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Lohitzune Solabarrieta, Sergey Frolov, Mike Cook, Jeff Paduan, Anna Rubio, Manuel González, Julien Mader, and Guillaume Charria

datasets. In this way, the number of comparison tracks increased substantially (see Fig. 3 , top and middle, as an example of the comparison track obtained for one particle). For the analysis of the forecast model performances in a longer period, trajectories have been generated every hour using trajectories launched in a regular 9 × 7 grid, covering the study area with regular node distances of 0.15° × 0.09° ( Fig. 3 , bottom). In all cases, the trajectories of the particles going out of the HF radar

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Zijun Gan, Youfang Yan, and Yiquan Qi

nontrivial test bed for the ocean models and allow for evaluation of their performance in the SCS. The paper is organized as follows. In section 2 , the data are introduced briefly. In section 3 , a short review of scaling analysis methods is presented to make the paper more self-contained. In section 4 , we present the results and discussions, and the conclusions are drawn in section 5 . 2. Study area and data used The study area is located between 0.5°–24.5°N latitude and 99.5°–124.5°E longitude

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T.L. Anderson, D.S. Covert, S.F. Marshall, M.L. Laucks, R.J. Charlson, A.P. Waggoner, J.A. Ogren, R. Caldow, R.L. Holm, F.R. Quant, G.J. Sem, A. Wiedensohler, N.A. Ahlquist, and T.S. Bates

used to measure the scattering coefficient of laboratory-generated particles of known size andrefractive index. Specifically, it evaluates the performance of a high-sensitivity, three-wavelength, total scatter/backscatterintegrating nephelometer (TSI, Inc., model 3563). Sources of uncertainty associated with the gas-calibrationprocedure, with photon-counting statistics, and with nonidealities in wavelength and angular sensitivity areinvestigated. Tests with particle-free gases indicate that

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Ali Tokay, David B. Wolff, and Walter A. Petersen

Parsivel could estimate the size of drizzle drops down to a 0.1-mm diameter with modifications made to the optical system. Third, they stated that the Parsivel estimates the size and fall velocity of snowflakes and is useful for discriminating the hydrometeor type, which makes the Parsivel a present weather sensor. LJ00 evaluated the performance of the Parsivel through comparison with a collocated impact-type Joss–Waldvogel (JW) disdrometer ( Joss and Waldvogel 1967 ) and a recording Hellmann

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Anant Parekh, Rashmi Sharma, and Abhijit Sarkar

). This leads us to believe that the different measurements can play both complimentary and supplementary roles. Their integration can be achieved after evaluating their interconsistencies and comparisons individually and with the analysis of known numerical models. Intercomparison and validation of satellite retrievals with in situ observations is also rendered complicated by several important differences between satellite and in situ measurements, for example, spatiotemporal inhomogeneity between in

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Shin-Hoo Kang, Tae-Young Goo, and Mi-Lim Ou

) monthly mean temperature was −1.2°C (26.8°C) in January (August). Annual precipitation for 2010 was 1444 mm, and the amount of rainfall in the summer was 765.5 mm ( KMA 2010 ). Field observations (26–27 May 2010, 3–4 November 2010, 23–24 March 2011, 17–18 May 2011, and 6–7 October 2011) were conducted 5 times by the National Institute of Meteorological Research (NIMR). The primary goal of the field observations was to evaluate the T / q retrieval performance of the AERI. In situ measurements of

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S.-G. Park, Hae-Lim Kim, Young-Woong Ham, and Sung-Hwa Jung

from splashing and improvement of the sampling rate from 10 to 25 kHz ( Battaglia et al. 2010 ). After further improvements, OTT recently (2011) developed the second-generation model of PARSIVEL (PARSIVEL 2 ); its main improvement is the more homogenous beams generated by the better laser device ( Tokay et al. 2014 ). This upgraded model of OTT PARSIVEL 2 was evaluated by Tokay et al. (2014) through a comparison with a collocated JWD, the first model of OTT PARSIVEL, and rain gauges. They

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David Farmer, Li Ding, Donald Booth, and Martin Lohmann

formidable challenge that is unlikely to be met with in situ measurement schemes. Accordingly, we selected a remote sensing approach using a bistatic configuration of sonars on the seafloor. The system was deployed in the North Sea close to a production platform in the Tyra field of the Danish sector in water of depth ∼38 m. The present discussion describes the measurement concept and illustrates aspects of its operation with a mathematical model. The model calculations are then compared with

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Jessica L. Proud, Kelvin K. Droegemeier, Vincent T. Wood, and Rodger A. Brown

are available for other phenomena or use by other neighboring radars). As a first step toward addressing this and related challenges, the goal of the present study is to use pseudo-observations of an idealized vertical vortex to evaluate a variety of sampling strategies for CASA radars in order to determine which might be most effective for real tornadoes and mesocyclones. Here, effectiveness is defined as the best fit of the pseudo-observations to an analytic model of tornadoes and mesocyclones

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David McKee, Jacek Piskozub, Rüdiger Röttgers, and Rick A. Reynolds

: Approximation of the size distribution of marine particles by a sum of log-normal functions . Limnol. Oceanogr. , 41 , 744 – 754 . Kirk, J. T. O. , 1992 : Monte Carlo modeling of the performance of a reflective tube absorption meter . Appl. Opt. , 31 , 6463 – 6468 . Leymarie, E. , Doxaran D. , and Babin M. , 2010 : Uncertainties associated to measurements of inherent optical properties in natural waters . Appl. Opt. , 49 , 5415 – 5436 . Maffione, R. A. , and Dana D. R. , 1997

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