NWC REU 2016

Analysis and Improvement of a Six-Axis Robotic Scanner for Millimeter-Wave Active Phased Array Antenna Calibration

Robert Baines —  Rice University
Mentor: Dr. Jorge Salazar and Rodrigo Lebron

Link to Abstract and Paper

What is already known:

• Phased array radars are the next logical step in both weather and military radars.
• Current work is optimizing phased array radar performance to match that of conventional radar.

What this study adds:

• This study provides a never-before created novel setup that enables comprehensive phased array radar calibration characterization under varying temperature conditions.
• This laboratory study is an important step toward full-scale phased array radar implementation in realistic conditions.

UAV-Based Calibration for Polarimetric Phased Array Radar

Christian Boyer — Millersville University
Mentors: Dr. Caleb Fulton

Link to Abstract and Paper

What is already known:

• Previous studies have detailed the challenges in calibrating polarimetric phased array radars to provide a high degree of polarization purity.
• Dual polarization phased array radars offer many advantages, and is a candidate for a future multifunctional phased array radar (MPAR) system that combines weather radar and air surveillance/traffic monitoring.

What this study adds:

• A circuit, called the "Twitching Eye of Horus,” transmits horizontally- and vertically- polarized fields for calibration of the radar receiver.
• This study created a technique for extracting estimates of a radar receiver scan-dependent polarimetric pattern from raw radar data.
• This study enables a sensor-equipped unmanned aerial vehicle (UAV) for scan-dependent calibration of a fixed phased array radar.

Ensemble Forecasts and Verification of the May 2015 Multi-Hazard Severe Weather Event in Oklahoma

Austin Coleman —  Valparaiso University
Mentor: Dr. Nusrat Yussouf

Link to Abstract and Paper

What is already known:

• The current prototype Warn-on-Forecast (WoF) system is a storm-scale ensemble at 3-km horizontal grid spacing that has the potential to extend probabilistic low level mesocyclone forecast lead times for severe convective events.
• The science and technology being developed to achieve WoF goals can also be used to improve 0-3 hour extreme rainfall forecasts for convective systems.
• The 3-km horizontal grid spacing of the current prototype WoF system is too coarse to resolve tornadic circulations.

What this study adds:

• The 0-3 hour heavy rainfall forecasts from the prototype system verifies better with NCEP’s Stage IV analyses and Mesonet observations in terms of locations compared to that from the operational HRRR forecasts for this case study.
• The ensemble forecasts systematically underestimate precipitation amounts, which indicates further investigation of microphysics scheme sensitivities as well as grid-spacing sensitivities are needed.
• Ensemble forecasts at 1-km horizontal grid spacing from the downscaled 3-km prototype system introduces many spurious cells with embedded spurious mesocyclones.

Assessing Future Projections of Climate Extremes Over the South Central USA

Dana Gillson —  Mount Holyoke College
Mentor: Dr. Esther Mullens and Dr. Derek Rosendahl

Link to Abstract and Paper

What is already known:

• Extreme weather events (heavy precipitation, drought, heat waves, and storms) impact multiple sectors of life including infrastructure, people, ecosystems, economy, and agriculture.
• The Expert Team on Climate Change Detection & Indices (ETCCDI) has defined 27 core extreme indices that can be calculated in Global Climate Models (GCM) such as the Coupled Model Intercomparison Project Phase 5 (CMIP5).
• Previous studies have compared the reliability of global reanalyses in a variety of regions but very few (if any) have been done in the south central USA.

What this study adds:

• Observation-based reanalyses can be significantly different from one another and therefore result in varying model biases depending on which is used.
• Model performance is dependent on region, season, and extreme indice, and therefore no single model was found to be best for all situations.
• Similar models from the same institution tend to contain similar biases.
• This study provides future projections that show a possible differentiation between the best and worst performing models.

