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Steven Ackerman Cooperative Institute for Meteorological Satellite Studies University of Wisconsin, Madison |
Mike Baldwin National Severe Storms Laboratory |
Tom Baltzer Unidata |
Jack Kain National Severe Storms Laboratory |
L. Ruby Leung Pacific Northwest National Laboratory |
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Jordan Powers National Center for Atmospheric Research |
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Anne Wilson Unidata |
Unidata Users' Workshop home page
Mike Baldwin - The Betts-Miller-Janjic Convective Parameterization
The Betts-Miller-Janjic parameterization has been used in the National Centers for Environmental Prediction NAM (Eta) Model since it first became operational in the early 1990's. This convective scheme introduces characteristic profiles of temperature and moisture in model forecast soundings. These specified profiles can provide misleading representations of various vertical structures and can strongly affect model predictions of parameters that are used to forecast deep convection, such as convective available potential energy and convective inhibition. In this talk, the specific procedures and tendencies of this parameterization will be discussed, and guidelines for interpreting forecast soundings will be presented.
Bio:
Mike Baldwin currently works for the Cooperative Institute for Mesoscale Meteorological Studies at the University of Oklahoma. However, he has recently accepted a faculty position at Purdue University and has just moved to West Lafayette, IN and will begin working at Purdue this fall. Mike completed his PhD from the University of Oklahoma in 2003. After obtaining his Master's from OU in 1991, Mike spent several years working on Eta Model development at the Environmental Modeling Center at NCEP in Camp Springs, MD. His research and teaching interests center around forecast verification, numerical weather prediction, data mining, and data assimilation.
Mark Chandler - EdGCM: Global Climate Modeling Research in Educational Environments
EdGCM, or the Educational Global Climate Model, is a suite of software applications that allows researchers, educators and students to run the same, fully functional 3D global climate model (GCM) on desktop computers. Through the use of EdGCM, students learn to formulate climate experiments, run computer simulations, post-process raw data, analyze output using scientific visualization utilities, and report on their results in the manner of a working scientist.
Bio:
Mark Chandler is a research scientist at Columbia University and the NASA Goddard Institute for Space Studies. His interests focus on the use of global climate models to examine the broad range of Earth's past and future climates, from the current and previous global warmings to ancient ice ages. In addition, a key objective of his work is to improve simulations of paleoclimate in order to increase the reliability of model predictions of future climate change. His other major focus is on improving the usability of, and accessibility to, 3-D computer climate models beyond the typical research institutional setting. Chandler is the founder and director of the Educational Global Climate Modeling (EdGCM) Cooperative, which develops, distributes, and supports a fully functional version of a NASA Global Climate Model for use in pre-college and university-level science courses.
Rich Clark - Science is as Science does: Bringing LEAD capabilities to undergraduate geoscience education
Undergraduates are rarely afforded the opportunity to work with numerical prediction systems beyond analyzing and interpreting the plethora of products they produce. And for years this may have been sufficient. But what if new emergent IT environments presented the undergraduate with a portal to interactive capabilities for mining, accessing, and visualizing observational and assimilated data and model output; discovering relationships across different atmospheric realms and between seemingly disparate physical properties through smart ontologies; or employing intelligent phenomenon extraction algorithms to steer high resolution WRF runs along user-selected regions of interest? Would learning be more authentic if undergraduates working in collaborative teams at different institutions could change model attributes, create workflows, and run WRF on their local servers or across a distributed network to produce multimember ensembles? Can interactive learning modules be linked to user-designed activities to facilitate guided inquiry, better comprehension, and new concepts of testing student learning? Can this new environment spawn a sea-change in the paradigm for undergraduate education in the atmospheric and related sciences? These are but a few of the challenges being undertaken by a multi-institutional team of computer science and meteorology researchers, developers, and educators through the NSF ITR Collaborative project known as Linked Environments for Atmospheric Discovery (LEAD).
