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Stanley Q. Kidder and Andrew S. Jones

1. Introduction Forecasters today are faced with many sources of data. What they need is meteorologically significant data fields blended from all available data sources, not numerous maps of observations from individual sources. In this paper we detail our process for blending data for one such meteorological parameter, the total precipitable water (TPW), which is the amount of water vapor in a column from the surface of the earth to space (in kilograms per square meter or, equivalently, in

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Yuhang Zhu, Yineng Li, and Shiqiu Peng

). In the summer and autumn of each year, TCs caused enormous property loss of over $10 trillion with an affected population of 250 million in the southeastern coastal areas of China and the surrounding TC-affected area ( Wu and Kuo 1999 ; Liu et al. 2009 ). Therefore, an accurate forecasting of TC tracks, especially the landfall locations, is very important for the disaster reduction and prevention in the areas of high TC incidence. Forecasting of TCs dates back to the 1960s. The original forecast

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

1. Introduction Sea surface height anomalies (SSHAs) result from ocean processes and are important variables in climate research ( Gill and Niller 1973 ; Meyssignac et al. 2017 ; Zhuang et al. 2010 ). Changes in regional sea surface height are caused by both physical ocean characteristics, such as temperature and salinity, and dynamic ocean processes, resulting in complex spatiotemporal variations ( Talley 2011 ). Investigations of SSHA contribute to improving forecasts of the changing oceans

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W. L. Smith Sr, Qi Zhang, M. Shao, and E. Weisz

vapor profiles to improve numerical weather prediction (NWP) model forecasts of intense weather through the quasi-continuous assimilation of the atmospheric sounding data. The goal of this research is to demonstrate that sounding products are useful to weather service agencies for nowcasting and NWP purposes. The “nowcasting” products are produced and made available in near–real time using soundings retrieved by the fusion of direct broadcast operational polar (IASI and CrIS) hyperspectral sounding

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S. N. Londhe and Vijay Panchang

Real Time System (PORTS) that is intended to aid navigation. While many of these instruments provide hourly measurements of water levels, waves, and other oceanographic parameters in near real time, efforts are required to obtain a forecast from these instrumental data. This paper attempts to enhance the value of the expanding base of measurements by providing a forecast through the use of artificial neural networks. Of course, forecasts can be obtained through the continuous operation of numerical

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

1. Introduction It is well known that tropical cyclone (TC) motion is largely determined by environmental steering flows (see, e.g., Chan and Gray 1982 ; Holland 1984 ; Carr and Elsberry 1995 ; Berger et al. 2011 ). Numerous modeling studies with barotropic models showed that reasonably accurate TC tracks could be obtained without details of the inner-core dynamics ( Aberson and DeMaria 1994 ). Despite such prevailing control of the large-scale slow manifold environment, forecasting TC

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Steven R. Felker, Brian LaCasse, J. Scott Tyo, and Elizabeth A. Ritchie

categories, either intensifiers or dissipaters, based on their relative intensity evolution following ET (e.g., Demirci et al. 2007 ; Kofron et al. 2010a , b ). This binary classification system is useful in practice, because the main goal in forecasting these transitions is to determine which storms will regain strength after the transition process is complete, and potentially result in broad maritime and coastal impacts. The transition process itself has been defined by Klein et al. (2000) as a

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Rod Frehlich

1. Introduction Improved short-term forecasts of winds from an operational numerical weather prediction (NWP) system would benefit current wind farms ( Mueller et al. 2003 ; Benjamin et al. 2004 ; Saxen et al. 2008 ; Hannon et al. 2008 ; Benjamin et al. 2010 ; Marquis et al. 2011 ). The output power of a wind turbine is determined by the wind profile over the altitude range of the turbine blades. Using just the wind speed at hub height provides an acceptable calculation of power production

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Yinghao Chu, Hugo T. C. Pedro, Lukas Nonnenmacher, Rich H. Inman, Zhouyi Liao, and Carlos F. M. Coimbra

1. Introduction The rapid increase in electric power production from solar irradiation in recent times dictated a growing need for accurate tools to forecast solar irradiance and the power output of solar farms ( Inman et al. 2013 ). Given that cloud cover is the most important factor that determines the amount of solar irradiance at ground level, forecasting tools for solar and power output depend on good characterizations of cloud cover (cloud opacity, cloud motion, etc.). Forecasting models

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Dae-Hui Kim and Hyun Mee Kim

1. Introduction The future state of the atmosphere can be predicted by integrating the numerical weather prediction (NWP) model forward in time, from a chosen initial state. During this process, the uncertainty associated with the initial condition is one of the factors leading to the forecast error ( Rabier et al. 1996 ; Kim et al. 2004 ). Many studies have been performed to quantify the effect of initial conditions on the improvement of the forecast accuracy ( Langland et al. 1999 ; Baker

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