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RESEARCH EXPERIENCES FOR UNDERGRADUATES (REU)

Department of Atmospheric Sciences

 Research Themes

REALM leverages our Department’s strength in alpine atmospheric science and education, provides students with clear links between science and societally-relevant research, and provides opportunities for students to experience mountain environments that they may not have previously had. Dr. Whiteman, who will be the keynote speaker at the opening REALM retreat, is a recipient of the 2012 Research and Leadership award from the AMS Committee on Mountain Meteorology. Dr. Jim Steenburgh, Mentor, was similarly recognized by that AMS committee this year. His popular book, “Secrets of the Greatest Snow on Earth” explains complex science in layman's terms as it explores mountain weather, avalanches and snow safety, historical accounts of weather events and snow conditions, and the basics of climate and weather forecasting.

Research Themes: Here are concise themes focused on work underway by the REALM research mentors.

Measurement, Analysis, and Prediction of Orographic Precipitation

Mountainous climate regimes are seeing a general shift towards precipitation types found in warmer climates such as wet snow and rain. Adequate long-term measurement capabilities do not currently exist to observe these transitions. Several faculty members within the Department of Atmospheric Sciences are working to improve measurement capabilities of alpine precipitation. For example, Dr. Garrett has developed new technology with the invention and commercialization of the Muti-Angle Snowflake Camera (Garrett et al. 2012) that will be utilized with this REU to study Thundersnow. Dr. Cooper has created new techniques to combine satellite and ground-based remote sensing to improve precipitation estimates in mountain regions (Cooper et al. 2017), and will incorporate undergraduates in analyzing remote sensing data. In November 2017, a Center for Severe Weather Research Doppler on Wheels (DOW) radar visited the University of Utah for the Outreach and Radar Education in Orography (OREO) field campaign led by Dr. Steenburgh.  Students at the University of Utah used the DOW to chase orographic storms in Northern Utah. Data from these campaigns will form the basis for an REU project.  Dr. Zipser, Fellow of the AMS and author of over 130 peer reviewed publications, will assist REU students with using remote sensing data to observe thunderstorm initiation over complex terrain (e.g., Liu and Zipser, 2015). Predictive models of orographic precipitation have been developed on a variety of spatial and temporal scales by faculty within the Department. For example, Dr. Strong studies climate by developing and using computer models (e.g. Scalzitti et al., 2016), and is especially interested in linkages between the atmosphere and cryosphere, including mountain snowpack.  He will lead an REU project focused on investigating the effects of climate change on mountain snowpack. 

Fire Weather Applications

Dr. Horel’s research is supported by federal and state fire agencies to improve the information available to wildfire professionals to make decisions when hazardous weather is expected in the vicinity of major wildfires (Horel et al. 2014; Lammers and Horel 2014; Blaylock et al. 2018). Dr. Krueger’s research group has been involved in wildfire modeling and field experiments for many years (e.g., Sun et al. 2009, Kochanski et al.  2013a,b, Clements et al. 2018). Dr. Krueger is currently PI of a project supported by NSF's PREEVENTS (Prediction of and Resilience against Extreme Events) program that is developing the Multistage Wildfire Research and Prediction System (MWRPS), a powerful modeling approach that will provide real-time prediction at the fire-line scale for research and operational forecasting needs, while incorporating the effects of complex terrain. These projects involve analyzing and visualizing "big data" obtained from numerical weather prediction models and observations in the vicinity of major wildfires. The objective of fire-related studies is to develop improved observational and computer-based tools that operational wildfire personnel can use to make informed decisions about conditions that could lead to explosive fire development. REALM students will be involved in monitoring online information related to major wildfires in the western United States and Alaska, and the ability of modeling systems to identify periods when fires may undergo explosive growth. They will also have first-hand experience with a tilting incendiary wind tunnel (using wood shavings for the fuel bed), which clearly illustrates the impacts of slope and wind speed on fire rate of spread. 