This workshop session is designed to first expose participants to the LEAD education initiatives, with emphasis on undergraduate learning environments, and to describe some of the planned key education targets for the project. Following this preview, workshop participants will engage in hands-on, computer-based activities using resources and smart tools developed or sequestered by LEAD researchers. Entering the LEAD portal, participants will be able to query real-time and archival data sets (including model output); access online data repositories and resource catalogs; visualize using Unidata’s Integrated Data Viewer (IDV); employ the LEAD ontology to query, acquire, analyze, mine information, and discover relationships and interdependencies; modify a phenomenon extraction algorithm; instantiate a workflow, include data assimilation, and create a WRF run; collaborate within the LEAD portal; and save work to MyLEAD.
The objectives underpinning the hands-on session are congruent with NSF goals for Geoscience Education and CyberInfrastructure (NSF, April 2004). Participants will employ collaboration and communication tools to enhance researcher-to-educator-to-student interaction. The use of LEAD technology will help stimulate informal and ubiquitous learning environments across the geosciences and among institutions and individuals. This workshop session will elucidate ways to repurpose data stored in repositories between the education and research communities. LEAD tools can be used to engage students in authentic learning – science is as science does – to solve real-world problems by automating the collection and analysis of research-quality data and metadata. LEAD learning modules can provide a common base for guided inquiry while testing individual student comprehension, and can be modified to explore new models of student understanding.
Bio:
Richard D. Clark is the Chair of the Department of Earth Sciences and Professor of Meteorology at Millersville University of Pennsylvania. His research interests are boundary layers and turbulence, air chemistry, and science education. He has a Ph.D. in atmospheric science from the University of Wyoming and is a member of the American Meteorological Society and the American Geophysical Union.
Kelvin Droegemeier - Transforming the Sensing and Numerical Prediction of High Impact Local Weather Through Dynamic Adaptation: People and Technologies Interacting with the Atmosphere
Those who have experienced the devastation of a tornado, the raging waters of a flash flood, or the paralyzing impacts of lake-effect snows understand that mesoscale weather develops rapidly, often with considerable uncertainty with regard to location. Such weather is also locally intense and frequently influenced by processes on both larger and smaller scales. Ironically, few of the technologies used to observe the atmosphere, predict its evolution, and compute, transmit, or store information about it operate in a manner that accommodates the dynamic behavior of mesoscale weather. Radars do not adaptively scan specific regions of thunderstorms; numerical models are run largely on fixed time schedules in fixed configurations; and cyberinfrastructure does not allow meteorological tools to run on-demand, change configurations in response to the weather, or provide the fault tolerance needed for rapid reconfiguration. As a result, today’s weather technology is highly constrained and far from optimal when applied to any particular situation.
This presentation describes a major paradigm shift now underway in the field of meteorology -- away from today's environment in which remote sensing systems, atmospheric prediction models, and hazardous weather detection systems operate in fixed configurations, and on fixed schedules largely independent of weather -- to one in which they can change their configuration dynamically in response to the evolving weather. A major driver of this change is a project known as Linked Environments for Atmospheric Discovery (LEAD) -- a 5-year NSF Large Information Technology Research (ITR) grant that is developing cyberinfrastructure to allow scientists, students, tools and sensors to interact with weather. In addition to describing the research and technology development being performed to establish this capability, I discuss the associated economic and societal implications of dynamically adaptive weather sensing, analysis and prediction systems.
Bio:
Kelvin K. Droegemeier earned a B.S. with Special Distinction in Meteorology in 1980 from the University of Oklahoma, and M.S. and Ph.D. degrees in atmospheric science in 1982 and 1985, respectively, from the University of Illinois at Urbana-Champaign. He joined the University of Oklahoma in September, 1985 and in 1989 co-founded the NSF Science and Technology Center (STC) for Analysis and Prediction of Storms (CAPS) and served as its director from 1994 until 2006. He now is director emeritus. In 2003, Dr. Droegemeier co-founded the NSF Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) and serves as its deputy director. He also directs the Sasaki Institute, which is a non-profit organization at the University of Oklahoma that fosters the development and application of knowledge, policy, and advanced technology for the mutual benefit of the government, academic and private sectors. In 2004, Dr. Droegemeier was appointed by President George W. Bush to a 6-year term on the National Science Board.
