Earth system modeling, climate modeling, water resource research as well as integrated modeling (e.g., climate impact studies) require the coupling of hydrological and meteorological models. The paper presents recent concepts on such a coupling. It points out the difficulties to be solved, and provides a brief overview on recently realized couplings. Furthermore, a concept of a hydrometeorological module to couple hydrological and meteorological models is introduced. / Wasserresourcenforschung, Erdsystem- und Klimamodellierung sowie integrierte Modellierung (z.B. Klimafolgenforschung) erfordern das Koppeln von hydrologischen und meteorologischen Modellen. Dieser Artikel präsentiert Konzepte für eine solche Kopplung. Er zeigt die zu lösenden Schwierigkeiten auf und gibt einen kurzen Überblick über bisher realisierte Kopplungen. Ferner stellt er ein Konzept für einen hydrometeorologischen Moduls zur Kopplung von hydrologischen mit meteorologischen Modellen vor.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Meteorology and Physical Oceanography, 1981. / Microfiche copy available in Archives and Science. / Bibliography: leaves 98-99. / by Ronald Francis Fournier. / M.S.

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The ability to predict the weather carries great societal benefit. To ascertain reliable predictions the numerical weather prediction models used need evaluation with particular attention paid to their representations of atmospheric processes. This type of process-based model evaluation is performed through comparison of large datasets of observational data and  model results. The Year Of Polar Prediction Project site Model Intercomparison Project (YOPPsiteMIP) works to further process-based model evaluation in polar regions and has, to this end, created extensive datasets for these types of analysis. However, the lack of standardized tools to visualize the analyses carries with it significant limitations for both the usability of the data as well as the standardization of the visualizations created from it. To amend this, a set of visualization tools have been created. They were evaluated in the context of visualization quality and source code maintainability. They were found satisfactory in all cases except for the runtime. These tools further the ability to perform process-based analysis with the YOPPsiteMIP datasets in standardized formats. They are limited to the project specific MDF file type. However, with the continued spread of the MDF file type the tools become increasingly useful in furthering model evaluation on larger scales than YOPPsiteMIP.

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<p> Exposure to traffic-related air pollutants has been found to be damaging to human health. Nitrogen dioxide (NO2) levels, commonly used to indicate traffic-related pollution levels, vary significantly over small areas with higher levels found near sources such as major roads and industrial areas. The temporal and spatial variability in NO2 levels is partly caused by fluctuations in meteorological variables, and better understanding of these: meteorological influences can be used to enhance exposure assessment in health effects models.</p> <p> In this study, the interaction between measured hourly NO2 concentrations and climate variables at 11 locations in the Toronto-Hamilton Urban Airshed (THUAS) is examined. Analysis of meteorological data shows that two large urban heat islands (UHI) are present in the THUAS, centred on the downtown areas of Toronto and Hamilton. Lake breezes are found to occur frequently in the region, on up to 50% of summer days at lakeshore locations. These temperature and wind patterns influence NO2 and pollutant distributions. NO2 concentrations are highest in the early morning and late evening. Mean concentrations are highest in winter, although individual 1-hour NO2 concentrations are found to be highest in summer because of higher production rates. Wind direction is the strongest control on hourly NO2 concentration, and temperature and wind speed also have an effect. Seasonal variations in meteorology and emissions mean that the degree of spatial variability in NO2 concentrations changes from season-to-season in the THUAS resulting in variable exposure of urban populations.</p> <p> An attempt to improve an existing Land Use Regression (LUR) model, used for predicting nitrogen dioxide (NO2) concentrations and estimating human exposure, was made by incorporating high resolution interpolated observed up- and downwind effects of wind transport on NO2 concentrations around major roadways. Incorporation of observed wind direction effects in the LUR model slightly improved the accuracy of NO2 concentration estimates in densely populated, high traffic, and industrial/business areas in both Toronto and Hamilton. However the short-term nature of initial NO2 concentration data limits the utility of the model in light of the significant seasonal variation in climate parameters in the THUAS and their influence on NO2 transport and distribution.</p> / Thesis / Master of Science (MSc)

