Research

Below you will find descriptions of my research and a selection of my conference presentations. Please feel free to reach out to me with any questions!

Research Interests

My PhD research investigates the predictability and forecast accuracy of tropical cyclone precipitation, especially when these storms interact with midlatitude/synoptic-scale features. How skillful are our current forecast models at forecasting storm-total and 3-hourly TC precipitation? What aspects of the TC precipitation forecast are driving forecast errors? How do midlatitude features, such as fronts, introduce uncertainty into the TC precipitation forecast? These are all questions I hope to address during my PhD research and into my career.

Most studies on TC precipitation utilize traditional verification metrics (i.e., gridpoint-to-gridpoint), which tend to treat all incorrect forecasts the same regardless of how the error manifests (e.g., location, shape, orientation, size). Therefore, I am also interested in integrating object-based metrics into my research to better diagnose where and why these errors are occurring. Lastly, I am interested in applying an ensemble-based sensitivity tool to study the synoptic-scale dynamics of landfalling TC precipitation events and investigate the sources of uncertainty driving errors in TC precipitation forecasts.

Beyond the scope of my PhD research, I am interested in the predictability and verification of TC hazards, midlatitude cyclones, and extreme precipitation (e.g., atmospheric rivers, tropical cyclones, and lake-effect snow). In a general sense, I am motivated by work that directly impacts and improves operational forecasts, and am interested in pursuing career opportunities in applied meteorology and climatology and research-to-operations.

PhD Research

The Predictability and Verification of Precipitation from Landfalling Tropical Cyclones Using an Object-Oriented Framework

Precipitation from landfalling tropical cyclones (TCs) poses a significant risk to life and property in both coastal and inland communities. Early warning systems can help mitigate the impacts of TC-induced flooding; however, this requires accurate quantitative precipitation forecasts (QPFs). Forecasting precipitation from landfalling TCs is a challenge, as the intensity, duration, and location of precipitation is dependent on numerous storm-related and environmental factors. A handful of studies have applied traditional and advanced verification metrics to TC QPF in an attempt to identify and correct NWP model deficiencies and reduce forecast uncertainty. However, these studies have used outdated verification metrics, limited samples of forecasts, and have not assessed the synoptic-scale uncertainty related to TC QPF.

My dissertation to evaluate the precipitation forecasts of landfalling TCs using advanced, object-based verification methods to investigate what aspects of the precipitation forecast are driving QPF errors and to better understand the sources of uncertainty in the precipitation forecast. The Model Evaluation Toolkit (MET) verification software package is utilized to verify storm-total and 3-hourly QPFs for TCs that made landfall in CONUS between 2018–2024 using a wide range of traditional and object-based verification metrics. Through these analyses, the forecast skill of NWP models will be quantified in terms of location, intensity, timing, shape, and size errors.

In addition, ensemble-based sensitivity analysis will be employed to investigate how the uncertainty of near-storm environmental features impacts the uncertainty of TC precipitation forecasts. Particular interest is given to TCs that interact with midlatitude features in order to understand how and why these interactions impact the predictability of TC precipitation.

MS Research

Comparison of 2018–2022 Tropical Cyclone Track Forecasts Before and After NOAA G-IV Missions

Note: The analysis for 2022 was not in the original MS thesis document submitted to the University at Albany, SUNY. This analysis was added post hoc and is included in the publication (in review as of Dec. 2024).

Tropical cyclone hazards are primarily determined by the TC position; thus, accurate TC track forecasts are critical to predicting TC hazards. Many different features can influence a TC’s motion and introduce uncertainty to the track forecast, yet these features are not always well sampled by in-situ observations over the open ocean, creating a need for supplemental observations collected via aircraft. In 1997, the National Hurricane Center began operational synoptic surveillance missions in the near-storm environments of TCs using the Gulfstream IV-SP jet aircraft (G-IV), with the goal of reducing track forecast errors. In the first 10 years of operational missions, the dropsonde data collected during 176 G-IV missions led to a 10–15% improvement in 0–60-h track forecast errors for forecasts initialized at mission nominal times (Aberson 2010). In 2018, the G-IV targeting strategy was updated to include an inner-circumnavigation of dropsonde releases and to employ an ensemble-based sensitive technique to aid in identifying regions in the TC environment that are driving uncertainty in the track forecast. However, since these updates, limited research has been done to solely investigate the impacts of G-IV missions on TC track predictability.