Dr. Droegemeier's research interests lie in thunderstorm dynamics and predictability, variational data assimilation, mesoscale dynamics, computational fluid dynamics, massively parallel computing, and aviation weather. Elected to the UCAR Board of Trustees in 2002 and as its Vice Chairman in 2003, he became Chairman of the Board in 2004. Dr. Droegemeier has authored and co-authored nearly 60 refereed journal articles and over 200 conference publications, and has graduated 27 students and served on the committees of numerous others. He is a Fellow of the American Meteorological Society and in 2004 was elected a Councilor. Dr. Droegemeier also serves on the Board of Directors of the Norman Chamber of Commerce and has been a consultant to the National Transportation Safety Board and American Airlines.Rob Fovell - Using Numerical Models to Illustrate Basic and Advanced Physical and Thermodynamical Concepts
I will demonstrate how I use relatively simple numerical models to illustrate basic and advanced physical and thermodynamical concepts in my classes. These include using momentum and heat sources to generate gravity waves (stratospheric waves, obstacle effect waves, low and high frequency tropospheric waves, etc.), creating sea- and land-breezes, convective rolls, etc. These are made with a simple 2D model that the students make themselves, but I would provide the code and let them change numbers and see things for themselves.
Bio:
Prof. Robert Fovell is a faculty member in the Department of Atmospheric and Oceanic Sciences at UCLA. He received his PhD at the University of Illinois and joined UCAL following a postdoctoral appointment at the University of Washington. His research primarily focuses on the initiation, behavior and structure of organized convective storms, and teaches classes in atmospheric dynamics and thermodynamics, synoptic meteorology, numerical methods and modeling, and statistical methods. He received the UCLA Distinguished Teaching Award in 2005.
Bill Gallus
- A virtual tornadic storm enabling students to construct knowledge about
storm dynamics through data collection and analysis
Both the NRC and NSF have recommended that all students learn science by direct
experience with scientific methods and processes of inquiry. In meteorology,
forecasting activities using traditional weather maps are often used as a hands-on
educational tool for non-majors. Taking into account that most students
are inherently fascinated by severe weather, and desiring to go beyond traditional
forecasting activities, a virtual reality tornadic thunderstorm has been developed
which effectively makes students be researchers out in the field on a severe
weather day. The activity runs on both windows and linux platforms and
includes a graphics window which shows the "virtual world" and its
visually-realistic tornadic thunderstorm, and a GUI window where students plot
data that they collect in the virtual world by clicking their mouse. Because
of the inadequate realism in numerical simulations of tornadic storms several
years ago when the activity was first developed, the activity was created from
scratch using photographs and videos. The data representing weather parameters
in the storm was based loosely on a few VORTEX studies. An artist was heavily
involved in the project in the effort to achieve visual and audio realism. The
activity can supplement teaching about favorable conditions for severe storms
where that data is supplied by a Unidata feed and analyzed using nsharp and gempak
or garp. It is believed that similar virtual reality applications could
be developed for larger scale phenomena directly using Unidata data.
Bio:
William Gallus is a professor of meteorology at Iowa State University. Since arriving at Iowa State in 1995, he has worked on funded research projects focusing on numerical weather prediction, warm season rainfall forecasting, severe local storms, and geoscience pedagogy. He teaches courses in synoptic and mesoscale meteorology, and has been the recipient of the College of Liberal Arts and Sciences Master Teacher Award and the Iowa State Foundation Award for Outstanding Achievement in Teaching. In addition to his research and teaching activities, he currently serves as the professor-in-charge of ISU's meteorology program, and as an associate editor for Monthly Weather Review and Weather and Forecasting.
John Horel- Empirical
Models and Data Assimilation
Most undergraduate curricula are not designed to cover data assimilation concepts
in much depth. Is it possible to introduce some of the core concepts to students
as part of existing courses? The lecture and accompanying lab are intended to
highlight ways to improve students' understanding of statistical methods that
are the foundation for data assimilation systems. Topics that will be addressed
include: defining the unknown "true" state of the atmosphere and observational
uncertainty, assessing analysis and forecast error, and examining the best linear
unbiased estimates of the current state of the atmosphere. Concepts progress
from examining the error growth of persistence and perfect model forecasts to
applications of Kalman filter methods. Short practical examples using Matlab
interactively will be presented and demonstrated in the lab.
