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Publications

Kirtman, B.P., et al., (2024). A Simplified Physics Atmosphere General Circulation Model for Idealized Climate Dynamics Studies. Bull. Am. Meteorol. Soc., submitted.

Malloy, K. and Tippett, M.K. (2024). Forecasting U.S. Tornado Outbreak Activity and Associated Environments in the Global Ensemble Forecast System (GEFS). Wea. Forecasting, in revision.

Tippett, M.K., Malloy, K., and Lee, S.H. (2023). Modulation of U.S. tornado activity by year-round North American weather regimes. Mon. Wea. Review, https://doi.org/10.1175/MWR-D-24-0016.1.

Malloy, K. and Tippett, M.K. (2024). A Stochastic Statistical Model for U.S. Outbreak-level Tornado Occurrence based on the Large-scale Environment. Mon. Wea. Review, https://doi.org/10.1175/MWR-D-23-0219.1.

Malloy, K. and Tippett, M.K. (2023). ENSO and MJO Modulation of U.S. Cloud-to-ground Lightning Activity. Mon. Wea. Review, https://doi.org/10.1175/MWR-D-23-0157.1.

Malloy, K. and Kirtman, B.P. (2023). Subseasonal Great Plains Rainfall via Remote Extratropical Teleconnections: Regional Application of Theory-guided Causal Networks. JGR: Atmospheres, https://doi.org/10.1029/2022JD037795

Malloy, K. and Kirtman, B.P. (2022). The Summer Asia-North America Teleconnection and its Modulation by ENSO in Community Atmosphere Model, Version 5 (CAM5). Climate Dynamics, https://doi.org/10.1007/s00382-022-06205-4

Malloy, K. and Kirtman, B.P. (2020). Predictability of Midsummer Great Plains Low-Level Jet and Associated Precipitation. Wea. Forecasting, 35, 215–235, https://doi.org/10.1175/WAF-D-19-0103.1.

Mahoney, K., D. Swales, M.J. Mueller, M. Alexander, M. Hughes, and K. Malloy. (2018). An Examination of an Inland-Penetrating Atmospheric River Flood Event under Potential Future Thermodynamic Conditions. J. Climate, 31, 6281–6297, https://doi.org/10.1175/JCLI-D-18-0118.1.

Invited Talks

Predictable Climate Variability and its Applications to Climate Forecasting and Risk | University of North Dakota Dept. Atmoshperic Sciences Seminar​ | October 2024

Modeling Severe Convective Storms: Understanding Current Risk and its Climate Signals | ILS Bermuda Convergence Conference 2024​ | October 2024

A Stochastic Statistical Model for U.S. Outbreak-level Tornado Occurrence based on the Large-scale Environment | Laboratoire de Science du Climat et de l’Environnement (LSCE)​ | January 2024

Subseasonal Great Plains Rainfall via Remote Extratropical Teleconnections: ​Regional Application of Theory-guided ​Causal Networks​ | AGU Early Career Science Seminar​ | March 2023

Predictability of U.S. Great Plains Summer Hydroclimate via ​Extratropical Teleconnections​ | Lamont-Doherty Earth Observatory (LDEO) Ocean and Climate Physics (OCP) Seminar | February 2023

Subseasonal Great Plains Rainfall via Remote Extratropical Teleconnections: ​Application of Theory-guided ​Causal Networks​ | AGU Annual Meeting Session on S2S Prediction | December 2022

Predictability of ​ U.S. Great Plains Summer Hydroclimate via East Asian Monsoon-forced Teleconnection​ | NASA GMAO Seasonal Prediction Group | June 2022

Predictability of the Great Plains Low-level Jet and its Associated Precipitation​ | NMME Monthly Meeting | February 2020

Education

Ph.D.: University of Miami Rosenstiel School of Marine & Atmospheric Science | 2022
    Department of Atmospheric Sciences
    Thesis: Predictability of U.S. Great Plains Summer Hydroclimate via Extratropical Teleconnections
    Adviser: Ben P. Kirtman

B.S.: University of Maryland, College Park | 2017
    Honors College, Departmental Honors
    Atmospheric & Oceanic Science
    Minor: Geography-Remote Sensing of Environmental Change

