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Zaizhong Ma, Ying-Hwa Kuo, F. Martin Ralph, Paul J. Neiman, Gary A. Wick, Ellen Sukovich, and Bin Wang

data is crucial for improving the skills of NWP models. The integrated water vapor (IWV) observations gathered from Special Sensor Microwave Imager (SSM/I) ( Hollinger et al. 1990 ) payloads aboard polar-orbiting satellites have proven crucial for monitoring these transient features over oceanic regions ( Ralph et al. 2004 , 2006 ; Neiman et al. 2008a , b ). However, SSM/I observations contain no information on the vertical structure of moisture or winds associated with AR events. Passive

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Xiang Wang and Haiyan Jiang

; Kidder et al. 2000 ), the Advanced Technology Microwave Sounder (ATMS; Zhu and Weng 2013 ), and dropsonde observations ( Durden 2013 ) have found that the strength of the warm core generally increases with the TC intensity. However, these studies mainly focused on a limited number of cases. The extent of the correlation between the warm-core strength and TC intensity and how it varies in different geographical locations and under different environmental conditions are still open questions

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Simon W. Chang, Randall J. Alliss, Sethu Raman, and Jainn-Jong Shi

, 0930, and 2200 UTC 4 January. To facilitatethe comparison with synoptic analysis, the frontal positions of Neiman et al. (1993) were linearly interpolated in time to produce the front structure at 0930and 2200 UTC (Fig. 4). We should note that thesefrontal positions are based on eyeball interpolation ofNeiman et al. and are not supported by any observations.3. SSM/I: Sensor and algorithm The microwave sensor SSM/I, from which observations were made for this study, was launched in June1987. This

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G. Deblonde, J-F. Mahfouf, B. Bilodeau, and D. Anselmo

.e., H 𝗕 H T ), which will be shown to be substantially larger than SOE. This choice leads to a more balanced assimilation: the weights given to the background field and to the observations are more similar (see the appendix ). This set of errors is referred to as large observation errors (LOEs). SRR retrievals are computed with the Precipitation Radar Adjusted TRMM Microwave Radiometer Estimation of Rainfall (PATER) scheme ( Bauer et al. 2002 ). This algorithm initially developed for TMI has been

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William T. Thompson, Stephen D. Burk, and J. Rosenthal

activities, particularly those involved with aviation, air quality, and microwave refractivity. Conditions leading to the onset of the eddy are typically preceded by a frontal passage with advancing high pressure over the Pacific Northwest while troughing conditions aloft prevail offshore of Southern California. The widespread, deep low cloudiness results in strong cooling near the coast, bringing relief from the hot summertime weather in this region. This regime also aids firefighters in gaining control

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Josep M. Aparicio and Godelieve Deblonde

large samples of quality data. In particular, the CHAMP mission, with its focus on the completeness and homogeneity of the dataset, offers a nearly uninterrupted series of observations since 2001. The recently launched Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) constellation of six satellites ( Rocken et al. 2000 ) and the Global Navigation Satellite System (GNSS) Receiver for Atmospheric Sounding (GRAS) mission onboard Meteorological Operational (METOP

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Virginie Marécal and Jean-François Mahfouf

1. Introduction The general problem of assimilation of observations in numerical weather prediction is the definition of the best initial conditions of a forecast model, using all the available information on the atmospheric state in an optimal way. Analysis systems based on three-dimensional (3DVAR) or four-dimensional (4DVAR) variational methods are currently the most promising approaches for global initialization. Their basis is to minimize an objective function measuring the distance of a

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Elizabeth R. Sanabia, Bradford S. Barrett, Nicholas P. Celone, and Zachary D. Cornelius

irregularly available microwave satellite observations ( Kuo et al. 2009 ; Yang et al. 2013 ). Thus, techniques that can identify possible CEs and map their changes as part of ERCs using regularly available observations, including those from geostationary satellites, would be potentially useful in an operational setting. Strong TCs often have been observed with an inner (primary) and outer (secondary) eyewall separated by a region of minimal convection ( Willoughby et al. 1982 ). Although variable and

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Rolf H. Reichle, Dennis B. McLaughlin, and Dara Entekhabi

moisture as a tuning parameter. Houser et al. (1998) focus on the four-dimensional assimilation of in situ observations and soil moisture retrievals. The weak-constraint variational method of Reichle et al. (2001b) yields near-optimal estimates of the land surface states from direct assimilation of microwave observations. Reichle et al. (2001a) prove the concept of optimal downscaling for the case where soil moisture estimates are required at scales smaller than the scale of the microwave

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Michael Peterson, Scott Rudlosky, and Daile Zhang

1. Introduction Partitioning between convective and nonconvective cloud regions is important for assessing storm hazards and their effects on the environment. Multiple algorithms have been developed to perform convective–stratiform partitioning using precipitation radars ( Awaka et al. 2007 , 2016 ), passive microwave imagers ( Anagnostou and Kummerow 1997 ; Hong et al. 1999 ; Olson et al. 2001 ), and multispectral imagers such as the Advanced Baseline Imager (ABI; Schmit et al. 2005 ) on

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