Bio:
Dr. John Horel's research is centered on the observation and analysis of weather and climate processes in mountainous regions. He received his Bachelor of Science in Meteorology from San Jose State University in 1977, and his Ph.D. in Atmospheric Sciences from the University of Washington in 1982. Dr. Horel helped establish the NOAA Cooperative Institute for Regional Prediction in 1996 and currently serves as the Director of the Institute, which conducts a broad program of research aimed at improving weather and climate prediction in regions of complex terrain. The development and implementation of weather support for the 2002 Winter Olympics and Paralympics was a critical component of Institute activities from 1996-2002.
Dr. Horel's current research activities include further development of MesoWest (see http://www.met.utah.edu), which provides access to surface weather observations for operational, research, and educational applications. MesoWest has evolved since 1996 from providing weather information at a few dozen weather stations in northern Utah using a handful of graphical displays to the current availability of weather conditions at thousands of stations around the nation using a state-of-the-art database and dozens of tabular and graphical displays. Specialized application software has been developed to support the fire weather community (see http://www.met.utah.edu/roman). The MesoWest observations also provide a foundation from which to conduct research to improve data assimilation techniques over complex terrain.
Jack Kain - The Kain-Fritsch Convective Parameterization
Convective parameterization continues to be an integral component of operational numerical weather prediction systems. Convective schemes have a substantial impact on numerical forecasts of many types of weather systems, modulating convective precipitation fields and sounding structures, and sometimes having a strong influence on broader scale evolution of storms. Yet, the internal workings of convective parameterization schemes (CPSs) remain poorly understood by most users of numerical guidance. In this talk, the concept of a mass-flux approach to convective parameterization is discussed, using the Kain-Fritsch CPS as an example. In particular, the basic constraints on deep convective initiation, rainfall, and environmental modification associated with this scheme are presented. In addition, the scheme’s shallow convective component is described, focusing on its impact on environmental sounding structure. In an accompanying lab, participants will learn to use a stand-alone 1-D version of this CPS and investigate many of its sensitivities to environmental variables and to internal parameters.
Bio:
Dr. Kain has a broad range of experience in model development, numerical weather prediction, and collaboration with operational forecasters. He is most widely known for the Kain-Fritsch convective scheme, a parameterization he developed with Mike Fritsch in the late 80s and early 90s. In addition to the more traditional applications, he has used this parameterization as a catalyst for collaboration with the operational forecasting community, working with frontline forecasters from the NCEP/Storm Prediction Center to refine the parameterization and tailor it to the specific needs of NWS severe weather forecasters. As part of this effort, he worked with colleagues at NSSL and model developers at NCEP/EMC to establish a semi-operational, Eta-based local modeling system at NSSL in the late 90s and early 00s. He continues to work at the interface of research and operations at NSSL and in the newly formed NOAA/Hazardous Weather Testbed in Norman, OK.
Gary Lackmann - Models as Teaching Tools: Simple Experiments, Tropical Cyclones, and the Rossby Radius of Deformation
The horizontal length scale for geostrophic adjustment in the atmosphere is the Rossby radius of deformation; the relative size of unbalanced atmospheric disturbances to this distance determines the extent of mass or motion adjustment and the strength and structure of disturbances after the adjustment process has taken place. Although the mathematical basis underlying this development can be complex, the physical interpretation is important and relatively straightforward, meaning that idealized model experiments can be profitably employed to assist students in grasping this concept.
Here, the Weather Research and Forecasting (WRF) model is used to test the adjustment process for an unbalanced initial disturbance placed within an idealized, quiescent tropical atmosphere. Disturbances of varying size are included in the model initial condition, and the theoretical Rossby radius is determined. Students are asked to predict the outcome of the various experiments- which initial conditions would be expected to spin up a full-blown hurricane versus a weak, transient disturbance that fails to amplify? For this setup, does the theory agree with the model experiments? If not, is it a problem with the theory, with the model, or with our application of the theory?
The results confirm that for initial disturbances that are of a size comparable to the Rossby radius, a hurricane spins up, whereas small (relative to the Rossby radius) disturbances with the same amplitude yield no developing tropical cyclone. The results are not simple, however, as the opportunity arises to examine sensitivity to the location (latitude) of the initial disturbance, environmental static stability (and humidity), and initial disturbance amplitude.
