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Shiqiu Peng, Yineng Li, and Lian Xie

instability, too many local minimum points, and nonpositive definite features of the background error covariance. 5. Conclusions and discussion In this study, we employ the adjoint technique to adjust the parameters of wind stress drag coefficient in the three-dimensional POM for improving storm surge forecasts. The identical twin experiments are performed by assigning different error sources. The twin experimental results indicate that it is an efficient and practical way to reduce errors in storm

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Seoyeon Lee and Kwang-Yul Kim

Stone P. , 1988 : Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model . J. Geophys. Res. , 93 , 9341 – 9364 , doi: 10.1029/JD093iD08p09341 . Hewitson, B. C. , and Crane R. G. , 1996 : Climate downscaling: Techniques and application . Climate Res. , 7 , 85 – 95 , doi: 10.3354/cr007085 . Hoskins, B. J. , 2013 : The potential for skill across the range of the seamless weather-climate prediction problem: A stimulus for our science . Quart

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Sid-Ahmed Boukabara, Kayo Ide, Yan Zhou, Narges Shahroudi, Ross N. Hoffman, Kevin Garrett, V. Krishna Kumar, Tong Zhu, and Robert Atlas

studies, 3) as a test bed to prototype and implement new techniques, and 4) to increase readiness to exploit new observing systems prior to their actual deployment. The design of an OSSE should be tailored to the particular goals of the OSSE ( Hoffman and Atlas 2016 ). Ideally, the DA and forecast systems used for the simulated-data OSSEs and the real-data OSEs should be close to the operational system. Since OSSEs are based on simulations of nature and observations, reliable results require that the

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Ken Dixon, Clifford F. Mass, Gregory J. Hakim, and Robert H. Holzworth

scale. A second group of studies assimilated lightning into higher-resolution, but not convection-permitting, regional models (Δ x = 10 km). In Papadopoulos et al. (2005) , model humidity profiles were nudged toward humidity profiles derived from observed soundings when lightning occurred. Although the technique produced improved convective precipitation forecasts during the assimilation period and the subsequent 12-h forecasts, it made use of regionally and seasonally specific moisture profiles

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Nicholas J. Elmer, Emily Berndt, and Gary J. Jedlovec

1. Introduction Real-time visible and infrared satellite imagery provide timely information about atmospheric processes and surface conditions, making them useful tools for enhancing situational awareness in an operational forecast setting. However, the limited number of spectral channels on most operational weather satellites precludes their use for more comprehensive applications conducted with multispectral imagery from research satellites such as the Moderate Resolution Imaging

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Xining Zhang and Hao Dai

cost is very high. The data-driven prediction methods for the time series data, which are independent of mathematical and physical models of study objects, examine inherent laws of data characteristics and forecast. The mature techniques are mainly based on supporting vector machine (SVM; Mahjoobi and Mosabbe 2009 ), filters ( Altunkaynak and Özger 2004 ), genetic algorithm (GA; Gaur and Deo 2008 ; Cañellas et al. 2010 ), fuzzy logic ( Özger and Sen 2007 ), and the hybrid of wavelet and fuzzy

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Rod Frehlich

critical for predicting power ramps is between υ thr and υ peak . The shortest forecast time for wind energy integration into the power grid is approximately 30 min, which is required to provide sufficient lead time to adjust the output of natural gas power plants. Longer forecasts times are required for coal-fired plants, resource allocation, and decisions on buying and selling power. There are several techniques to produce reliable short-term forecasts or nowcasts ( Mueller et al. 2003 ; Benjamin

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Do-Seong Byun and Deirdre E. Hart

) and tidal species modulation (TSM) with tidal constant correction (TCC) to overcome sea level record limitations [i.e., Kang’s (1997) TSM+TCC method]. Next, we explain a complete tidal species modulation (CTSM) equivalent of the CSHAP methods: the new hybrid technique integrates conventional tidal harmonic prediction factors (nodal factors and angles, astronomical arguments) into TSM, hence CTSM. Third, in order to overcome sea level record limitations inherited from TSM, like Kang (1997

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Yuxin Zhao, Dequan Yang, Wei Li, Chang Liu, Xiong Deng, Rixu Hao, and Zhongjie He

since then it has been widely applied in the geosciences ( Chen et al. 2010 ; Oh and Suh 2018 ). In recent years, it has become common practice to combine EOF techniques with statistical methods to improve forecast performance in ocean statistical forecasts ( Chowdhury and Chu 2015 ; Lee et al. 2016 ; Sharma et al. 2010 ). Xue and Leetmaa (2000) used a Markov model to forecast sea surface temperature (SST) and sea level in the tropical Pacific. Landman and Mason (2001) forecasted SST after an

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Chanh Q. Kieu, Nguyen Minh Truong, Hoang Thi Mai, and Thanh Ngo-Duc

CIMSS AMV data showed that this dataset could help improve the forecast quality of various mesoscale systems (see, e.g., Velden et al. 2005 ; Cherubini et al. 2006 ; Bedka and Mecikalski 2005 ; Berger et al. 2011 ). The main advantage of the CIMSS AMV data is that the observational errors have been highly quality controlled and calibrated using the recursive filter algorithm. Each data point is checked for the overall consistency with the surrounding data using the quality-indicator technique

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