Eight years (1980-87) of twice-daily high-resolution radiosonde data from a tropical mid-Pacific island station are analyzed to generate time series of the planetary boundary layer (PBL) top pressure, an ageostrophic parameter (related to the divergence), and a parameter of mean PBL specific humidity. Sample spectra of these time series are calculated along with a spectra for nighttime outgoing longwave radiation (OLR) data (centered at a gridpoint near the island station) and compared in order to investigate the relationship between the ageostrophy and dynamical phenomena of the tropical Pacific. Methods of boundary layer top diagnosis are compared. Data derived methods include temperature inversion detection, humidity jump detection, and wind shear detection. The model based diagnosis method uses a Richardson number scheme. Comparisons between data derived methods and model based methods show good agreement. Correlation coefficients for comparisons are all above 0.91. In each sample spectra, the dominant peak corresponds to the frequency of the annual cycle. With an estimated annual cycle removed from each of the time series the nighttime (12 GMT) sample spectra for PBL top pressure shows a peak at a frequency that corresponds to the 30-60 day Intraseasonal Oscillation (ISO). Removal of an estimated annual cycle was unsuccessful for the daytime (0 GMT) sample spectra for PBL top pressure, PBL mean specific humidity, and the ageostrophic parameter. Sample spectra of the ageostrophic parameter show peaks in the ISO frequency range for both 12 GMT and 0 GMT even before removal of the annual cycle was attempted. The ISO range peaks remained in the 12 GMT ageostrophic parameter spectrum when the annual cycle was successfully removed. The nighttime OLR spectrum is dominated by the annual cycle peak and its harmonics. The OLR spectrum also shows a significant peak in the ISO range of periods. Removal of an estimated annual cycle intensifies the peak in the ISO range. The ageostrophic parameter time series is compared to the results of an EOF analysis performed on the same 8 years of radiosonde humidity measurements. The first three EOF modes of specific humidity give sample spectra which are dominated by the annual cycle. With the annual cycle removed the sample spectra of the first and third EOF modes of specific humidity both show significant peaks in the ISO frequency range, while the second EOF mode sample spectrum is dominated by two peaks at frequencies corresponding to periods of approximately 4 and 5 months. The presence of common frequencies in the ISO range of the power spectra of the ageostrophic parameter (a measure of divergence), the nighttime OLR (a measure of deep convection), the nighttime planetary boundary layer top, and the first EOF mode of specific humidity, lends support to theories that relate the ISO to the interaction of dynamics and moist processes. / Graduation date: 1995

The seasonal variation of wind speed fluctuations is studied at four locations in The Dalles area of the Columbia River Gorge. Three of the sites are located in or near the valley floor while the fourth site is on top of a 900 m (3000 ft) ridge just north of The Dalles. The speed fluctuations or gustiness at these sites varies with terrain roughness, wind speed, and atmospheric stability. Due to the channelling effects of the Gorge, wind flow in The Dalles area is predominantly upriver or downriver. Strongest winds occur from the west at all four of the sites that were analyzed. Highest gustiness values occurred at the Martin Marietta site located near the rugged foothills of the eastern slopes of the Cascade Mountain Range. Moderate gustiness values were common at KCIV located on the top of the ridge north of The Dalles and at the D.C. Test Site surrounded by rolling hills. Smoothest flow was found along the relatively level valley floor at The Dalles Dam. Gustiness in relation to wind speed varied at all four sites. Gustiness values increased with speed through the moderate speed range at KCIV while gustiness decreased with speed at The Dalles Dam and the Martin Marietta site. No distinct relationship was found at the D.C. Test Site. At KCIV changes in gustiness are directly related to the amount of solar insolation and hence the atmospheric stability. Gustiness values were highest during the summer and daytime values were greater than those at night during both winter and summer. In contrast, at the other three sites near or on the valley floor no distinct relationship between the stability variations and the changes in gustiness could be found. Results indicated that the gustiness values during the winter at these three locations exceeded those during the summer. It appears that the unstable nature of the post frontal wintertime air mass is responsible for the strong and turbulent northwest flow. Although moderate speed fluctuations were common at KCIV, this site is the most appealing of the four locations for wind power generation due to the persistency of moderately strong winds during both summer and winter. Least attractive of the four sites is Martin Marietta where high gustiness values along with weak winter winds provide little usable wind energy. / Graduation date: 1977

Graduation date: 1983

Dissertation (Ph. D.)--University of Stellenbosch, 1992. / Bibliography. Also available via the Internet.

