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William Bell, Sabatino Di Michele, Peter Bauer, Tony McNally, Stephen J. English, Nigel Atkinson, Fiona Hilton, and Janet Charlton

radiometric performance of these instruments is a key factor in determining their impact in NWP systems. The purpose of this paper is to assess the sensitivity of NWP forecast accuracy to the radiometric performance of the 50-GHz temperature sounding channels to assist in the specification of future operational instruments. This has been tackled through a series of observing system experiments (OSEs) using both normal AMSU data and synthetically noise-degraded AMSU data within two operational NWP systems

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Alberto Alvarez

combination of any one of these sets of EOFs plus the corresponding mean field that was initially removed. EOF analysis has been recently employed as part of a system to predict certain aspects of the ocean evolution directly from satellite-observed data ( Alvarez et al. 2000a , b ). In this application, EOF decomposition reduces the problem of forecasting a satellite-observed field to predicting a small set of time series. If the EOF decomposition of the temporal variance is chosen, data forecasting will

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Kyoung-Ho Cho, Yan Li, Hui Wang, Kwang-Soon Park, Jin-Yong Choi, Kwang-Il Shin, and Jae-Il Kwon

1. Introduction Operational oceanographic systems have been developed to accurately predict both present and continuous future conditions for the marginal seas of the northwestern Pacific Ocean, including the Yellow Sea, the East and South China Seas, and the East/Japan Sea ( Kagimoto et al. 2008 ; Miyazawa et al. 2008 ; You 2010 ; Dombrowsky 2011 ; Lim et al. 2011 ; Zhu 2011 ). Ocean forecast information obtained from operational forecasting systems is provided to marine industries

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Valérian Jewtoukoff, Riwal Plougonven, Albert Hertzog, Chris Snyder, and Glen Romine

1. Introduction Several types of balloons are used to provide upper-air observations: radiosondes, superpressure balloons, and zero-pressure balloons ( Pettifer 2009 ). For several reasons, the ability of forecasting balloon trajectories can be of great importance: safety is the primary concern, as scientific balloon activities are viable only if they can be performed without putting in danger the overflown population. But other reasons are directly associated with the scientific activities and

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Vijai T. Jayadevan, Jeffrey J. Rodriguez, and Alexander D. Cronin

intrahour solar power forecasts ( Ghonima et al. 2012 ; Jayadevan et al. 2012 ; Marquez and Coimbra 2013 ; Chow et al. 2011 ). Though numerical weather prediction models and satellite image analysis are alternative ways of predicting intermittency due to clouds, the temporal and spatial resolutions of these predictions are too coarse to be useful for intrahour forecasts ( Perez et al. 2010 ; Remund et al. 2008 ; Lorenz et al. 2009 ; Mathiesen and Kleissl 2011 ). Hence, image analysis techniques

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Xin Zhang, Xiang-Yu Huang, Jianyu Liu, Jonathan Poterjoy, Yonghui Weng, Fuqing Zhang, and Hongli Wang

1. Introduction Since the 1980s, the four-dimensional variational data assimilation (4D-Var) technique ( Le Dimet and Talagrand 1986 ; Lewis and Derber 1985 ) has become one of the most widely used advanced analysis methods in atmospheric and oceanic research and operational centers. The European Centre for Medium-Range Weather Forecasts (ECMWF) was the first operational center to implement the 4D-Var system ( Courtier et al. 1994 ; Rabier et al. 2000 ). Following ECMWF, other national

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

1. Introduction and study objectives Observing system simulation experiments (OSSEs 1 ) allow “what if” experiments that quantify the expected real-world impact of changes to observing systems—the focus of this study—or changes to data assimilation (DA) and forecast systems. OSSEs are based on simulations of nature and observations, and compare results from a control configuration and a test configuration. The control configuration (usually) assimilates all currently available observations

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Michiko Otsuka, Hiromu Seko, Masahiro Hayashi, and Ko Koizumi

cloud-affected IR radiances operationally, though the assimilation of high-frequency GEO radiances has the potential to benefit short-range forecasts ( Geer et al. 2018 ), as has been demonstrated recently in mesoscale systems utilizing Himawari-8 data ( Honda et al. 2018b ; Minamide and Zhang 2018 ; Okamoto et al. 2019 ). Although the direct assimilation of VIS reflectances operationally seems to take extra time, fast radiative transfer models are under development. Scheck et al. (2018

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Nicholas A. Gasperoni, Ming Xue, Robert D. Palmer, and Jidong Gao

1. Introduction One of the most important variables related to convective-scale forecasting is the near-surface moisture field. The timing and location of convective initiation (CI) is often highly sensitive to moisture within the boundary layer (BL). Variations as small as 1 g kg −1 in specific humidity, which are typical of boundary layer moisture ( Weckwerth et al. 1996 ), can make the difference in whether or not storm initiation occurs. Xue and Martin (2006a , b ) performed a high

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