Air Quality in Mountainous Regions

Air quality in mountainous regions reflects the combined influences of nearby urban influences, regional-scale emissions, and long-range transport.  For instance, atmospheric composition measurements at mountain sites reveal the impacts of aridity on aerosol loading from wildland fires (Hallar et al., 2015; 2017).  Mountaintop observations of CO2 reveal the carbon cycle due to montane vegetation, as well as occasional impacts of urban emissions.  Dr. Lin’s research has included modeling of CO2 in the mountains (Lin et al., 2017), as well as observations of CO2 and air quality-relevant pollutants from cities up to mountains (Lin et al., 2018).  Dr. Mitchell has been using mobile measurements to investigate the spatial patterns of atmospheric composition that interacts with the surrounding mountains and urbanized valleys through strong thermally-driven circulation patterns (Mitchell et al., 2018).  Dr. Mendoza's research focuses on combining highly resolved emissions (Mendoza et al., 2013) with exposure measurements to model and predict health outcomes at sub-city resolution, with a particular focus on vulnerable populations (Pirozzi et al., 2018). This multidisciplinary approach encourages the REU student to postulate enactable mitigation options and suggestions that can not only further scientific and health research, but can also be used as the framework for future legislative efforts.  Dr. Kevin Perry’s research has recently focused on dust plumes from the Great Salt Lake, which reduce horizontal visibility and increase particulate matter concentrations to unhealthy levels.  He has identified portions of the lakebed that are active dust sources by bicycling (2250 miles) across the lakebed, documenting the surface crust characteristics, and collecting 5000 soil samples for subsequent physical, chemical, and optical characterization.  REALM students will be involved in the analysis and interpretation of these soil samples. Dr. Perry was recognized in 2018 by the University of Utah with an award for mentoring students in their career development and exploration. 

REALM RESEARCH PRojects

STRUCTURE AND PREDICTION OF OROGRAPHIC, LAKE-EFFECT, AND SEA-EFFECT STORMS

W. James Steenburgh, Professor

Background

The Steenburgh group seeks to advance the understanding and prediction of winter storms in complex terrain, focusing on the contiguous western United States and lake- and sea-effect regions around the world.  Snowfall in these regions is often intense, spatially variable, and difficult to predict.  We conduct field programs, analyze conventional meteorological data, validate operational models, develop forecasting techniques, and perform mesoscale- and cloud-model simulations to unlock the secrets of these storms and improve their prediction.

Student Role

We are currently producing high-resolution snowfall forecast for the western United States using techniques to downscale precipitation forecasts from ensemble modeling systems and estimate snow-to-liquid ratio.  We seek a student to examine the accuracy of these snowfall forecasts in the central Wasatch Mountains southeast of Salt Lake City where winter storms typically produce large spatial snowfall contrasts.  This will involve comparing snowfall and liquid precipitation equivalent observations collected by avalanche professionals at several locations with downscaled forecasts from operational modeling systems.  This could be done for one or more winter seasons, looking at cumulative statistics, or by focusing on case studies of well and poorly forecast events. 

Student Learning Outcomes

At the completion of this research experience the student will be able to:

  • Apply appropriate verification methods to identify the capabilities and limitations of precipitation forecasts
  • Use ensemble-derived probabilistic information and visualizations for precipitation and snowfall forecasting
  • Describe the limitations and uncertainties of snowfall observations and challenges of predicting winter storms in complex terrain
  • Summarize the economic benefits and societal impacts of winter storms in mountainous regions and communities 
  • Articulate the relevance of their research for a professional audience

APPLY HERE

 

MEASUREMENT OF THUNDERSNOW IN MOUNTAINOUS TERRAIN

Timothy Garrett, Professor

Background

The Garrett group is interested in the surveying the properties solid precipitation and linking them to meteorological conditions. Weather and climate models still rely on a very few measurements made by hand in the Washington Cascades in the 1970s. We hope to change this by using advanced automated techniques we’ve developed for photographing snow particles in free fall and measuring their mass and density and fallspeed.