Arctic Weather and Abrupt Sea Ice Loss

Uriel Gutierrez — Texas A&M University
Mentors: Dr. Steven Cavallo and Nicholas Szapiro

Link to Abstract and Paper

What is already known:

• The long term climate trend for Arctic sea ice is well established with the ice-albedo effect as a main driver.
• Wind patterns from inter-seasonal oscillations (such as Arctic oscillation) have effects on sea ice motion and extent.
• Abrupt sea ice loss events have been observed on time scales of days and coincide with surface cyclones.
• A better understanding of year-to-year variability is important for improving future predictions of sea ice.

What this study adds:

• Oscillations in change of sea ice extent (1979-2014) at synoptic time scales were shown to be statistically significant.
• Synoptic time scale reductions in sea ice extent occur most frequently in July and December.
• Composite of top 1% of abrupt loss in sea ice extent events revealed strong winds over loss area.
• These conditions always occurred with a nearby surface cyclone; enhancement from anticyclones could sometimes also occur.

Impact of Rain Gauge Location Errors on Verification of Radar-Based Precipitation Estimates

Sebastian Harkema — Central Michigan University
Mentors: Dr. Heather Grams and Steve Martinaitis

Link to Abstract and Paper

What is already known:

• The Multi-Radar Multi-Sensor (MRMS) system, which generates a 1-km grid of quantitative precipitation estimates (QPE) products, can provide insight to forecasters when issuing flash flood warnings.
• Rain gauges are treated as ground truth and can provide the most accurate verification of radar-based QPE.
• Verification and data accuracy using gauges is only as good as the instrumentation and observations. Even with the advancement of technology, inaccuracies of rain gauges persist and are well documented.

What this study adds:

• It is standard to accept that radar-based QPE values can vary from collocated observed gauge values; however, location errors with rain gauges can have an impact on the verification of MRMS QPE.
• A majority of Automated Surface Observing System (ASOS) stations in the Continental United States (CONUS) were found to be in a different MRMS grid box than the one indicated by the latitude and longitude in their original metadata.
• New QPE values based on the new latitude and longitude coordinates had better correlation with the observed precipitation than those QPE values based on the original metadata locations.

Quantifying the Carbon Footprint on Paris with Remote Sensing Observations

Briana Lynch — University of Massachussetts Lowell
Mentor: Dr. Sean Crowell

Link to Abstract and Paper

What is already known:

• Previous studies have shown that urban areas have a larger amplitude seasonal cycle of carbon dioxide concentrations.
• The basic interaction between atmospheric dynamics and pollutants in the planetary boundary layer has been studied, but its contribution to urban environments is not well understood.
• Near surface horizontal lidar instruments quantify carbon dioxide concentrations for the boundary layer more effectively than airborne and space-borne measurements, since the column average is less sensitive to the boundary layer.
• Disaggregation of natural and anthropogenic sources of CO2 is difficult and relies on existing inventories to interpret measurements.

What this study adds:

• This study used a new observational technique determine carbon dioxide concentration sources and sinks.
• This work confirmed that the Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE) made science-quality measurements for six months in an urban environment.
• A preliminary result shows that nitrogen dioxide is positively correlated with carbon dioxide, while ozone seems to be anti-correlated with carbon dioxide, though the mechanism is still not understood.

Modeling the Physical, Dynamical, and Chemical Characteristics of Extreme Extratropical Convection in the Upper Troposphere and Lower Stratosphere

Russell Manser — Saint Cloud University
Mentor: Dr. Cameron Homeyer and Daniel Phoenix

Link to Abstract and Paper

What is already known:

• Convection that penetrates the tropopause transports gases into the stratosphere.
• Numerical models can resolve gravity wave breaking and lofting of cirrus clouds in convection, which is a mechanism for transporting gases into the stratosphere.
• Stratosphere-troposphere exchange impacts the chemistry of the upper troposphere and lower stratosphere, the radiation budget through modification of greenhouse gases and, in turn, climate.

What this study adds:

• The ARW-WRF model coupled with chemistry is capable of simulating a real case of convection that penetrates the tropopause and has an above-anvil cirrus plume.
• Numerical models can resolve the irreversible transport of trace gases into the stratosphere. While water vapor is enhanced at all levels the cloud reaches in the stratosphere, transport of carbon monoxide (a tropospheric pollutant) is limited to the maximum height of the simulated radar reflectivity echo top, which typically lies 2 km below the cloud top.