This paper presents a broad overview of the equipment and rational of the experiment conducted by the VPI Satellite Communications Group under INTELSAT Contract 433. The object of this experiment is to assess the validity of meteorological radar as a predictor of satellite earth-space path fade statistics. To validate the data collected by the VPI radar for this experiment, the differential reflectivity (ZDR) measured during the November 29-30, 1985 rainstorm is compared with calculated ZDR and ZDR from published plots. The special hardware and calibration techniques required for this experiment are also described. An IBM-PC controlled antenna pointing system and a system to continuously monitor both the peak and average power of the radar transmitter are included. Also included is a calibration system for the radar receiver. A simple computer program is developed which will give the radar cross section of a metal sphere. This sphere is used as a calibrated radar target. / M.S.

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Prior research has shown pathogen prevalence on-farms is not uniformly distributed, instead pathogen prevalence is highly dependent on environmental factors and management practices. A study was performed to determine environmental factors (e.g., landscape features, meteorological events) and management practices (e.g., date of last irrigation, pesticide application) that may impact the prevalence of Salmonella spp. and Listeria spp. at the sub-field level (0.2 ha grids) on an Eastern Shore of Virginia farm. Virginia Tech's Eastern Shore Agricultural Research and Extension Center (ESAREC) farm was used due to the liability of testing for pathogens in commercial produce fields; however, production practices used at the ESAREC farm are similar, if not the same, to production practices used on commercial farms. Fifteen drag swab, one water, and up to five fecal samples were collected every two weeks per sampling occurrence from August to December 2016 (thus up to 21 samples may be collected during one sampling occurrence. Samples were collected from randomized field plots that were picked during each sampling occurrence. Salmonella spp. and Listeria spp. were isolated and confirmed using modified versions of the Food and Drug Administration's Bacteriological Analytical Manual. Environmental factors were retrieved by remotely-sensed data for the sample location or date. Management practices were recorded by an observational survey for each sample occurrence. Two hundred and seventy-four samples (210 drag swab, 50 fecal, and 14 water samples) were collected during the late summer, fall, and winter. Listeria spp. and Salmonella spp. was detected in 8.3% (23/274) and 1.8% (5/274) of samples, respectively. Neither pathogen was detected in any of the fourteen water samples tested. Findings from this study will support the development of mitigation strategies to reduce pathogen contamination on-farm, with emphasis at the sub-field level. For instance, mitigation strategies include growers electing to not harvest near edges of fields or directly after precipitation events to minimize contamination events. Additionally, management practices were found to be associated with pathogen prevalence; therefore, management practices should be carefully tailored for each unique farm landscape. / Master of Science in Life Sciences / Over the years, fresh produce consumption has been on the rise and the concern with the safety of fresh produce has been the focus of recent studies. Raw produce has been recognized to be a potential source of pathogens that has caused human foodborne illness. Foodborne illnesses are caused by pathogens such as Listeria monocytogenes and Salmonella spp. just to mention a few. It is essential to minimize potential contamination of products with no kill step including fruits and vegetables during the whole supply chain (farm to fork). A study of environmental factors and management practices was performed to determine the influence that the factors have on pathogen prevalence of Salmonella spp. and Listeria spp. at the sub field level. As well as develop mitigation strategies to minimize contamination of produce on-farm. Over the span of 8 months, environmental samples were collected from drag swabs, fecal, and pond water used for irrigation on the farm. Management and environmental factors were recorded during every sampling occasion. Samples where then processed for the selection of Salmonella and Listeria species. Historically, it has been noted that seasons play a role in pathogen prevalence. Amongst all the samples collected during the study the prevalence for Salmonella spp. was 1.8% and Listeria spp. was 8.3% Salmonella spp. and Listeria spp. recovery was performed by following the guidelines of the Food and Drug Administration Bacteriological Analytical Manual. Factors such as seasonality, cover crop use, and irrigation use were shown to have an effect on the likelihood of detecting a pathogen positive. Any of the three factors listed were shown to be associated with an increased pathogen prevalence. By identifying these factors, growers may develop targeted mitigation strategies to reduce pathogen contamination in the pre-harvest environment.