Research Experience

Postdoctoral Research Scientist, Columbia University

August 2022-Present
Supervisor: Michael K. Tippett

  • Subseasonal-to-seasonal predictability of severe convective storm activity
  • Developed statistical model for cloud-to-ground lightning activity based on large-scale environment
    • Assess subseasonal-to-seasonal modulation of lightning activity
  • Constructed a submonthly tornado outbreak index that predicts probability of outbreak-level tornado given environment
    • Assess subseasonal-to-seasonal modulation of tornado outbreak activity
  • High-level experience writing python code for the development of empirical models, evaluating the model performance, investigating links with climate variability
    • Specific modeling techniques include (but not limited to): linear regression, Poisson Regression, logistic regression, random forests, artificial neural networks
    • Skilled in data preprocessing, feature selection, and model evaluation techniques to ensure the robustness and reliability of statistical models
    • Proficient with Python libraries for staticial modeling and machine learning prediction, including (but not limited to): scikit-learn, statsmodels, tensorflow
  • Oral presentation at 2023 European Conference on Severe Storms
  • Poster presentation at 2023 European Conference on Severe Storms

Graduate Research Assistant, Univ. Miami Rosenstiel School

Fall 2017-Present
Committee: Ben Kirtman, Amy Clement, Emily Becker, Brian Mapes, Hosmay Lopez

  • Predictability of summer U.S. hydroclimate on subseasonal-to-seasonal and interannual timescales via understanding of large-scale circulation responses and interactions between teleconnections
  • Using Python and creating Jupyter notebooks for reading and visualizing data
  • High-level spatiotemporal data analysis on:
    • NASA, ECMWF, and NOAA reanalysis and observational datasets (ERA5, MERRA-2, ERSST, NCEP/NCAR, etc.)
    • Community Climate System Model, v4 (CCSM4) forecast
    • Dry nonlinear baroclinic atmospheric model
    • Community Atmospheric Model, v5 (CAM5) output
  • Community Earth System Model (CESM1.2) and CAM5 setup, build, & conducted four different prescribed SST experiments, and mentored other graduate students on CESM process
  • Setup, write code for monsoon forcing, developed, and conducted idealized forcing experiments with a dry nonlinear baroclinic AGCM; created documentation, and mentored other graduate students; created scripts/functions for reading model output used by other graduate students
  • Build linear QG model that generates an upper-level mid-latitude response given a mean state (jet stream climatology) and forcing
  • Defended doctoral dissertation in May 2022
  • Oral presentation for 2022 AMS annual meeting
  • 1-hour Seminar for Dept. of Atmospheric Science at Rosenstiel School in November 2021
  • Oral presentation at 2021 AMS annual meeting
  • Oral presentation at Rosenstiel School Student Seminar series in 2019, 2020, 2021
  • Poster presentation at 2020 AMS annual meeting

Collaborator, PyWR, Weather Typing, and S2S Sources of Predictability Project

Summer 2022-Winter 2023
Project leads: Ángel Muñoz and Andrew Robertson

  • Project in collaboration with participants of NCAR Advanced Summer Program The Science of S2S Predictions PyWR and Weather Typing group and International Research Institute/Lamont-Doherty Earth Observatory (IRI/LDEO) scientists
  • Applying weather typing via k-means clustering to explore summertime predictability of North Atlantic circulation and associated precipitation
    • Primary contribution – boreal summer intraseasonal oscillation (BSISO) and East Asian monsoon (EAM) as a source of predictability for summer weather types
  • Poster presentation for 2022 AMS annual meeting

Intern, NOAA Climate and Weather Prediction Center, Ocean Prediction Center

Fall 2016-Spring 2017

  • Building case study analysis of stratospheric air intrusion events and improving hurricane-force wind forecasts of extratropical cyclones in Atlantic Ocean using satellite imagery
    • Primary channels/products: Himawari-8 Airmass RGB product; AIRS, IASI, and ATMS/CrIS total column ozone; Himawari-8 Water Vapor (6.2 μm, 6.9 μm, 7.3 μm); ASCAT winds; AMSR winds; NUCAPS profiles of moisture and temperature
    • MERRA-2 Global Reanalysis time-averaged and instantaneous 3-hourly data for cross-sectional analysis
  • Give presentations or instructional kits to Alaskan Weather Forecast Offices and Ocean and Weather Prediction Centers
  • Working with GEMPAK/AWIPS software, Python language for analyzing/visualizing data, Linux/Unix environment
  • Research defended for senior thesis:
    • oral prospectus defense in Fall 2016
    • poster presentation in Spring 2017
  • Poster presentation at 2017 AMS Annual Meeting

Intern, NOAA Earth System Research Lab Physical Sciences Division (ESRL/PSD)

Summer 2016

  • Diagnosed case study of atmospheric river event by comparing “present-day” precipitation and moisture transport over western US with simulated “future” case using pseudo-global warming approach
  • Work with Weather and Research Forecasting (WRF) output to compare control (present-day) run with pseudo-global warming (future) run
  • Read papers about Community Earth System Model-Large Ensemble, which was run to produce delta moisture and temperature values to add to WRF
  • Oral presentation at NOAA Hollings Research Symposium
  • Poster presentation at 2017 AMS Annual Meeting

