Saturated hydraulic conductivity measurements are important for understanding and modeling hydrologic processes at the field scale. Few systematic studies have been conducted on how the size of double‐ring infiltrometers affects the measured hydraulic conductivity. To determine this size effect, we measured saturated hydraulic conductivity at seven sites using four different sizes of double‐ring infiltrometers. Inner‐ring diameters, di, were 20, 40, 80, and 120 cm. Detailed numerical investigations were also conducted to explain how the inner‐ring size of a double‐ring infiltrometer influences the measured hydraulic conductivity in a heterogeneous soil. Field and simulation results both demonstrated that the variability in measured hydraulic conductivity was greater for smaller inner rings (e.g., di <40 cm), and gradually decreased as the ring size increased. Our study indicates that where soil spatial variability is high, infiltrometers having a large inner ring (in general, di >80 cm) are essential for reliable measurement.

[1] The mixed layer salinity budget in the northeastern subarctic Pacific is evaluated using 5 years (2003)(2004)(2005)(2006)(2007) of Argo profiling float data, precipitation and evaporation, geostrophic velocity data, and wind stress observations. In this region the mixed layer salinity has a strong seasonal cycle, driven by seasonality in precipitation, evaporation, Ekman advection, and entrainment. Geostrophic advection effects show relatively little seasonal variability. Precipitation and Ekman effects in this area generally result in net decreases in salinity, while the evaporation, geostrophic advection, and entrainment terms yield increases. Within an annual cycle, the salinity tendency is positive during winter and fall, balanced by surface fluxes (evaporation and precipitation), entrainment, and geostrophic advection. The salinity tendency is negative during spring and summer. During these two seasons, it appears that salinity is controlled by precipitation, evaporation, and geostrophic advection. Overall, the precipitation term makes the largest contribution to the seasonal salinity budget, and the entrainment is especially important in autumn and winter.

[1] The seasonal variation of the mixed layer salinity budget in the Southern Ocean is evaluated over the latitude range 45°S-62°S using Argo profiling float data, freshwater fluxes (evaporation minus precipitation (E-P)), geostrophic velocity, wind stress, and sea ice concentration observations. The seasonal cycle of the mixed layer salinity is driven by seasonality in E-P, Ekman advection, entrainment, and sea ice. Over large areas, the geostrophic advection and diffusion show smaller contributions to the seasonal variation relative to other terms. The air-sea freshwater flux and Ekman advection in this area generally result in net decreases in salinity, while the entrainment term yields increases. Residual imbalance is consistent with a sea ice effect, whose contribution is evaluated. Sea ice is found to make a significant contribution, growing in importance toward the ice edge.Citation: Ren, L., K. Speer, and E. P. Chassignet (2011), The mixed layer salinity budget and sea ice in the Southern Ocean,

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Let V be a simple vertex operator algebra and G a finite automorphism group of V such that V G is regular. It is proved that every irreducible V G -module occurs in an irreducible g-twisted V -module for some g ∈ G. Moreover, the quantum dimensions of each irreducible V G -module are determined and a global dimension formula for V in terms of twisted modules is obtained.

An improved land-ocean global monthly precipitation anomaly reconstruction is developed for the period beginning in 1900. Reconstructions use the available historical data and statistics developed from the modern satellite-sampled period to analyze variations over the historical presatellite period. This paper documents the latest in a series of precipitation reconstructions developed by the authors. Although the reconstruction principle is still the minimization of mean-squared error, this latest reconstruction includes the following three major improvements over previous reconstructions: (i) an improved method that first produces an annual first guess, which is then adjusted using a monthly increment analysis; (ii) improved use of oceanic observations in the annual first guess using a canonical correlation analysis; and (iii) reinjection of gauge data where those data are available. These improvements allow more confident analyses and evaluations of global precipitation variations over the reconstruction period. Quantitative error estimates for the reconstruction are being developed and will be documented in a later paper.

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