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Robert F. Dale and Robert H. Shaw

An upward bias exists in probabilities of 0 or trace weekly total precipitation since small amounts often occur undetected and are recorded as 0 or trace at climatological stations where observations are made only once a day. Exact evaluation and correction of this bias is difficult, but individual estimates of 1-week P(0,T) for substations in the north-central region of the United States can be multiplied by a factor of 0.8 to reduce them to more reasonable values. Although the opportunity for low precipitation bias decreases with increasing length of period, significant bias still persists in the 2- and 3-week estimates in the western part of the north-central region during the winter season. Since the probability of measurable precipitation is 1–P(0,T), the P(0,T) bias is carried into the precipitation probabilities, but compensating biases in the gamma-distribution parameter estimates apparently contain most of the bias in the 0.01 to 0.09-inch interval.

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Robert F. Dale and Robert H. Shaw

Abstract

The average seasonal march and frequency of soil moisture in the corn root zone at Ames, Iowa, during a 30-yr period was estimated for a well-drained 5-ft soil profile holding 9 inches of available water at field capacity. Average seasonal marches of soil moisture in the top 5 ft were also prepared from simulated water balance computations for soils with three different available field capacities (6, 9 and 12 inches) and, for each capacity, three different 1 April soil moisture profiles (20, 60 and 100 per cent of available field capacity) from which to begin the moisture budget calculations. The average seasonal march and frequencies of evaporation from a Weather Bureau Class A evaporation pan and from corn with soil moisture not limiting were estimated. Using an experimentally derived atmospheric-soil moisture stress relation for corn, the climatology of potential evapotranspiration from corn was expressed as the soil moisture necessary in the corn root zone to prevent moisture stress in corn on any day of the season. The estimation of moisture stress in corn showed at least some stress days to occur in every one of the 30 years and an average of 40 non-stress days in the critical 63-day period for corn six weeks before silking to three weeks after silking.

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Robert A. McClatchey and J. H. Shaw

Abstract

No abstract available.

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N. Robert Wilson and Roger H. Shaw

Abstract

The equations of motion were used to develop a one-dimensional, nonbuoyant mathematical model of air flow within vegetative canopies. The model consists of equations for mean horizontal momentum, Reynolds stress, and for the three components of turbulent kinetic energy with closure achieved by parameterizing the higher order terms. This eliminates the need to model the Reynolds stress directly using an eddy viscosity. The closure schemes rely upon a prescribed length scale and have been used elsewhere in modeling the atmospheric boundary layer free of vegetation. The equations were solved numerically using specified boundary conditions.

Using a profile of plant area density for a crop of corn (Zea mays L.) the model predicted mean wind velocity, Reynolds stress and turbulent intensities for the region from the soil surface to twice the canopy height that compare well with experimental measurements (Shaw et al., 1974a,b).

The model is believed to overestimate the intensity of turbulence generated by the plants themselves since the dissipation of these smaller scale motions was not treated separately. However, this is not expected to have a large effect upon calculated mean wind and Reynolds stress profiles.

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Robert M. Banta, Yelena L. Pichugina, Lisa S. Darby, W. Alan Brewer, Joseph B. Olson, Jaymes S. Kenyon, S. Baidar, S. G. Benjamin, H. J. S. Fernando, K. O. Lantz, J. K. Lundquist, B. J. McCarty, T. Marke, S. P. Sandberg, J. Sharp, W. J. Shaw, D. D. Turner, J. M. Wilczak, R. Worsnop, and M. T. Stoelinga

Abstract

Complex-terrain locations often have repeatable near-surface wind patterns, such as synoptic gap flows and local thermally forced flows. An example is the Columbia River Valley in east-central Oregon–Washington, a significant wind energy generation region and the site of the Second Wind Forecast Improvement Project (WFIP2). Data from three Doppler lidars deployed during WFIP2 define and characterize summertime wind regimes and their large-scale contexts, and provide insight into NWP model errors by examining differences in the ability of a model [NOAA’s High-Resolution Rapid Refresh (HRRR version 1)] to forecast wind speed profiles for different flow regimes. Seven regimes were identified based on daily time series of the lidar-measured rotor-layer winds, which then suggested two broad categories. First, in three of the regimes the primary dynamic forcing was the large-scale pressure gradient. Second, in two other regimes the dominant forcing was the diurnal heating-cooling cycle (regional sea-breeze-type dynamics), including the marine intrusion previously described, which generates strong nocturnal winds over the region. For the large-scale pressure gradient regimes, HRRR had wind speed biases of ~1 m s−1 and RMSEs of 2–3 m s−1. Errors were much larger for the thermally forced regimes, owing to the premature demise of the strong nocturnal flow in HRRR. Thus, the more dominant the role of surface heating in generating the flow, the larger the errors. Major errors could result from surface heating of the atmosphere, boundary layer responses to that heating, and associated terrain interactions. Measurement/modeling research programs should be designed to determine which of these modeled processes produce the largest errors, so those processes can be improved and errors reduced.

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