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Shixuan Zhang, Zhaoxia Pu, Derek J. Posselt, and Robert Atlas

u – w vectors, where u is the radial velocity (m s −1 ) and w is the vertical velocity (cm s −1 )] with the vector magnitude legend below the color bar. Overall, assimilation of CYGNSS ocean SWSs directly improves the low-level inflow, which increases moisture transport to the inner-core region in the low level and enhances the low-level warm core. The maintenance of strong low-level inflow stimulates a moderate upward motion around the storm center, which leads to the enhancement of

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Christopher A. Fiebrich, Janet E. Martinez, Jerald A. Brotzge, and Jeffrey B. Basara

10 m, temperature and relative humidity at 1.5 m, and bare soil and sod temperatures at 10-cm depth. A majority of sites also measure wind speed at 2 and 9 m, temperature at 9 m, net radiation, soil moisture at 5-, 25-, 60-, and 75-cm depths, and soil temperatures at 5 and 30 cm. Furthermore, 10 sites that have IRT sensors installed are also designated as Oklahoma Atmospheric Surface-Layer Instrumentation System (OASIS) Super Sites ( Fig. 1 ; Brotzge et al. 1999 ). In addition to the net

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

1. Introduction Infrared radiance spectra observed with operational polar satellite hyperspectral sounding (PHS) instruments [e.g., the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-Track Infrared Sounder (CrIS)] provide relatively high-vertical-resolution temperature and moisture sounding information. This information, when received via a direct broadcast system (DBS), can be used to monitor the atmospheric stability of the atmosphere for the purpose of predicting where and

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R. A. Pielke, G. Kallos, and M. Segal

breeze (sections 2 and 4)and upslope flow (section 3), while providing a qualitative general evaluation of their characteristics (section 5). The potential impact of nonuniform surfacethermal forcing within a mesoscale domain on wind,temperature, and moisture fields is outlined in section6. General scaling evaluations as related to possibleerrors due to insufficient horizontal profiler resolutionare given in section 7.2. Sea breeze analysis In order to investigate what spatial and

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Junhong Wang

their models. In addition, there have been increased demands of dropsondes over land for field experiments to map moisture and validate airborne remote sensors, such as IHOP_2002. Previous limited studies suggest a dry bias of ∼5%–20% in dropsonde humidity data ( Jaubert et al. 1999 ; Kooi et al. 2002 ; Vance et al. 2004 ). Therefore, the goal of this paper is to evaluate the dropsonde humidity sensor, provide evaluation results to the dropsonde user community, and build their confidence on

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James D. Means and Daniel Cayan

derivation of this relation relies on an assumption of azimuthal symmetry, since different slant paths to different GPS satellites are combined. Azimuthal symmetry implies that there are not strong lateral gradients in the pressure, temperature, and moisture field, so the relationship will hold best in quiescent weather situations and may have significant errors in the vicinity of fronts. The following expression for the semiempirical function is given by Bevis et al. (1992) : Here is the integrated

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Andrew K. Heidinger, Istvan Laszlo, Christine C. Molling, and Dan Tarpley

all AVHRR sensors. PFAAST offers the advantage of being very quick. It is strictly a transmission model and does not provide the capability to simulate scattering or surface emission. PFAAST does require knowledge of the atmospheric profiles. The temperature and moisture profiles for real-time products are taken from spatially and temporally interpolated NCEP Global Forecast System (GFS) 12-h forecasts. For climate applications, these profiles are taken from NCEP Climate Forecast System Reanalysis

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C. Anderson, J. Figa, H. Bonekamp, J. J. W. Wilson, J. Verspeek, A. Stoffelen, and M. Portabella

soil moisture retrieval ( Bartalis et al. 2007 ) and sea ice mapping and drift measurements ( Lavergne et al. 2010 ). The accuracy of the retrieved geophysical information depends on the accuracy of the underlying radar backscatter measurements. These are expressed in terms of the normalized radar cross section (NRCS), which is the ratio of the received backscattered energy to that of an isotropic surface scatterer as given by the two-way radar equation. NRCS measurements, denoted by σ 0

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L. Mahrt

significantly larger than the moisture flux for most of the Microfronts’ data and its errors presumably contribute more to the imbalance of the energy budget. At night, the energy budget is sometimes dominated by net radiation, and soil heat flux and the errors in the heat flux have less impact on the energy imbalance. Each time series is divided into six 10-min records ( i = 1, 6), which in turn are divided into six 100-s segments ( j = 1, 6) (see Fig. 5 ). The within-record and between-record standard

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Julian Kinzel, Karsten Fennig, Marc Schröder, Axel Andersson, Karl Bumke, and Rainer Hollmann

Environmental Prediction (NCEP). Similarly, Caires and Sterl (2003) carried out TC analysis to validate significant wave height and wind speed fields from ERA-40 against altimeter measurements of buoys, ERS-1 , and the Ocean Topography Experiment (TOPEX/Poseidon, NASA). Janssen et al. (2007) applied the TC method for wave height analyses. The introduction of the TC method into the field of satellite-based soil moisture research ( Scipal et al. 2010 ) demonstrates the approach’s potential for a wide

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