Student Role

Summertime mountain precipitation is often in the form of large graupel and small hail that falls from convective clouds triggered by land heating and forced mountain uplift of winds. The student will help deploy instrumentation to the Wasatch Front range next to Salt Lake City. Student data analysis will focus on analyzing precipitation particle microphysical properties and relating them to mountain meteorology.

Student Learning Outcomes

  • Learn about the various types of precipitation and their range of microphysical properties
  • Become skilled at operating new instrumentation for measuring precipitation and data collection
  • Deploy instrumentation in a mountain environment as part of a scientific team
  • Analyze precipitation data using MATLAB
  • Compare precipitation properties to mountain meteorological conditions
  • Summarize scientific results in a written report

 

 APPLY HERE

 

INVESTIGATING WEATHER CONDITIONS NEAR WILDFIRES

John Horel, Professor

Background

Wildfire professionals have to make difficult decisions when hazardous weather is expected in the vicinity of major wildfires in the United States. The project involves analyzing and visualizing "big data" obtained from numerical weather prediction models, satellite,  and observations in the vicinity of major wildfires during the 2020 summer season. Fire professionals are already using online tools developed by our research group to monitor wildfire potential near the Great Lakes (glff.mesowest.org), Alaska (akff.mesowest.org), and nationwide (mesowest.utah.edu). We are increasingly involved with assisting electrical utilities throughout the West to monitor hot, dry, and windy conditions within their service areas.

(Photo: High winds forecast at the time of the Camp Fire in northern California shown for locations of utility lines operated in that area)

Student Role

You will participate in research with faculty, staff, and graduate and undergraduate students in the MesoWest group (meso1.chpc.utah.edu/mesowest_overview). Research and development related to fire weather, the Great Salt Lake, and air quality along the Wasatch Front and in the Uintah Basin are among some of the projects underway. You will help monitor information related to major wildfires in the western United States during the 2020 summer season with particular attention towards hazardous conditions that might require action by electrical utilities. That information will be used to identify periods when fires underwent explosive growth and use weather graphics available to our group to document those cases. Background in the atmospheric sciences is not required. 

You also have the opportunity to spend time assisting with field work related to a network of environmental monitoring stations operated by our group in remote locations of northern Utah. You will obtain hands-on experience with how weather equipment is installed, maintained, and operated.

Student Learning Outcomes

  • be involved in societally-relevant research that has the potential to protect lives and property threatened by future wildfires
  • gain experience in methodologies in collaborative research to examine environmental information
  • increase familiarity with ways to acquire, archive, and visualize environmental information through online instruction and hands-on field work with environmental sensors
  • become familiar with the linux operating system on workstations housed by the Center for High Performance Computing as well as techniques to access data from cloud providers, such as Amazon.

 APPLY HERE

THE PHYSICS OF WILDFIRES

Steve Krueger, Professor

Scientific Background

Wildfires are increasing in frequency and size and the associated destruction of structures, loss of life, and impacts on air quality are also increasing. Heat waves, droughts, earlier snowmelt associated with global climate change have strong impacts and yield more favorable conditions for longer fire seasons and more extreme fire behavior, as have decades of fire suppression in the western U.S. that has allowed fuels to build up. Population growth in the wildland-urbant interface (WUI) without adequate consideration of wildfire risks has also contributed to wildfire losses. Inadequate maintenance of electrical power lines has also sparked several disasterous wildfire in California. Wildfire intensity and spread is determined by three factors: fuel, wind, and slope. Fine fuels respond to dry conditions most quickly, and also are easiest to ignite. Fuels and winds vary greatly in short distances in mountainous terrain. Fires spread more rapidly upslope than downslope. Coupled fire-atmosphere numerical weather prediction models are increasingly being used to guide real-time wildfire decisions.

