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contributor authorBishop, Craig H.
contributor authorHolt, Teddy R.
contributor authorNachamkin, Jason
contributor authorChen, Sue
contributor authorMcLay, Justin G.
contributor authorDoyle, James D.
contributor authorThompson, William T.
date accessioned2017-06-09T16:26:29Z
date available2017-06-09T16:26:29Z
date copyright2009/01/01
date issued2009
identifier issn0027-0644
identifier otherams-67927.pdf
identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4209428
description abstractA computationally inexpensive ensemble transform (ET) method for generating high-resolution initial perturbations for regional ensemble forecasts is introduced. The method provides initial perturbations that (i) have an initial variance consistent with the best available estimates of initial condition error variance, (ii) are dynamically conditioned by a process similar to that used in the breeding technique, (iii) add to zero at the initial time, (iv) are quasi-orthogonal and equally likely, and (v) partially respect mesoscale balance constraints by ensuring that each initial perturbation is a linear sum of forecast perturbations from the preceding forecast. The technique is tested using estimates of analysis error variance from the Naval Research Laboratory (NRL) Atmospheric Variational Data Assimilation System (NAVDAS) and the Navy?s regional Coupled Ocean?Atmosphere Mesoscale Prediction System (COAMPS) over a 3-week period during the summer of 2005. Lateral boundary conditions are provided by a global ET ensemble. The tests show that the ET regional ensemble has a skillful mean and a useful spread?skill relationship in mass, momentum, and precipitation variables. Diagnostics indicate that ensemble variance was close to, but probably a little less than, the forecast error variance for wind and temperature variables, while precipitation ensemble variance was significantly smaller than precipitation forecast error variance.
publisherAmerican Meteorological Society
titleRegional Ensemble Forecasts Using the Ensemble Transform Technique
typeJournal Paper
journal volume137
journal issue1
journal titleMonthly Weather Review
identifier doi10.1175/2008MWR2559.1
journal fristpage288
journal lastpage298
treeMonthly Weather Review:;2009:;volume( 137 ):;issue: 001
contenttypeFulltext


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