Oceanography and Atmospheric Sciences and Meteorology Commons^™

A Deep Learning Framework With Explainable Ai For Atmospheric Blocking Detection And Interpretation, Devansh Khandelwal

Discovery Undergraduate Interdisciplinary Research Internship

Atmospheric blocking is a large-scale quasi-stationary phenomenon in mid-latitude circulation, characterized by persistent high-pressure systems that disrupt the typical west-to-east flow of the jet stream. These systems can cause extreme weather events—such as heatwaves, cold spells, or droughts—that persist for days or even weeks. This study proposes a deep learning framework to predict and interpret the occurrence of atmospheric blocking by integrating geophysical precursors such as geopotential height (Z500), stream function (SF200), and potential vorticity. These features, which are dynamically linked to blocking onset and persistence, serve as inputs to a Convolutional Neural Network model trained on the CESM Large …

Machine Learning-Based Variance Analysis Of Brightness Temperature In Simulated Satellite Footprints, Chhaya R. Kulkarni, Nikki Prive, Vandana P. Janeja

I-GUIDE Forum

This study investigates the variance in brightness temperature (BT) within simulated satellite footprints for Observing System Simulation Experiments (OSSE), focusing specifically on Channels 5 and 11 of the Advanced Microwave Sounding Unit (AMSU-A). High-resolution atmospheric simulations from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) dataset were utilized to generate brightness temperature data using the Python interface for the Community Radiative Transfer Model (PyCRTM). A computational design map incorporating Random Forest and Association Rule Mining was employed to identify and validate key atmospheric variables influencing BT variance. This ensemble approach facilitated a deeper understanding of atmospheric …

Validating Atmospheric Freezing Level Heights Using Purdue University Weather Balloon Data, Danielle Harr

The Journal of Purdue Undergraduate Research

No abstract provided.

A Meteorological Investigation Of A Tornado- Producing, “Hybrid” Supercell-Multicell Storm Near Delphi, Indiana, On May 8, 2023, Evelyn Rose K. Girardi

The Journal of Purdue Undergraduate Research

No abstract provided.

Statistical Downscaling Of Climate Datasets With Deep Generative Model And Bayesian Inference, Guiye Li, Guofeng Cao

I-GUIDE Forum

Facing the challenges of global climate change, precise and high spatial resolution climate data are crucial and in pressing need for scientific research and analysis. However, most existing datasets are only available with very coarse spatial resolution and demand large-scale resolution enhancement. Meanwhile, climate datasets own much more intricate textures than natural images. Statistical downscaling or super-resolution (SR) with the deep-learning-based generative model might be a promising approach to address these challenges. It is worth noting that a learned Bayesian reconstruction with generative models (L-BRGM) method was proposed recently. The proposed Bayesian deep learning framework employs a single pre-trained generative …

Typology Of Atmospheric Conditions Leading To Dam Overtopping In The Eastern Us, Hodo I. Orok, Deanna Hence

I-GUIDE Forum

Statistical characterization of reanalysis datasets during over 300 hydrologic dam incidents between 2003 and 2022 will create a detailed typology of weather systems associated with dam overtopping in the eastern United States. Dam overtopping poses significant risks to infrastructure and public safety, necessitating a comprehensive understanding of the multi-scale atmospheric conditions that lead to such events. To better account for the natural flow of water to the affected dams, we will adopt a watershed-focused Principal Component Analysis (PCA) on regional atmospheric data collected from ERA5 alongside USGS streamflow and Stage IV precipitation observations to enhance understanding of high-risk weather conditions. …

The Effects Of Wildfire Aerosol Emissions On Air Quality, Emma Braun, Audrey Shirley

The Journal of Purdue Undergraduate Research

No abstract provided.

