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Evan J. Coopersmith, Michael H. Cosh, and Jennifer M. Jacobs

1. Introduction Soil moisture plays a pivotal role in hydrologic models. These measurements and models provide estimates of subsurface soil water storage and loss mechanisms that are crucial for drought research ( Sheffield et al. 2004 ) and other climatic analyses (e.g., Campoy et al. 2013 ; Joetzjer et al. 2013 ). Soil moisture data are also relevant for decision support within agricultural regions in the Midwest, with one such example being the assessment of whether large equipment will

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Andres Patrignani, Mary Knapp, Christopher Redmond, and Eduardo Santos

similar standards as the Soil Climate Analysis Network ( Schaefer et al. 2007 ) for soil temperature and soil moisture observations. As part of the ongoing expansion, detailed characterization of the soil profile of the new 13 stations was made by NRCS personnel and a new online platform was created for data dissemination ( http://mesonet.k-state.edu ). The third phase of the network spans the period from 2013 to the present time. During this period the network underwent major organizational and

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Song Yang and Eric A. Smith

whether or not there are similarities between the mean convective heating profiles of AMEX and western Pacific ocean profiles, there are no similar data for the latter region. The western tropical Pacific is the area that contains large-scale atmospheric convergence associated with the ascending branch of the Walker circulation, superimposed with ascending motion driven by the western Pacific warm pool ( Webster 1983 ). The convergence of air and moisture from the Pacific and Indian oceans leads to

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Laurence C. Breaker, David B. Gilhousen, and Lawrence D. Burroughs

, humidity sensors must be adequately protected from excess heating due to incoming solar radiation; and finally, humidity sensors must recover from periods of saturation rapidly and without change to their calibration ( Coantic and Friehe 1980 ). Since atmospheric moisture is a difficult parameter to measure accurately over the ocean, it is not surprising that it has been even more difficult to acquire observations of boundary layer moisture from unattended instruments for extended periods of several

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Sabine Philipps, Christine Boone, and Estelle Obligis

, and moorings), large regions with only a few measurements persist, in particular in the Southern Hemisphere. Bingham et al. (2002) point out that 27% of the oceans 1° squares have never been sampled for SSS. A satellite mission is therefore essential to get global SSS coverage with high temporal resolution. Soil Moisture and Ocean Salinity (SMOS) was chosen by the European Space Agency (ESA) as the second Earth Explorer Opportunity mission with an expected launch in 2007. The satellite will be

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M. K. Rama Varma Raja, Seth I. Gutman, James G. Yoe, Larry M. McMillin, and Jiang Zhao

1. Introduction Atmospheric water vapor is an important parameter to be considered for a wide range of applications, including studies of the earth’s radiation budget, hydrological cycle, atmospheric chemistry, and global warming, and therefore its accurate measurement is of great interest. The task of accurately measuring atmospheric water vapor is challenging, given that moisture field variations are more sporadic in nature than variations in temperature or pressure. Conventional in situ

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Daniel Birkenheuer and Seth Gutman

retrievals to provide a measurement of the layer and total precipitable water in clear and partly cloudy conditions ( Schmit et al. 2002 ). The product provides moisture in three sigma-p layers plus a total column value. For this examination, only the TPW data were used for comparison to GPS-IPW data derived for local zenith. The GOES moisture product has been in existence for more than a decade. The GOES retrieval algorithm uses radiances from either a 5 × 5 or 3 × 3 set of averaged pixels to determine

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Richard S. Penc

temperature, moisture, and pressure, and hence gradient of the refractive index. Radars of sufficient wavelength are capable of sensing these refractive index inhomogeneities, as they are almost always present within the turbulent atmosphere below the stratopause. This paper presents a study of the moisture profiles within a Type I cloud-topped boundary layer (CTBL) using wind profiler and rawinsonde data. It closely mirrors the study of the moisture structure of a Type II CTBL conducted by White et al

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Hyun-Sung Jang, Byung-Ju Sohn, Hyoung-Wook Chun, Jun Li, and Elisabeth Weisz

1. Introduction With the advent of satellite-based hyperspectral infrared measurement technologies such as the Atmospheric Infrared Sounder (AIRS; Chahine et al. 2006 ), global pictures of three-dimensional temperature and moisture became available, recently yielding a high vertical resolution of ~1–2 km. One-dimensional variational (1DVAR)-based physical methods have been developed for retrieving relevant parameters in a manner consistent with both satellite measurements and a priori

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B. B. Stankov, B. E. Martner, and M. K. Politovich

488 JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY VOLUME 12Moisture Profiling of the Cloudy Winter Atmosphere Using Combined Remote Sensors B. B. STANKOV AND B. E. MARTNERNOAA Environmental Technology Laboratory, Boulder, Colorado M. K. POLITOVICHResearch Applications Program, National Center for Atmospheric Research, Boulder, Colorado(Manuscript received 8 June 1994, in final form 30 September 1994)ABSTRACT A new method for

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