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R. G. Hanea, G. J. M. Velders, A. J. Segers, M. Verlaan, and A. W. Heemink

eigenvectors. Because of the reduction, the covariance matrix is always underestimated; although this bias reduces with the number of modes. As a result, the algorithm is sensitive to filter-divergence problems. The RRSQRT approach can be viewed as an EnKF for which the modes are not chosen randomly, but in the direction of the largest eigenvectors. In both cases the number of modes represents a measure of the storage and computation time required by the filter, and should be as low as possible, while

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Elizabeth J. Thompson, Steven A. Rutledge, Brenda Dolan, V. Chandrasekar, and Boon Leng Cheong

1. Introduction and background Reducing uncertainty associated with winter storm precipitation type, accumulation, and timing is a major forecasting, safety, and socioeconomic challenge ( Ralph et al. 2005 ; Kringlebotn Nygaard et al. 2011 ; Smith et al. 2012 ). These rapidly evolving mesoscale systems will be better understood with the national dual-polarization radar upgrade through use of hydrometeor classification algorithms (HCAs; Liu and Chandrasekar 2000 ; Zrnić et al. 2001 ; Park

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Matthew B. Wilson and Matthew S. Van Den Broeke

separation signature is in differentiating between tornadic and nontornadic supercells in a large sample of storms and developing ways to implement this signature in warning operations. Furthermore, Loeffler and Kumjian (2018) have developed a semiautomated algorithm to quantify the K DP – Z DR separation signature in tornadic nonsupercell storms, and Loeffler et al. (2020) applied this algorithm to supercells. One parameter that recent work by Loeffler and Kumjian (2018) and Loeffler et al

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Anita D. Rapp, M. Lebsock, and C. Kummerow

to a common resolution, shows that inhomogeneity effects are still very large. In this paper, we examine the consequences of data convolution and deconvolution on an optimal estimation (OE) retrieval algorithm that uses microwave radiometer measurements to retrieve cloud LWP, wind speed, and total precipitable water (TPW). Results show that data resampling has a substantial effect on the retrieved parameters when compared with retrievals performed on microwave radiometer observations at their

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Christian D. Kummerow, David L. Randel, Mark Kulie, Nai-Yu Wang, Ralph Ferraro, S. Joseph Munchak, and Veljko Petkovic

1. Introduction The Goddard profiling (GPROF) algorithm was first developed in the early 1990s to retrieve surface rainfall and its vertical structure from spaceborne passive microwave observations ( Kummerow and Giglio 1994 ). The impetus for that work came from the Tropical Rainfall Measuring Mission (TRMM) ( Simpson et al. 1988 ) that was seeking to quantify not only the surface rainfall but also the three-dimensional structure of latent heat release in the tropics. While the primary

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C. R. Rose and V. Chandrasekar

1. Introduction Following the success of the Tropical Rainfall Measuring Mission (TRMM) launched in 1997, the next-generation precipitation radar (PR) is expected to be launched aboard the Global Precipitation Measurement (GPM) core satellite around 2009. The TRMM PR operates at a single frequency of 13.8 GHz and uses retrieval algorithms that rely on the surface-reference technique (SRT) to estimate path attenuation and correct the measured Ku-band reflectivity measurements. With the

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Tony de Paolo and Eric Terrill

, while either beam forming ( Teague 1986 ), least squares ( Lipa and Barrick 1983 ), or the MUSIC algorithm developed by Schmidt (1982 , 1986 ) is used to determine a bearing estimate for that current velocity (D. E. Barrick and B. J. Lipa, Radar angle determination with MUSIC direction finding, U.S. Patent No. 5990834). The predominant system in use today is the commercially available SeaSonde by CODAR Ocean Systems, which employs the compact antenna array and the Multiple Signal Characterization

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Nan Li, Ming Wei, Yongjiang Yu, and Wengang Zhang

along the line of the object and the radar—that is, the radial direction—a Doppler radar provides only radial speed (receding from the radar or toward the radar). Therefore, algorithms are necessary to retrieve the total wind through the radial speed measured by the Doppler radar. Many studies have been conducted on wind retrieval algorithms of single-Doppler radar since it was used in meteorology detection. The most frequently used simple-assumption algorithms are velocity–azimuth display (VAD) and

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Qingyong Li, Weitao Lu, and Jun Yang

al. 2006 ; Calbo and Sabburg 2008 ). In these approaches, the pixels whose red/blue ratios are less than a fixed threshold are labeled as sky; on the contrary, the pixels with greater ratios are labeled as cloud. Note that most TSI algorithms use different thresholds depending upon the relative position between pixels and the sun ( Long et al. 2006 ). As a variation, Heinle et al. (2010) used the difference between the red (R) and blue (B) channel instead of the R/B ratio. Second, saturation

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Takuji Kubota, Shinta Seto, Masaki Satoh, Tomoe Nasuno, Toshio Iguchi, Takeshi Masaki, John M. Kwiatkowski, and Riko Oki

. 2012 ; Iguchi 2020 ). In generating precipitation datasets, it is necessary to develop computationally efficient, fast-processing DPR level-2 (L2) algorithms that can provide estimated precipitation rates, radar reflectivity factors, and precipitation information, such as the DSD and precipitation type ( Kubota et al. 2014 ; Iguchi et al. 2018 ; Iguchi 2020 ). In the L2 algorithms, an assumption related to clouds is one of uncertain factors; the algorithm assumes cloud liquid water content (CLWC

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