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In winter storms, enhanced radar reflectivity is often associated with heavy snow; however, some higher reflectivities are the result of melting and mixed precipitation. The correlation coefficient (a dual-polarization radar variable) can identify regions of and mixed precipitation, but this information is usually presented separately from reflectivity. Especially under time pressure, even experienced meteorologists can mistake regions of mixed precipitation for heavy snow because of the high cognitive load associated with comparing data in two fields while simultaneously attempting to discount a portion of the high reflectivity values. We developed an image muting method for regional radar maps that visually deemphasizes the high reflectivity values associated with mixed precipitation. These image muted depictions of winter storm precipitation structures are useful for monitoring real-time weather conditions and for analyzing storms.

Mesoscale, wave-like perturbations in horizontal air motions in the troposphere (velocity waves) are associated with vertical velocity, temperature, and pressure perturbations that can initiate or enhance precipitation within clouds. The ability to detect velocity waves from horizontal wind information is an important tool for atmospheric research and weather forecasting. This paper presents a method to routinely detect velocity waves using Doppler radial velocity data from a scanning weather radar. The method utilizes the difference field between consecutive position plan indicator (PPI) scans at a given elevation angle. Using the difference between fields a few minutes apart highlights small-scale perturbations associated with waves because the larger-scale wind field changes more slowly. Image filtering retains larger contiguous velocity bands and discards noise. Wave detection scales are limited by the size of the temporal difference relative to the wave motion and the radar resolution volume size.

Large, abrupt clearing events have been documented in the marine stratocumulus cloud deck over the subtropical Southeast Atlantic Ocean. In these events, clouds are rapidly eroded along a line hundreds–to–thousands of kilometers in length that generally moves westward away from the coast. Because marine stratocumulus clouds exert a strong cooling effect on the planet, any phenomenon that acts to erode large areas of low clouds may be climatically important. Previous satellite-based research suggests that the cloud-eroding boundaries may be caused by westward-propagating atmospheric gravity waves rather than simple advection of the cloud. The behavior of the coastal offshore flow, which is proposed as a fundamental physical mechanism associated with the clearing events, is explored using the Weather Research and Forecasting model. Results are presented from several week-long simulations in the month of May when cloud-eroding boundaries exhibit maximum frequency. Two simulations cover periods containing multiple cloud-eroding boundaries (active periods), and two other simulations cover periods without any cloud-eroding boundaries (null periods). Passive tracers and an analysis of mass flux are used to assess the character of the diurnal west-African coastal circulation. Results indicate that the active periods containing cloud-eroding boundaries regularly experience stronger and deeper nocturnal offshore flow from the continent above the marine boundary layer, compared to the null periods. Additionally, we find that the boundary layer height is higher in the null periods than in the active periods, suggesting that the active periods are associated with areas of thinner clouds that may be more susceptible to cloud erosion.

Geospatial analysis is crucial for addressing many of the world's most pressing challenges. Given this, there is immense value in improving and expanding the visualization techniques used to communicate geospatial data. In this work, we explore this important intersection -- between geospatial analytics and visualization -- by examining a set of recent IEEE VIS Conference papers (a selection from 2017-2019) to assess the inclusion of geospatial data and geospatial analyses within these papers. After removing the papers with no geospatial data, we organize the remaining literature into geospatial data domain categories and provide insight into how these categories relate to VIS Conference paper types. We also contextualize our results by investigating the use of geospatial terms in IEEE Visualization publications over the last 30 years. Our work provides an understanding of the quantity and role of geospatial subject matter in recent IEEE VIS publications and supplies a foundation for future meta-analytical work around geospatial analytics and geovisualization that may shed light on opportunities for innovation., Comment: 5 pages, 4 figures, IEEE VIS Short Paper Proceedings 2020