Climate Change Hazards: Extreme Precipitation Events & Flooding in Oklahoma’S Tribal Nations

Kristina Mazur —  Rutgers University
Mentors: April Taylor, Dr. Esther Mullens, and Dr. Derek Rosendahl

Link to Abstract and Paper

What is already known:

• Flooding caused by extreme precipitation events is one of the top hazards effecting Citizen Potawatomi Nation, Choctaw Nation of Oklahoma and Chickasaw Nation.
• Climate change can lead to more extreme weather events such as extreme precipitation and flooding.
• Patterns such as the intensity, frequency, timing, and duration of extreme weather events are changing as a result of climate change.

What this study adds:

• This study provides tribal nations with future climate projections to help them prepare for and mitigate damages caused by extreme precipitation events.
• Tribal nations in the future should expect an increase in extreme rainfall events, rather than an increase in the average daily precipitation rate.
• There is reasonable confidence in extreme precipitation changes across this region; however, the 15 models displayed a range of possible outcomes.

The Impact of a Violent Tornado in Norman, Oklahoma

Karen Michelle Montes Berríos — University of Puerto Rico, Rio Piedras Campus
Mentors: Dr. Ashton Robinson Cook, Amber Cannon, Somer Erickson, and Dr. Mark Shafer

Link to Abstract and Paper

What is already known:

• Previous studies with geographic information systems (GIS) have estimated natural hazards’ impacts in metropolitan areas, like in Chicago and Dallas-Fort Worth.
• Oklahoma City and Moore have had a history of tornadoes in its metropolitan area, but some communities have not.
• GIS analyses can help emergency management officials, meteorologists, and sustainability researchers to effectively prepare for and respond to a disaster because they incorporate infrastructure and land use information.

What this study adds:

• This study analyzes the impact of an 1.07 mile wide EF4 tornado path through central Norman, Oklahoma.
• Damage to residential areas were calculated using Z Estimates, and showed a potential cost of over $1B.
• Evaluation of key locations throughout the tornado track, evaluating their sustainability and vulnerability according to its position.

Verification of Automated Hail Forecasts From the 2016 Hazardous Weather Testbed Spring Experiment

Joseph Nardi — Carleton College
Mentors: Dr. Amy McGovern, Dr. Nate Snook, and Dr. David John Gagne II

Link to Abstract and Paper

What is already known:

• It is challenging to forecast severe hail due to uncertainties in numerical weather prediction models and observations.
• HAILCAST, a popular hail prediction model, shows considerable skill in its ability to forecast hail size
• Machine learning approaches show some advantages over physics-based hail forecasts.

What this study adds:

• The Gagne Machine Learning Method has slightly higher skill and discrimination in both the forecasts of 25 mm and 50 mm hail than HAILCAST or the Thompson Hail Size Method.
• HAILCAST performed better at forecasting hail greater than 50 mm in the case study, however, it also has a greater false alarm rate.
• The Gagne Machine Learning Method is more consistent over all the microphysics schemes as the model is calibrated to each microphysics scheme.

Analysis of Anti-Ice Coatings on Field Operational Anemometers

Jamin Rader — University of Washington
Mentors: Brad Illson

Link to Abstract and Paper

What is already known:

• Norman, Oklahoma, has lost more than 26 days of wind data over the last decade due to ice accumulation on anemometers—a product of freezing precipitation.
• Many have researched the success of superhydrophobic coatings as anti-ice technologies, though no effective solutions have been found.

What this study adds:

• An R. M. Young Alpine Wind Monitor, made for winter conditions, and an R. M. Young Wind Monitor covered in NeverWet were not successful as anti-ice technologies through six freezing precipitation case studies in Norman, Oklahoma.
• Neither of these technologies were deemed beneficial for operational use for the Oklahoma Mesonet.