Student’s Role

My research involves improving a coupled fire-atmosphere numerical weather prediction model. An important aspect of model development is comparing model predictions to measurements of actual wildfires. It is quite difficult to make the kinds of detailed measurements that we need in uncontrolled wildfires, so instead we make detailed measurements of prescribed burns or laboratory-scale fires. To give the student some experience in such measurements, he or she will make measurements of fire spread in the University of Utah Incenderiary Wind Tunnel, under various conditions of fuel, wind, and slope, and then analyze the measurements to quantify the rate of spread. The student will also analyze satellite data to determine rate of spread from observed fire perimeters and to estimate fire plume heights. The student will also analyze the results of numerical simulations of actual wildfires and compare them to satellite and surface measrements. Finally, the student will be introduced to the methods of computational fluid dynamics, with an emphasis on simulating wild fires.

Student Learning Outcomes & Benefits

  • Have observed laboratory demonstrations of fire spread in the University of Utah Incenderiary Wind Tunnel.
  • Quantified the effects of fuel, wind, and slope on fire spread in the wind tunnel.
  • Learned how to measure a fire's rate of spread (speed and direction) using an array of thermocouples.
  • Have met and talked to scientists who are developing and testing state-of-the-art coupled fire-atmosphere numerical weather prediction models, and others who are using satellite imagery to track fires from space.
  • Learned about the basic physical components of fire spread and how they are represented in numerical models.
  • Learned how fuel moisture is measured and modeled.
  • Learned about the different modes of fire spread and aspects of extreme fire behavior.
  • Learned about how satellite imaging is used to track fire perimeters from space.

 APPLY HERE

ANALYSIS OF DOPPLER WIND LIDAR DATA IN COMPLEX TERRAIN FOR AIR QUALITY APPLICATIONS

Sebastian Hoch, Research Assistant Professor

 Background

The Salt Lake Valley and other densely populated topographic basins in northern Utah and throughout the world suffer from prolonged pollution episodes during wintertime that are associated with Persistent Cold Air Pools (PCAPs). PCAPs develop when high pressure systems and subsidence temperature inversions trap colder air and anthropogenic emissions in topographic basins. While atmospheric mixing and transport processes are generally suppressed under the statically stable atmospheric conditions of PCAPs, some thermally and synoptically driven processes still work to modulate particulate pollutant and pollutant precursor concentrations within and along the edges of the PCAPs. For the SLV, these processes include (1) canyon circulations through tributaries, (2) lake breeze circulations from the Great Salt Lake (GSL), (3) basin sidewall ventilation, (4) synoptically forced airmass exchanges with the atmosphere over the GSL, and (5) inter-basin exchanges.

Over the past winter seasons, Doppler wind LiDAR observations were conducted to target some of these different PCAP mixing or exchange processes.

Student Role

We are looking for a student to analyze the LiDAR dataset in combination with additional available chemical and meteorological datasets to evaluate the importance of these circulations in modulating spatial and temporal variations in pollution concentrations throughout the SLV. A comparison of these observed processes with output of the HRRR model or with a cold-air drainage model are additional research options. Further, a short LiDAR deployment targeting thermally-driven circulation systems in the SLV are planned for hands-on experience with the wind LiDAR.

Student Learning Outcomes

At the completion of this research experience the student will be able to:

  • Describe and discuss the meteorological and chemical processes involved in the life cycle of Utah’s wintertime pollution episodes.
  • Post-process Doppler wind LiDAR data from different scanning strategies.
  • Combine LiDAR-retrieved wind fields with chemical datasets to evaluate and estimate pollution mass transport.
  • Deploy and operate a Doppler Wind LiDAR or model drainage flows with a cold-air pooling and drainage model.
  • Articulate the relevance of their research for a professional audience.