Bio:
Gary Lackmann grew up in Seattle, Washington and earned B.S. and M.S. degrees in atmospheric science from the University of Washington in 1986 and 1989, respectively. Upon graduation, Gary worked for the Naval Postgraduate School in Monterey, CA studying arctic meteorology and participating in arctic field observation programs. In order to pursue his desire to teach meteorology at the college/university level, Gary headed east to obtain his doctoral degree from the University at Albany, State University of New York, in 1995. After a 13-month postdoc at McGill University in Montreal, Gary began his teaching career at the State University of New York, College at Brockport, in 1996. Opportunities to work with graduate students and for closer collaboration with the National Weather Service led Gary to head to Raleigh to join the faculty of the Department of Marine, Earth, and Atmospheric Sciences at NC State University in the fall of 1999. Gary is a tenured associate professor, and teaches courses spanning the spectrum from freshman to graduate-level, with emphasis on synoptic-dynamic meteorology, weather forecasting, and numerical weather prediction.
L. Ruby Leung - Regional Climate Modeling
Regional Climate Models (RCMs) have been developed primarily as a dynamical downscaling tool to provide regional climate information regarding climate variability and change. They have been used most frequently to generate regional climate change scenarios for assessing climate change impacts. More recently, RCMs have also been used to address a wide range of research topics including understanding processes, such as aerosol-cloud and land-atmosphere interactions, that influence the regional hydrological cycle, and extreme climate events. This talk will provide an overview of regional climate modeling research, including recent development using the Weather Research and Forecasting (WRF) model, and discuss examples of how RCMs have been used. This session will include a lab where we will explore ways to analyze some RCM simulation results.
Bio:
Ruby Leung is a Laboratory Fellow at the Pacific Northwest National Laboratory and an Affiliate Scientist at the National Center for Atmospheric Research. She received her MS and Ph.D. in Atmospheric Science from the Texas A&M University in 1988 and 1991. Her primary research focus is in regional climate modeling. In the early 1990s, very few studies had examined climate change and its potential impacts on natural resources. Global climate model, the tool of choice for providing climate change scenarios for assessment of climate change effects, was deem to lack sufficient spatial specificity for impact assessment because of the coarse spatial resolution. To bridge the gap between what GCM can provide and what are needed to investigate climate change effects on water resources, agriculture, and ecosystems, Dr. Leung developed a regional climate model with special features that account for the subgrid scale effects of topography, lake, and vegetation. Her model enables the coupling of climate and hydrologic processes in regions with complex orography. Dr. Leung has led several multi-disciplinary projects to examine the impacts of climate variability and change and the effects of aerosols on the regional hydrological cycle. Her studies are among the first to show the large potential impacts of greenhouse warming on mountain snowpack and river runoff. In 2001, Dr. Leung organized the Workshop on “Regional Climate Research: Needs and Opportunities” co-sponsored by the National Science Foundation and Department of Energy to examine various approaches to modeling regional climate. More recently, she is working with collaborators at NCAR to develop regional climate modeling capability with the Weather Research and Forecasting (WRF) model. She organized the Workshop on “Research Needs and Directions of Regional Climate Modeling Using WRF and CCSM” sponsored by NCAR in 2005.
David Maidment - CUAHSI Hydrologic Information Systems
Hydrology and atmospheric science are intimately linked together as is made clear when severe storms produce flooded rivers, and anomalous patterns of atmospheric circulation produce droughts. The formation of the Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) was initiated by NSF in 2000 to provide infrastructure and services for the support of hydrologic science in the US universities. Today, 109 universities are members of CUAHSI. The CUAHSI Hydrologic Information System project is aimed at providing better access to hydrologic and atmospheric science data by using web services, by which data can be directly ingested into applications such as Excel, ArcGIS or Matlab directly from remote data archives, without manually using web pages. An HIS workbook will be demonstrated which can be used to guide students to acquire data using CUAHSI web services, such as streamflow from USGS gauging stations, gridded climate data from the NCAR DayMet archive, forecast precipitation from the 12-km North American Model, remote sensing products from MODIS, or land surface – atmospheric flux data from the Ameriflux network.
Bio:
Dr. David Maidment is an Engineering Foundation Professor of Civil Engineering and the Director of the Center for Research in Water Resources, University of Texas, Austin, Texas. Dr. Maidment teaches water resources engineering, and conducts research on the application of geographic information systems in water resources. He has been on the faculty at the University of Texas at Austin since 1981.
