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Nathan M. Reiss and James C. Hofmann

here is to impart the experts' knowledge to the students, it was decided to enter the rulesbeforehand. Because the rules of weather forecastingare certainly ill defined, an expert system designed foruse in an operational setting (e.g., at a forecast office)might well be of the self-learning variety. Some of the early expert systems were developed forproviding medical consultations (Shortliffe, 1976),performing spectral analysis (Buchanan and Feigenbaum, 1978), and structural studies (Bennett and

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Zaizhong Ma, Eric S. Maddy, Banglin Zhang, Tong Zhu, and Sid Ahmed Boukabara

resolutions but coarse spectral resolutions. Recent usage of the geostationary infrared observations has shown that geostationary instruments, for instance, the Spinning Enhanced Visible and Infrared Imager (SEVIRI), were shown to be a valuable source of information for atmospheric analysis and weather forecast ( Szyndel et al. 2005 ; Stengel et al. 2009 ). In addition, the benefit of directly assimilating Geostationary Operational Environmental Satellite (GOES) radiance data has been investigated. The

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Sid-Ahmed Boukabara, Kayo Ide, Yan Zhou, Narges Shahroudi, Ross N. Hoffman, Kevin Garrett, V. Krishna Kumar, Tong Zhu, and Robert Atlas

into a DA and forecast system that is as close as possible to existing operational practice. In the test configuration, either a new observing system is added to the control configuration or the DA and forecast system is modified relative to the control configuration. By way of example and introduction: The nature run (NR) of the OSSE system used here is a 2-yr-long 7-km-resolution forecast of the Goddard Earth Observing System Model, version 5 (GEOS-5). This NR is commonly referred to as the

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Pamela G. Posey, Richard A. Allard, Ruth H. Preller, and Gretchen M. Dawson

simulations were performed with and without data assimilation. Additional tests were run to investigate the effect of wind forcing with differing spatial resolution. Winds used during these tests were from the COAMPS model available at resolutions of 27 km (a standard operational resolution) and a higher resolution of 5 km (typically available only by special request). Our testing showed that the most accurate forecasts were made utilizing winds from the higher-resolution (5 km) test case. Subsequently

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Sung-Min Kim and Hyun Mee Kim

that 24–120-h forecast errors of the hybrid-4DVAR are approximately 1% less than those of 4DVAR using various reference states (e.g., analysis of their own system, ERA-Interim, and observations). The hybrid-4DVAR and 4DVAR systems are used operationally in KMA, and as mentioned in section 2 , the only difference between the hybrid-4DVAR and 4DVAR systems is the BEC. Using the radiosonde (TEMP) observations as the reference, the 6-h forecast errors (i.e., bias) and analysis errors of the hybrid-4

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Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, and Lars Nerger

observation) pronounced in LSEIK-FF97 is significantly reduced for LSEIK-EF. The data assimilation shows that there is considerable sensitivity to the explicit representation of forcing uncertainty by applying ensemble forcing. The forecasts and uncertainty estimates of both sea ice concentration and thickness are improved with ensemble forcing; therefore, we recommend this ensemble implementation for Arctic sea ice–ocean state estimation and real-time operational forecasts. Finally, this study shows that

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Judy S. St-James and Stéphane Laroche

; Laroche et al. 1999 ), along with the Global Environmental Multiscale (GEM) model ( Côté et al. 1998 ). Extension of the analysis scheme to four-dimensional variational data assimilation (4DVAR) was under way during the writing of this paper in view of its operational implementation by early 2005. This paper presents an assessment of the value of the NPN winds in view of their assimilation in the global forecasting system. In particular, the impact of the vertical observation error correlation is

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S. J. Thomas, M. Desgagné, and R. Benoit

summertime, it was chosen because a dedicated SX-4/32 node was available on this particular day, and the analyses were easily available as part of the operational runs at CMC. The MC2 model was therefore nested within the operational SEF T219L28 to produce a 24-h forecast at 10-km resolution. Boundaries were updated every 6 h, and linear time interpolation was employed between updates to produce time-dependent boundary conditions at every time step. The model lid was set at 30 km. Again, here, for

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K. M. Kwong, Max H. Y. Wong, James N. K. Liu, and P. W. Chan

the detection of wind shear under rain-free conditions, a light detection and ranging (lidar) system was installed at HKIA in mid-2002. It is the first system of its kind in the world used in providing weather alerts to an operational airport. Fig . 1. Map of HKIA and Lantau Island with the location of the lidar (square). Runway corridors are shown as arrows with the names marked alongside. Lidar is an optical analog of radar (radio detection and ranging). Lidar uses a ground-based pulsed laser to

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Bradley W. Klotz and Eric W. Uhlhorn

operational version of the SFMR ε versus U sfc model function was developed mainly from observations in mature hurricanes primarily to measure the maximum wind as it pertains to estimating a storm’s intensity ( Uhlhorn et al. 2007 ). Therefore, general application to all tropical systems was not, until now, thoroughly tested, especially for wind speeds weaker than hurricane force. This has important operational implications for forecasters making decisions on system classifications, for example, when

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