Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (p. 97-106).

Thesis (M.S. in Meteorology)--Naval Postgraduate School, March 2010. / Thesis Advisor(s): Durkee, Philip A. Second Reader: Nielsen, Kurt E. "March 2010." Description based on title screen as viewed on April 27, 2010. Author(s) subject terms: Lightning, Thunderstorm, GOES, Geostationary, Satellite, Convection, Convective Initiation, Lightning Initiation, Nowcast, Applied Meteorology. Includes bibliographical references (p. 97-101). Also available in print.

400m), and overestimates their corresponding trapping layer depth by ~20%. For deeper boundary layer cases the duct strength was well represented, however, the trapping layer depth was over estimated by ~ 33%.

Submitted to the Information Technology (IT) Department in conformity with the requirements for the degree of Doctor of Philosophy in Information Technology, Durban University of Technology. Durban, South Africa, 2016. / This doctoral research introduces an integration of satellite systems and new stratospheric platforms for weather observation, imaging and transfer of meteorological data to the ground infrastructures. Terrestrial configuration and satellite communication subsystems represent well-established technologies that have been involved in global satellite sensing and weather observation area for years. However, in recent times, a new alternative has emerged based on quasi-stationary aerial platforms located in the Stratosphere called High Altitude Platform (HAP) or Stratospheric Communication Platforms (SCP). The SCP systems seem to represent a dream come true for communication engineers since they preserve most of the advantages of both terrestrial and satellite communication systems. Today, SCP systems are able to help, in a more cost effective way, developments of space Earth sensing and weather observation and weather sensing and observation. This new system can provide a number of forms ranging from a low altitude tethered balloon to a high altitude (18 – 25 km) fuel-powered piloted aircraft, solar-powered unmanned airplanes and solar-powered airship.

The objective of this thesis is to evaluate the sources of the differences between the NO2 satellite retrieval products provided by the Royal Dutch Meteorological Institute (KNMI) and the National Aeronautics and Space Administration (NASA). Ground studies have shown that although both products use the same satellite, these products yield different observations for NO2 tropospheric columns concentrations. This study does not validate either retrieval product, but rather indentifies the main sources for the discrepancy. There are several parameters which allow successful retrieval of NO2 vertical columns. For this study, only the difference between the radiative models and the a priori NO2 chemical transport models were considered relevant. All other parameters, such as cloud properties, slant columns, stratospheric serration and their assumptions, were held constant. Here, the models are referred to by their proprietor's acronym: "TOMRAD" refers to the radiative model used by NASA, "DAK" refers to the radiative model used by KNMI, "TM4" refers to the a priori chemical transport model used by KNMI, and "REAM" refers to the a priori chemical transport model maintained by the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. Mixing these parameters creates four retrievals for comparison. Many significant differences were identified after comparing these four retrievals. First, there are viewing geometry biases between the port side and the starboard side of the satellite retrieval for each swath. These viewing geometry biases lead to artificial periodicities in the retrievals of NO2 tropospheric vertical columns over a specific coordinate or site, such as a city. Furthermore, there were significant differences found after using different a priori NO2 chemical transport models. The low horizontal resolution of TM4 and the satellite retrieval/TM4 coupling effect compared to REAM leads to considerable questioning of the near real time application of the KNMI NO2 retrieval product. Though the TM4 model performs poorly, TM4 retrievals do perform nearly as well as REAM retrievals at capturing day-to-day variability and the spatial variability of the cities used as examples here. The retrievals using TOMRAD outperformed the retrievals using DAK when compared to the high resolution, hourly REAM a priori chemical transport model. In sum, these findings should lead to better optimizations of both the KNMI and NASA retrievals, and thus make their publicly available data products more reliable and accurate for general use.

Meteorological satellite images at visible and infra-red wavelengths are an invaluable source of information on cloud systems because of their extensive coverage of the whole of the Earth's surface, providing data in areas that are only sparsely monitored, if at all, by other means. Although this information has been used subjectively by forecasters for many years, the lack of automatic, quantitative analysis techniques largely prevents its assimilation into numerical weather prediction (NWP) models, which are the basis of all modern weather forecasting. This thesis investigates the use of neural network techniques for the analysis of the images in order to make fuller use of the available data. The recognition of a particular type of cloud is dependent on the determination of a set of features from the satellite image spectral bands that will give discriminating information. This feature extraction and selection process is dealt with in detail, and a feature selection process based on the radial basis function (RBF) neural network is presented. The high-dimensional feature space is visualized on a two-dimensional plane by the use of three techniques: the Kohonen map, the Sammon map, and a recently-developed technique known as the Generative Topographic Mapping (GTM). Classification results using a multi-layer perceptron (MLP) and an RBF neural network are presented. The results of independently classifying each pixel in an image are compared with a method that makes use of contextual information, the Markov Random Field (MRF) model. The limitations of the pixel-based approach are highlighted, and a region-based approach is presented that enables the definition of large-scale regions of uniform cloud type. Two segmentation methods are used, the active contour (or snake) model, and the more recentlydeveloped level set technique. The latter method was found to provide many benefits over the former. The region-based approach will facilitate the assimilation of cloud system information into NWP models in the future.

