MIDWEST STUDENT CONFERENCE ON ATMOSPHERIC RESEARCH
CONFERENCE PROGRAM
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN OCTOBER 7TH - OCTOBER 8TH, 2017
WELCOME TO THE MIDWEST STUDENT CONFERENCE ON ATMOSPHERIC RESEARCH
On behalf of the entire conference committee, we welcome you to the 2017 Midwest Student Conference on Atmospheric Research (MSCAR). This conference is designed to create an opportunity for students, both graduate and undergraduate, to present their research to other students in a conference setting. We wish to create a conference conducive to gaining valuable skills in presenting, networking, and problem solving.
Marking its first year, MSCAR brings together nearly 100 attendees across 17 departments and institutions. This conference is unique in its ability of providing all attendees the means of giving feedback to each student presenter. We hope that all attendees leave the conference learning a lot about the new, innovative research carried out by students in our field.
We are delighted to have Dr. Louis Uccellini and Mr. Tom Skilling accept our invitations as keynote speakers and for co-facilitating a group discussion on communicating natural disaster impacts from an operational forecasting perspective. We would like to thank our faculty advisers and colleagues, who are listed below, for their instrumental support and assistance throughout the entire planning process. Lastly, thank you all for your interest in attending the conference, and we hope that you have a great experience this weekend. Sincerely, Jeff Thayer, Holly Mallinson, Joseph Finlon MSCAR Committee Chairs MSCAR Committee Budget Agenda Website Speakers Abstracts Jeff Thayer Holly Mallinson Joe Finlon Joe Finlon Jeff Thayer Holly Mallinson Jeff Thayer Sarah Szymborski Andrew Janiszeski Holly Mallinson Divyansh Chug Paloma Borque Brittany Welch Tzu-Shun Lin Piyush Garg Bryan Engelsen Sid Gupta Randy Chase Dan Stechman Sid Gupta Vendors Networking Faculty Advisers Support Staff Geoff Marion Holly Mallinson Jeff Thayer Bob Rauber Tammy Warf Dan Moser Bryan Engelsen Amy Chen Deanna Hence Donna Miller Shichu Zhu Joe Finlon Divyansh Chug Nicole Riemer David Wojtowicz Logo Design Remy Shao Hung Chen Rachel Gutierrez CrowleyFarenga Yu Yao Andrew Janiszeski
1 CONFERENCE SITE INFORMATION
Address: Natural History Building 1301 W. Green Street Urbana, IL 61801
Construction on Green Street has resulted in road closures near NHB. See the map to the right to view parking availability.
Wi-Fi: IllinoisNet_Guest (no password)
The Natural History Building The majority of the conference will be held in the newly renovated Natural History Building. This 148,000 square-foot space features modular classrooms and laboratories employed with the latest technology suitable for collaboration among faculty and students. Our visualization studio allows researchers to analyze satellite weather data from NASA mission data to examining the eye of a hurricane. The 300-person auditorium will host the research presentations on both days, while the commons area on the third floor provides ample space for the poster sessions.
The Union The Saturday Keynote Dinner and Sunday Keynote Lunch will be held in the Illini Union Ballroom. The Illini Union, located on the north side of the Main Quad, serves as a hub where students can eat and relax. The bottom floor features many restaurants as well as an arcade and a bowling. The Illini Union Hotel is situated on the top levels of the building, making it a convenient location for conference attendees from out of town to enjoy the campus environment.
Follow us on Twitter @MSCAR_Illinois
2 KEYNOTE SPEAKERS
Dr. Louis Uccellini received his Bachelors, Masters, and Doctoral degrees from the University of Wisconsin-Madison. After graduating in 1977 he began his career at NASA Goddard Space Flight Center's Laboratory for Atmospheres as the head of the Mesoscale Analysis and Modeling Section. Following this he joined the National Weather Service as the chief of their Meteorological Operations Division before becoming Director of the Office of Meteorology in 1994. Dr. Uccellini led the National Centers for Environmental Prediction and oversaw seven other centers such as the National Hurricane Center and Storm Prediction Center. Currently Dr. Uccellini serves as the NOAA Assistant Administrator for Weather Services and Director of the National Weather Service. Throughout his career, Dr. Uccellini has published more than 60 academic journal articles. He is arguably most known for his work in co-authoring the two-volume book "Northeast Snowstorms" and creating the "Northeast Snowfall Impact Scale" along with Dr. Paul Kocin. Dr. Uccellini is a fellow of the American Meteorological Society and served as the organizations president from 2012-2013. He has received numerous awards including the NASA Medal for Exceptional Scientific Achievement (1985) and the National Weather Associations Research Achievement Award for Significant Contribution to Operational Meteorology (1996), as well as several Presidential Rank Awards in recognition of his work with the government.
Mr. Tom Skilling began his career at the age of 14, first working for a local radio station before joining WLXT-TV in Aurora. In 1970, he began studying journalism and meteorology at the University of Wisconsin-Madison and continued working for local radio and television stations. Tom has been with WGN-TV since August 1978. In 2004, Mr. Skilling helped in coordinating the Tribune Weather Center which includes a state-of the-art computer graphics system that allows the WGN-TV weather team to give detailed weather reports for the Chicagoland area. He has been instrumental engaging and educating the public with his Chicago Tribune column "Ask Tom Why”, his hosting of World Environment Day programs in the Chicago area ,and his annual Fermilab Tornado and Severe Storms Seminar. In addition to all this, Mr. Skilling has also created many weather specials over the years including multiple tornado documentaries that have been used for educational and public awareness efforts. Mr. Skilling is a Fellow of the American Meteorological Society and the National Weather Association. He is a recipient of the AMS Award for Outstanding Service by a Broadcast Meteorologist and has several honorary doctorates.
3 CONFERENCE SCHEDULE
SATURDAY, OCTOBER 7
TIME EVENT LOCATION 8:00 AM – 9:00 AM Check-in NHB 2nd Floor West 9:00 AM – 9:15 AM Opening Remarks NHB Auditorium Oral Session I: 9:15 AM – 10:30 AM Remote Sensing NHB Auditorium Urban Envir. & Society 10:30 AM – 11:00 AM Coffee Break NHB 2nd Floor West Oral Session II: 11:00 AM – 12:00 PM NHB Auditorium Cloud Microphysics (Part I) 12:00 PM – 1:30 PM Lunch Break [on your own] Oral Session III: 1:30 PM – 2:30 PM NHB Auditorium Weather/Climate Impacts Poster Session NHB 3rd Floor 2:30 PM – 3:45 PM Optional NHB Tours Commons Open Forum: 4:00 PM – 4:50 PM Communicating Natural NHB Auditorium Disaster Impacts 5:00 PM – 6:30 PM Break 6:30 PM – 8:30 PM Keynote Dinner Illini Union Ballroom
SUNDAY, OCTOBER 8
TIME EVENT LOCATION 7:30 AM – 8:30 AM Check-in NHB 2nd Floor West Oral Session IV: 8:30 AM – 9:30 AM NHB Auditorium Cloud Microphysics (Part II) 9:30 AM – 10:00 AM Coffee Break NHB 2nd Floor West Oral Session V: 10:00 AM – 11:15 AM Mesoscale Predictability & NHB Auditorium Variability 11:30 AM – 1:00 PM Keynote Lunch Illini Union Ballroom 1:00 PM – 1:15 PM Closing Remarks Illini Union Ballroom
4 CONFERENCE SESSIONS
Remote Sensing of Mesoscale Systems This session focuses on the applications of remote sensing of mesoscale systems, including but not limited to: • Current and future improvements of datasets to better understand the formation and decay of mesoscale structures • Present state of observing air-sea interactions pertaining to the development of tropical and mid-latitude mesoscale systems • Development of applications for processing, calibrating, assimilating, and analyzing observations
Observations of Cloud Microphysics Cloud microphysical research is crucial for refining quantitative precipitation forecasts, reducing uncertainties in cloud-aerosol feedbacks on anthropogenic radiative forcing, and improving understanding of aerosol physics. Abstracts are invited for observational studies on cloud and precipitation physics, cloud chemistry, and cloud-aerosol interactions. Key areas of research include: • Measurement techniques (of cloud and precipitation properties) and uncertainties • Mixed-phase and tropical clouds • Cloud and precipitation chemistry • Cloud-aerosol interactions
Urban Environment and Society Rapidly growing population centers pose difficult socioeconomic and environmental challenges. Submissions concerning advances in observational and modeling studies of urban areas can cover local to global scales, including but not limited to: • Urban hydrology and ecology • Pollution and urban geochemistry • Societal, economic, and health impacts of urbanization • Influence of urbanization on weather and climate
The Mesoscale: Short-term Predictability and Long-term Variability Advances in mesoscale modeling are essential for minimizing uncertainties and biases in short-term mesoscale prediction and for improving knowledge on the frequency and severity of mesoscale phenomena in a future climate. Abstracts are invited for, but are not limited to, the following topics: • Improving parameterizations for simulating mesoscale processes • Application of data assimilation in model development and performance • Forecasting techniques and tools used in short-term mesoscale prediction • Changes in long-term variability of mesoscale phenomena • Understanding mechanisms corresponding to the life cycle of mesoscale systems
5 Weather, Climate, and their Impacts on the Midwestern United States We welcome observational and modeling research pertaining to Midwest weather and climate including but not limited to the following topics: • Meeting societal agricultural needs in the late 21st century • Future Midwest regional climate variability • Limiting risk and complacency associated with extreme weather events • The future role of renewable energy in the Midwest
OPEN FORUM SATURDAY, OCTOBER 7 | 4:00 PM – 4:50 PM
How to Communicate Natural Disaster Impacts from an Operational Forecasting Perspective
With devastating natural disasters (such as the recent events of Hurricanes Harvey, Irma, and Maria), scientists and forecasters must communicate the severity of these events and their risks in a way that allows individuals to take appropriate action without causing public panic. Adding to the complexity is how to communicate forecast uncertainty without having the forecast disregarded. This open forum will be co-facilitated by Dr. Louis Uccellini and Tom Skilling (our keynote speakers). They will address the topic, lead and facilitate discussion, and answer questions. We encourage you to think on this topic ahead of time and bring questions with you to this section of the conference.
