Thesis (M.S.)--University of Wisconsin--Madison, 1964. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 51-53).

Thesis (M.S.)--University of Wisconsin--Madison, 1962. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaf 34).

Thesis (M.Sc.)(Geography)--University of Pretoria, 2004. / Includes summary. Available on the Internet via the World Wide Web.

Thesis (Ed.M.)--Boston University

<p> There is a need for understanding boundary layer depth and climatology over the urban area of San Jose, California. In this paper, Doppler LiDAR data are observed from San Jose. The adopted methods of vertical velocity variance and skewness are used to determine the estimated height of the convective boundary layer and to analyze sources of turbulence. The use of these methods helped identify a few types of the boundary layer that are common in San Jose. Also examined in this paper is a brief climatology of the mean maximum convective boundary layer height in San Jose over the period of 2013&ndash;2015. Vertical velocity variance and skewness is applied to identify seasonal trends in the convective boundary layer height. The influence that the marine layer has on the boundary layer over San Jose is analyzed and a conduit for future work is set forth.</p><p>

<p> Assimilation of observation data in cloudy regions has been challenging due to the unknown properties of clouds such as cloud depth, cloud vertical profiles, or cloud drop size distributions. Attempts to assimilate data in cloudy regions generally assume a drop size distribution, but most assimilation systems fail to maintain consistency between models and the observation data, as each has its own set of assumptions. This study tries to retain the consistency between the forecast model and the retrieved data by developing a Bayesian retrieval scheme that uses the forecast model itself for the a-priori database. Through the retrieval algorithm, vertical profiles of three variables related to the development of tropical cyclones, including vertical velocity, latent heating, and hydrometeor water contents are derived from the same reflectivity observation. Vertical velocity and latent heating are variables related to dynamical processes of tropical cyclones, whereas hydrometeors are byproducts of those processes. Each retrieved variable is assimilated in the data assimilation system using a flow dependent forecast error covariance matrix. The simulations are compared to evaluate the respective impact of each variable in the assimilation system. </p><p> In this study, the three assimilation experiments were conducted for two hurricane cases captured by the Global Precipitation Measurement (GPM) satellite: Hurricane Pali and Hurricane Jimena. Analyses from these two hurricane cases suggest that assimilating latent heating and hydrometeor water contents have similar impacts on the assimilation system while vertical velocity has less of an impact than the other two variables. Using these analyses as an initial condition for the forecast model reveals that the assimilations of retrieved latent heating and hydrometeor water contents were also able to improve the track forecast of Hurricane Jimena.</p>

The largest warming over the last several decades has been observed in high latitudes. Cai (2005) proposed that part of the large amplitude climate warming in high latitudes could be explained by the "dynamical amplifier" feedback. This study will first provide observational and modeling evidences to validate the dynamical amplifier theory. The second part will address the question whether part of the differences in the CGCM's global warming projections can be explained by the dynamical amplifier theory. The theory predicts an upward trend of the net radiation surplus (deficit) in low (high) latitudes forced by anthropogenic greenhouse gases. The radiation budget at the top of the atmosphere (TOA) using the ERA40 reanalysis and climate model simulations forced by anthropogenic radiative forcings made at 14 climate centers were analyzed. The results indicate that both the radiation energy surplus in low latitudes and deficit in high latitudes at the TOA have been strengthened over the last several decades. Such an intensification of the radiation energy imbalance at the TOA is also confirmed by most of the climate model simulations. Furthermore, the analysis of the net radiation budget between the surface and the TOA confirms that the change in the TOA energy imbalance is indeed due to the upward trend in the poleward heat transport, in accordance with the dynamical amplifier theory. There is a large model-to-model variability of the intensification of the poleward heat transport among the 14 climate model simulations. It is found that about 59% of the global warming projection uncertainties, which varies from 1.5K to 4K, forced by the 2×CO2 forcing can be explained by the variation of the intensification of the poleward heat transport among models. The inter-model variability of the change in the poleward heat transport explains about 66% of the warming projection uncertainties for the Northern Hemisphere (NH) and 54% for the Southern Hemisphere (SH). The differences in the poleward heat transport intensification also explain about 71% and 49% of the warming uncertainties in the NH and SH high latitudes. Therefore, it can be concluded that a large part of the uncertainties in the CGCM's global warming projections can be explained by the dynamical amplifier theory. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Summer Semester, 2005. / June 28, 2005. / Dynamical Amplifier Theory, High Latitude Warming, Models' Sensitivity, Global Warming, Heat Flux, Radiations, Top of the Atmosphere, Warming Projections, Models' Uncertainties, IPCC, Poleward Heat Transport / Includes bibliographical references. / Ming Cai, Professor Directing Thesis; Kwang-Yul Kim, Committee Member; Paul H. Ruscher, Committee Member.

