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The purpose of this research is to simulate warm-season mesoscale convective systems (MCSs) using the Weather Research and Forecasting Model (WRF) to determine whether modeled atmospheric variables are capable of discriminating between derecho formation and intensity. Fifty total events are selected with half being derecho-producing MCSs and half being non-derecho producing MCSs. WRF is used to model each event with a high-resolution domain centered over the Midwest using the North American Regional Reanalysis (NARR) dataset as initial and boundary conditions. Atmospheric conditions downstream of the MCS damage path are compared to thresholds established by previous research to determine if the model accurately simulates the expected environment. The goal of the research is to gain insight into how well a high-resolution model can simulate the environment that is expected. It is anticipated that the model will be able to distinguish between environments associated with a derecho-producing MCS and a non-derecho MCS.

The Weather Research and Forecast model (WRF) was utilized to study the effects of warmer lake surface temperatures on the lake effect snow (LES) environments of Lake Erie and Lake Ontario. Composites of recorded LES cases were created for WRF input to represent average LES conditions which revealed three distinct large-scale patterns. WRF runs consisted of altering lake temperatures up to 4.3°C for three future time frames. Lake Erie projections exhibited more sensitivity to alterations as more WRF runs revealed significant (p-value ≤ 0.05) changes to the environment. Lake Erie solely showed any distinctive changes with early and mid-century WRF runs with increased surface CAPE around 80 J/kg and total precipitation around 1.5 mm. Late century alterations for both lakes revealed significant (p-value ≤ 0.05) changes including up to 2.1 g/kg increased specific humidity and a 9K surface-850mb temperature difference indicating both lakes were most sensitive to late century alterations.

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Yes / Solar images, along with other observational data, are very important for solar physicists and space weather researchers aiming to understand the way the Sun works and affects Earth. In this study a 3D modelling technique for visualizing solar magnetic field lines using solar images is presented. Photospheric magnetic field footpoints are detected from magnetogram images and using negative and positive magnetic footpoints, dipole pairs are associated according to their proximity. Then, 3D field line models are built using the calculated dipole coordinates, and mapped to detected pairs after coordinate transformations. Final 3D models are compared to extreme ultraviolet images and existing models and the results of visual comparisons are presented.

Research has shown the color used to represent threat information can influence perceived risk and how individuals respond to watches and warnings. However, there is no standardized color scheme for hazardous weather products across the weather enterprise. This study’s objective was to determine if color inconsistencies have an effect on a product’s intended risk perception utilizing two public surveys. Results suggest color inconsistencies when representing hazardous weather products have a detrimental effect on that product’s intended message. The first survey found people use color to help determine risk and rely on whether a filled or outlined polygon is displayed. The second survey found the term “warning” is perceived to have more risk than the term “watch” for all hazardous weather types tested. The results from both surveys suggest a national, uniform color scale based on risk should be implemented across all weather enterprise agencies.

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No description available.