6 ORAL SESSION I: REMOTE SENSING OF MESOSCALE SYSTEMS SATURDAY, OCTOBER 7 | 9:15 AM – 10:30 AM
Fine-scale Structure of the 2-3 February 2015 Nor’easter using high-resolution HIAPER Cloud Radar Observations
Andrew Janiszeski1, Robert Rauber1, Greg M. McFarquhar1,2, Brian F. Jewett1, Scott Ellis3 1Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, 2School of Meteorology, University of Oklahoma, 3National Center for Atmospheric Research
On 2 February 2015, the HIAPER Cloud Radar (HCR) aboard the National Center for Atmospheric Research Gulfstream-V High-Performance Instrument Airborne Platform for Environmental Research (HIAPER) aircraft flew over a Nor’easter cyclone along six flight legs, all between the northern tip of Delaware Bay and Bangor, Maine, to observe the fine- scale structure of the storm. The HCR is a W-band, dual-polarization, Doppler research radar which records reflectivity, radial velocity, spectral width, and linear depolarization ratio with a 0.7º beam pointed at nadir. The range resolution used this day was 19.2 m with the along track resolution between 20 and 200 m, depending on radial distance. The air mass structure, vertical motions, boundary layer structure, cloud-top generating cells, layers of turbulence and other fine-scale features characterized using cross- sections of the detailed HCR observations of reflectivity, radial velocity, spectral width and linear depolarization ratio were often on a scale of 5 km or less, and varied significantly with horizontal distance. Air mass origin and history is determined using back trajectories from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. This allowed characterization of the air mass structure. By overlaying thermodynamic fields from the Weather Research and Forecasting (WRF) model, the air mass structure, layers of stability/instability, and frontal boundaries are related to the generating cells, elevated convection, gravity waves, boundary layer circulations, and other features observed by the HCR within the Nor’easter.
7 Analysis of PECAN 2015 MCSs utilizing airborne- and ground-based Doppler observations and airborne in-situ microphysical data
Daniel M. Stechman1, Robert M. Rauber1, Greg M. McFarquhar, Michael M. Bell, Brian F. Jewett1, Robert A. Black, Terry J. Schuur 1Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
During the summer of 2015, numerous mesoscale convective systems (MCSs) were observed as a part of the Plains Elevated Convection at Night (PECAN) experiment. The NOAA P-3 was outfitted with the X-band (3.2 cm wavelength) NOAA Tail Doppler Radar (TDR), providing for high resolution remote sensing of reflectivity and radial Doppler velocity. Additionally, Optical Array Probes (OAPs) were mounted on the NOAA P-3 and their data used to compute particle number, sizes, and shapes. A subset of the TDR data collected during missions containing microphysical spiral ascents/descents has been synthesized with data from several ground-based radars using the Spline Analysis at Mesoscale Utilizing Radar and Airborne Instrumentation (SAMURAI) technique. These SAMURAI analyses provide a detailed estimate of the kinematic and radar reflectivity structure during several periods of system evolution. Data collected by the OAPs during these spirals were processed by the University of Illinois OAP Processing Software, allowing for the generation of vertical profiles of particle mass and number distributions, total water content, total number concentration, and median mass diameter. When considered in the context of the SAMURAI analyses, these profiles and accompanying profiles of in-situ aircraft relative humidity and temperature help explain how the microphysical cooling processes occurring in various regions behind the MCS leading convective line influenced the system dynamics. The relationship between diabatic cooling and the flows within this nocturnal elevated MCS will be discussed.
8 Novel Radar Observations of Convection near the Sierras de Córdoba, Argentina
Jake Mulholland, Robert Trapp, and Stephen Nesbitt Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Satellite observations have revealed that the world’s most intense convective storms occur across subtropical South America. This convection has been linked to damaging wind gusts, large hail, and tornadoes across regions such as Argentina. The satellite data fail to reveal the time evolution of these storms and thus, how convective mode/evolution relates to the extreme intensity. This research is particularly interested in how isolated convection, initiated across the higher terrain of the Sierras de Córdoba in Argentina transitions to relatively larger mesoscale convective systems. As part of a new (2015) observing network in Argentina, a C-band, dual-polarization radar was installed in Córdoba, now allowing for characterization of convective storm properties in the region surrounding the Sierras de Córdoba. Radar reflectivity and radial velocity were used to characterize features of convection over a 3 ̊ x 2.5 ̊ domain centered on the Córdoba radar. A total of 85 convective-storm cases were identified between July 2015 – April 2016; the analysis of data from the 2016 – 2017 warm season is ongoing. Cases were grouped by convective mode, initiation location/time, and time between initiation and upscale convective growth. Preliminary results indicate that 10 (12%) of the cases were predominately discrete-supercell, 20 (24%) discrete-non-supercell, 25 (29%) multicell- organized, and 30 (35%) multicell-unorganized. Environmental characteristics associated with the convective modes and pathways of upscale convective growth were analyzed using ERA-Interim reanalysis composites. These analyses have been undertaken in preparation for RELAMPAGO (Remote sensing of Electrification, Lighting, And Mesoscale/microscale Processes with Adaptive Ground Observations (1 November – 15 December 2018; https://publish.illinois.edu/relampago/).
9 ORAL SESSION I: URBAN ENVIRONMENT & SOCIETY SATURDAY, OCTOBER 7 | 9:15 AM – 10:30 AM
Understanding Effects of Forest Revitalization on the Seasonal Albedo Cycle in Ithaca, NY
C. Bieri, N. Mahowald Cornell University, Ithaca, NY
Changes in land use and land cover have occurred due to numerous societal and environmental factors over the course of the Earth’s history. Recently, human-induced land use changes in the United States have occurred in the form of large-scale deforestation within the last 30 to 40 years. Now, as modern societies endeavor to mitigate the effects of a changing climate, reforestation efforts have emerged. For instance, in Ithaca, NY, USA, the site of Cornell University, there are plans to covert unused lands (mostly abandoned croplands) owned by the university to native forests. Trees act as effective terrestrial carbon sinks, ideal for taking up excess atmospheric carbon that contributes to climatic warming. Reforestation, however, can cause land surfaces to become visibly darker, lowering the amount of shortwave solar radiation reflected at Earth’s surface (albedo) and resulting in radiative warming. Through analysis of two satellite-based datasets, this study estimates surface albedo changes due to land cover transitions in Ithaca and the surrounding region, as well as shortwave radiative forcings induced by these changes. We find these forcings to be mostly positive, indicating that changes in albedo are a source of warming associated with reforestation. However, other geophysical parameters and their forcings must also be considered to gain a more comprehensive understanding of the net climatic effects in such land cover change scenarios.
10 Seasonal Variation of the PM2.5 Diurnal Cycle over the Contiguous United States
Remy CrowleyFarenga, Nicole Riemer, Larry Di Girolamo Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
PM2.5 penetrates deeply into the human respiratory system and can cause severe, deleterious health effects. This research aims to describe the intra-annual spatiotemporal variation of PM2.5 over the contiguous United States using observations from over 400 ground-based monitors. The observations span 01/01/2012 - 12/31/2015. Average diurnal cycles are constructed for each ground-based monitor for each season, winter and summer by taking the median across the hour for the specified months in over the 4-year period. The diurnal cycles are then normalized to isolate the spectral characteristics, and fed into SciKit Learn’s K Means clustering algorithm to describe their spatial variation. We find that 2 clusters are ideal for minimizing the residual sum of squares between points in the clusters and their centroids, and we categorize them by region. We find that each cluster’s average diurnal cycle displays bimodal oscillation with variation in the time and relative amplitude of minima and maxima. Compared to winter, the cycles in summer showed shallower minima and lower frequency in variation. We also find that each cluster’s mean of the average diurnal cycle is approximately 10 µ�/m3 with an amplitude of 2-3 µ�/m3, with values slightly higher in the winter than the summer.