Characterizing Differential Reflectivity Calibration Dependence On Environmental Temperature Using The X-Band Teaching And Research Radar (Xtrra): Looking For A Relationship Between Temperature And Differential Reflectivity Bias, Emma Miller

The Journal of Purdue Undergraduate Research

Calibration scans are important for the maintenance of data and the quality of the information that radars output. In this study we looked for a temperature dependency in a full year’s worth of differential reflectivity (ZDR) calibration scan data collected by the X-band Teaching and Research Radar (XTRRA) located near the Purdue University campus. In a vertically pointing calibration scan, the radar scans the drops from below while rotating. From this angle, the overall shape will be circular, which corresponds to a ZDR value of approximately 0 dB. To process the data for the year 2021, a Python script was …

A Computational Profile Of Invasive Lionfish In Belize: A New Insight On A Destructive Species, Joshua E. Balan

The Journal of Purdue Undergraduate Research

Since their discovery in the region in 2009, invasive Indonesian-native lionfish have been taking over the Belize Barrier Reef. As a result, populations of local species have dwindled as they are either eaten or outcompeted by the invaders. This has led to devastating losses ecologically and economically; massive industries in the local nations, such as fisheries and tourism, have suffered greatly. Attempting to combat this, local organizations, from nonprofits to ecotourism companies, have been manually spear-hunting them on scuba dives to cull the population. One such company, Reef Conservation Institute (ReefCI), operating out of Tom Owens Caye outside of Placencia, …

Clouds In The Ancient Lunar Atmosphere: Water Ice Nucleation On Aerosol Simulants, Mariana C. Aguilar

The Journal of Purdue Undergraduate Research

Today’s moon is vastly different from what it was 3 billion years ago. At that time, it was home to a collisional atmosphere formed through massive amounts of volcanism, releasing enough subsurface gas to sustain surface pressures of up to 1 kPa. Observations of our solar system have taught us that all dense atmospheres are host to clouds and aerosols, and we expect the Moon’s to be no different. Knowing when, where, and under what conditions cloud particles form is important for understanding the evolution of the lunar atmosphere, how it reacted to temperature gradients, and how it cycled volatiles. …

Deep Learning Approaches For Chaotic Dynamics And High-Resolution Weather Simulations In The Us Midwest, Vlada Volyanskaya, Kabir Batra, Shubham Shrivastava

Discovery Undergraduate Interdisciplinary Research Internship

Weather prediction is indispensable across various sectors, from agriculture to disaster forecasting, deeply influencing daily life and work. Recent advancement of AI foundation models for weather and climate predictions makes it possible to perform a large number of predictions in reasonable time to support timesensitive policy- and decision-making. However, the uncertainty quantification, validation, and attribution of these models have not been well explored, and the lack of knowledge can eventually hinder the improvement of their prediction accuracy and precision. Our project is embarking on a two-fold approach leveraging deep learning techniques (LSTM and Transformer) architectures. Firstly, we model the Lorenz …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

Polarimetric Radar And Vhf Lightning Observations In A Significantly Tornadic Supercell, Jacob Bruss

The Journal of Purdue Undergraduate Research

No abstract provided.

Agricultural Aerosols: The Impact Of Farming Activity On Ice Nucleating Particles, Joseph Robinson

The Journal of Purdue Undergraduate Research

Farming activities cause particles such as soil dust and plant material to be emitted into the air. Some of these aerosols can become ice nucleating particles (INPs), serving as seeds for ice and mixed-phase clouds. While there have been ground-based studies of these particles in the western Great Plains and a single air-based study in Indiana, there is a distinct lack of ground-based studies in the Midwest. In Indiana, over two-thirds of the state is farmland, with over 75% of land in Tippecanoe County used for agriculture. Despite farming being such an essential part of life in Indiana, the connection …

Physics-Informed Machine Learning To Predict Extreme Weather Events, Rthvik Raviprakash, Jonathan Buchanan, Mahdi Bu Ali

Discovery Undergraduate Interdisciplinary Research Internship

Extreme weather events refer to unexpected, severe, or unseasonal weather events, which are dynamically related to specific large-scale atmospheric patterns. These extreme weather events have a significant impact on human society and also natural ecosystems. For example, natural disasters due to extreme weather events caused more than $90 billion global direct losses in 2015. These extreme weather events are challenging to predict due to the chaotic nature of the atmosphere and are highly correlated with the occurrence of atmospheric blocking. A key aspect for preparedness and response to extreme climate events is accurate medium-range forecasting of atmospheric blocking events.