Intern, UC San Diego Scripps Undergraduate Research Fellowship (SURF)

Summer 2015

  • Compared vertical profiles of Feb. 6th 2015 atmospheric river event using NCEP/NCAR Final Reanalysis model and dropsonde data
    • Wrote Matlab scripts to read and organize dropsonde and reanalysis data
    • Wrote Matlab scripts to plot vertical profiles of moisture flux and surface analyses of atmospheric river development
  • Simulated GPS radio occultation techniques (Doppler shift, bending angles, refractivity profiles)
  • Poster presentation at SIO SURF Student Symposium
  • Poster presentation at 2016 AMS Annual Meeting

Teaching Experience

Tutor for middle and high school students, mostly math and science | 2018-2022
Teaching Assistant for Data Analysis Methods (graduate course) | Spring 2020
Teaching Assistant for Weather Forecasting | Spring 2019
Teaching Assistant for Large-scale Atmospheric & Oceanic Dynamics | Spring 2017
Teaching Assistant for Atmospheric Thermodynamics | Fall 2016

Relevant Extracurriculars & Service

Co-founder, Writer, Editor, Seasoned Chaos blog about subseasonal-to-seasonal forecasting | Present
Lead Coordinator, Students for Students Outreach | Present
Mentor, Rosenstiel School Graduate-Undergraduate Mentoring (GUM) program | 2021-2022
Rosenstiel School Climate Group | 2017-2022
Rosenstiel School Marine Science Graduate Student Organization’s Sustainability Initiative | 2020-2021
Rosenstiel School Marine Science Graduate Student Organization’s Earth Week Committee | 2020-2021
Rosenstiel School New Student Orientation Committee | 2020
Creator, Rosenstiel School Seas by Degrees Video Seminar Series | March 2021
      Opening a Climate Scientist’s Toolbox: What is a Climate Model?
Rosenstiel School COMPASS Seminar Committee | 2019-2020
Presenter/Collaborator, Rosenstiel School Lunch Bytes Seminar Series | Spring 2019
SEGUE Student Reviewer (for UCAR Comet modules) | Fall 2019-Spring 2020
Rosenstiel School Atmospheric Science Dept. Student Ambassador | 2018-2019

Awards & Skills

  • Proficient in a wide range of modeling techniques, including:
    • Running state-of-the-art climate models to assess representation of climate dynamics/circulation and analyze long-term trends and large-scale climate variability
    • Building or running idealized climate models and designing experiments to investigate specific aspects of climate systems
    • Applying data-driven, empirical models to analyze and interpret climate data, identify patterns, and make predictions
  • Excellent writing skills and overall science communication skills (by medium of oral presentations, writing, video-making, interviews)
  • Involvement in many extracurricular and community organizations, including taking on leadership positions
  • Attended the 2021 NCAR Advanced Summer Program “The Science of Subseasonal-to-Seasonal Predictions” Colloquium and Workshop
  • Participated in 2022 AMS Short Course on Machine Learning for Environmental Sciences
  • Tutoring and teaching experience from middle school to graduate level
  • Experience in reviewing journal articles (https://orcid.org/0000-0002-1989-7490)
  • Runner-up for 2020-2021 Rosenstiel School Student Seminar Best Presentation Skills award
  • Finalist for Rosenstiel School Outstanding Outreach Award
  • Languages (in order of proficiency): Python, Matlab, Shell, Git Bash, Fortran, Markdown/HTML, NCAR Command Language (NCL), C
  • Software/Operating Systems (no particular order): Linux/Unix, Git Bash, Microsoft Office (Word, Excel, Powerpoint, etc.)
  • Involved in Machine Learning/Artificial Intelligence literature reading group with some experience in applying to climate data
  • Gave software and programming seminars to Rosenstiel School colleagues through “Lunch Bytes” program
  • Accepted into 2020 Swiss Climate Summer School (canceled because of COVID-19)
  • Attended Summer 2018 Weather and Climate Extremes NCAR Tutorial/Workshop
  • 2017 University of Maryland Undergraduate Researcher of the Year
  • 2017 University of Maryland Philip Merrill Presidential Scholar
  • 2017 Richard Jordan Scholar (for atmospheric & oceanic science senior thesis presentations)
  • 2016-2017 Outstanding Student Service in Atmos. & Oceanic Science Department
  • 2014-2017 Jeffrey & Lily Chen Scholar (for atmospheric & oceanic science majors)
  • 2015-2016 NOAA Ernest F. Hollings Scholar