterization and covariance localization. Hamill (2006) mostly speculates on prospects for having operational

Full access
Scott R. Fulton, Paul E. Ciesielski, and Wayne H. Schubert

of multigrid methods, concentrating on their role asfast solvers for elliptic boundary-value problems. Analysis of simple relaxation schemes for the Poisson problemshows that their slow convergence is due to smooth error components; approximating these components on acoarser grid leads to a simple multigrid Poisson solver. We review the principal elements of multigrid methodsfor more general problems, including relaxation schemes, grids, grid transfers, and control algorithms, plustechniques for

Full access
Volkmar Wirth, Michael Riemer, Edmund K. M. Chang, and Olivia Martius

latitude band, with the weighting function being proportional to the zonal variance of the meridional wind. This algorithm self-adjusts to the optimum range of latitudes and avoids the need to predetermine a fixed latitude band. Another algorithm makes the latitudinal band depend even on longitude with the aim to follow the main waveguide ( Martius et al. 2006 ). A systematic comparison between different types of Hovmöller diagrams shows that the refinements are beneficial in situations where otherwise

Open access
Andrew Staniforth and Jean Côté

MONTHLY WEATHER REVIEW VOLUME 119Equation (4) may be iteratively solved for the displacement am, for example by am(k+l) = AtU[Xm -- am(k), tn], (5)with some initial guess for amr, provided U can beevaluated between mesh points. To evaluate F and Ubetween mesh points, spatial interpolation is used. Thesemi-Lagrangian algorithm for passive advection in 1Din summary is thus: (i) Solve (5

Full access
Zhiyong Meng and Fuqing Zhang

of Hurricane Humberto [shown in (c)], which is observed at 0.58 base scan at the KHGX radar at 0300 UTC 13 Sep 2007. The potential of using ensemble-based data assimilation at regional scales is also being explored in several operational meteorological centers. For example, the Italian National Meteorological Service compared a local ensemble transform Kalman filter (LETKF) with its operational 3DVar algorithm for a regional NWP system at realistic model resolution, but reduced observation

Full access
Peter Jan van Leeuwen

size of the ensemble of particles. Typically, given the capabilities of present-day supercomputers and the expected resolution needed to describe the processes of interest, on the order of 50 to maybe 1000 particles can be afforded. Because of this small size, we cannot afford to completely reject many particles, which will happen quite frequently because the large-dimensional state spaces tend to be very empty in terms of probability. For this reason the accept–reject algorithm, and variants

Full access
Markus Gross, Hui Wan, Philip J. Rasch, Peter M. Caldwell, David L. Williamson, Daniel Klocke, Christiane Jablonowski, Diana R. Thatcher, Nigel Wood, Mike Cullen, Bob Beare, Martin Willett, Florian Lemarié, Eric Blayo, Sylvie Malardel, Piet Termonia, Almut Gassmann, Peter H. Lauritzen, Hans Johansen, Colin M. Zarzycki, Koichi Sakaguchi, and Ruby Leung

combined, reproduce the time–space-averaged behavior of the whole system being modeled. The remainder of the paper is organized as follows. Section 2 focuses on issues related to process splitting in the time-stepping algorithm. The time–space convergence behavior of current models is also discussed. Section 3 then proceeds to illustrate convergence from the perspective of time–space averaging and the assumption of separation of scales, as well as how to accurately reproduce the asymptotic limits

Open access
William H. Raymond and Arthur Garder

purposes. For the reader'sconvenience this algorithm is presented in appendix Ain Eqs. (A 11 )- (A 14 ) for a bandwidth of 7. However,the Gaussian procedure does not vectorize. Thus, atsome point, as the order of the implicit filter is increased, an alternative numerical procedure is thesemivectorizable cyclic reduction algorithm (Ortegaand Voigt 1985). The traditional recursive filters require no matrixinversion. Nevertheless the number of arithmetic operations remain identical (or larger) provided

Full access
Loïk Berre and Gérald Desroziers

using a Hessian-based estimate of local analysis error standard deviations and a simple inflation algorithm to obtain local background error standard deviation estimates. In such a context, another possible approach is to use an ensemble of perturbed variational assimilations to estimate geographical variations of background error standard deviations. This has been tried by Belo Pereira and Berre (2006) for the estimation of static but space-dependent standard deviations. A realistic

Full access
Clark Evans, Kimberly M. Wood, Sim D. Aberson, Heather M. Archambault, Shawn M. Milrad, Lance F. Bosart, Kristen L. Corbosiero, Christopher A. Davis, João R. Dias Pinto, James Doyle, Chris Fogarty, Thomas J. Galarneau Jr., Christian M. Grams, Kyle S. Griffin, John Gyakum, Robert E. Hart, Naoko Kitabatake, Hilke S. Lentink, Ron McTaggart-Cowan, William Perrie, Julian F. D. Quinting, Carolyn A. Reynolds, Michael Riemer, Elizabeth A. Ritchie, Yujuan Sun, and Fuqing Zhang

. (2013) in the context of a broader TC tracking algorithm. Within the CPS framework, ET begins when B exceeds the empirically derived value of 10 m and ends when becomes negative (indicating a cold-core thermal structure; Evans and Hart 2003 ). Both B and are computed from averages taken within 500 km of the cyclone’s center. The CPS parameters are often derived from numerical weather prediction (NWP) model analyses and forecasts, but CPS applications have been expanded to reanalysis

Open access