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Yulong Bai and Xin Li

techniques have to deal with this same problem. Therefore, to improve the error parameterization efficiency and the output accuracy of DA systems, the motivations of this paper are trying to unify the common error parameterization methods from the methodological point of view and to choose the error factors more reasonably. Inspired by modern biological evolution, an evolutionary algorithm is an evolutionary computation technique for searching and optimization; it can simulate natural evolutionary

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Mikhail Ovtchinnikov and Richard C. Easter

spatial distribution of advected variables (e.g., Chlond 1994 ; Walcek 2000 , hereinafter W00 ). Although these modifications provide the algorithms with desired properties such as monotonicity and improved gradient preservation, they also make these algorithms nonlinear. Consequently, any relations among interrelated tracers advected separately are not necessarily preserved. This presents a serious problem for models in which variables derived from several tracers represent important properties

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Yong-Keun Lee, Zhenglong Li, Jun Li, and Timothy J. Schmit

could be adequate substitutes for current GOES sounder legacy products. Jin et al. (2008) developed the GOES-R ABI legacy atmospheric profiles (LAP) retrieval algorithm. They tested the algorithm using the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)’s Spinning Enhanced Visible and Infrared Imager (SEVIRI) measurements as proxy and concluded that the GOES-R ABI LAP will provide useful legacy products with a quality similar to that of the current GOES sounder

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David M. Winker, Mark A. Vaughan, Ali Omar, Yongxiang Hu, Kathleen A. Powell, Zhaoyan Liu, William H. Hunt, and Stuart A. Young

–polarization techniques. Nevertheless, the original measurement requirements defined for CALIOP (see Table 1 ) constitute a unique and important dataset and form the core of the CALIOP data products. This overview paper provides a brief summary of the CALIPSO mission, the CALIOP instrument and data products, and the algorithms used to produce them. Few lidars have flown in space and none with the capabilities of CALIOP. Therefore, many aspects of the CALIOP algorithms are unique. We describe the conceptual basis of

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Yulong Xing, Andrew J. Majda, and Wojciech W. Grabowski

this paper is to present new efficient sparse space–time algorithms for superparameterization (SSTSP), which require less computational cost and yet provide statistically accurate large-scale features. We note that the small-scale models are actually solved over the whole time in the original superparameterization, which occupies the most computational time. In the new efficient algorithm, we can solve the small-scale models for a reduced partial time and over a reduced periodic domain. The

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Munehisa K. Yamamoto, Shoichi Shige, Cheng-Ku Yu, and Lin-Wen Cheng

. Additionally, the great success of the Tropical Rainfall Measuring Mission (TRMM) has accelerated the development of rain retrieval algorithms such as the Goddard profiling algorithm (GPROF; Kummerow et al. 2015 ) and the Global Satellite Mapping of Precipitation (GSMaP) algorithm ( Aonashi et al. 2009 ). The MWR algorithms used for estimating the rainfall rate over land are based on the scattering effect in the high-frequency channels. This is due to vertically integrated solid hydrometeors above the

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Robert J. Kuligowski, Yaping Li, Yan Hao, and Yu Zhang

an operational forecasting environment, precipitation information needs to be available with very little delay and updated frequently (e.g., Zhang et al. 2013 ), and this has made it challenging to directly use PMW information in an operational environment. Consequently, despite the challenges of using IR data for estimating rainfall, it remains an important source of information for real-time forecasting applications. As a legacy algorithm based on concepts from the 1970s [before water vapor

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R. Andrew Weekley, Robert K. Goodrich, and Larry B. Cornman

1. Introduction The analysis of times-series data plays a fundamental role in science and engineering and relies on the identification and classification of various features in the data. Quality control may be viewed as a subclass of problems in general feature identification and classification (e.g., differentiating between a “good” signal and a “contaminated” signal). Existing time-series algorithms detect outliers when the assumptions inherent in the technique are reasonably well satisfied

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Ke Yang

bit in the UHDD is very important. In our previous work, we proposed a navigation algorithm to solve the problem of attitude tracking and the position of the bit in UHDD ( Yang et al. 2016 ) in a nonvibration environment. To improve drilling efficiency, we have modified the bit, the hydraulic system, and the pumping station. The experiments show that the drilling efficiency has been significantly improved but that the vibration of the bit has been significantly increased. The navigation algorithm

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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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