11 ORAL SESSION II: OBSERVATIONS OF CLOUD MICROPHYSICS (I) SATURDAY, OCTOBER 7 | 11:00 AM – 12:00 PM
Interactions of aerosols above clouds over the South East Atlantic Ocean. An overview of ORACLES 2017
Rose Miller1, Greg McFarquhar, Siddhant Gupta1, Mike Poellot, Joseph O’Brien, David Delene 1Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
The ObseRvations of Aerosols above Clouds and their intEractionS (ORACLES) project provided in-situ measurements and remotely sensed retrievals of aerosol and cloud properties over the South East Atlantic off the coast of Sao Tome and Principe during August- September 2017. Biomass burning aerosol from Southern Africa is advected toward the South East Atlantic at elevated altitudes and overlies the ubiquitous stratocumulus cloud deck over the ocean. The aerosols subside farther from the coast so that the vertical displacement between the clouds and aerosols varies, and whose effect on aerosol-cloud interaction is poorly known. During the ORACLES field campaigns, the NASA P3-Orion was equipped with in-situ probes measuring aerosol and cloud microphysical properties, while the NASA ER-2 was equipped with remote sensors retrieving cloud and aerosol quantities.
12 Characterizing Drop-Size Distributions of Light Rainfall During LPVEx and ORACLES
Andrew M. Dzambo and Tristan L’Ecuyer University of Wisconsin – Madison, Madison, WI
Accurate measurements of cloud and precipitation properties are critically important toward understanding the global energy budget and water cycle. CloudSat provides global coverage of cloud cover with its W-band radar, and the 2C-RAINPROFILE (2C-RP) rainfall retrieval algorithm enables global characterization of rainfall for climate studies. One of the largest sources of uncertainty in 2C-RP is the drop-size distribution (DSD) assumption, but validating this assumption is challenging due to the lack of coincidental in-situ cloud probe and W-band radar measurements. During the Light Precipitation Validation Experiment (LPVEx) and ObseRvation of Aerosols above CLouds and their intEractionS (ORACLES) Experiment, airborne W-band radar and cloud probes respectively captured numerous profiles of precipitating clouds and in-situ DSD measurements. The DSDs measured in precipitating clouds from LPVEx and ORACLES are compared with the Marshall & Palmer (MP) and Abel & Boutle (AB) DSDs, both of which have been used for CloudSat’s operational 2C-RP algorithm. Presently, we find that the AB DSD performs much better than MP, but some large uncertainties remain especially for very small drop sizes. Additionally, Mie reflectivity measurements derived from cloud probe DSD measurements are compared with W-band reflectivity measurements during spiral-descent legs.
13 Evaluation of Triple-Frequency Radar Retrieval of Snowfall Properties using Coincident Airborne In-Situ Observations during OLYMPEx
Randy Chase Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Approximately 85% of mid-latitude surface precipitation involves ice processes1, such as riming or aggregation of ice particles. Thus, in order to retrieve ice water content and snowfall rate a priori assumptions of particle characteristics such as density and shape are required. Previous literature has provided evidence that a triple-frequency radar would provide additional information on particle shape, density and mean size. As the first study to investigate airborne triple-frequency radar observations coincident with airborne in-situ microphysical observations, this study examines if the retrieval of particle shape, particle bulk density and particle mean size are consistent with intrinsic DFR theory. Data from the Olympic Mountains Experiment (OLYMPEx) resulted in 1.3 hours of coincident radar data with microphysical data that showed observations in both the aggregate and spheroidal region of the DFR plane. Analysis of a case study supports past investigations showing increased bulk density with increased DFR between Ka- and W-band. Meanwhile, bulk statistics resulted in limited variability of bulk density and mean diameter with variable values of DFR between Ka-W-band.
1Field, P. R., and A. J. Heymsfield (2015), Importance of snow to global precipitation, Geo- phys. Res. Lett., 42, 9512–9520, doi:10.1002/2015GL065497.
14 Microphysical Influences on Cold Pool Properties
Holly M. Mallinson, Sonia Lasher-Trapp University of Illinois at Urbana-Champaign, Department of Atmospheric Science, 1301 W. Green Street, Urbana, IL 61801, United States
An outstanding question surrounding deep cumulus convection is the inter-relations between updrafts, downdrafts, and cold pools and how they are influenced by both external and internal factors. External factors such as environmental CAPE and vertical wind shear affect the overall storm dynamics, while internal factors related to microphysical processes also influence, and are influenced by, the storm dynamics. This study investigates the hydrometeor types and associated microphysical processes that are most important for determining cold pool size, depth, and strength. Numerical simulations of deep convection observed during the MC3E field campaign are produced with the CM1 model using the NSSL (6-class, double moment) microphysics scheme and a grid spacing of 250 meters. Sensitivity tests run with varying amounts of CCN are used to identify the role of the warm-rain process. Microphysical budgets are calculated to quantify the contributions of melting/sublimating graupel and hail, and evaporating rain. Three-dimensional visualizations of these quantities, along with the associated downdrafts and the resulting cold pools, help to illustrate the most important microphysical factors in controlling the cold pool characteristics.
15 ORAL SESSION III: WEATHER & CLIMATE IMPACTS ON THE MIDWESTERN US SATURDAY, OCTOBER 7 | 1:30 PM – 2:30 PM
Impact Analysis of Climate Change and Adaptive Management Strategies on Multiple Food Crops Using Two Land Surface Models
Tzu-Shun Lin and Atul K. Jain Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Climate change is most likely to impact global food supply and security. Currently, models outcome of future crop productivity are quantitatively diverse because of uncertainties in projected climate change trends and variabilities, adaptive human management practices and parameterization processes within land surface models. To study impacts of climate change and management practices on agricultural production over the 21st century, we apply the integrated biogeophysical and biogeochemical models, the Integrated Science Assessment model (ISAM), for row crops (corn, soybean and wheat) in the United States. This modeling framework accounts for dynamic crop growth processes with adaptation of photosynthesis, crop-specific phenology, biomass accumulation, leaf area development and the effects of temperature, light and soil water and nitrogen availability on crop photosynthesis and temperature control on crop phenology and carbon allocation. The results are compared to historical agricultural census dataset and the corresponding simulations performed with the Community Land Model (CLM4.5). Both models are driven with historical atmospheric forcing data (1901-2005), and projected atmospheric forcing data (2006-2100) with 4.5 and 8.5 representative concentration pathway (RCP) scenarios from community earth system model (CESM) simulations. For each period of atmospheric forcing data, we implement optimal agricultural management practices including irrigation and nitrogen fertilizer to evaluate the crop yields with adaptation. The study is of importance to consider carbon-temperature-water-nitrogen interactions and helps to understand the uncertainties in the model estimated potential productivity of food crops under climate change.
16 The Implications of Growing Bioenergy Crops on Water Resources, Carbon and Nitrogen Dynamics
Xiaoming Xu, Yang Song, Atul K Jain Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
What is the potential for the crops Corn, Miscanthus and switchgrass to meet future energy demands in the U.S.A., and would they mitigate climate change by offsetting fossil fuel greenhouse gas (GHG) emissions? The large-scale cultivation of these bioenergy crops itself could also drive climate change through changes in albedo, evapotranspiration (ET), and GHG emissions. Whether these climate effects will mitigate or exacerbate climate change in the short- and long-term is uncertain. This uncertainty stems from our incomplete understanding of the effects of expanded bioenergy crop production on terrestrial water and energy balance, carbon and nitrogen dynamics, and their interactions. This study aims to understand the implications of growing large-scale bioenergy crops on water resources, carbon and nitrogen dynamics in the United States using a data-modeling framework (ISAM) that we developed. Our study indicates that both Miscanthus and Cave-in-Rock switchgrass can attain high and stable yield over parts of the Midwest, however, this high production is attained at the cost of increased soil water loss as compared to current natural vegetation. Alamo switchgrass can attain high and stable yield in the southern US without significant influence on soil water quantity.
17 Quantifying the influence of Natural Variability on changes in Temperature Extremes over the CONUS
Emily Hogan Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Extreme weather events are responsible for some of the largest losses of human life. Lack of long-term data has limited the attempt to quantify how extreme temperature events will evolve within a changing climate, though studies suggest that they are becoming more frequent and severe. General Circulation Models (GCMs) have shown skill in capturing the mean statistics of variables. Here, we also compare the skill of the models based on how well they capture the tail ends of the distribution, as these encompass the events that drive damages. We use Generalized Extreme Value (GEV) theory, a branch of statistics often used to evaluate far tails (extremes events) in temperature distributions. We evaluate skill and projections over different spatial scales in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and in a 50-member ensemble using a low-resolution version of the Community Earth System Model (CESM). CESM shows a cold bias when modeling the statistics of observed temperature extremes over the last 50 years. We find a positive shift in projected distributions for the location and scale parameters over the CONUS, but less change in the shape parameter for both ensembles. We additionally determine time dependent variations in the GEV parameters of each ensemble member and how these differ between an ensemble sampling structural model differences (CMIP5) and an ensemble sampling initial conditions uncertainty (CESM).