 APPLY HERE

FIELD STUDY OF COLD-AIR POOL EVOLUTION

Dave Whiteman, Emeritus Research Professor

Scientific Background

Cold air on sloping terrain drains into low-lying mountain basins, valleys and declivities of different scales at night and in winter. The coldest air settles in the lowest terrain, with surrounding temperatures increasing with altitude. The resultant temperature inversions or stable layers affect animal and plant life and can have important effects on human health, home heating, air pollution, fog, transportation, and fire weather. The Salt Lake Basin has frequent temperature inversions and the effects of cold air drainage down the basin tributaries and the formation of cold-air pools within the basin and surrounding mountainous terrain are largely unexplored. This project will conduct nighttime field studies to investigate the evolution of temperature structure and winds in cold-air pools.

(Photo: Atmospheric Sciences students involved in a cold-air pool study at Arizona’s Meteor Crater, 2006.)

Student's Role

Students will design and conduct field experiments under the supervision of Professors Whiteman and Hoch to evaluate and document the evolution of nocturnal cold-air pools during clear, undisturbed background weather conditions. Students will begin by performing a literature review to determine what is presently known about cold-air pools in general and about existing scientific studies in the Wasatch Mountains and the Salt Lake Valley. Students will then design and conduct field experiments using observational tools such as fixed, hand-carried, bicycle-borne, automobile-borne, and balloon-borne meteorological instrument packages that may measure temperature, humidity and wind. A high-tech scanning Doppler lidar will be used to measure the wind field exiting one or more tributary canyons. Students will process and analyze their field data and prepare a comprehensive written report at the end of the program. Because of safety issues with nighttime work there is a 2-student minimum.

Student Learning Outcomes and Benefits

At the completion of this research experience, the student will have learned to:

  • identify and review relevant scientific literature
  • design effective field experiments
  • operate simple meteorological instrumentation and gain experience with communication protocols
  • process and analyze field data
  • develop and test scientific hypotheses
  • gain experience with scientific writing and presentation

APPLY HERE

Transport of Ozone in the red butte canyon research natural area

John Lin, Professor and Ryan Bares, Sr. Laboratory Specialist

Background

Tropospheric Ozone (O3) is a critical atmospheric oxidant, causing direct harm to human health in the summer and involved the formation of wintertime particulate matter.  Thus, O3 is a key pollutant in both the summer and winter months. Despite the importance of this pollutant, many questions remain regarding its formation, transport and roles in secondary chemical reactions. In an effort to better understand the role of canyons in the transport of O3 rich air into the valley, the Utah - Atmospheric Trace gas & Air Quality lab has installed O3 monitoring equipment throughout Red Butte Canyon, a tributary canyon located directly above the University of Utah.  This is a yearlong data collection effort to help understand winter and summer air quality along the Wasatch Front.

Student Role

The student will assist in field and laboratory tasks.  The role of the student includes the calibration of sensors in the laboratory, deployment of sensors to field sites within Red Butte Canyon, monitoring real time data to identify and resolve problems, and analysis of data post collection for reports and lab meetings. 

Student Learning Outcomes

  • A great advantage of working in the Utah – Atmospheric Trace gas & Air Quality lab is that students are introduced to a wide array of air quality and greenhouse gas research.
  • Students will have the opportunity to learn hands on instrumentation and data collection techniques with cutting edge technology used in a wide array of measurement platforms.
  • Students will also learn about the atmospheric chemistry that drives the Salt Lake Valley’s air quality problems, as well as gain insight into urban emissions and (potentially) atmospheric modeling techniques.
  • Students will have the opportunity to conduct data analysis on one of a kind datasets to help better understand our air quality problems and inform decision makers.
  • Since the student is required to attend weekly lab meeting and contribute analysis for reports as well as resolve issues during fieldwork, they will gain experience in communication skills, analysis of data, and problem solving.
  • These skill sets will directly contribute to a student’s professional development in the fields of scientific or academic research.