Unlike …

Automated Detection And Characterization Of Mesocyclones In X-Band Radar Observations, Raychel E. Nelson

The Journal of Purdue Undergraduate Research

No abstract provided.

The Effects Of Climate Change On The Vertical Structure Of Severe Weather Environments, Isaac Davis

The Journal of Purdue Undergraduate Research

No abstract provided.

A Comparison Of The Localized Aviation Mos Program (Lamp) And Terminal Aerodrome Forecast (Taf) Accuracy For General Aviation, Douglas D. Boyd, Thomas A. Guinn

Journal of Aviation Technology and Engineering

Background. For general aviation (GA) pilots, operations in instrument meteorological conditions (IMC) carry an elevated risk of a fatal accident. As to whether a general aviation flight can be safely undertaken, aerodrome-specific forecasts (TAF, LAMP) provide guidance. Although LAMP forecasts are more common for GA-frequented aerodromes, nevertheless, the FAA recommends that for such aerodromes (and for which a TAF is not issued) the airman uses the TAF generated for the geographically closest airport for pre-flight weather evaluation. Herein, for non-TAF-issuing airports, the LAMP (sLAMP) predictive accuracy for visual (VFR) and instrument (IFR) flight rules flight category was determined.

Method. sLAMP …

Reginald Sutcliffe And The Invention Of Modern Weather Systems Science, Jonathan E. Martin

Purdue University Press Book Previews

Despite being perhaps the foremost British meteorologist of the twentieth century, Reginald Sutcliffe has been understudied and underappreciated. His impact continues to this day every time you check the weather forecast. Reginald Sutcliffe and the Invention of Modern Weather Systems Science not only details Sutcliffe’s life and ideas, but it also illuminates the impact of social movements and the larger forces that propelled him on his consequential trajectory. Less than a century ago, a forecast of the weather tomorrow was considered a practical impossibility. This book makes the case that three important advances guided the development of modern dynamic meteorology, …

Influence Of Atmospheric Circulation On Severe Flooding In The Atacama Desert, Jonathan Degraw

The Journal of Purdue Undergraduate Research

No abstract provided.

High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner

The Journal of Purdue Undergraduate Research

Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using …

Internet Of Things For Environmental Sustainability And Climate Change, Abdul Salam

Faculty Publications

Our world is vulnerable to climate change risks such as glacier retreat, rising temperatures, more variable and intense weather events (e.g., floods, droughts, and frosts), deteriorating mountain ecosystems, soil degradation, and increasing water scarcity. However, there are big gaps in our understanding of changes in regional climate and how these changes will impact human and natural systems, making it difficult to anticipate, plan, and adapt to the coming changes. The IoT paradigm in this area can enhance our understanding of regional climate by using technology solutions, while providing the dynamic climate elements based on integrated environmental sensing and communications that …

Internet Of Things For Water Sustainability, Abdul Salam

Faculty Publications

The water is a finite resource. The issue of sustainable withdrawal of freshwater is a vital concern being faced by the community. There is a strong connection between the energy, food, and water which is referred to as water-food-energy nexus. The agriculture industry and municipalities are struggling to meet the demand of water supply. This situation is particularly exacerbated in the developing countries. The projected increase in world population requires more fresh water resources. New technologies are being developed to reduce water usage in the field of agriculture (e.g., sensor guided autonomous irrigation management systems). Agricultural water withdrawal is also …

Integrated Species–Phenon Trees: Visualizing Infraspecific Diversity Within Lineages, Abdullah Khan Zehady, Barry G. Fordham, James G. Ogg

Purdue University Libraries Open Access Publishing Fund

The unprecedented detail with which contemporary molecular phylogenetics are visualizing infraspecific relationships within living species and species complexes cannot as yet be reliably extended into deep time. Yet paleontological systematics has routinely dealt in (mainly) morphotaxa envisaged in various ways to have been components of past species lineages. Bridging these perspectives can only enrich both. We present a visualization tool that digitally depicts infraspecific diversity within species through deep time. Our integrated species–phenon tree merges ancestor–descendant trees for fossil morphotaxa (phena) into reconstructed phylogenies of lineages (species) by expanding the latter into “species boxes” and placing the phenon trees inside. …

Weather Courtyard: Reflections On Interactive Stem Learning Spaces, Ryan Day

Purdue Journal of Service-Learning and International Engagement

In this article, the author discusses his experiences in service-oriented engineering developing an interactive weather station for DCES students. Day details this process and the lessons learned over the course of the project development, as well as the project’s influence on his aspirations for a career in civil and environmental engineering. To provide substantive takeaways from the project, he concludes by reviewing the benefits of interactive STEM learning spaces in the instructional environment and links them to the impacts of the weather station project on the community.