18 The Influence of a Pre-Existing Snow Pack on an Extratropical Cyclone
Robert C. Fritzen, Dr. Walker Ashley, Dr. Victor Gensini Department of Geographic and Atmospheric Sciences, Northern Illinois University
Baroclinic instability is one of the primary drivers of the extratropical cyclogenesis and maturation. During the cool-season months in the continental high- and mid-latitudes, modifications in lower tropospheric thermal gradients and, thus, baroclinity can occur due to localized changes in land-surface snow coverage. An assessment of how possible changes in seasonal snow pack effects extratropical cyclone tracks and intensity is important since these storms produce a large proportion of the hazards and precipitation in these regions. Using a numerical modeling framework, this research analyzes the effects of enhanced, as well as reduced, snow pack on a selected North American cyclone case that was driven primarily by low-tropospheric thermal gradients and related baroclinity. Several ensemble families of the Weather Research and Forecasting model (WRF) were generated to study the effects of changing snow pack character on the selected storm. It was hypothesized that under an enhanced snow pack, the lower tropospheric thermal gradient near the storm would be more intense, resulting in stronger baroclinity. This enhancement of a fundamental ingredient for extratropical system formation and intensification was expected to promote a stronger storm characterized by a deeper central sea level pressure, and possibly, a shift in track and resulting precipitation fields. Conversely, the reduced snow pack simulations are expected to result in reduced baroclinity and storm intensity. Results from the experimental modeling framework demonstrated however, that low level baroclinity modified the frontogenesis of the cyclone, changing the character of precipitation in coverage and intensity, while the cyclone’s intensity remained unchanged.
19 ORAL SESSION IV: OBSERVATIONS OF CLOUD MICROPHYSICS (II) SUNDAY, OCTOBER 8 | 8:30 AM – 9:30 AM
Climatic Trend in Cloudiness over South Asian Monsoon Region
Soumi Dutta1, Dr. Sagnik Dey1, Prof. Larry Di Girolamo2 1Indian Institute of Technology Delhi, India, 2University of Illinois at Urbana-Champaign, USA
Examining climatic trends of cloud characteristics is critical to understand climate change, because of the dual nature (short wave cooling and long wave heating) of clouds in modifying the Earth's radiation budget. In 2005, GEWEX (Global Energy and Water Cycle Experiment) Cloud Assessment was initiated to address this issue. There is not enough study over the South Asian monsoon region focusing on long-term changes in cloud characteristics. In the present study, cloud data from passive remote sensing (ISCCP) for the period 1983- 2008 and ground based station datasets (EECRA - Extended Edited Synoptic Cloud Report Archive) for the period 1971-2009 over land and 1952-2009 over ocean are analyzed for the same region. These two datasets are chosen to get multi-decadal variability in cloudiness. High and low cloud fractions are showing opposite trends over land and ocean for the monsoon season (JJAS). High clouds are reducing over land, whereas low clouds are increasing. On the other hand, high clouds are increasing and low clouds are decreasing over ocean. Cloud distribution shows large heterogeneity both in spatial and seasonal timescale in this region. The observed cloud pattern is explained in terms of changing meteorology under warming climate in this region. Further, CERES and MODIS products for the period of 2000-2013 are used to understand the variability in net cloud radiative forcing (CRF) and its relation to the variability in cloud macrophysical and microphysical properties. Except in the monsoon season where net CRF is -27.5±15 W m-2 over the Indian landmass; SW cooling by the clouds is almost cancelled by LW warming in the other seasons.
20 Measurements of the HDO/H2O Isotopic Ratio in the Asian Summer Monsoon
Benjamin Clouser Department of Physics, University of Chicago
The Asian monsoon is one of the world’s largest weather systems, and forms one of the main pathways by which water vapor enters the UT/LS. The Chicago Water Isotope Spectrometer (Chi-WIS) participated in the July/August 2017 StratoClim campaign, measuring water vapor and its isotopic composition between 12 and 20 kilometers. We can use these measurements to diagnose the importance of overshooting convection in water transport by the Asian monsoon, and to characterize the extent to which convection-driven water vapor perturbations propagate to higher altitudes and contribute to the overall stratospheric water budget. In addition, satellite measurements of the HDO/H2O ratio of UT/LS water, a strong tracer of convective origin, have suggested significant differences in transport behavior between the Asian and North American monsoons, with strong UT/LS enhancement occurring only over North America. Here I discuss the instrument, its performance, and show preliminary results from the campaign.
21 An Investigation of Entrainment in Developing Thunderstorms with Numerical Simulations
Bryan Engelsen and Sonia Lasher-Trapp Dept. of Atmospheric Sciences, University of Illinois at Urbana-Champaign
It has been observed in nature that the early stages of deep cumulus clouds portray thermal-like behavior, with multiple, discrete toroidal circulations near their tops. However, historically numerical simulations of mature supercells appear to behave more like jets, with turbulent, yet continuous ascent. Correctly modeling this behavior has implications on entrainment. Entrainment is the process of mixing environmental air into the cloud by turbulent eddies, which leads to dilution, i.e. the reduction in the cloud water content and buoyancy. Thermals entrain more quickly than jets in laboratory studies. Thus, accurate representation of entrainment is essential for the prediction of storm development, longevity, and its precipitation. We test the hypotheses that a transition might occur in supercell thunderstorms from thermal-like behavior in the earliest stages to jet-like behavior thereafter, that similar to laboratory results the entrainment rate is less for jet-like behavior compared to thermal-like behavior, and that the behavior in numerically-simulated storms may be influenced by the technique used to initiate it. Two sets of simulations of developing supercell thunderstorms are initiated with the Weisman sounding, using two different initiation techniques within the CM1 model. For one set, an instantaneous, initial thermal perturbation is used (i.e. a warm bubble), and for the other set a Gaussian heat flux at the bottom of the domain ramps up, is sustained, and then decays over a period of 20 minutes. Entrainment is calculated from the mass flux in and out of the storm core, defined by thresholds of positive vertical velocity and total water and ice mass. Initial results will be presented using 3D animations, vertical profiles of entrainment, and cross sections through storm cores.
22 Machine Learning Program to Automatically Classify Ice Crystal Habit
Javier Villegas Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Knowledge about the light scattering and absorption properties of cloud particles is crucial to know the effect clouds have on climate. Accurate information about the size, shape and phase of cloud particles are needed to represent cloud processes in climate models. Current programs use parameters (i.e. maximum dimension, projected area, perimeter) from pictures obtained by aircraft mounted cloud particle imagers to classify the ice crystals by shape, but these programs are not nearly as precise or accurate enough as manual classification, which is tedious, time consuming, and subjective. A more reliable automatic method to identify crystal shape would be a powerful tool for scientists to further study radiative transfer through clouds. In this project, a machine learning program is created using a convolution neural network to more accurately and quickly identify ice crystal shapes in clouds. Currently it classifies 8 crystal habits (bullet rosette, column, plate, etc …), with 78% accuracy. The program is still being improved to show skill and practicality over Lindqvist 2012 which uses principle component analysis coupled with Bayesian and kNN machine learning techniques to achieve 81% accuracy with 8 ice crystal habits.
23 ORAL SESSION V: THE MESOSCALE – SHORT-TERM PREDICTABILITY & LONG-TERM VARIABILITY SUNDAY, OCTOBER 8 | 10:00 AM – 11:15 AM
Moisture Discrepancies of WRF Forecasts of Great Plains Nocturnal Low-Level Jet-Driven MCSs during their Initiations
Nicholas J. Vertz and William A. Gallus Jr Department of Geological & Atmospheric Sciences, Iowa State University
Nocturnal Mesoscale Convective Systems (MCS) frequently affect the Great Plains every summer, and a contributing factor to their initiation is the Great Plains low level jet (LLJ). Moisture brought in by the LLJ plays a large role in the formation and sustenance of MCSs, and thus errors in model depictions of specific humidity are likely to play a role in the accuracy of the forecasts of the MCSs. In this study, the Weather Research and Forecast (WRF) model is used to examine the relationship between displacement errors for the initiating MCSs and moisture errors that are present in the WRF model output. A total of 18 cases are examined -- 9 type A cases representing weakly forced synoptic regimes, and 9 type C cases for strongly forced synoptic regimes. Rapid Update Cycle (RUC) analyses were used as our in-situ observation data. The WRF was configured to use the WSM6 microphysics scheme and the Yonsei University (YSU) planetary boundary layer scheme. After splitting all MCS events into their respective type A and C cases, a significant correlation was found between the displacement error distances for the initiating MCS in the WRF model and the average moisture content errors within subdomains of 125 km by 125 km centered near and upstream from where the MCSs initiated. The east-west displacements had a larger correlation with respect to moisture errors than both the north-south displacements and the total displacement. Much of the significant correlation values came from lower levels of the atmosphere up to 1500 m above ground level. Correlations were small for layers higher than this level.
24 An examination of moist absolutely unstable layers observed during period of elevated convection
Paula Sumrall and Patrick Market School of Natural Resources, University of Missouri
As a part of the Program for Research on Elevated Convection with Excessive Precipitation (PRECIP), dozens of soundings were collected over 8 intense observing periods (IOP). Of those cases, 6 IOPs with a total of 32 soundings, were analyzed to determine each radiosonde’s path in both the horizontal and vertical and compare the data returned to the observed reflectivity for the same x,y,z location. This allowed us to determine whether or not some radiosonde flights, which terminated early, were because of interaction with a significant precipitation core or some other cause. This activity also revealed two cases where the existence of moist absolutely unstable layers (MAULs) was very likely. In both cases the MAUL was also the location of a notable increase in reflectivity (5-15 dBZ) over the depth of the MAUL. No MAUL was identified in the absence of precipitation, and in both cases the atmosphere remained saturated for at least 50 hPa more, thus ruling out the possibility of fictitious cooling through evaporation or sublimation. Above the MAUL layer, no single trend in reflectivity is evident. These two soundings will be further examined and placed in the context of the existing literature on MAULs.