 APPLY HERE

MODELING AND OBSERVATIONS OF AIR QUALITY AND ASSOCIATED HEALTH IMPACTS

Daniel Mendoza, Assistant Professor

 Background

Exposure to air pollution has been associated with multiple negative health outcomes such as pulmonary and cardiovascular events, particularly among vulnerable populations. Over 200,000 people live in Salt Lake City, capital city of Utah and county seat, with over 1.2 million residents in the Salt Lake City Metropolitan area. Salt Lake City is surrounded by mountains to the south, east and west, creating a topographical basin that traps pollution during wintertime stable layers or cold-air pools (also known as inversions) leading to high levels of pollutants, especially fine particulate matter (PM2.5). Interstate highways, an international airport and railroad traffic, industrial pollution sources, windblown dust and wildfires are among the complex sources that contribute these episodic pollution events that are most frequent and severe in the winter and summer. With a growing population and increasing wildfire and dust storm occurrences summertime air quality is becoming an increasing public health concern. Due to the lack of granular, reliable air quality measurements, all previous pollutant exposure and health-related studies have intrinsic resolution issues when examining scales smaller than a county or city. This reduces applicability, since a single sensor cannot portray intra-city variability, nor truly represent individual or neighborhood-scale exposure. This leads to significant mischaracterization of a population’s vulnerability and potential health outcomes. Understanding that the burden of poor air quality is not shared equally among populations is a key motivator for understanding environmental exposure at neighborhood scales.

Student Role

The student will be encouraged to develop a research project as independently as possible. This research experience will develop skills in project management and development that will result in a complete product to share with the community at large in addition to an academic audience. The student will learn communication methods to engage with and involve stakeholders as part of the project development process. The student will also become familiar with the various air quality observation platforms and emissions datasets available, as well as health outcome metrics. The student will also develop quantitative and programming skills to analyze exposure and health data sets as part of the project. Collaborative research with investigators across disciplines will be facilitated so the student can contextualize the proposed project. If a particular on-going project is of interest to the student, this can serve as a starting point and the student will be encouraged to provide their own insight and approach to it in order for it to maximize impact and learning benefits.

Student Learning Outcomes & Benefits

At the completion of this research experience, the student will:

  • Understand pollutant emission modeling approaches
  • Be familiar with air quality observation methodology
  • Have hands-on experience with air quality sensors
  • Estimate exposure metrics at different temporal scales
  • Learn how to find and retrieve applicable health data to study
  • Utilize a statistical software package (R, Matlab, etc.) to perform data analysis
  • Convey enactable applications of their findings and results
  • Develop and manage a project to be presented at the end of the summer
  • Gain experience communicating with stakeholders outside of academia

 APPLY HERE

Using public transit based mobile observations to examine air quality

Logan Mitchell, Associate Professor

Scientific Background

The Wasatch Front suffers from poor air quality during the winter and summer as a result of emissions, atmospheric mixing and chemical reactions, and our unique topography surrounding the city.  In recent years our research team has deployed a novel air quality and greenhouse gas measurement platform on several TRAX light-rail train cars in order to gain a better understanding of how these pollutants vary across the city.  This is a unique data set that is getting national and international attention, yet there are many questions that have yet to be investigated using the data.  There are many opportunities associated with doing research on this data set that include (but are not limited to): 1) quantify methane leakage, 2) evaluate data calibration techniques, 3) examine how holidays or special events affect air quality, 4) examine how vegetation affects air quality, 5) examine how the mountains surrounding the canyons affect air quality, 6) examine how traffic volume or other factors affect air quality.

Student’s Role

The student will conduct data analysis on the extensive TRAX data set on a topic of their interest in collaboration with our research team.  They will also have the opportunity to perform maintenance on the TRAX instrumentation suite if they desire to get hands-on experience with instrumentation.