Climatological Changes: Meteorological Parameters Affecting The Spatial Redistribution Of U.S. Tornadoes, Ashley Dicks

The Journal of Purdue Undergraduate Research

Climatological changes in the environments of key meteorological parameters that affect Significant Tornado Days (SigTorDs) have been determined for two active tornado regions defined as Box α and Box β, centered, respectively, over Oklahoma and Alabama and their respective environs. The North American Regional Reanalysis data was selected for 1980–2013, providing two successive 17-year periods corresponding to the last 34 years of previous research findings that focused on the aforementioned regions. This data record also corresponds to an increasing surface air temperature trend for the continental United States. Period I (1980–1996) and Period II (1997–2013) defined the years of changing …

Estimating Watershed Residence Times In Artificially-Drained Landscapes And Relation To Nutrient Concentrations, Emma Beck, Lisa Welp, Alexandra L. Meyer

The Summer Undergraduate Research Fellowship (SURF) Symposium

Nutrient runoff from agricultural lands feeds harmful algae blooms that create a variety of problems in freshwater ecosystems. In order to reduce the effects of this nutrient runoff, Best Management Practices (BMPs) are being put in place in agricultural lands. Most of these BMPs focus on slowing down the flow of water through the watershed to give nutrient concentrations time to deplete before the water flows to the stream or river. However, the effectiveness of these BMPs are highly unknown and the process of monitoring nutrient runoff is often complex and costly. The data in this study consists of 7 …

Extreme Precipitation Events, Impacts, Trends And Projections For Indiana, Sam Lashley

Purdue Road School

The National Weather Service is working with core partners to build a Weather Ready Nation for present and future generations by taking advanced action against the devastating impacts of extreme weather events, including extreme precipitation and flooding. One way in which this can be accomplished is by studying trends in historical weather data and applying what we learn to future mitigation efforts. The goal is to gain a better understanding of the magnitude and impacts that future extreme precipitation events may have on local infrastructure.

This presentation will review extreme rainfall and flooding events that have occurred across Indiana along …

Using P-Band Signals Of Opportunity Radio Waves For Root Zone Soil Moisture Remote Sensing, Phillip H. Lipinski, Benjamin R. Nold, James L. Garrison

The Summer Undergraduate Research Fellowship (SURF) Symposium

Retrieval of Root Zone Soil Moisture (RZSM) is important for understanding the carbon cycle for use in climate change research as well as meteorology, hydrology, and precision agriculture studies. A current method of remote sensing, GNSS-R uses GPS signals to measure soil moisture content and vegetation biomass, but it is limited to 3-5 cm of soil penetration depth. Signals of Opportunity (SoOp) has emerged as an extension of GNSS-R remote sensing using communication signals. P-band communication signals (370 MHz) will be studied as an improved method of remote sensing of RZSM. P-band offers numerous advantages over GNSS-R, including stronger signal …

Ocean Wind Speed Measurement Using Wideband Gnss-R Signals, Brandon J. Kozel, Han Zhang, James L. Garrison, Benjamin Nold

The Summer Undergraduate Research Fellowship (SURF) Symposium

The use of Global Navigation Satellite System-Reflectometry (GNSS-R) for remote sensing of ocean wind speeds has been explored for nearly two decades and has become an important passive remote sensing technique for verification of hurricane formation models. To obtain wind speed measurements, reflected GNSS signals are first cross-correlated with locally generated copies to construct delay-doppler maps (DDMs). Through statistical models, DDMs can provide information about the mean-square slope (MSS) of the ocean surface, which is related to wind speed. Previous studies have focused on legacy signals such as GPS L1. However, it is expected that the MSS relationship with ocean …