25 Perryville Tornado Mesoanalysis
Matthew Roark and Robert Pasken Department of Earth and Atmospheric Sciences, Saint Louis University, Saint Louis, Missouri 63108
On February 28, 2017, the Quantum Weather® local model predicted that a tornado would form in Illinois across the Mississippi River from Perryville, Missouri. Around 7:55 PM CST, a large EF-4 tornado with peak winds of 185 mph touched down in Perryville. By 8:57 PM, the long-lived tornado had tracked 50 miles resulting in 12 injuries and one fatality. Afterward, a study was conducted in order to determine why the EF-4 tornado occurred in Perryville, Missouri. Data was collected from the Quantum Weather® mesonet and National Weather Service WSR-88D radar. These data were compared with one another in order to determine the small-scale features which effected the supercell that produced the Perryville Tornado. Data from the mesonet was compared with the radar data in order to determine if any preemptive signs of a mesoscale vortex signature were apparent in the mesonet surface observations.
26 Impact of Terrain Resolution on Precipitation Formation in a Simulated Orographic Cloud
Shaowen A. Chen1,2, Lulin Xue3, Sarah A. Tessendorf3 1Significant Opportunities in Atmospheric Research and Science (SOARS) Program, National Center for Atmospheric Research/University Corporation of Atmospheric Research, 2Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, 3Research Application Laboratory, National Center for Atmospheric Research
Orographic precipitation is the primary water resource in the Western United States. Snowmelt from orographic precipitation in the mountains of Idaho powers over a dozen hydroelectric power plants and irrigates over 2 million acres of land. Although advances have been made in understanding orographic precipitation formation and associated cloud microphysics, investigations on the relationship between precipitation and complex terrain on a fine grid scale are still limited. This research aims to better understand the impact of terrain height on orographic clouds, and their subsequent precipitation formation, using a high-resolution simulation (900-m grid spacing) of the Weather Research and Forecasting (WRF) model. This modeling study is based on a case from the SNOWIE (Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment) field campaign that occurred on 31 January 2017. In this case, a shallow cloud formed with an abundance of supercooled liquid water and strong winds, which were over 33 ms-1 at around 4875 m. Modifications were made to the resolution of the WRF topography to explore the role of terrain on the formation of natural orographic precipitation in this case. The results of topography sensitivity tests will be described, including the dynamics, cloud fields, and precipitation from a control simulation (using default high-resolution terrain) and a sensitivity simulation with 20 times coarser resolution terrain data.
27 Model Comparison of the 22-24 January 2016 Nor’easter
Holly M. Mallinson1, Stephen D. Nicholls2, Amber E. Emory3 1University of Illinois at Urbana-Champaign, Department of Atmospheric Science, 1301 W. Green Street, Urbana, IL 61801, United States, 2Joint Center for Earth Systems Technology, University of Maryland-Baltimore County, Baltimore, MD 21250, United States, 3Mesoscale Atmospheric Processes Laboratory, NASA-Goddard Space Flight Center, Code 612, 8800 Greenbelt Road, Greenbelt, MD 20771, United States
The 22-24 January 2016 nor’easter was rated the fourth most severe snowstorm to impact the northeast United States since 1950 and significantly affected the urban corridor, a region home to over 50 million people and of great significance to the U.S. economy. Numerical weather prediction models correctly predicted snowfall totals exceeding 60 centimeters (~2 feet) over the southern Mid-Atlantic, yet snowfall totals from northern New Jersey and into southern New England were under predicted by 30 centimeters or more. This study uses a nine-member ensemble of Weather Research and Forecasting (WRF) model simulations, varying only by initialization time (3-5 days prior to the event) or model input source (ECMWF, NAM, or GFS model analysis), to investigate how well these simulations addressed the nor’easter from its initial cyclogenesis through maturity. Particular focus was given to the storm’s northern precipitation edge (specifically, mesoscale snow bands, precipitation type, and radar reflectivity) during the storm’s mature phase when snowfall total varied greatest from observations. Ensemble model output was validated against rawinsondes profiles, NEXRAD WSR-88D radar reflectivity, and ECMWF model analysis. Of the nine members, only the ECMWF-based WRF run initialized four days prior to the event (Jan. 20) brought snowfall to Long Island which was consistent with ground validation measurements. Consistent with model analysis and NEXRAD data, this run accurately resolved the location and intensity of the main deformation zone along the Mid- Atlantic coast and also generated a strong, mesoscale snow band propagating from central New Jersey into northern New York City.
28 POSTER SESSION: REMOTE SENSING OF MESOSCALE SYSTEMS SATURDAY, OCTOBER 7 | 2:30 PM – 3:45 PM
Microphysical Analysis of a Quasi-Linear Convective System — A PECAN Case Study 20 June 2015
Marchi, A. M.1, Stechman, D.1, Rauber, R. M.1, McFarquhar, G., Jewett, B. F.1, Bell, M. M. 1Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
An analysis of a quasi-linear convective system (QCLS) observed on 20 June 2015 during the Plains Elevated Convection at Night (PECAN) project is presented. On this day, the NOAA P-3 aircraft gathered data in a nocturnal mesoscale convective system (MCS) that formed over western South Dakota, performing dual-Doppler flight legs and spiral descents and ascents in the stratiform precipitation regions behind the convective line. The analysis examines the effects of evaporation and sublimation on nocturnal inversions during the MCS evolution. Multiple-Doppler syntheses were completed using NOAA Tail Doppler Radar and WSR-88DP data collected within the region of several spirals. Vertical profiles of particle number and mass distributions, total water content, total number concentration, and median mass diameter and accompanying profiles of relative humidity and temperature were combined with the multiple-Doppler syntheses to relate the microphysical characteristics of the QCLS transition zone to the storm system evolution.
Poster Number: 01
29 Hydrometeorological Study over Carcarana River Basin in Argentina
Sujan Pal, Francina Dominguez Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
This study gives an overview of a hydrometeorological field campaign and coupled modeling study to understand the coupled mechanisms driving the life cycle of intense organized convection and associated hydrologic response of the terrestrial system. The physical processes and land-atmosphere exchanges of moisture and energy is very crucial in regions where organized mesoscale convective systems (MCSs) contribute to extreme precipitation causing severe weather, including flash floods and riverine floods. The Carcarana river basin in Argentina stretches from the foothills of Andes and Sierras de Cordoba to eastern Argentina and is a “hotspot” for land-atmosphere interactions (Ruscica et al. 2014). Complementing the RELAMPAGO project to understand the multi-scale characteristics of convective events in this region, the main science questions we are trying to address in this study is – How does land cover heterogeneity impact initiation and growth of convective precipitation at the local and mesoscale through land atmosphere interaction? Being aware of the fundamental scientific processes in hydrometeorology, improvement in fully-coupled hydrometeorological models can be achieved which will ultimately help in improving predictive skills of high impact weather events. The mesoscale modeling study is done using WRF-WRF-Hydro coupled system which is introduced here. The data used to force WRF-Hydro is precipitation from Tropical Rainfall Measurement Mission (TRMM) and Global Land Data Assimilation Systems (GLDAS). Preliminary results reveal that the modeling framework works well for the basin and might be used as an operational forecasting tool.
Poster Number: 02
30 Observations of the Thunderstorms Early Life Cycle in southeastern Brazil: Satellite Multi- Channel Model for Warning System
Lina Zea1, Luiz Machado2, Enrique Mattos3 1University of Illinois at Urbana-Champaign, 2National Institute for Space Research, 3Federal University of Itajubá
The objective of this study was to identify typical cloud-top signatures of incipient thunderstorms and its early electrification process in satellite multi-channel observations as means of building a tool of thunderstorm detection based on brightness temperature and electrification life cycle association. The methods toward this objective have analyzed the data set of the CHUVA-Vale field campaign from 01 November 2011 to 31 March 2012 in southeastern Brazil; including multi-channel observations from the SEVIRI infrared fields, a radar-lightning co-located data set and a sample of 40 compact isolated thunderstorms. The methods sequence for 4 infrared fields comprises the parallax correction; the co-location of satellite and radar-lightning data; the selection of an evaluation area for thunderstorm detection, and the construction of brightness temperature relative cumulative-frequency distributions. Consequently, 4 thresholds resulted to be used in tandem for detecting the largest differentiation among the thunderstorm lightning time steps and the most significant cumulus cloud intensification to be attained. These thresholds described a representative behavior of the thunderstorms early electrification life cycle, and will allow a potential development of nowcasting tools at the boundary of subtropical regions using data from the MSG Satellite, and in the near future, using data from the GOES-16 Satellite.
Poster Number: 03
31 Investigation of Preliminary Results from the SNOWIE Field Campaign
Adam Springer1, Robert M. Rauber1, Scott Ellis2 1University of Illinois at Urbana-Champaign, 2National Center for Atmospheric Research
The Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE) field campaign operated from January 7, 2017 – March 17, 2017 in the Payette Basin just northeast of Boise, ID. The goal of this campaign was to use radar and in-situ measurements to observe seeded and natural orographic clouds to prove the efficacy of orographic cloud seeding over the Payette Basin. One of the platforms used was the Wyoming King Air aircraft equipped with the Wyoming Cloud Radar, a 3 mm wavelength cloud radar, which flew through, and collected data on orographic clouds to obtain fields of reflectivity and radial velocity. Preliminary results and analysis of several intriguing aspects of these natural and orographic clouds, including gravity waves, generating cells, and seeding signatures, are presented herein.