This study evaluated the impacts of dropsonde data from the G-IV missions on ECMWF EPS and GEFS track forecast errors and skill for 2018–2022 Atlantic basin TCs. Through a multi-season analysis of various bulk statistics, it was found that, overall, ECMWF EPS and GEFS track forecasts are 1–24% more skillful with the inclusion of G-IV data than without this data. The results also suggested that the first forecast initialized with G-IV dropsonde data per TC experienced the largest positive impact on track forecast skill.

In addition, this study evaluated two case studies, Hurricanes Marco and Zeta (2020), to investigate the driving factor behind large track forecast improvements following the assimilation of G-IV data. For Hurricane Marco, the track forecast improvement appears to be related to an initial position change that placed Marco in a steering flow more similar to observations. For Hurricane Zeta, the improvements seem to be a result of a reduction in the along-track component of the steering flow.

This work has been accepted in the American Meteorological Society's Weather and Forecasting journal (Feb. 2025). A citation will be added once the manuscript is published.

Select Conference Presentations

33rd Conference on Weather Analysis and Forecasting (WAF)/29th Conference on Numerical Weather Prediction (NWP) / 105th AMS Annual Meeting - "Verification of GFS Storm-Total Precipitation Forecasts for Landfalling Tropical Cyclones in CONUS Using an Object-Based Framework"

January 2025, Oral Presentation

Piper_AMS_Annual_2025_PDF.pdf

20th Cyclone Workshop - "An Analysis of the Predictability of Tropical and Post-Tropical Ida's (2021) Heavy Precipitation"

October 2024, Oral Presentation

Cyclone-Workshop.pdf

36th Conference on Hurricanes and Tropical Meteorology - "An Analysis of the Predictability of Tropical and Post-Tropical Ida's (2021) Heavy Precipitation"

May 2024, Poster Presentation
Awarded "Outstanding Student Poster Presentation"

AMS_Tropical_2024_Poster.pdf

6th Special Symposium on Tropical Meteorology and Tropical Cyclones / 104th AMS Annual Meeting - "Development of an Ensemble-Based Sensitivity Metric for Tropical Cyclone Hazard Forecasts"

January 2024, Poster Presentation

AMS_Annual_2024_Poster.pdf

Fifth Special Symposium on Tropical Meteorology and Tropical Cyclones / 103rd AMS Annual Meeting - "Comparison of 2018–2021 Atlantic Tropical Cyclone Track Forecasts Before and After NOAA G-IV Missions"

January 2023, Oral Presentation
Awarded "1st Place - Best Oral Presentation"

Piper_AMS2023.pdf

Class Projects

"A Climatology of Tropical Cyclone Interactions with Deformation Steering Flows in the Atlantic Ocean"

This project originated from Dr. Kristen Corbosiero's course in Spring 2022: ATM 527 – Observations and Theory of Tropical Cyclones. Alex Mitchell and I were paired together for this work, which culminated in a course paper and a poster at the 103rd AMS Annual Meeting in Denver, CO in January 2023. There are a lot of unanswered questions from this work, and I would be greatly interested in revisiting this project in the future.

ABSTRACT: Tropical cyclones (TCs) in large-scale deformation steering flows have been shown in previous case studies to be associated with large position errors and track uncertainty. It has also been shown that errors in the steering flow surrounding the center of a TC reveal which side of the axis of contraction the TC would move to and, thus, the future position of the storm. In this study, a climatology of TC interactions with deformation steering flows is developed in order to quantify the total deformation of the environmental steering flow during the lifetime of all TCs over the North Atlantic from 2010–2021. The frequency in which TCs interact with deformation zones and the characteristics of the upper percentile of deformation steering flow zones in proximity to TCs will be analyzed. The environmental steering flow is calculated at 00 and 12 UTC for each day a storm remains a TC using the ECMWF fifth generation reanalysis dataset (ERA-5) on a 1 degree grid across a domain of 0–60N, 0–110W. The total deformation steering flow is calculated using the optimal steering flow for a TC described in the methods of Galarneau and Davis (2013) and averaged within 500 km of the TC position at each time step. TCs that interacted with deformation steering flows are identified using a threshold value, which will serve as a procedure for extracting characteristic deformation steering flow patterns. Additionally, the steering flow regimes associated with the upper percentile of deformation values will be examined to identify potential sources of TC track forecast errors that are associated with a TC’s interaction with the deformation steering flow patterns. In summary, the presentation aims to climatologically identify and investigate the environmental TC–deformation steering flow interactions and evaluate the upper percentile of the deformation steering flow zones in the aforementioned climatology.

AMS2023_Poster_upd.pdf

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