1-10 of 189 results
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Graphics Tools for Meteorology Research and Education
PI Mark Sinclair
A software package called MADS (Meteorological Analysis and Diagnostic Software) is being developed to provide gridded data (both archived and real-time) and graphical software to produce maps, cross-sections, vertical profiles, time series graphs and statistical (climatological) displays of a large number of basic and derived quantities.
Unlike similar proprietary software products, MADS is intuitive and very easy to use. Students produce publication-quality color maps and graphs with only a few minutes of instruction and typically remark on how easy the software is to use. Meteorology faculty have used MADS plots for their research, and MADS assignments have been implemented into meteorology classes. MADS is ideal for institutions with limited computing support and is maintained by various automated scripts that download or update archived datasets. This system is continually being enhanced to accommodate more and more features expected in a modern meteorological graphics display package.This project has the potential to enhance meteorology education. Weather analysis and forecasting require both critical thinking and three-dimensional spatial analysis skills to apply complex theory to the diagnosis of atmospheric processes from multiple environmental variables in a variety of graphical formats. Outside websites used by meteorology students to visualize atmospheric fields typically offer a limited menu of “standard” meteorological displays. Upper-division theory classes are usually taught from a purely mathematical standpoint, with limited application to real-time atmospheric phenomena. MADS allows students to visualize contributions of the individual terms in dynamical meteorology or thermodynamics equations and overlay them to see their relative impact in the current meteorological context.Categories: Faculty-Staff
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Ice Cloud Parameterizations and Aircraft Icing
PI Dorothea Ivanova
Ice and mixed phase clouds have an important impact on aviation, but they are often poorly represented in the models.
This proposal seeks to help improve our understanding of aircraft icing occurrence through better parameterizations of the ice microphysical cloud properties. The goal of this proposal is to create a new Global Climate Model (GCM) parameterization for Arctic ice and mixed-phase clouds, and explore possible relationship between different type size distributions (SDs), and airplane icing. The study will utilize data for different ice crystal size spectra in arctic cold clouds, and data for the corresponding airplane icing occurrences. The PI has already developed and published parameterizations for mid-latitude and tropical ice clouds (Ivanova 2001, Ivanova 2004, Mitchell and Ivanova 2006, Mitchell et al. 2008). The tropical and mid-latitude schemes predict different behavior of the SDs for the same ice water content (IWC) and temperatures. As temperature decreases beyond -35C, the concentration of the small crystals is enhanced with the tropical scheme, but the opposite occurs with the mid-latitude scheme. This finding indicates that the microphysics properties of tropical and mid-latitude cold clouds are considerably different for the same IWC. It may also point to the different mechanisms by which convective and non-convective cold clouds are generated. Clearly, there is a need for Arctic and polar ice cloud parameterization, and for a study to explore the possibility of a relationship between the environmental conditions (temperature, IWC, supercooled liquid water content), different predicted size spectra, and aircraft icing. Cold cloud interactions with aircrafts that fly through them require knowledge of cloud microphysics. Aircrafts must be designed to fly into supercooled clouds, or they must avoid those clouds in order to prevent problems associated with airframe and engine icing. De-icing or anti-icing systems must be engineered to withstand reasonable extremes in terms of ice water content (IWC), supercooled liquid water content (LWC), ice particle size distributions (SDs), and temperature. The aircraft design or certification envelopes (FAR 25, Appendix C; Federal Aviation Administration, 1999) were developed before the advent of modern cloud physics instrumentation. In the case of ice and mixed-phase clouds, data from the new arctic field campaigns suggest that cloud temperature is one of the main parameters governing cloud microstructure, the size distributions, and ice water content affecting aircraft icing. Korolev et al. (2001) showed that the cold cloud size distributions may depend on the value of the ice particle size assumed. Parameterizations of ice particle sizes for mid-latitude and tropical ice clouds (Ivanova et al., 2001, Boudala et al., 2002; Ivanova 2004; Mitchell et al., 2008) appear in recent literature, and were implemented in the U. S. Community Climate model 3 (CCM3) Global Climate Model (GCM), and U.K. MetOffice GCM, but little is done to study high latitude cold clouds size distributions and how they may be related to the aircraft icing.Contact Information
Categories: Faculty-Staff Undergraduate
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Mesoscale Computer Modeling of the North American Monsoon over Arizona
PI Dorothea Ivanova
The Department of Meteorology is involved in research on the North American (Mexican) Monsoon in Arizona and the U.S. Southwest.
