Greetings! My name is Garrick Hague, and I am a climate analyst.

Welcome to my climate analyst portfolio! I am passionate about unlocking insights and driving business value through data. With a strong background in Atmospheric Science, I have honed my skills in data analysis, visualization, and storytelling to provide clear and actionable insights to decision-makers.

In this portfolio, you will find examples of my work that showcase my ability to translate complex data into meaningful insights and actionable recommendations. Thank you for taking the time to review my portfolio, and I look forward to hearing from you soon!

Portfolio

I have included a couple of projects in my portfolio that demonstrate my expertise as a climate analyst. To access the Jupyter notebooks for these projects, simply click on the corresponding image, which will take you to my GitHub repository. Each project title is accompanied by a list of the skills that were employed to complete it.

Earthquake Analysis from 1972-2022

  • Analysing Data Frames using Panda's
  • Querying Data
  • Data Cleaning

    • Analyzing Max Precipitation Events Using Extreme Value Theory

  • Familiarize with the topography of the Lake Tahoe region.
  • Examines precipitation differences between three locations.
  • Compare correlation of yearly max precipitation.
  • Apply Extreme Value Theory to estimate the likelihood of maximum precipitation per region.

    • Understanding the Impact of ENSO on Canadian Wildfires: A Comprehensive Analysis

  • Reveals nuanced patterns and insights regarding the frequency, intensity, and regional impacts of wildfires in Canada in relation to ENSO phases.
  • Utilizes data from Canadian Wildland Fire Information System and NOAA to create a comprehensive analysis dataframe.
  • Investigates correlation between Canadian wildfires and ENSO phases.

    • Weather Variability Influences Precipitation Levels in Lake Tahoe: A La Nina and El Nino Study

  • Processing Large Multi Dimensional Data
  • NetCDF Formated Data
  • OLS Linear Regression

    • Analysis of Fires >200 Hectares in Canada: Impact of Climate Indices

  • Integrating climate indices data to understand their relationship with wildfire occurrences.
  • Employed advanced machine learning techniques, including Linear Regression, Random Forest Regressor, and HistGradientBoosting Regressor, to analyze and predict wildfire patterns..
  • Utilized grid search and 5-fold cross-validation to optimize model performance, enhancing accuracy in predicting wildfire occurrences and severity.

    • About Me

    As a US Navy Veteran, I developed a strong sense of discipline, responsibility, and teamwork that have continued to guide me in all aspects of my life. When I'm not studying, I can often be found rock climbing or mountain biking, pushing myself to new heights and enjoying the natural world around me. I received my undergraduate degree in atmospheric science from the University of Nevada, Reno, where I gained a deep understanding of the complex processes that shape our planet's climate and weather patterns. In addition, I also had the opportunity to teach earth and space science to underserved high school students, which inspired me to pursue a career in data-driven decision-making. Now, as I pursue my master's degree in Weather Climate Risk Analytics at the University of Illinois Urbana-Champaign, I am excited to use my skills and knowledge to help organizations and individuals make informed decisions based on data-driven insights.

    Contact

    If you'd like to reach out to me, feel free to send me an email using the address provided below. Alternatively, you can also connect with me on LinkedIn or GitHub.

  • Located: Reno Nevada
  • Email: garricklive@gmail.com
  • linkedin: /in/garrickhague
  • GitHub: garrickhague