Dr. Maidment received his Bachelor of Agricultural Engineering with First-Class Honors in 1971 from the University of Canterbury in Christchurch, New Zealand. He received his Master of Science degree in 1974 and his Doctor of Philosophy in 1976 from the Department of Civil Engineering at the University of Illinois at Urbana-Champaign. In 2003 Dr. Maidment received the Lifetime Achievement Award from the Environmental Systems Research Institute for contributions to GIS in Water Resources, presented at the ESRI International User Conference in San Diego, CA.
Michael C. Morgan - Spectral Modeling Techniques
This lab will be a demonstration of spectral modeling techniques using a two-dimensional, nondivergent, global spectral baratropic model. Participants will receive scripts and software to run the baratropic model initialized with realtime GFS global analysis data from Unidata's IDD.
Bio:
Dr. Michael C. Morgan has been at the University of Wisconsin - Madison since the Fall of 1995. Prior to that he did his undergraduate and graduate education at MIT, followed by a one year post-doc at Texas A&M. His research interests are in the analysis, diagnosis, and prediction of mid-latitude and tropical weather systems. Dr. Morgan's current research concerns the predictability of mid-latitude weather systems, tropical cyclogenesis, and tropical cyclone motion. He has taught classes in atmospheric dynamics, synoptic meteorology, atmospheric data assimilation, and numerical weather prediction.
Louisa Nance - Downslope Windstorm Lab
The objectives of this lab are to: 1) reinforce the mountain wave concepts presented in a companion lecture that discussed linear mountain wave characteristics and the atmospheric conditions that lead to downslope windstorms, and 2) develop insight into the sensitivities of the mountain wave response to changes in the characteristics of the large-scale flow. The exercises that make up this lab employ a nonlinear, two-dimensional model to illustrate how the mountain wave structure varies in relation to changes in the large-scale flow. The lab is composed of three components: 1) an html-based idealized mountain wave exercise that presents the students with a number of idealized flow conditions, presents the students with questions about what type of mountain wave response they would expect for each flow, and then provides an illustration and discussion of the response, 2) a forecast exercise based on an actual downslope windstorm event, and 4) an exercise where the students are given basic instructions for modifying a sounding from the actual downslope windstorm event and use this modified sounding as input to the two-dimensional, nonlinear model to determine how the modifications impact the mountain wave response. The second and third components of the lab are broken utilize a combination of hands-on computer exercises and group discussions.
Bio:
Louisa Bogar Nance received her Bachelor’s degree in Atmospheric Sciences from Oregon State University in 1988 and her Master’s and PhD in Atmospheric Sciences from University of Washington in 1992 and 1995, respectively. Her graduate studies employed two-dimensional numerical models to investigate the accuracy of sound-proof systems and the nonstationarity of trapped mountain lee waves. Following her graduate studies, Dr. Nance was funded through the COMET post-doctoral fellowship program to investigate using a two-dimensional nonlinear numerical model as a forecast tool for downslope windstorms. The Downslope Windstorm Lab presented at the 2006 Unidata Users' Workshop is an extension of this work. Following her COMET post-doctorial fellowship, Dr. Nance was a National Research Council Research Associate (1998-99) and a Research Associate with the Cooperative Institute for Research in Environmental Studies (CIRES – 1999-2003). Since July 2003, Dr. Nance has been a Project Scientist with the WRF Developmental Testbed Center (DTC) at the National Center for Atmospheric Research (NCAR), whose mission is to accelerate the testing and evaluation of new Numerical Weather Predication models and techniques for research applications and operational implementation.
In this session, Leigh Orf will demonstrate how Vis5d, a scientific data visualization tool designed for meteorologists, can be used to gain insight into numerically simulated meteorological phenomena. The basic features of Vis5d will be explored using datasets including three-dimensionally model output of supercell thunderstorms and microbursts. Following an instructional session, participants will use the software in a lab session which will explore isosurfaces, vectors, streamlines and trajectories. Datsets explored in this session will be made freely available to participants for future use.
