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Jeffrey L. Hanson, Barbara A. Tracy, Hendrik L. Tolman, and R. Douglas Scott

1. Introduction The U.S. Army Corps of Engineers (USACE) Wave Information Study (WIS) program ( Tracy and Cialone 2004 ) is establishing a multidecade wave climatology for the Pacific basin to support a variety of coastal planning and engineering activities. To facilitate selection of an appropriate wave hindcast technology, the performance of three modern numerical spectral wave models is evaluated in the Pacific basin over calendar year 2000. The technologies evaluated include the third

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Toshihisa Matsui, Xiping Zeng, Wei-Kuo Tao, Hirohiko Masunaga, William S. Olson, and Stephen Lang

the observed regional difference in PCT b 85 distributions. 5. Summary and discussion Long-term simulations of convective cloud systems observed during SCSMEX and KWAJEX using the GCE model are evaluated through comparison between TRMM observations and simulated radiances and reflectivities using multisensor simulators. A proposed methodology for evaluating the simulated radiances and reflectivites using three of TRMM’s sensors, known as T3EF, was used to systematically evaluate the performance

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A. Alvarez and B. Mourre

minimum mean error obtained from an optimum interpolation scheme. Genetic algorithms were also employed by Heaney et al. (2007) to optimize sampling strategies of a fleet of gliders based on the estimated performance of ocean predictions when glider data are assimilated into ocean models. Alvarez and Martinez (2011) , Alvarez and Mourre (2012) , and Mourre and Alvarez (2012) used simulated annealing and pattern search as optimization engines. Cooperative and unaware networks of gliders have been

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A. Serrano, G. Sanchez, and M. L. Cancillo

. J. Atmos. Oceanic Technol. , 18 , 297 – 314 , doi: 10.1175/1520-0426(2001)018<0297:MOBDSI>2.0.CO;2 . Gueymard, C. A. , and Myers D. R. , 2009 : Evaluation of conventional and high-performance routine solar radiation measurements for improved solar resource, climatological trends and radiative modeling . Sol. Energy , 83 , 171 – 185 , doi: 10.1016/j.solener.2008.07.015 . Gulbrandsen, A. , 1978 : On the use of pyranometers in the study of spectral solar radiation and atmospheric

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A. Bizard, K. Caillault, C. Lavigne, A. Roblin, and P. Chervet

is well suited to give information about thick cloud-top and cloud-base heights. As an example of our climatology, Fig. 1 shows occurrences of clouds with optical depth higher than 0.3, in the range of cloud top altitudes 11–13 km, in spring, at nighttime. Fig . 1. Occurrences of clouds (%) with optical depth > 0.3 with top heights between 11 and 13 km in spring during nighttime from CALIOP. b. Transmittance probabilities Statistical evaluation of airborne or satellite sensors' performances

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Cuong M. Nguyen and V. Chandrasekar

. In section 5 , Colorado State University–University of Chicago–Illinois State Water Survey (CSU–CHILL) radar data in both uniform and staggered PRT transmission scheme are used to illustrate the performance of GMAP-TD and are compared against GMAP. The last section summarizes the important results of this paper. 2. GMAP-TD a. Signal model For meteorological targets, the returned signal is the sum of the backscatter from individual hydrometeors in a radar pulse volume. Precipitation particles

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Emma Cotter and Brian Polagye

existing model. Finally, classification is implemented in real time at second location, approximately 100 m away. Real-time performance is evaluated, classification models are refined, and recommendations are given for implementing machine learning classification at new marine energy sites. 2. Methods a. Data 1) Test site We collected data during two deployments in Sequim Bay, Washington, in 2017 and 2019, at the locations shown in Fig. 1 . The site is a tidal channel at the mouth of Sequim Bay that

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Joaquin Cuomo and V. Chandrasekar

organized as follows. First, a comparison between using or not residual connection in the proposed models. Second, a comparison against the baseline models to evaluate the performance of the proposed models. Then two different experiments show some of the advantages and disadvantages of using machine learning approaches. The first experiment addresses potential limitations of the data-driven aspect of machine learning models. The other experiment addresses potential issues with specific techniques used

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Jackson Tan, George J. Huffman, David T. Bolvin, and Eric J. Nelkin

software improvements may reduce this latency in the future. In this study, we will evaluate the morphing scheme using vectors computed from six model-based variables: total (surface) precipitation from atmospheric model physics (PRECTOT), total precipitable water vapor (TQV; also known as total column water vapor), total precipitable liquid water (TQL), total precipitable ice water (TQI), specific humidity at 500 hPa (Q500), and specific humidity at 850 hPa (Q850). TQV, TQL, and TQI are the vertically

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Mark D. Orzech, Jayaram Veeramony, and Hans Ngodock

performance is qualitatively evaluated by comparing how well they reproduce the observed spectra at the offshore boundary and all four instrument locations, including nonassimilated spectra as well as the selected innovation spectrum. For a more quantitative comparison, overall model accuracy is also evaluated using an RMS skill score computed from spectral densities as shown: In Eq. (8) , S mod is the model spectrum and S obs is the observed spectrum (from nonlinear forward SWAN). Spectral energy

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