Thesis (M.S.)--Brigham Young University. Dept. of Civil and Environmental Engineering, 2008. / Includes bibliographical references (p. 51-54).

Thesis (Ph. D.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2003. / Includes bibliographical references (p. 231-237).

published_or_final_version / abstract / toc / Statistics / Master / Master of Philosophy

No description available.

The use of an ocean surface velocity dependent wind stress is examined in the context of a 3-layer double-gyre quasigeostrophic wind-driven ocean circulation model. The new wind stress formulation results in a large reduction of the power input by the wind into the oceanic circulation. This wind stress is proportional to a quadratic function of Ua--u o, where Ua is the wind at 10m above the ocean surface and uo is the ocean surface current. Because the winds are typically faster than the ocean currents, the impact of the ocean surface velocity on the wind stress itself is relatively small. However, the power input is found to be greatly reduced with the new formulation. This is shown by simple scaling argument and numerical simulations in a square basin. Our results suggest that the wind power input may be as much as 35% smaller than is typically assumed. / The ocean current signature is clearly visible in the scatterometer-derived wind stress fields. We argue that because the actual ocean velocity differs from the modeled ocean velocities, care must be taken in directly applying scatterometer-derived wind stress products to the ocean circulation models. This is not to say that the scatterometer-derived wind stress is not useful. Clearly the great spatial and temporal coverage make these data sets invaluable. Our point is that it is better to separate the atmospheric and oceanic contribution to the stresses. / Finally, the new wind stress decreases the sensitivity of the solution to the (poorly known) bottom friction coefficient. The dependence of the circulation strength on different values of bottom friction is examined under the standard and the new wind stress forcing for two topographic configurations. A flat bottom and a meridional ridge case are studied. In the flat bottom case, the new wind stress leads to a significant reduction of the sensitivity to the bottom friction parameter, implying that inertial runaway occurs for smaller values of bottom friction coefficient. The ridge case also gives similar results. In the case of the ridge and the new wind stress formulation, no real inertial runaway regime has been found over the range of parameters explored.

The statistical prediction of local sea surface winds at a number of locations over the global ocean (Northeast Pacific, Northwest Atlantic and Pacific, tropical Pacific and Atlantic) is investigated using a surface wind statistical downscaling model based on multiple linear regression. The predictands (mean and standard deviation of both vector wind components and wind speed) calculated from ocean buoy observations on daily, weekly and monthly temporal scales are regressed on upper level predictor fields (derived from zonal wind, meridional wind, wind speed, and air temperature) from reanalysis products. The predictor fields are subject to a combined Empirical Orthogonal Function (EOF) analysis before entering the regression model. It is found that in general the mean vector wind components are more predictable than mean wind speed in the North Pacific and Atlantic, while in the tropical Pacific and Atlantic the difference in predictive skill between mean vector wind components and wind speed is not substantial. The predictability of wind speed relative to vector wind components is interpreted by an idealized Gaussian model of wind speed probability density function, which indicates that the wind speed is more sensitive to the standard deviations (which generally are not well predicted) than to the means of vector wind component in the midlatitude region and vice versa in the tropical region. This sensitivity of wind speed statistics to those of vector wind components can be characterized by a simple scalar quantity theta=arctan(mu/sigma) (in which mu is the magnitude of average vector wind and sigma is the isotropic standard deviation of the vector winds). The quantity theta is found to be dependent on season, geographic location and averaging timescale of wind statistics. While the idealized probability model does a good job of characterizing month-to-month variations in the mean wind speed based on those of the vector wind statistics, month-to-month variations in the standard deviation of speed are not well modelled. A series of Monte Carlo experiments demonstrates that the inconsistency in the characterization of wind speed standard deviation is the result of differences of sampling variability between the vector wind and wind speed statistics. / Graduate