Bio:
Leigh Orf is an Assistant Professor of Meteorology at Central Michigan University. He received his Ph.D. from the University of Wisconsin in 1997. His interests include the numerical modeling of mesoscale and microscale phenomena and data visualization.His current research focus includes the processes leading to tornadogensis in supercell thunderstorms.
Jordan Powers - Use of the Weather Research and Forecasting (WRF) Model in Polar Modeling
Historically, applications of mesoscale numerical weather prediction (NWP) models in the polar regions have lagged those in the middle latitudes and tropics. The emergence of the next-generation Weather Research and Forecasting (WRF) Model, however, may provide a vehicle for the acceleration of polar research and polar NWP capability development. This talk will provide an introduction to the most widely-used mesoscale model in the world today, WRF, and will survey its growing polar applications. The discussion will offer a look at a range of issues and results in the area of polar mesoscale modeling.
Bio:
Dr. Powers is a Project Scientist with the Mesoscale and Microscale Meteorology (MMM) Division of NCAR. He heads the Real-Time Systems Subgroup of the Mesoscale Prediction Section, a group responsible for the development of real-time applications of the mesoscale models supported to the community by MMM (historically the MM5 and WRF). With respect to polar modeling, he leads the Antarctic Mesoscale Prediction System (AMPS) effort. AMPS is an implementation of the MM5 and WRF models that provides numerical weather prediction for the activities of the United States Antarctic Program as well as a number of foreign nations in Antarctica. The effort also seeks to advance mesoscale modeling capabilities for polar regions through the investigation of model performance in, and the development of modifications for, the high latitudes.John Snow - STELLA Models in the Classroom: From static images to dynamic, interactive models
Students' introduction to concepts such as positive and negative feedback often comes via static textbook diagrams of natural systems. Such diagrams fail to convey the dynamic nature of the interacting atmosphere, ocean, and land surface. The STELLA modeling software offers the opportunity for instructors and students to move from such diagrams to simple, yet powerful numerical models of such systems. The resulting interactive numerical models can be powerful tool for the students to learn and apply many important fundamental science and mathematical concepts. They also learn basic modeling principles as foundation for their ultimately working with more complex, less transparent numerical models.
Instructors desiring to add numerical modeling tools to their classroom tool kits face several challenges. Developing and using such models requires four types of activity to be carried on in parallel by the instructor: understanding the science to be modeled in a quantitative way; understanding the systems concepts to be used; developing a pedagogical plan on how a model will support students learning of specified objectives; and using the software to meld these three considerations into a working classroom tool. In this presentation, I will offer some suggestions on how to overcome these challenges to using modeling in the classroom. I will demonstrate a few Earth-System-related STELLA models updated to Version 9.0 to illustrate both the power of interactive modeling and how these challenges have been addressed in specific cases. (For those not familiar with the STELLA software, it is a moderately friendly numerical modeling system with a number of built-in documentation/teaching/presentation tools. It runs on both Windows and Apple/Mac platforms. See http://www.hps-inc.com/ for software details.)
Bio:
Dr. John Snow received his B.S.E.E.from Rose Polytechnic Institute in 1968, his M.S.E.E. from Rose Polytechnic Institute 1969, and his Ph.D. from Purdue University 1977. He currently serves as Dean of the College of Atmospheric and Geographic Sciences at the University of Oklahoma. Dr. Snow's expertise and research interests include dynamics of geophysical columnar vortices ranging in scale from small dust devils to fire whirls, with a primary focus on tornadoes; meteorological measurements and instrumentation, especially surface-based instruments for weather observations; post-event analyses of tornadoes and tornado-producing thunderstorms (debris transport); experimental fluid mechanics as applied to atmospheric problems; earth science education at all levels, K-12, undergraduate and graduate; technology transfer and economic development.
Donna Tucker - Thunderstorm Initiation in the Rocky Mountains: A Case Study
The locations where thunderstorms initiate in the Rocky Mountains are strongly influenced by the interaction of the wind field with the underlying orography. Thunderstorms are more likely to occur when the wind direction is along the ridgeline than when the wind direction is across the ridgeline. Thunderstorm generation is also preferred when the wind speed is slow. Therefore, for a given wind direction, some places are more preferred for thunderstorm initiation than others. Likewise, a particular ridge will initiate thunderstorms more often when the wind direction is along the long axis of the ridge.