Poster Number: 04
32 Role of Multiscale Atmospheric Conditions in the Evolution of Convective Organization during MJO-1 of DYNAMO/CINDY/AMIE
Jeffrey D. Thayer and Deanna A. Hence University of Illinois at Urbana-Champaign
The multiscale atmospheric interactions that create a change in convective behavior in the tropical Indian Ocean, such as that which occurs during the passage of the Madden- Julian Oscillation (MJO), are not yet fully understood. This analysis examines the evolution of convection that occurred during an MJO event in late-October 2011 of the DYNAMO/CINDY/AMIE field campaign, which was chosen to highlight the transition in convective organization observed and to characterize the convection during this MJO in greater detail. This case study focuses on the region immediately surrounding the S-PolKa dual- polarization radar stationed on Addu Atoll (0.7°S, 73°E) in the central Indian Ocean, with environmental conditions provided by 3-hourly quality-controlled soundings and 6-hourly ERA-interim reanalysis data. The changes in precipitation areal coverage and vertical distributions of moisture and winds reveal two distinct convection periods at the beginning and end of the MJO passage over the radar. Shifts in reflectivity and dual-polarization characteristics of four precipitation types over these time periods showed a transition towards shorter bursts of more intense convective precipitation over a smaller portion of the radar domain. These convective elements displayed greater upscale organization as the surrounding environment gradually became more strongly sheared with greater instability, associated with persistent lower-level dry-air advection from the westerly wind burst. These bursts of convection, especially in the first time period, appeared with periodic dry-air intrusions into the central equatorial Indian Ocean. The changes in the vertical distribution of ice particles indicate that graupel progressively occurred over a greater depth, associated with the overall increasing intensity of convective precipitation, while other ice particle types occurred over shallower depths with decreased reflectivity values. This change in the aggregates and ice crystals signals a transition towards shorter residence times as a result of weaker stratiform precipitation with smaller or less abundant ice particles.
Poster Number: 05
33 POSTER SESSION: URBAN ENVIRONMENT & SOCIETY SATURDAY, OCTOBER 7 | 2:30 PM – 3:45 PM
Observed Influence of Vegetation Variability and Change on the Climate of South America
Divyansh Chug Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Land surface variability and change can affect the overlying atmosphere through biogeophysical and biogeochemical feedbacks. The goal of our work is to quantify the local and remote influences of vegetation on the climate of South America using observational records. We first analyze the spatio-temporal variability of vegetation over South America, with a special focus on the La Plata River basin. The analysis uses a 34- year (1981-2014) record of modified Enhanced Vegetation Index (EVI2) from the Vegetation Index and Phenology (VIP) datasets of the NASA MEaSUREs project, in addition to 17-year (2000-2016) remotely sensed Enhanced Vegetation Index (EVI) data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra and Aqua satellites. The dominant patterns of variability in space and time are analyzed using empirical orthogonal function/principal component (EOF/PC) analysis on a basin-wide scale. The dominant modes can be attributed to anthropogenic deforestation using observational records of land use change from the History Database of the Global Environment (HYDE), and to natural causes using observed records of terrestrial surface temperature and precipitation provided by the University of Delaware. The second part of the study analyzes how these dominant modes of variability affect the overlying atmosphere at the continental scale. We use generalized equilibrium feedback assessment (GEFA) to statistically quantify the observed seasonal impacts of dominant terrestrial and oceanic forcings on the South American climate.
Poster Number: 06
34 Introducing Water Tracers in Noah-MP
Huancui Hu Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Numerical water tracers are incorporated in the Noah land surface model with multiparameterization options (Noah-MP). This water tracer tool is designed to “tag” the water from precipitation events and track its movement into different storages and fluxes in the terrestrial system. The new perspectives provided by this tool are illustrated by two cases. In the first case, the tracers are used in a single-column simulation to estimate the residence times at different depths within the soil. We then compare our estimates with isotope observations in the published literature. In the second case, the water tracers are used to investigate the regional impacts of an extreme precipitation event on the timescales from days to seasons. Most of the extreme precipitation remains in the system as soil moisture, and contributes to local evapotranspiration and subsurface runoff months after the precipitation has occurred.
Poster Number: 07
35 Assessment of the GEFS/CFSv2 and the Effects of ENSO/NAO on Predictive Skill
Douglas Miller and Zhuo Wang Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Subseasonal to seasonal (S2S) prediction, with forecast lead times from 2 weeks to a season, is of considerable socioeconomic value as the products are utilized across many sectors (e.g. energy, agriculture, public health, etc.). In order to improve our current forecast capabilities, models must be continuously assessed in order to discover where improvements can be made. One particular focus is to identify sources of predictability and evaluate their representations in operational models. Low frequency climate modes are a key source of predictability on the subseasonal to seasonal time scales, and such modes may modulate prediction skill of the mid-latitude atmosphere. The 200-hPa geopotential height from the Climate Forecast System Version 2 (CFSv2) reforecasts are used to assess the effects that low frequency climate modes, specifically the ENSO and the NAO, have on the northern hemisphere winter predictability. In addition, the representation of teleconnections between tropics and extratropics in the CFSv2 are evaluated through the analysis of 200-hPa geopotential height, precipitation rate, and sea surface temperature data, with the objective to identify the windows of high predictability and assist in model improvements.
Poster Number: 08
36 A neural network based model for peak ionospheric parameters using Radio Occultation Data
Arka Mitra and S. Tulasi Ram Upper Atmospheric Division, Indian Institute of Geomagnetism, Mumbai, India
The COSMIC (FORMOSAT-3) mission was a joint US-Taiwanese project aimed at improving our understanding of meteorology, ionospheric research and climate using the GPS Radio Occultation Technique. The Big Data available through this mission, especially in the field of ionospheric research, provides us a way of understanding previously unknown relations, incorporating nonlinearities in models and bridging general gaps in our understanding of the upper atmosphere through the improved capabilities of Machine Learning. In the present work, we have utilized an improved Multi-Layered Perceptron (Neural Network) algorithm developed and improved primarily by Vladimir Krasnopolsky (NCEP/EMC/Marine Modeling and Analysis Branch, Camp Springs, MD) to create a global, two-dimensional model for the variation of peak ionospheric parameters (namely, peak ionospheric electron density, NmF2, and the height at which this density occurs, HmF2). Here, we take both a single global model approach and a gridded higher-resolution approach. These models are designed to take inputs of daytime, season, geolocation, solar forcing, geomagnetic condition and winds to predict the global peak parameters. Many known features of ionospheric behavior were extracted to within a 5 percent margin of error in the gridded approach, including (possibly) for the first time for an ionospheric model, the Equatorial Ionospheric Anomaly (EIA) was predicted over tropical latitudes. This improvement signals a need for the incorporation of Machine Learning algorithms to improve existing models in the atmospheric sciences.
Poster Number: 09
37 The Truck Blowover Algorithm for the Pikalert® System
Brittany Welch1, Amanda Siems-Anderson2, Seth Linden2, William Petzke2 1Significant Opportunities in Atmospheric Sciences, 2National Center for Atmospheric Research
Adverse weather conditions have an extreme impact on the ability to safely operate a motor vehicle, with over 5000 road weather fatalities occurring every year. These impacts are strongly felt along the 402-mile long Interstate 80 (I-80) corridor in Wyoming, where extreme weather occurs year-round at elevations between 6,000 and 8,600 feet. One of these extreme forms of weather, high winds, preferentially affects freight traffic due to their high profiles. Freight traffic makes up half of the daily traffic volume in this corridor; thus 50 percent of the vehicles traveling along I-80 are at high risk of being impacted by one of Wyoming’s most dangerous and common forms of road, wind. The Wyoming Department of Transportation (WYDOT), Federal Highway Administration (FHWA), and the National Center for Atmospheric Research (NCAR) are collaborating to combine vehicle data and weather data into applications that can aid in the drivers decision-making process when hazardous road conditions are present or expected as part of the WYDOT Connected Vehicle Pilot Deployment Initiative (WYDOT CV Pilot). With previous support from FHWA, NCAR developed The Pikalert System, which is capable of ingesting, quality checking, and interpreting weather and vehicle data and outputting warnings, advisories, and roadway conditions. The Pikalert System currently uses three algorithms for hazardous weather advisories and warnings, but lacks a wind algorithm, which is vital along the I-80 corridor. To address this shortcoming, a blowover algorithm was developed and added to the Pikalert System using a fuzzy logic methodology. A small group of case studies were used to assess the initial results of the algorithm, and based off of these results the weights and functions within the algorithm were changed to provide a more appropriate interest value output for each case. The algorithm was further verified against a seven year I-80 crash database. The resulting algorithm, along with the rest of the Pikalert System, will be available to the community as part of the open source code developed for the WYDOT CV Pilot.