With current computational limitations, the accuracy of high resolution precipitation forecasts has limited temporal and spatial resolutions. Forecast accuracy drops dramatically after a 24 hour forecast. Current operational mesoscale models run only to 48-72 hours. However, with the recent development of the superensemble technique, the potential to improve precipitation forecasts at the regional resolution exists. The purpose of this study is to apply the superensemble technique to regional precipitation forecasts to generate more accurate forecasts pinpointing exact locations and intensities of strong precipitation systems. This study will determine the skill and predictability of a regional superensemble forecast out to 60 hours. Precipitation results were stratified by time of day to allow detections of the diurnal cycle. As expected, warm season daytime precipitation is commonly forced by convection which is difficult to accurately model. Results were also stratified by lead time which reveals how quickly the forecasts degrade in time. Currently, mesoscale models such as those utilized in the ensemble are approaching the limits of precipitation predictability. Major synoptic regimes, including subtropical high, mid-latitude trough/front, and tropical cyclone, were examined to determine the skill of the superensemble under various synoptic conditions. Finally, different rainfall intensities were examined which revealed the superensemble forecast significantly improved the forecast at significant rainfall amounts. The regional superensemble consists of 12 to 60-hour daily quantitative precipitation forecasts from 6 models. Five are independent operational models, and one comes from the physical-initialized FSU regional spectral model. The superensemble forecasts are verified during the summer 2003 season over the southeastern US using a merged RFC Stage IV radar/gauge and satellite analyses. Precipitation forecasts were skillful in outperforming the operational models at all model times. Skill measurements that were examined include ETS, Bias, FAR, and POD. / A Dissertation submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester, 2004. / October 19, 2004. / Numerical Weather Prediction, Superensemble, QPF, Ensemble, Precipitation Forecasts, Mesoscale, Warm Season / Includes bibliographical references. / T. N. Krishnamurti, Professor Directing Dissertation; Ruby Krishnamurti, Outside Committee Member; Paul H. Ruscher, Committee Member; Carol Anne Clayson, Committee Member; Guosheng Liu, Committee Member.

The varying tasks required for assimilating satellite radiance observations from the Atmospheric Infrared Sounder (AIRS) into the initial conditions of a numerical weather prediction model are discussed. The tangent linear and adjoint observation operators were developed from a fast and computationally inexpensive radiative transfer model (RTM). The adjoint model was used to conduct a sensitivity analysis of the RTM-produced radiances at each of the 2378 AIRS spectral channels. The results of this study confirm that the RTM is simulating the radiative transfer process well when using forecast model data as input. This analysis will be used to conduct an efficient channel selection study prior to assimilating AIRS radiances. The errors associated with both the AIRS observations and the RTM calculations are discussed. The error in the AIRS observations for the selected test case compare favorably with expected values obtained by the AIRS science team from both pre-flight and early orbit testing. Errors associated with the RTM when using forecast model fields as input were investigated. The bias of the model was computed and the results of this study will be used to correct the bias in the model solution prior to assimilation. The variance of the model was also computed and will be used to identify outliers and to construct the estimated model error covariance matrix, which will be used in the cost function calculation. The models developed and the errors calculated for all fields will be used in future work to assimilate radiance values into numerical weather forecasts. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2004. / October 20, 2004. / Data Assimilation, 4D-Var, QPF, AIRS / Includes bibliographical references. / Xiaolei Zou, Professor Directing Thesis; Paul Ruscher, Committee Member; Kwang-Yul Kim, Committee Member.

The Madden-Julian Oscillation (MJO) is a coupled air-sea interaction that dominates intraseasonal variability in the tropical oceans. This mode of variability is especially important in the tropical western Pacific Ocean warm pool because this region contains the warmest sea surface temperatures (SST), largest annual precipitation, and largest latent heat release in the atmosphere, which strongly affect the global redistribution of heat, moisture, and momentum. The MJO is difficult to reproduce in models, and some speculate it is because of the relationship between the MJO and diurnal SST variability (e.g. Zheng et al. 2004). A single-column coupled atmosphere-ocean model (SCCM) is used to calculate and evaluate the effects of diurnal SST variability on the marine boundary layer and convection during the Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean-Atmosphere Response Experiment (COARE) Intensive Observations Period (IOP). Results show that the use of a diurnally-varying SST as opposed to a daily-averaged SST impact the lower atmosphere by several degrees and the upper atmosphere through convection. Large-scale advective tendencies of air temperature and specific humidity can act to enhance or reduce the effects of local feedbacks resulting from diurnal warming. The absence of the diurnal SST cycle substantially impacts the transition phases of the MJO with considerable differences in low-level and mid-level cloud amount, due to changes in low-level moistening, which is essential in preconditioning the atmosphere for deep convection. These results support the hypothesis that a lack of diurnal SST variability in large-scale models could contribute to incorrect moistening during the transition phase, which is important to simulating the MJO. / A Thesis submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2007. / July 12, 2007. / Madden-Julian Oscillation, Sea Surface Temperature Variability, Diurnal Warming / Includes bibliographical references. / Carol Anne Clayson, Professor Directing Thesis; Mark Bourassa, Committee Member; Philip Cunningham, Committee Member.