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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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Mekonnen Gebremichael, Enrique R. Vivoni, Christopher J. Watts, and Julio C. Rodríguez

). Two major ephemeral (seasonal) rivers flow north–south through the region: the Río San Miguel (west) and Río Sonora (east), with the former draining into the latter south of the study area. b. Rain gauge network Our dataset consists of hourly rainfall rates at 12 rain gauge stations, with records spanning from 1 July through 31 August 2004. The dataset has no periods of missing data. Although 14 gauges were installed in this region, we excluded two of them from our analysis because they had some

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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

conclusions, and recommend fruitful avenues for future work. 2. Observations and sampling methods In the following, we describe the study site, data collection, instrumentation, and analysis used to investigate the hydrometeorological conditions along the topographic transect. The field experiment was designed to assess the influence of land surface properties on the variability of monsoon precipitation and its hydrologic response. Our experimental plan is based on similar soil moisture field campaigns

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J. Craig Collier and Guang J. Zhang

located in mesh cell k , r ( g ∈ k ; t ) was summed to obtain mesh cell total R k ( t ). The mesh cell totals were then averaged onto the model’s T85 horizontal grid to obtain R ( t ). The phase and amplitude of the diurnal cycle were determined by fitting the regional-mean hourly mean precipitation rates R ( t ) to the diurnal harmonic, such that where and δ ( t ) is a residual. Estimates of the coefficients, â and b̂ , were determined by least squares regression, and formulas for the

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David J. Gochis, Christopher J. Watts, Jaime Garatuza-Payan, and Julio Cesar-Rodriguez

USW, and C 1 (=0.00145) and C 2 [set equal to 1.0 in accordance with Duchon and Essenberg (2001) ] are regression parameters found using a least squares fitting technique and the experimental controlled flow rate data. This functional form, whose resulting bias-corrected values are shown as open circles in Fig. 2a , permits the correction for larger errors at higher flow rates while providing negligible correction at rates approaching zero. As shown in Fig. 2b , the bias in TE525USW

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