Student Learning Outcomes & Benefits

  • Get introduced to a wide array of air quality and greenhouse gas research and instrumentation.
  • Learn data analysis techniques with a unique data set that has significant public interest. There will be opportunities to publish results if desired.
  • Attend regular lab meeting and contribute analysis for reports. This will develop skills in written and verbal communication, analysis of data, and problem solving. 
  • Learn about opportunities to communicate research results about air quality and the changing climate with colleagues, the public, and policymakers.
  • These skill sets will directly contribute to a student’s professional development in the fields of scientific or academic research.

 APPLY HERE

CHARACTERIZING THE DUST PRODUCED BY THE GREAT SALT LAKE

Kevin Perry, Associate Professor

Scientific Background

Due to a combination of water diversion and drought, the terminal basin Great Salt Lake (GSL) has receded significantly exposing more than 1960 km2 (~757 mi2) of playa. Although much of the playa is covered by a protective crust, there are regions which produce massive dust plumes when the soil moisture is low and the wind speed is high enough. These dust plumes can have a significant impact on local air quality and pose a potential health threat to adjacent populations.

Student Role

During a two-year field campaign, I collected soil samples from the entire exposed GSL lakebed and documented the surface crust characteristics at more than 5250 locations. The elemental composition and particle size distributions of the soil samples were then measured in the laboratory. I am seeking a student to help use the data to 1) determine the chemical fingerprint of the major GSL dust source regions, 2) produce compelling maps to visualize the spatial variability of the surface crust conditions/chemical composition, and 3) investigate the role of particle size distribution on dust production. This project will include at least one field trip to explore the GSL playa.

Student Learning Outcomes and Benefits

At the end of this research experience the student will be able to:

  • Perform statistical analyses (e.g., positive matrix factorization, student-t tests, etc.) to formally test hypotheses about the relationships discovered during the data analysis
  • Use computer software to visualize spatial distributions of key parameters
  • Develop a quantitative understanding of the use of elemental composition data derived from Synchrotron X-Ray Fluorescence (S-XRF) and Inductively-Coupled Plasma Mass Spectrometry (ICP-MS).
  • Effectively communicate findings from the research to a professional audience
  • Have a greater appreciation of the Great Salt Lake ecosystem and factors which threaten its future

 APPLY HERE

(Photo Top: MODIS satellite image of the Great Salt Lake from July, 2017. Photo Bottom: Example of dust from the Great Salt Lake impacting local air quality in Nov. 2016)

HIGH RESOLUTION DYNAMICAL MODELING OF THE EFFECTS OF CLIMATE CHANGE ON MOUNTAIN SNOWPACK

Court Strong, Associate Professor

Background

The Strong group uses high-resolution regional climate models run on supercomputers to understand and predict precipitation in complex mountainous terrain. Our work with the Weather Research & Forecasting (WRF) model extends from Utah’s Wasatch Range, shown here, to the most extreme peaks of High-mountain Asia. We are interested in how terrain influences the dynamics and variability of snow and monsoonal rainfall, and a strong focus of our work is quantifying how climate change will impact snow as a resource for recreation and water.

Student's Role

We have performed several decades of regional climate model simulations with WRF for Utah and High-mountain Asia covering the historical period and future climate out to the year 2100. Output from these simulations is recorded hourly at the surface and multiple levels of the atmosphere. We seek a student to help analyze these simulations to investigate how terrain influences precipitation patterns, and to quantify how greenhouse gas-driven warming will alter the future snowpack. This will involve developing code for extracting and calculating variables from the model archives, and performing statistical analyses to test hypotheses about the relationships uncovered through the data analysis. Interested students also have the opportunity to run additional experiments with the WRF model on our supercomputers at the University of Utah Center for High Performance Computing (https://www.chpc.utah.edu/).