Poster Number: 10
38 POSTER SESSION: OBSERVATIONS OF CLOUD MICROPHYSICS SATURDAY, OCTOBER 7 | 2:30 PM – 3:45 PM
Using Radar Data to Evaluate the Variability of Mass-Dimension Parameters Within Ice Clouds
Joseph A. Finlon1, Greg M. McFarquhar1, Robert M. Rauber1, Stephen W. Nesbitt1, Wei Wu1,2, Michael R. Poellot3 1Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, 2National Center for Atmospheric Research, Boulder, CO, 3Department of Atmospheric Sciences, University of North Dakota, Grand Forks, ND
Mass-dimension (m-D) relationships used to derive bulk microphysical properties such as total water content (TWC) and radar reflectivity factor (Z) are used in both numerical models and remote sensing retrievals. The most common way of estimating a-b coefficients used in m=aDb relationships is to minimize the difference between the TWC or Z derived from number distribution functions and that directly measured by a bulk water probe or radar. These a and b values, however, can vary significantly based on meteorological conditions, particle habit, definition of particle maximum dimension, probes used to obtain the data, or even the techniques used to process the cloud probe data. Microphysical data collected by two-dimensional optical array probes (OAPs) installed on the University of North Dakota Citation aircraft during the Midlatitude Continental Convective Clouds Experiment (MC3E) and the Olympic Mountain Experiment (OLYMPEX) are used here in conjunction with TWC data from the Nevzorov probe and ground-based radar data at S-band to test a novel approach that determines m-D relationships for a variety of environments. A surface of equally realizable a and b coefficients in (a,b) phase space is determined using a technique that minimizes the chi- squared difference between TWC or Z derived from the OAPs and that directly measured by a TWC probe or radar, accepting as valid all coefficients within a specified tolerance as equally realizable solutions to the m=aDb relationship. The surfaces of solutions for different cases are compared to establish how environmental conditions and spatial and temporal variability within clouds controls the a-b coefficients. It is shown that using fixed a-b coefficients in selected numerical modeling and remote retrieval schemes cannot adequately represent the ensemble-retrieved particle mass-dimension variability of observed cloud conditions.
Poster Number: 11
39 POSTER SESSION: WEATHER & CLIMATE IMPACTS ON THE MIDWESTERN US SATURDAY, OCTOBER 7 | 2:30 PM – 3:45 PM
Overview of Contributions to the Jet Superposition Associated with the 24–26 October 2010 North American Storm Event
Brittany L. Newman1, Dominique V. Watson1, Jacob A. Strohm1, Kai Funahashi1, Robert C. Fritzen1, and Zachary J. Handlos2
1Department of Geographic and Atmospheric Sciences, Northern Illinois University, DeKalb, IL 60115, 2School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332
On 24–26 October 2010, an extratropical cyclone, associated with a record-low minimum in sea level pressure over the upper Midwest, impacted the eastern half of the contiguous United States. Cursory examination of the rapid cyclogenesis associated with the event reveals the presence of a vertical superposition of the polar and subtropical jet streams. Motivated by recent literature revealing the role that vertical jet superposition events play in the development of extreme extratropical cyclones (e.g., Winters and Martin 2014, 2016), this study investigates the development of the superposed jet and its role in the rapid intensification of the 24–26 October 2010 cyclone. Employing NCEP/NCAR Reanalysis I data along with an objective jet identification scheme (Christenson et al. 2017), the case-study analysis performed in this study reveals that atmospheric rivers over the eastern Pacific Ocean initiated a steep potential vorticity gradient characteristic of a vertical jet superposition event. Instability on the equatorward side in concert with geostrophic cold air advection poleward of the vertically superposed jet helped to initiate and sustain the superposition. This superposition exacerbated horizontal temperature gradients, inducing strong baroclinic instability that intensified the cyclone of 24–26 October 2010. Future work includes comparing the results of this case study with other extreme cyclones associated with vertical polar and subtropical jet superposition events (e.g., Winters and Martin 2016), as this will enhance understanding of the connections between the jet superposition events and rapid cyclogenesis.
Poster Number: 12
40 Goose Creek Flux Tower – A flux footprint analysis
Leila Hernandez-Rodriguez, Allison Goodwell, Praveen Kumar University of Illinois at Urbana-Champaign
In the Midwestern United States, the agricultural ecosystem is a dominant influence on interactions between the intensively managed landscape and the atmospheric boundary layer. Flux tower studies in agricultural sites have mainly been done at plot scale, where the footprint of the instruments is small such that the data reveals the behaviour of the nearby crop on which the study is focused. The poster shows the calculated upwind distance and flux footprint for a flux tower located in Central Illinois, where the instruments are located at 25m above the surface. In addition, we calculate the daily energy balance during the summer of 2016 from the flux tower measurements and compare with the modelled energy balance from a representative corn crop located in the flux tower footprint using the Multi- Layer Canopy model, MLCan. Our results demonstrate how the instrument heights impact the footprint of the captured eddy covariance fluxes, and we explore the implication for hydrological analysis. The convective atmosphere during the daytime shows a wide footprint of more than 10 km2, which reaches 3km length for the 90% contribution. In contrast, the stable atmosphere during the night-time shows a narrower footprint that goes beyond 8km2 and grows in the direction of the prevalent wind, which exceeds 4 km in length. This study improves our understanding of agricultural ecosystem behaviour in terms of the magnitude and variability of fluxes. This study is part of the Intensively Managed Landscapes Critical Zone Observatory (IMLCZO).
Poster Number: 13
41 Tropical Cyclone-Ocean Interactions in the High-Resolution Community Earth System Model
Hui Li Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
High resolution Atmosphere General Circulation Models (AGCMs) are capable of directly simulating realistic tropical cyclone (TC) statistics, providing a promising approach for TC-climate studies. Here we investigate the interactions between TCs and the upper ocean using the high resolution configurations of the Community Earth System Model (CESM). We first investigate the impact of ocean coupling on the directly simulated TCs by performing a suite of CESM simulations in which the high resolution (25km) atmosphere component is configured with three different levels of ocean coupling: prescribed sea surface temperature (SST), mixed layer ocean, and dynamic ocean. We find that the inclusion of ocean coupling can influence simulated TC characteristics, including TC number, intensity, and geographic distributions. In particular, storm intensification and the maximum wind speed are sensitive to the representations of local surface flux feedbacks in different coupling configurations. Key differences in storm number and distribution can be attributed to variations in the modeled large-scale climate mean state and variability that arise from the combined effect of intrinsic model biases and air-sea interactions.
Poster Number: 14
42 Atmospheric Pressure Fluctuations in Natural and Wind-Farm Boundary Layers
Aaron Mehner Department of Meteorology & Geography, Valparaiso University
Atmospheric pressure fluctuations redistribute turbulent kinetic energy within the atmospheric boundary layer at sub-cm scales. These perturbations create a pressure pumping at the surface which influences biological soil and plant processes. Pressure fluctuations on larger scales affect wind turbine efficiency within large wind farms. Wind turbines also create pressure perturbations that could impact crops or reduce the power efficiency of nearby turbines. Measurements of pressure fluctuations taken around wind turbines are limited; however, up to 10-Pa of pressure fluctuation around the turbine tower base have been reported from numerical simulations. This study examines spatial and temporal variations of pressure fluctuations in both natural and wind-farm boundary layers in central Iowa. Two nanobarometers measure microscale resolution of pressure in conjunction with temperature and wind speed data from two 120-m meteorological towers in an agricultural region, one outside of a large wind farm (characterizing a natural boundary layer) and one within a large wind farm (characterizing a wind farm boundary layer). Pressure fluctuations were measured over 30-minute to 1-hour periods to identify typical flow characteristics of daytime and nighttime conditions in each tall tower location. Pressure perturbations created by turbines at night contain higher contributions of energy over a broader range of frequencies than pressure fluctuations measured in the natural boundary layer not influenced by wind turbines, which supports a greater TKE redistribution by pressure perturbations. Future research will look at wind farm influences on other TKE budget terms, such as momentum flux.
Poster Number: 15
43 An Evaluation of Precipitation Extremes from a Sparse Network
Emma Scott Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Changes in the frequency of extreme precipitation events impact the public safety, urban planning, and agriculture sectors. Differences between gauge shielding, minimum reported amounts, or temporal and spatial resolution between datasets make them harder to compare and evaluate for changes in extreme precipitation frequency. The United States Climate Reference Network (USCRN) provides reference triple-sensor sub-hourly precipitation records at 114 sites across the United States. This study evaluates the ability of a sparsely dense reference network such as the USCRN to capture precipitation extremes with a one to five-year return interval over a ten-year period of record. Precipitation totals were calculated for each station based on rolling duration intervals. 89 of the stations were in areas with gridded NOAA Atlas 14 precipitation frequency data, to which the calculated precipitation totals were compared. Exceedance of the NOAA Atlas 14 precipitation frequency for each return interval and corresponding duration was noted. Throughout the NOAA Atlas 14 coverage area, a larger number of exceedances per year than predicted by the return interval were found for durations in the five-minute to one-day time frame. The network’s higher temporal (5-minute) and precipitation (0.2 mm) resolutions at the sub- hourly scale and better shielding increased the number of extreme precipitation events captured. The USCRN’s ability to capture extreme precipitation can be put to further use as a reference for studies evaluating changes in the frequency of extreme precipitation events.