The objectives of this project are:- To achieve a better understanding of the evolution of the North American monsoon system and its variations.
- To achieve a better understanding of the response of warm season atmospheric circulation and precipitation patterns to slowly varying boundary conditions (e.g. sea surface temperatures—SSTs, soil moisture), using advanced computer models.
- To run atmospheric mesoscale models (MM5 and WRF) utilizing the parallel-processor supercomputer on the Prescott Campus.
Contact Information
Categories: Faculty-Staff
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Cbud Computing for Meteorology Education
PI Curtis James
Weather analysis and forecasting require both critical thinking and three-dimensional spatial analysis skills to apply complex theory to the diagnosis of atmospheric processes from multiple environmental variables in a variety of formats.
Existing websites used by meteorology students to visualize atmospheric fields are not designed to facilitate synthesis of weather information because they offer a limited menu of “standard” meteorological displays without pedagogical intent or clear reference to theoretical underpinnings. Thus, there exists a significant opportunity to enhance online weather visualization tools in the context of meteorology education. This project seeks to create a virtual online LINUX server using a cloud service provider for 4D weather analysis and visualization in real time. University Corporation for Atmospheric Research's (UCAR's) Unidata will configure the server using the Local Data Manager (LDM), a prototype installation of AWIPS II standalone EDEX server and CAVE client, and a RAMADDA server. Other meteorological tools will be configured for real-time use by National Weather Service meteorologists and the Department of Meteorology. All of these software packages will be accessible from any computer or mobile device using a web browser, and will support the Department's new focus in Emergency Response Meteorology practices and applications.
Contact Information
Categories: Faculty-Staff
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Evaluating Simulation Tools to Study the Impact of Space Shuttle Launch on the National Air Transportation System
PI Ahmed Abdelghany
The objective of this project is to provide a comparative study to evaluate the functionalities of the available airspace simulation tools.
In particular, the objective is to evaluate how these available simulation tools can be used to capture the impact of space shuttle launch on the National Air Transportation System. This impact could be in the form of flight delays, flight cancellations, trajectory amendments, etc.Categories: Faculty-Staff
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Volusia County Transportation Challenge: A Commentary Report on Volusia County's Long Range Transportation Plan
PI Ahmed Abdelghany
The objective of this project is to evaluate the long-term (5-10 years) transportation plan of Volusia county.
The plan includes the list of all transportation construction projects that are proposed by the county. The objective is to study these projects together with their validation study and verify their importance for the county.Categories: Faculty-Staff
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Fusing Satellite and Drone Data with GIS to Create New Analytical Decision Support Tools for Varying Farm Types
PI Kevin Adkins
PI Nickolas Macchiarella
CO-I Ronny Schroeder
CO-I University of Michigan School for Environment and Sustainability (SEAS) and the Department of Ecology and Evolutionary Biology
The synergy between moderate resolution satellite imagery and fine resolution drone imagery, LiDAR data, and meteorological data, along with generally available GIS data, must be identified and optimized. These data will be integrated to produce a variety of products that help identify what tools, inputs, and management strategies most effectively contribute to an increase in the productivity and resilience of an important agricultural system to a major weather or climate related disturbance.
