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Masakazu Taguchi

the northern tropospheric circulation following the onset of SSWs. In spite of such extensive studies about MSSW predictability, a clear answer for the question has not necessarily been obtained. One main reason is that the existing studies differ in verification measures and definitions of successful forecasts. This study therefore seeks to answer the question in an objective and quantitative manner by analyzing the JMA operational 1-month ensemble forecast data for 12 recent northern winters in

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Irving I. Gringorten

development or state of the weather. To delve into the problem of relatingthe weather forecast to its operational usefulness, this paper defines an income matrix, which is essentiallya table of numerical values of the utility of each course of action followed by each state of the weather.The probabilities of the several states of the weather, arranged in a single-columned matrix, are multipliedwith the figures in the income matrix to give the expected gain or loss from each course of action. A decision

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C. Cardinali and R. Buizza

published literature (e.g., Palmer et al. 1998 ) for a discussion of similarities and differences among these techniques. Targeting techniques also include the quasi-inverse linear method ( Pu et al. 1997 , 1999 ) and the ensemble transform Kalman filter (ETKF) [ Bishop et al. (2001 ), the ETKF had been used operationally as targeting guidance during the 2000, 2001, and 2002 WSR missions]. This study explores the forecast impact results from the assimilation of targeting dropsondes during NORPEX, one

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Masaru Inatsu, Naoto Nakano, and Hitoshi Mukougawa

background to link the FPE coefficients with subseasonal predictability, section 4 shows subseasonal predictability and statistically estimated error growth based on the SDE projected onto the 2D phase space and illustrates the statistical stability of the FPE coefficients, and section 5 concludes the paper. 2. Data and method We used the operational 1-month ensemble forecasts of the JMA in December–February (DJF) from 2001/02 to 2009/10. The JMA has conducted the forecast every Wednesday and

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Masaru Inatsu, Naoto Nakano, Seiichiro Kusuoka, and Hitoshi Mukougawa

the stochastic spread reproduced well the ensemble spread of the operational forecast for the tropospheric LFV conducted by the Japan Meteorological Agency (JMA). Hence, it was suggested that the empirically estimated SDE for the tropospheric LFV was mostly driven by the stochastic diffusion. To represent the variability of the stratospheric circulation and examine its predictability in a low-dimensional system, we have to take the deterministic dynamics into consideration. This is because the

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Ernst Klinker and Prashant D. Sardeshmukh

statements are qualified by the errors in the balance requirement itself. The extent to whichthis is a problem is discussed. A distinctive feature of these calculations is their internal consistency; that is, all the terms in the budget areevaluated as in the version of the ECMWF model used for assimilating the observations. This offers severaladvantages, not the least of which is that it makes our budget residuals identical to the systematic initial tendencyerrors of the operational weather forecasts

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Ben Harvey, John Methven, and Maarten H. P. Ambaum

climate models. The jet streams and associated Rossby waves reside on the large isentropic gradient of potential vorticity (PV) at the tropopause ( Hoskins et al. 1985 ). Using operational forecast data from recent winters, Gray et al. (2014) showed that global NWP models exhibit a pair of systematic biases associated with these features. First, a fast reduction of the isentropic gradient of PV at the tropopause occurs during the first 1–2 days of forecasts. That is, the transition from low

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John O. Roads

equilibrium kinetic energy.Because of a lag relationship between the equilibrium kinetic energy and the available potential energy, it ispossible to marginally predict times of large and small error growth. Removal of the orography during aforecast produces much larger and more linear growth rates characteristic of present operational forecastmodel errors.1. Introduction When a forecast is made by a numerical model, itwould be beneficial to know whether the forecast islikely to be good or bad and what

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Jan-Huey Chen, Melinda S. Peng, Carolyn A. Reynolds, and Chun-Chieh Wu

Operational Global Atmospheric Prediction System (NOGAPS) to demonstrate that the analyzed position and forecast of one typhoon can have an impact on the forecast of another typhoon. Peng and Reynolds (2006) further examined the dynamics of TC motion for the Northern Hemisphere TCs in 2003 and found a distinct relationship between the NOGAPS SV sensitivity and the local potential vorticity gradient surrounding the storm. The SV sensitivity also indicated that environmental influences away from the

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Christopher M. Danforth and Eugenia Kalnay

-independent error correction did not improve the forecast skill. By adding a state-dependent empirical correction to the model, inspired by the procedure proposed by Leith, they were able to extend forecast skill up to the limits imposed by observation error. However, Leith’s technique requires the solution of a N d -dimensional linear system. As a result, before the procedure can be considered useful for operational use, a low-dimensional representation of Leith’s empirical correction operator is required

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