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Margaret A. LeMone, Mukul Tewari, Fei Chen, Joseph G. Alfieri, and Dev Niyogi

1. Introduction This paper is the third of a series that addresses the horizontal variability of sensible and latent heat fluxes, H and LE, and their representation in land surface models, this time in the form of the Noah land surface model–based High-Resolution Land Data Assimilation System (HRLDAS; Chen et al. 2007 ). In the first two papers ( LeMone et al. 2003 , 2007b ), we examined horizontal variability along the amply watered and densely vegetated eastern track in Fig. 1 , using

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S. B. Trier, F. Chen, K. W. Manning, M. A. LeMone, and C. A. Davis

on seasonal precipitation amounts (e.g., Koster et al. 2004a , b ; Ruiz-Barradas and Nigam 2005 ). In this paper, we use a three-dimensional atmospheric model coupled with different land surface models (LSMs) to examine relationships between the land surface, the planetary boundary layer (PBL), and precipitation. The PBL evolution is a potentially important linkage between soil moisture and precipitation because soil wetness has been observed to strongly impact the daytime moist static energy

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F. Couvreux, F. Guichard, P. H. Austin, and F. Chen

, and = 200 Wm −2 (0.1645 K m s −1 ), these three length scales equal L Rau = 4 km, L wm = 45 km, and L Rau2 = 90 km. Accordingly, 4 km is the finest resolution analyzed here. Atmospheric conditions compete with surface heterogeneity to influence mesoscale water vapor variability. Findell and Eltahir (2003) underlined the importance of the state of the atmosphere in determining the potential influence of the land surface on convective triggering. Alapaty et al. (1997) used a 1D soil

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Margaret A. LeMone, Fei Chen, Mukul Tewari, Jimy Dudhia, Bart Geerts, Qun Miao, Richard L. Coulter, and Robert L. Grossman

. 2004 ). The eastern track is characterized by a mix of mostly grassland and winter wheat, with trees bordering many fields and waterways. The track extends across the eastern side of the Walnut River watershed southeast of Wichita and into the watershed to the east. The numerical simulations are done with the coupled Advanced Research Weather Research and Forecasting modeling system (ARW-WRF; Skamarock et al. 2005 ), initialized using the High-Resolution Land Data Assimilation System (HRLDAS

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Margaret A. LeMone, Fei Chen, Mukul Tewari, Jimy Dudhia, Bart Geerts, Qun Miao, Richard L. Coulter, and Robert L. Grossman

numerical simulations use the Advanced Research Weather Research and Forecasting (ARW-WRF) model ( Skamarock et al. 2005 ), coupled to the Noah land surface model (LSM), which was initialized using the National Center for Atmospheric Research (NCAR) High-Resolution Land Data Assimilation System (HRLDAS; Chen et al. 2007 ). The data were collected in southeast Kansas using aircraft, surface flux towers, and three radar wind profilers, during May–June, 2002, as part of the International H 2 O Project

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Diane Strassberg, Margaret A. LeMone, Thomas T. Warner, and Joseph G. Alfieri

were not measured at 10 m AGL. The stations were located to sample the major land-use types—grassland, winter wheat, bare ground, and sagebrush—along the three tracks. In addition to scattered buildings, there are trees along all three tracks, mainly located along rivers or bordering fields. Relevant surface measurements are summarized in Table 3 . We used half-hour data, available from www . rap.ucar.edu/research/land/observations/ihop.php. Sensible heat flux H and latent heat flux LE were

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Monica Górska, Jordi Vilà-Guerau de Arellano, Margaret A. LeMone, and Chiel C. van Heerwaarden

et al. (2007a) related horizontal flux gradients to vegetation. From analyzing two field projects, the Cooperative Atmospheric Surface Exchange Study 1997 (CASES-97) and IHOP_2002, LeMone et al. (2007a) found that land-use patterns have a strong influence on the horizontal distribution of sensible heat ( H ) and latent heat (LE) fluxes. The dominant vegetation types, grass and winter wheat, reverse roles with the season: while the grass was green and the winter wheat was senescent in IHOP_2002

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John R. Mecikalski, Kristopher M. Bedka, Simon J. Paech, and Leslie A. Litten

1. Introduction The study of Mecikalski and Bedka (2006 , hereinafter MB06 ) demonstrates the use of eight infrared (IR) channels as “interest fields” from the Geostationary Operational Environmental Satellite-12 ( GOES-12 ) for predicting convective initiation (CI) on the 1-km visible (VIS) pixel scale. Within MB06 , two unique attributes of the GOES-12 data stream are manipulated toward efficiently monitoring and tracking convective (i.e., cumulus) clouds in successive 5–15-min

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Robin L. Tanamachi, Wayne F. Feltz, and Ming Xue

addition, a fourth-order centered difference advection scheme was used [more details can be found in Xue et al. (2000) , ( 2001 ), and ( 2003 )]. Three-second-resolution topographical data and 1-km-resolution land surface characteristics data were used to define the land surface characteristics in the soil–vegetation model. The ARPS Data Analysis System (ADAS; Brewster 1996 ) was used to create high-resolution analysis using routine as well as special observations, including those of regional

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Lindsay J. Bennett, Tammy M. Weckwerth, Alan M. Blyth, Bart Geerts, Qun Miao, and Yvette P. Richardson

detectable because of the scattering from insects within the updrafts of the thermals. The cells were composed of updrafts around the edges and downward motion in the center. The cells observed by Weckwerth et al. (1999) had diameters of ∼2.4 km and those reported herein were 3 km on average. This paper describes the development of the boundary layer over an essentially flat land surface from before sunrise to the time when it became a mature convective boundary layer, using a synthesis of datasets

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