Satellite imagery has been used in agriculture for some time and the increasing implementation of drones into agriculture and agriculture science holds unique promise. However, the synergy between moderate resolution satellite imagery, fine resolution drone imagery, fine resolution LiDAR (Light Detection And Ranging) data, fine-resolution meteorological data, and generally available GIS (Geographic Information Systems) data must be identified and optimized. To be most useful, this fusion of data should help provide estimates in the health and yield of agriculture systems as well as insight into the microclimate and ecosystem variation within a farm site. These data will be integrated to produce a variety of fine-resolution maps that can be analyzed to identify what tools, inputs, and management strategies most effectively contribute to an increase in productivity, agroecological system health, and resiliency or restoration (typically in response to weather or climatic disturbance) of a given farming operation and site. This research will apply these data science methods and tools to varying farm types in Puerto Rico. We expect new insight into how the fusing of a multitude of data can be effectively integrated into an agriculture operation and, subsequently, determine which outputs are most valuable to the varied farm types, practices, and locations. This investigation will also provide critical information on the resistance and resilience of an important agricultural system to major weather or climate-related disturbances and, subsequently, inform management decisions related to climate change adaptation.Categories: Faculty-Staff
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GUMP: General Urban Area Microclimate Predictions Tool
PI Kevin Adkins
CO-I Nickolas Macchiarella
CO-I National Aeronautics and Space Administration NASA
Hyperlocal weather predictions are often necessary in order to determine whether a particular sUAS route will be safe to fly. The General Urban area Microclimate Predictions tool (GUMP) seeks to provide such predictions through the use of machine learning (ML) models and computational fluid dynamics (CFD) simulations. The computed wind flow field is converted into an intuitive risk map for sUAS operators through the use of appropriate thresholds on wind velocities.
Adverse weather conditions, particularly, high winds, can have a highly adverse impact on small unmanned aircraft system (sUAS) operations. These conditions can vary significantly within a small area (particularly, in an urban environment); thus, hyperlocal weather predictions are often necessary in order to determine whether a particular sUAS route will be safe to fly. The General Urban area Microclimate Predictions tool (GUMP) seeks to provide such predictions through the use of machine learning (ML) models and computational fluid dynamics (CFD) simulations. Specifically, ML models are trained to ingest mesoscale forecasts from the National Oceanic and Atmospheric Administration (NOAA) and output refined forecasts for some specific location, typically, a weather station that serves as a source of ground truth data during training. At the same time, CFD simulations over 3D models of structures (e.g., buildings) are utilized to extend the refined forecast to other points within the area of interest surrounding the location. Because it is difficult to perform such simulations in real-time, they are executed offline under a wide range of boundary conditions, generating a broad set of resulting wind flow fields. During deployment, GUMP retrieves the wind flow field that is most consistent with the ML model’s forecast. The wind flow field can be converted into an intuitive risk map for sUAS operators through the use of appropriate thresholds on wind velocities. I addition to NASA, additional partners on this project are Intelligent Automation Inc. and AvMet.Categories: Faculty-Staff
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Novel n x n Bit-Serial Multiplier Architecture Optimized for Field Programmable Gate Arrays (FPGA)
PI Akhan Almagambetov
CO-I David Feinauer
CO-I Holly Ross
Bit-serial multipliers have a variety of applications, from the implementation of neural networks to cryptography. The advantage of a bit-serial multiplier is its relatively small footprint, when implemented on a Field Programmable Gate Array (FPGA) device. Despite their apparent advantages, however, traditional bit-serial multipliers typically require a substantial overhead, in terms of component usage, which directly translates to a large area of the chip being reserved while many of those resources are unused.
This research addresses the possibility of an efficient two's complement bit-serial multiplier (serial-serial multiplier) implementation that would minimize flip-flop and control set usage on an FPGA device, thereby potentially reducing the overall area of the circuit. Since the proposed architecture is modular, it functions as a "generic" definition that can be effortlessly implemented on an FPGA device for any number of bits.
Categories: Faculty-Staff
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Increasing student learning and engagement using a TV series: Leadership in the Final Frontier
PI Anke Arnaud
Educators are continuously concerned with developing innovative and effective teaching methodology to increase student learning and engagement. This study is designed to assess the effectiveness of an innovative instructional methodology, using a TV series to teach and develop leadership understanding, skills and knowledge.
During a semester long class on leadership, students were taught abstract leadership concepts and theories using Episodes from the Star Trek Series. We used inductive reasoning methodology, watching an episode of Star Trek and then developing leadership theory, and deductive reasoning methodology, learning about a leadership theory and then analyzing the theory using an episode of Star Trek, to develop leadership understanding, skills and knowledge. Student journal entries, questionnaires on student engagement and learning, and end of course evaluations were used to assess the effectiveness of the teaching methodology. Results support our expectation that student learning and engagement can be enhanced using the effective application of TV episodes.Categories: Faculty-Staff
1-10 of 189 results