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Chunmei Zhu and Dennis P. Lettenmaier

feedback analysis (see, e.g., Zhu et al. 2007 ). The dataset reported here is patterned on previous work by Maurer et al. (2002) over the North American Land Data Assimilation System (N-LDAS) domain. We note that the dataset described by Maurer et al. (2002) has been used in over 50 published studies, which speaks to the value of such long-term derived datasets. The Maurer et al. domain includes the conterminous United States and portions of Canada and Mexico, but extends south only to 25°N, and

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Enrique R. Vivoni, Hugo A. Gutiérrez-Jurado, Carlos A. Aragón, Luis A. Méndez-Barroso, Alex J. Rinehart, Robert L. Wyckoff, Julio C. Rodríguez, Christopher J. Watts, John D. Bolten, Venkataraman Lakshmi, and Thomas J. Jackson

). Despite its regional impact, relatively little is currently known about the potential interactions between the monsoon system and land surface properties (e.g., topography, soil moisture, vegetation) that may play a role in initiating and sustaining moist convection. The land and atmosphere interaction may be particularly important for topographically complex areas in the monsoon region. For example, Gochis et al. (2004) showed important terrain controls on the distribution of precipitation using

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Katrina Grantz, Balaji Rajagopalan, Martyn Clark, and Edith Zagona

and daily COOP station data for the periods 1948–2004 and 1949–99, respectively. Trends are assessed using the Spearman rank correlation analysis and the Kendall–Theil slope estimator, which are robust to outliers and principal component analysis (PCA) is used to extract the dominant spatial patterns. These dominant patterns are then correlated with antecedent land–ocean–atmosphere variables to ascertain driving factors for the NAMS. The paper is organized as follows. Datasets and the analysis

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Christopher J. Watts, Russell L. Scott, Jaime Garatuza-Payan, Julio C. Rodriguez, John H. Prueger, William P. Kustas, and Michael Douglas

response to the extended dry period in August and provides useful information for monitoring ET. However, the rapid dry-out observed at the desert sites (DS+B, SR, KN, LH) means that more frequent (∼daily) LST data would be required in order to monitor ET at these sites. 9. Summary of results In this paper we have examined the relation between land surface and atmospheric properties using data from satellites and micrometeorological stations during the North American Monsoon Experiment in the summer of

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Chunmei Zhu, Tereza Cavazos, and Dennis P. Lettenmaier

not directly influence monsoon rainfall in July and August because it disappears during the monsoon season. The Matsui et al. (2003) study appears to be the only attempt to evaluate the connection between monsoon onset and/or intensity and antecedent land surface conditions using observations. A major reason for the absence of other studies is the scarcity of long-term observations of the relevant land surface variables ( S m , T s , SWE) over the NAM region. Small (2001) performed experiments

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Christopher R. Williams, Allen B. White, Kenneth S. Gage, and F. Martin Ralph

. White , A. B. , D. J. Gottas , E. T. Strem , F. M. Ralph , and P. J. Neiman , 2002 : An automated brightband height detection algorithm for use with Doppler radar spectral moments. J. Atmos. Oceanic Technol. , 19 , 687 – 697 . White , A. B. , P. J. Neiman , F. M. Ralph , D. E. Kingsmill , and P. O. Persson , 2003 : Coastal orographic rainfall processes observed by radar during the California Land-Falling Jets Experiment. J. Hydrometor. , 4 , 264 – 282 . Williams

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Wayne Higgins and David Gochis

parameterized for more realistic simulations and accurate predictions with coupled ocean–atmosphere–land (O–A–L) models. A fundamental first step toward improved prediction is the clear documentation of the major elements of the monsoon system and their variability within the context of the evolving OAL annual cycle. NAME employs a multiscale (tiered) approach with focused monitoring, and diagnostic and modeling activities in the core monsoon region, on the regional and continental scales ( Fig. 1 ). An

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Myong-In Lee, Siegfried D. Schubert, Max J. Suarez, Isaac M. Held, Arun Kumar, Thomas L. Bell, Jae-Kyung E. Schemm, Ngar-Cheung Lau, Jeffrey J. Ploshay, Hyun-Kyung Kim, and Soo-Hyun Yoo

different atmospheric and land surface initial states: these states were taken from different years of preexisting long simulations forced with observed SSTs. The diurnal cycle was computed from hourly model outputs for the three summer months of June, July, and August (JJA), allowing for a 1-month spinup (September was not used in the analysis). We prescribe a climatological-mean SST forcing in order to avoid potential statistical sampling problems associated with interannual variability. Based on the

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X. Gao, J. Li, and S. Sorooshian

oceans is from the PERSIANN estimates. The NCEP–National Center for Atmospheric Research (NCAR) Regional Reanalysis (NARR) data are produced with reinitializations every 2.5 days (with an additional 12-h run for spinning up) and also leveraged by frequent three-dimensional observation data assimilation (3DDA) including precipitation and many other physical variables ( Mesinger et al. 2005 ). For the use of 3DDA, the daily NCEP gauge data over land and the (satellite based) Climate Prediction Center

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Richard H. Johnson, Paul E. Ciesielski, Brian D. McNoldy, Peter J. Rogers, and Richard K. Taft

.g., Gallus and Johnson 1991 ) where relatively dry conditions (compared to the Tropics) in the lower troposphere contribute to enhanced precipitation evaporation. This effect can also be seen in the Q 2 profiles ( Figs. 18 and 19 ) where moistening is observed in the lower troposphere. While these results are consistent with past studies over land, they must be regarded as tentative and awaiting further analysis using additional sounding data. Determination of the vertical profile of heating in the

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