Search Results

You are looking at 1 - 7 of 7 items for :

  • Regional effects x
  • Third THORPEX International Science Symposium x
  • All content x
Clear All
Mio Matsueda, Masayuki Kyouda, Zoltan Toth, H. L. Tanaka, and Tadashi Tsuyuki

, T. , W. Ohfuchi , H. Nakamura , and M. A. Shapiro , 2007 : Remote effects of tropical storm Cristobal upon a cut-off cyclone over Europe in August 2002 . Meteor. Atmos. Phys. , 96 , 29 – 42 . Fourrie , N. , D. Marchal , F. Rabier , B. Chapnik , and G. Desroziers , 2006 : Impact study of the 2003 North Atlantic THORPEX Regional Campaign . Quart. J. Roy. Meteor. Soc. , 132 , 275 – 295 . Froude , L. S. R. , 2010 : TIGGE: Comparison of the prediction of Northern

Full access
E. A. Irvine, S. L. Gray, J. Methven, and I. A. Renfrew

fact that observations taken close to orography may measure local flow effects that the model cannot represent and therefore may degrade the forecast. The structure of the paper is as follows. In section 2 the experimental setup is described, including details of the representation of dropsonde observation errors in the Met Office 4D-Var scheme. Results from the experiments are presented in section 3 . In section 3a the forecast impact from assimilating different sets of observations with

Full access
William A. Komaromi, Sharanya J. Majumdar, and Eric D. Rappin

explore this, several objective sensitivity methods , such as singular vector ( Peng and Reynolds 2006 ; Chen et al. 2009 ; Kim and Jung 2009 ), adjoint-derived sensitivity steering vector ( Wu et al. 2007 ), and ensemble sensitivity ( Torn and Hakim 2008 ), have been devised. These methods have been used to identify locations in which to target observations during field campaigns such as The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T

Full access
Benoît Vié, Olivier Nuissier, and Véronique Ducrocq

complex interactions, involving nonlinearities and threshold effects, reduce that predictability. Precise forecasting of both the location and intensity of the quasi-stationary MCSs involved in HPEs is thus still very challenging, and yet the hydrological response of the Mediterranean steep coastal watersheds is very sensitive to the precise location of the heaviest precipitation ( Chancibault et al. 2006 ; Vincendon et al. 2010 ). The hydrological runoff forecasts may be strongly affected by the

Full access
Thomas M. Hamill, Jeffrey S. Whitaker, Michael Fiorino, and Stanley G. Benjamin

GSI ( Liu et al. 2000 ) can be incorporated into our EnKF, so that the ensemble of positions does span the observed position and analysis quality is improved. Other major questions are how we can improve the treatment of the model-related uncertainty, including uncertainty effects specific to TCs, and whether regional models with EnKF initialization can be nested within the global EnKFs and provide details on the hurricane structure and intensity not yet possible with global models

Full access
Sharanya J. Majumdar, Kathryn J. Sellwood, Daniel Hodyss, Zoltan Toth, and Yucheng Song

important at longer lead times. We emphasize that while the ETKF combines data assimilation with predictions of evolving error variance ( Bishop et al. 2001 ), this paper focuses on the evolution of observation sensitivity . In other words, this paper aims to examine qualitatively the characteristics of the targets, as opposed to the practical application in which actual targeted data are assimilated. Our goal is to provide hypotheses for field campaigns in which the actual effects of assimilating

Full access
Ronald Gelaro, Rolf H. Langland, Simon Pellerin, and Ricardo Todling

( Courtier et al. 1994 ). In this case, the analysis increment is not x a − x b = 𝗞 d as implied by (2) , but rather, after loop j , the total increment is where d j = y − H ( x j −1 ) and 𝗛 j is the observation operator linearized around the previous state estimate, x j −1 ( Trémolet 2008 ). The effects of the outer loops in these schemes can be important to the quality of the analysis, especially in four-dimensional variational data assimilation (4D-Var) in which H

Full access