Poster Number: 16
44 Toward probabilistic climate change assessment with the Hector simple climate model
Benjamin Vega-Westhoff Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
Probabilistic climate assessments require robust characterizations of decision- relevant uncertainties. Simple climate models are useful tools for quantifying uncertainty. Given their flexibility and computational efficiency they are suitable for large- ensemble frameworks necessary for statistical estimation using resampling techniques (e.g., Markov chain Monte Carlo—MCMC). Hector, one such simple climate model, includes a representation of the global carbon cycle and is able to reproduce global historical trends of atmospheric [CO2], radiative forcing, and surface temperature. Hector is freely available (https://github.com/JGCRI/hector) and runs in under a second on a modern laptop. Here we present preliminary results from a new study utilizing Hector for probabilistic climate assessment. We summarize new model development efforts, including coupling Hector with a diffusive ocean heat and energy balance model (DOECLIM: Diffusion Ocean Energy balance CLIMate model) and a sea-level rise model (BRICK: Building blocks for Relevant Ice and Climate Knowledge) that includes contributions from glaciers and ice caps, the Greenland ice sheet, the Antarctic ice sheet, and thermal expansion. We show results from preliminary Bayesian calibrations of this new version of Hector-DOECLIM-BRICK. We investigate the effects of different observational constraints on the resulting statistical estimations. This model and ensemble framework will enable us to explore probabilistic assessment of relevant climate impacts with special emphasis on tail-area events (e.g. sea-level rise, floods, temperature, etc.).
Poster Number: 17
45 Historical multi-model analysis of solid precipitation in the Great Lakes region
Karlie A. Wells, Allison L. Steiner Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI
Being the largest group of freshwater lakes on Earth, the Great Lakes supply clean drinking water to millions of people and support many different industries. In recent years, water quality in the western Lake Erie basin has been threatened by increasing occurrences of harmful algal blooms (HABs). The reason for this increase in HAB events is unclear, but recent work suggests that cold season processes may impact nutrient loading in the region, thus driving the variability in HAB formation. This project investigates the simulation of solid-phase precipitation in 17 global climate models (GCMs) from the IPCC Climate Model Intercomparison Project (CMIP5). We examine the seasonal and interannual simulation of solid precipitation in the Great Lakes region over a historical period (1980-1999), identify the range of variability amongst the models, and evaluate the simulations versus available observations. Four snow metrics (snowfall flux, snow area fraction, snow depth, and snow melt) are analyzed temporally and spatially. A monthly average reveals the largest variability in the snow depth variable, with a standard deviation of 0.0766m. Spatially averaged between December and February (DJF), most models underestimate snow area fraction in the northeast region of the Great Lakes by up to 70%. The DJF multi-model average overestimates total precipitation and percent snowfall in the region by 24.15% and 11.26% respectively. Overall, these results suggest substantial variability amongst the models in representing snow processes, and curating model selection for those that reproduce cold- season observations is likely more important than using the multi-model ensemble mean.
Poster Number: 18
46 POSTER SESSION: THE MESOSCALE – SHORT-TERM PREDICTABILITY & LONG-TERM VARIABILITY SATURDAY, OCTOBER 7 | 2:30 PM – 3:45 PM
Relative Impacts of Tropical and Extratropical Forcing on Atlantic Tropical Cyclones in Numerical Model Simulations
Chuan-Chieh Chang and Zhuo Wang Department of Atmospheric Sciences, University of Urbana-Champaign, Urbana, Illinois, USA
This study aims to explore the relative importance between the tropical warm sea surface temperature (SST) anomalies and the extratropical processes. Those two factors are both critical to the Atlantic tropical cyclone (TC) activity. Seven seasonal simulations with different microphysics, initial times are carried out during the hurricane season in 2005, 2013 and the mixed scenario, individually. The atmospheric initial conditions, and boundary forcing taken from 2013, and the surface temperatures derived from 2005 are used to drive the mixed experiments. The results show that the observed contrast of TC activity between those two years is reasonably reproduced by the simulations. In addition, the suppressed TC activity can be still identified in the mixed experiments. The increased vertical wind shear (VWS), decreased mid-upper-level moisture, and recurrent occurrence of Rossby wave breaking (RWB), relative to those in the 2005 simulations, are found both in the 2013 and mixed simulations. A case study of RWB suggests that the key characteristics of observed RWB, including the high-PV centers at the tropopause and their associated anomalies of cold temperatures, the increased VWS over the western main development region (MDR), and the outbreak of dry air from the midlatitudes, are present in the 2013 simulation. The warm SST anomalies in the mixed simulation are incapable of altering those inimical conditions to TC development in this case. Furthermore, the analyses of pattern correlation coefficients (PCCs) and root mean square errors (RMSEs) quantitively suggest that the boundary condition or extratropical forcing plays a dominant role in controlling the atmospheric evolutions in the mixed experiments. Noticeably, a potentially higher predictability in the 2013 Atlantic hurricane season is suggested if reasonable boundary conditions are prescribed. Overall, this study highlights that the extratropical forcing can play an important role in modulating the Atlantic TC activity in some years, and it should be considered in the seasonal prediction schemes of TC activity.
Poster Number: 19
47 Investigating the Environment of the Indiana and Ohio Tornado Outbreak of 24 August 2016 using WRF Model simulation
Kevin Gray Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign
On 24 August 2016, a tornado outbreak impacted Indiana and Ohio with 22 confirmed tornadoes. Though severe weather was predicted for this area, a tornado outbreak is something that caught meteorologists off guard. On the day of the event, high moisture in the area well ahead of a cold front, in the warm sector, allowed for low LCLs. This, along with strong low-level shear and instability provided an environment favorable for tornadoes. Of particular interest is the transition of convection from a linear mode to a cellular mode occurring from 1700 to 1900 UTC. After this transition in modes is when tornadoes began to form. Observations show a mesoscale convective vortex approaching Illinois in the morning hours. Visible satellite imagery shows convection initiating on the eastern edge of this MCV and it is believed that this had a role in the outbreak. An analysis of WSR-88D data shows the lack of a strong gust front, which may have assisted in allowing the transition of modes. It is shown in literature that the orientation of the shear vector with respect to the convective boundary may determine mode. It is hypothesized that the shear vector became more favorable for cells rather than a line of storms from 1700 to 1900 UTC. The WRF model is used to simulate this event. Preliminary model runs are proving the difficulty of capturing the transition in modes of convection. The models tend to hang on to the linear convective mode rather than displaying a definite transition to discrete cells. Model output will be presented to investigate the environment of this event and possible reasons for the mode transition.
Poster Number: 20
48 Creation and Verification of a Short Term, Multi-Model Ensemble Forecast System Using the QuantumWeather® Mesonet
Tyler Ritch Department of Earth and Atmospheric Sciences, Saint Louis University
Ensemble forecasts have long been used to predict variability in hurricane tracks and other synoptic-scale phenomena. Though they’ve proven effective in that regime, ensemble forecast systems have not been well tested at predicting smaller events in shorter time frames. Here, a short term (12 hour) ensemble forecast system is created by using initialization data from two different weather models, by varying how weather in the Planetary Boundary Layer is calculated, and by ingesting data from the QuantumWeather® surface mesonet. With a focus on forecasting wind speed and direction, both stormy and quiet days are analyzed to highlight the ensemble forecast system’s statistical integrity.
Poster Number: 21
49 Spatio-Temporal Changes in Non-Extreme Precipitation Variability over North America
Susana Roque-Malo and Praveen Kumar Department of Civil & Environmental Engineering, University of Illinois
Precipitation variability encompasses attributes associated with the sequencing and duration of events of the full range of magnitudes. However, climate change studies have largely focused on extreme events. Using analyses of long-term weather station data we show that high frequency events, such as fraction of wet days in a year and average duration of wet and dry periods, are undergoing significant changes across North America. Further, these changes are more prevalent and larger than those associated with extremes. Such trends also exist for events of a range of magnitudes. Existence of localized clusters with opposing trend to that of broader geographic variation illustrates the role of microclimate and other drivers of trends. Such hitherto unknown patterns over the entire North American continent have the potential to significantly inform our characterization of the resilience and vulnerability of a broad range of ecosystems, and agricultural and socio-economic systems. They can also set new benchmarks for climate model assessments.
Poster Number: 22
50 CLOSING REMARKS
I would like to thank all of you for attending the 2017 Midwest Student Conference on Atmospheric Research, and for showing your support for all of our student researchers. This student-led conference has been a great experience for the organizers and volunteers, and an excellent opportunity for the presenters to showcase their research. The diversity of research topics presented during this conference provides a unique atmosphere for discussing cross-disciplinary topics in our field, and I hope that enthusiasm for collaboration extends beyond this conference.
I would also like to thank Dr. Louis Uccellini and Mr. Tom Skilling for their invaluable time attending the conference. The two are instrumental in the field of atmospheric sciences, and we are greatly honored to have them with us this weekend.
On behalf of the Department of Atmospheric Sciences at the University of Illinois at Urbana- Champaign, we look forward to seeing you all at our conference next year!
Sincerely, Bob Rauber Department Head Department of Atmospheric Sciences
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