Student Learning Outcomes

At the completion of this research experience the student will be able to:

  • Develop efficient computer code for accessing petabyte-scale simulation archives and calculating derived variables such as potential vorticity
  • Perform statistical analyses to formally test hypotheses about the relationships discovered during the data analysis
  • Run a regional climate model on a supercomputing platform if desired
  • Summarize the impacts of climate change on mountain precipitation and snow as a resource for recreation and water
  • Effectively communicate findings from the research to a professional audience

 APPLY HERE

THUNDERSTORM INITIATION OVER COMPLEX TERRAIN: THE USE AND ABUSE OF RADAR AND SATELLITE OBSERVATION

Edward Zipser, Professor

Scientific Background

On many summer days, there is a chance for local circulations over the mountains to initiate convective clouds.  For these clouds to develop into thunderstorms, sufficient moisture and instability are essential, but observations are not always sufficient for accurate forecasts.  Once convective clouds do form over mountains, radar and satellite observations can be used to assess storm depth, potential for lightning, heavy rainfall or severe weather.  However, proper use of those data requires understanding of their limitations as well as their strengths.  This project should prepare the student to make good use of available data while avoiding some common pitfalls.

(Photo: UCAR Photo Archive, taken by Bob Maddox of storms near Estes Park Colorado leading to the Big Thompson Flood of 1976 - many fatalities that evening.)

Student's Role

The student will examine surface and upper air sounding data each day that are useful for anticipating cloud and storm development over local area, or as appropriate, elsewhere in the intermountain west.  During midday when storms are most likely to develop, use high resolution visible and infrared data from the GOES-16 satellite to assess where storms are producing precipitation.  The student will also use data from available weather radars in real time, and learn locations where radar data  can provide quantitative information about rain and hail, and where beam blockage and other important issues prevent this. 

Student Learning Outcomes and Benefits

At the completion of this research experience, the student will be able to:

  • Evaluate morning soundings to assess the probability of thunderstorms later in the day
  • Evaluate surface data sources during the day to improve the accuracy of the outlook for thunderstorms.
  • Develop a quantitative understanding of the location of the radar beam, and what radar can and cannot tell us about when and where rain and hail are falling.
  • Develop a quantitative understanding of the use of VIS, IR, and moisture channels of GOES-16.
  • Know enough about mountain thunderstorms to be a safer hiker.

 APPLY HERE

THE INFLUENCE OF AEROSOLS ON FORMATION AND EVOLUTION OF TROPICAL CYCLONES

A. Gannet Hallar, Associate Professor

Zhaoxia Pu, Professor

Background

Previous studies indicated that aerosol has effects on tropical cyclone genesis, evolution, and precipitation distribution.  The objective of this project is to understand the influence of aerosols on the formation and development of tropical cyclones with mesoscale community Weather Research and Forecasting (WRF) model. The specific case study will be conducted for an Atlantic hurricane in recent years when it is near the landfall.

Student Role

Under the supervision of Dr. Hallar, the student will gain hands-on experience running WRF numerical model, diagnosing model outputs, and comparing model results with available insitu aerosol, lidar, satellite and radar observations. 

Specifically, student will investigate data from the Hurricane and Severe Storm Sentinel (HS3) a mission specifically targeted to investigate the processes that underlie hurricane formation and intensity change in the Atlantic Ocean basin.  HS3 utilized two Global Hawks. The NASA Global Hawk Unmanned Aircraft Systems are ideal platforms for investigations of hurricanes, capable of flight altitudes greater than 55,000 ft and flight durations of up to 30 hr.  The REU student will specifically investigate Hurricane Nadine. Hurricane Nadine developed in close proximity to the dust-laden Saharan air layer.   The student will also explore the availability of aerosol measurement (both insitu and remote sensing) from surface sites in the region (e.g., sites at Santa Cruz de Tenerife and Azores).

Student Learning Outcomes:

At the completion of this research experience the student will:

  • Build knowledge in numerical weather prediction and weather analysis
  • Improve understanding of the use of radar and satellite data in the weather analysis forecasting.
  • Learn about microphysical and thermodynamic processes associated with tropical cyclones.
  • Understand the strengths and weaknesses of different methods used to measure dust in the atmosphere (both insitu and remote sensing).

APPLY HERE

 

Last Updated: 7/27/20