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Paul M. Della-Marta, Mark A. Liniger, Christof Appenzeller, David N. Bresch, Pamela Köllner-Heck, and Veruska Muccione

of the frequency of rare events is the number of observations of such events. Della-Marta et al. (2009) used the 40-yr European Centre for Medium-Range Weather Forecasting (ECMWF) reanalysis (ERA-40) to estimate the return period (RP) of extreme winds at continental and regional scales. They found that the uncertainties associated with long RPs (approximately 30 yr) are in the range between −60% and +200% of the RP estimate. This places limitations on the use of these data for reinsurance risk

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Jordane A. Mathieu and Filipe Aires

the best results for the the central regions, the LIN model is a good and easy solution on average. The best quality of the NN model lies in its spatial homogeneity, and, even if it does not give the best generalization rates on average, it provides better results than do the LIN or ME models for some states (see Fig. 8 ). An independent statistical forecasting of corn yield at the U.S. scale is provided by the NASS model from the USDA. The NASS currently uses two major survey techniques for crop

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William H. Raymond, Gary S. Wade, and Tom H. Zapotocny

a forward radiative transmittance model, a numerical optimization scheme, and a modern atmospheric forecast model to assimilate remotely sensed moisture observations. In contrast to radiance assimilation, our suboptimal ( Joiner and Dee 2000 ) assimilation procedure requires no linearization and no adjoint technique. The iterative scheme is very similar to finding the root of a nonlinear equation. The forward radiative transmittance model that simulates the brightness temperature is tuned by

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Christopher M. Hayden

experiments with a simple two4evel primitive equation model. Data are insertedinto a running forecast on an orbit-by-orbit basis. The method of insertion is held fixed but initial conditionsand techniques for achieving geostrophic adjustment are varied. It is shown that the real temperaturedata can be readily assimilated and retained by the model, and that the assimilation is greatly enhancedif a simple wind law initialization is performed at the time of insertion. There is a suggestion that

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J. Shao

Introduction As a part of an integrated winter road-weather service system, the thermal mapping technique, which uses vehicle-mounted infrared radiometers to detect spatial variation of road surface temperature (RST) in a road network, plays an important role in revealing the real-time spatial distribution of cold and warm road sections in a road network. Combined with a site-specific road ice prediction model, the technique assists meteorologists, as well as highway engineers, in the

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Rita D. Roberts and James W. Wilson

assimilation of a large quantity of radar data by the forecaster. To improve upon thiseffort, a forecaster-computer environment is proposed to allow the forecaster to readily view radar reflectivityand Doppler velocity information in both unprocessed and analyzed form. Use of multi-image radar displaysand time-height profiles of quantitative radar estimates of reflectivity and radial shear are suggested to providean environment where rapid progress can be made in developing techniques to nowcast

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Kyle A. Hilburn, Imme Ebert-Uphoff, and Steven D. Miller

1. Introduction Geostationary Operational Environmental Satellite (GOES) imagery is a key element of U.S. operational weather forecasting, supporting the need for high-resolution, rapidly refreshing imagery for situational awareness ( Line et al. 2016 ). While used extensively by human forecasters, its usage in data assimilation (DA) for numerical weather prediction (NWP) models is limited. Instead DA makes greater usage of microwave and infrared sounder data on low-Earth-orbiting satellites

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David R. Ryglicki and Robert E. Hart

Oceanography Center as well as in the Automated Tropical Cyclone Forecasting system that is used by the National Hurricane Center and the Joint Typhoon Warning Center to track TCs. The techniques that are primarily used in global models are convenient for tracking the position of a storm. What they are unable to do is to present any information on the finer details of the vertical structure of the storm. Part of the reason for this fact is simply because, at grid spacings on the order of degrees, finer

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Roy M. Endlich

shearing deformation. Some possible applications of this technique in analysis and forecasting are described briefly.1. Introduction Wind observations are the primary source of information for analyzing certain meteorological phenomenasuch as jet streams and dear-air turbulence, and for depicting circulation patterns in the tropics. In numericalprediction, wind fields are becoming increasingly important because they are required in primitive equationmodels presently coming into use. A further

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Hamada S. Badr, Benjamin F. Zaitchik, and Seth D. Guikema

1. Introduction Seasonal prediction of precipitation is a core challenge for applied climatology. The attempt to forecast statistics of rainfall several months in advance requires that the forecaster engage with the theory of memory in the climate system, consider trade-offs between physically based dynamical methods and empirically grounded statistical methods, and decide between models that are generalizable and those that provide the best fit to recent observations. The forecaster also faces

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