Thunderstorm initiation on a particular day will illustrate how these principles work out for an actual event. Wind direction and speed, horizontal and vertical moisture distribution and atmospheric static stability are determined from the initial analysis of the Rapid Update Cycle (RUC) model. We will look at the usefulness and limitations of the model output for determining the initiation points of thunderstorms. Thunderstorm initiation locations are identified from lightning strikes.
Bio:
Donna Tucker received her B.S. from Cornell University and her M.S. and Ph.D. from Colorado State University. These degrees are all in Atmospheric Sciences. She was a research meteorologist at the U.S. Army Atmospheric Sciences Laboratory at White Sands Missile Range and taught meteorology part time at New Mexico State University. She was an Assistant Professor in the Department of Atmospheric Sciences at Creighton University. She is currently an Associate Professor in the Department of Geography at the University of Kansas Her research interests include numerical modeling, mesoscale precipitation systems and the effect of mountains on precipitation . She has published papers in Monthly Weather Review, Weather and Forecasting, The Journal of Climate, The Bulletin of the American Meteorological Society, Meteorology and Atmospheric Physics and a number of conference proceedings. She is active in a number of professional societies including The American Meteorological Society, The American Geophysical Union, The National Weather Association, The Association of American Geographers and Sigma Xi.
Tom Whittaker and Steve Ackerman - Using Interactive Applets in Your Teaching
We continue to create a series of web-based applets for integration into curriculum in order to provide interactive ways to introduce and/or solidify concepts in the Atmospheric and related Sciences. In this workshop, we will introduce a few of these applets, without a course context, to demonstrate the different phenomenon, and then work with the participants to create potential classroom activities using one or more of these applets in their own course environments.
Bios:
Tom Whittaker received his BS and MS from the University of
Wisconsin-Madison
in Meteorology, with a minor in CompSci. After working 3 years for the
Weather Bureau, he began a career at the University of Wisconsin in
Meteorology and later in the Space Science and Engineering Center. He
created much of the conventional data analysis tools in the early
McIDAS and has since worked more in education, creating small,
interactive teaching tools (applets) as well as the core software for
the NWS teletraining activities (VISITview).
Steve Ackerman is a faculty at University of Wisconsin-Madison in the department of Atmospheric and Oceanic Sciences. He is also director of the Cooperative Institute for Meteorological Satellite Studies, a collaboration between UW-Madison, NOAA and NASA. He has received several teaching awards and has written an introductory textbook on weather with John Knox. He and Tom Whittaker have collaborated on developing applets for teaching for nearly 10 years.
Anne Wilson and Tom Baltzer - LEAD Project
Workshop participants will be given the opportunity to work with technology being produced by the LEAD project. The primary LEAD ideal that will be demonstrated is that of "democratization". That is, the idea that researchers and students with an interest in mesoscale modeling can gain access to "big iron" (Teragrid) computing via LEAD developed software. In these labs the workshop participants will be given a chance to submit mesoscale WRF model runs to the Teragrid via two different capabilities being developed in the LEAD project. The first will be a "thin client" model where the participants will work with the LEAD portal to set up, submit and monitor their runs, and then view the results afterward. The second will be a "thick client" model where the participants will download a desktop application that provides them the capabilities to set up, submit and monitor their runs and then view their results afterward. Participants will be asked to evaluate the two models and provide feedback as well as being offered the opportunity to join in the Beta Test community for the LEAD project going forward.
Bios:
Tom Baltzer is a software engineer who has been working at Unidata and on the LEAD project for nearly 2 and 1/2 years. Prior to working at Unidata, he worked extensively in the contract engineering market place developing scientific and visualization software for NASA and DoD interests.
Dr. Anne Wilson is a Software Engineer who has been working in the area of meteorological software tools and data for ten years. At Unidata she has been involved in the LEAD project mostly since its inception several years ago. In addition to working on the LEAD project, she is currently developing the new THREDDS Data Repository (TDR) component of the THREDDS Data Server (TDS). In the past she has worked in the area of data relay via Unidata's LDM package and also other methods. Before joining Unidata she worked at the Forecast Systems Lab where she built extensions to the NWS' AWIPS information processing, display, and telecommunications system.
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