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Eugenio Gorgucci, V. Chandrasekar, and Luca Baldini

%, demonstrating the excellent performance of the SC attenuation-correction procedure. The self-consistent algorithm imposes the internal consistency of the specific attenuation estimates, with respect to variability in DSD as well as variability in raindrop shape model. This section evaluates the sensitivity of the procedure to variability in the drop shape model. While at this point the variability of shape model within a storm is not clearly known, the attenuation-correction process comes up with a best

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J. M. Baker, D. C. Reicosky, and D. G. Baker

. BAKERUniversity of Minnesota, St. Paul, Minnesota(Manuscript received 30 October 1987, in final form 21 March 1988) Many models in a variety of disciplines require air temperature throu~,hout the day as an input, yet 6fien theonly data available are daily extreme. Several methods for estimating the diurnal change in temperature fromdaily extreme have been reported. This paper compares the performance of three such algorithms (a sine wave,a sine-exponential, and a linear model) at all times of the year

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Rob K. Newsom and Robert M. Banta

velocity field. In evaluating J obs the calculation is greatly simplified if the error covariance matrix is diagonal. In this case J obs is given by where Δ m = u m  ·  r m − u obs rm . (9) The observed radial velocity is u obs rm , σ m is the corresponding measurement error, and r m is the unit vector from the lidar to the m th observation. The velocity field generated by the forward model is denoted by u m , where the overbar implies interpolation to the

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Weiguo Wang, Kenneth J. Davis, Daniel M. Ricciuto, and Martha P. Butler

measurement point from a surface point source (sink) with an emission rate Q at the origin, z m is the measurement height, and F m ( x, y, z m ) is the vertical flux measured at position ( x , y , z m ) in the Eulerian field. In Lagrangian models, F m can be evaluated by recording the trajectories of the particles released from the source into the atmosphere. In the fluid with zero mean vertical velocity, F m can be written as ( van Dop et al. 1985 ) where 〈 w ( x , y , z m )〉 is an

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Eugenio Gorgucci, Gianfranco Scarchilli, V. Chandrasekar, and V. N. Bringi

( Z h , Z dr ), R β ( K dp ), and R β ( K dp , Z dr ) as a function of β. It can be seen from Fig. 4 that the bias due to variation in β is negligible compared to that shown in Fig. 1 . The model presented in this paper makes a linear approximation to the shape–size relationship. However, as pointed out earlier in the introduction some commonly used models for shape–size relations are nonlinear. The following analysis evaluates the performance of R β algorithms under this context

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

1 Gflop s −1 or higher are capable currently of 100 Gflop s −1 aggregate performance. The message-passing interface (MPI) ( Gropp et al. 1994 ) has emerged as an international standard for distributed-memory programming, and the majority of weather centers are now developing numerical atmospheric models based on a subset of the Fortran 90 programming language in combination with MPI. An overview of the techniques used to build parallel regional weather models such as MM5, HIRLAM, ARPS, and the

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I. Hoteit, B. Cornuelle, V. Thierry, and D. Stammer

contribute to model biases. 2) Reynolds SST data Typically SST fields are used to evaluate the performance of models in specific regions of the tropical Pacific (e.g., Niño-1–Niño-4). We will use the SST fields as a measure of model skill over the entire model domain so as to compare with the earlier SSH comparisons. For later reference, the observed RMS of the monthly mean SST anomalies varies between 0.8° and 2°C across the model domain. The RMS differences between the model and Reynolds and Smith

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R. Harikumar, N. K. Hithin, T. M. Balakrishnan Nair, P. Sirisha, B. Krishna Prasad, C. Jeyakumar, Shailesh Nayak, and S. S. C. Shenoi

Jason altimetric data as inferred from comparison with buoys, we used these altimetry sources to further evaluate the OAS. The data from the forecast model grids coinciding with the satellite track are extracted first. Satellite data in a particular 1° × 1° grid are averaged, and then the OAS data at that particular region are computed using the same methodology adopted for the OAS-SWHM Hs comparison. These collocated datasets are used for seasonal and regional evaluation of the forecasted Hs. 4

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Matthieu Le Hénaff, Pierre De Mey, Baptiste Mourre, and Pierre-Yves Le Traon

model error on the North Sea shelf and the added impact of tide gauge measurements. The relative performances of the various simulated observation networks were evaluated by a statistical criterion based on an ensemble Kalman filter (EnKF) ( Evensen 1994 , 2003 ). The authors showed that tide gauges helped to constrain the short-scale model sea level error close to the coast. Farther away on the shelf, the dense spatial coverage of the simulated wide-swath altimetry measurements provides the

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Luwen Chen, Yijun Zhang, Weitao Lu, Dong Zheng, Yang Zhang, Shaodong Chen, and Zhihui Huang

1. Introduction Lightning location systems (LLSs) have been widely applied in many countries and regions as pivotal equipment for lightning detection. The detection efficiency and location accuracy are considered to be the most important performance indices for LLSs. One of the directly effective methods for objectively evaluating performance of LLS is to compare the reliable observation of lightning ground truth with the corresponding LLS records. Triggered lightning observation experiments

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