Recent advances in satellite sensor technology and micrometeorological instrumentation for water flux measurement, coupled with the expansion of automatic weather station networks that provide routine measurements of near-surface climate variables, present new opportunities for combining satellite and ground-based instrumentation to obtain distributed estimates of vegetation water use over wide areas in South Africa. In this study, a novel approach is tested, which uses satellite leaf area index (LAI) data retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) to inform the FAO-56 Penman-Monteith equation for calculating reference evaporation (ET₀) of vegetation phenological activity. The model (ETMODIS) was validated at four sites in three different ecosystems across the country, including semi-arid savanna near Skukuza, mixed community grassland at Bellevue, near Pietermaritzburg, and Groenkop, a mixed evergreen indigenous forest near George, to determine potential for application over wider areas of the South African land surface towards meeting water resource management objectives. At Skukuza, evaluated against 170 days of flux data measured at a permanent eddy covariance (EC) flux tower in 2007, the model (ETMODIS) predicted 194.8 mm evapotranspiration relative to 148.9 mm measured fluxes, an overestimate of 31.7 %, (r² = 0.67). At an adjacent site, evaluated against flux data measured on two discrete periods of seven and eight days in February and May of 2005 using a large aperture scintillometer (SLS), ETMODIS predicted 27.4 mm and 6.7 mm evapotranspiration respectively, relative to measured fluxes of 32.5 and 8.2 mm, underestimates of 15.7 % and 18.3 % in each case (r² = 0.67 and 0.34, respectively). At Bellevue, evaluated against 235 days of evapotranspiration data measured using a surface layer scintillometer (SLS) in 2003, ETMODIS predicted 266.9 mm evapotranspiration relative to 460.2 mm measured fluxes, an underestimate of 42 % (r² = 0.67). At Groenkop, evaluated against data measured using a SLS over three discrete periods of four, seven and seven days in February, June and September/October respectively, ETMODIS predicted 9.7 mm, 10.3 mm and 17.0 mm evapotranspiration, relative to measured fluxes of 10.9 mm, 14.6 mm and 23. 9 mm, underestimates of 22.4 %, 11.2 % and 24.1 % in each case (r² = 0.98, 0.43 and 0.80, respectively). Total measured evapotranspiration exceeded total modelled evapotranspiration in all cases, with the exception of the flux tower site at Skukuza, where evapotranspiration was overestimated by ETMODIS by 31.7 % relative to measured (EC) values for the 170 days in 2007 where corresponding modelled and measured data were available. The most significant differences in measured versus predicted data were recorded at the Skukuza flux tower site in 2007 (31.7 % overestimate), and the Bellevue SLS flux site in 2003 (42 % underestimate); coefficients of determination, a measure of the extent to which modelled data are able to explain observed data at validation periods, with just two exceptions, were within a range of 0.67 – 0.98. Several sources of error and uncertainty were identified, relating predominantly to uncertainties in measured flux data used to evaluate ETMODIS, uncertainties in MODIS LAI submitted to ETMODIS, and uncertainties in ETMODIS itself, including model assumptions, and specific uncertainties relating to various inputs; further application of the model is required to test these uncertainties however, and establish confidence limits in performance. Nevertheless, the results of this study suggest that the technique is generally able to produce estimates of vegetation water use to within reasonably close approximations of measurements acquired using micrometeorological instruments, with r² values within the range of other peer-reviewed satellite remote sensing-based approaches.

Submitted to the Information Technology (IT) Department in conformity with the requirements for the degree of Doctor of Philosophy in Information Technology, Durban University of Technology. Durban, South Africa, 2016. / This doctoral research introduces an integration of satellite systems and new stratospheric platforms for weather observation, imaging and transfer of meteorological data to the ground infrastructures. Terrestrial configuration and satellite communication subsystems represent well-established technologies that have been involved in global satellite sensing and weather observation area for years. However, in recent times, a new alternative has emerged based on quasi-stationary aerial platforms located in the Stratosphere called High Altitude Platform (HAP) or Stratospheric Communication Platforms (SCP). The SCP systems seem to represent a dream come true for communication engineers since they preserve most of the advantages of both terrestrial and satellite communication systems. Today, SCP systems are able to help, in a more cost effective way, developments of space Earth sensing and weather observation and weather sensing and observation. This new system can provide a number of forms ranging from a low altitude tethered balloon to a high altitude (18 – 25 km) fuel-powered piloted aircraft, solar-powered unmanned airplanes and solar-powered airship.

In tracing the history of the TIROS meteorological satellite system, this dissertation details the convergence of two communities: the DOD space scientists who established US capability to launch and operate these remote sensing systems and the US Weather Bureau meteorologists who would be the managers and users of satellite data. Between 1946 and 1964, these persons participated in successive coalitions. These coalitions were necessary in part because satellite systems were too big—geographically, fiscally, and technically—to be developed and operated within a single institution. Thus, TIROS technologies and people trace their roots to several research centers—institutions that the USWB and later NASA attempted to coordinate for US R&D. The gradual transfer of persons and hardware from the armed services to the non-military NASA sheds light on the US’s evolution as a Cold War global power, shaped from the “top-down” (by the executive and legislative branches) as well as the “bottom-up” (by military and non-military scientific communities). Through these successive coalitions, actor terms centered on “basic science” or the circulation of atmospheric data were used to help define bureaucratic places (the Upper Atmospheric Rocket Research Panel, International Geophysical Year, NASA, and the World Weather Watch) in which basic research would be supported by sustained and collaboration could take place with international partners.