CM1 Computer Model in Meteorology

Sep 14, 2024

Lecture Notes on CM1 Computer Model by Dr. Lee Orff

Introduction

  • Dr. Lee Orff, Atmospheric Scientist, University of Wisconsin-Madison
  • Research focus: Tornadoes and thunderstorms
  • Lecture objective: Showcase the potential of the CM1 computer model and its application in supercomputing in meteorology.

Lecture Structure

  1. Background on Cloud Modeling
    • Video detailing 30 years of cloud modeling history.
  2. Overview of CM1
    • Developed by George Bryan at NCAR (National Center for Atmospheric Research).
    • CM1 available for researchers to use, including simple tests on laptops.
  3. Visual Output from CM1
    • Animations and visualizations from Dr. Orff's previous work.
  4. Goal of Research
    • Improve severe weather prediction for societal benefits.
  5. Nature of Numerical Modeling
    • Involves mathematics and physics, simulates physical phenomena.
    • Models represent the physical world using complex equations.
  6. Question and Answer Session
    • 5 minutes for student inquiries at the end of the lecture.

Dr. Orff's Background

  • Experience in storm simulation since the 1990s.
  • Focus on downbursts and tornadoes due to their impact worldwide.
  • Breakthrough simulation in 2014: High-fidelity tornado simulation.
  • Previous teaching positions: UNC Asheville, Central Michigan University.
  • Returned to UW-Madison in 2015 to focus on storm simulation research.

Historical Context of Cloud Modeling

  • 1950s: ENIAC's first weather forecast.
  • 1960s: Emergence of supercomputers (e.g., CDC 6600, CDC 7600).
  • 1970s: Cray Corporation founded by Seymour Cray; development of Cray XMP.
  • 1980s-1990s: Evolution to massively parallel distributed memory architectures.
  • Modern Supercomputers: High-speed networks, increased processor counts, and graphical processing units (GPUs).

CM1 Model

  • Conceptual understanding of numerical models: forecasting time and space into the future.
  • Key equations in CM1: Changes in wind components (u, v, w) over time.
  • Model operations: Compiles code, executes simulations, and outputs results.

Working with the CM1 Model

  • Supercomputers require careful management of text-based code (Fortran).
  • CM1 uses nested loops for three-dimensional computations.
  • Data management is crucial: scientists must handle large volumes of output effectively.
  • Importance of collaboration in sharing and visualizing data.

Visualization of CM1 Output

  • Tools for meteorological data visualization: e.g., Vapor and ParaView.
  • Example visualizations:
    • Reflectivity (2D radar-like view) and updraft (3D representation).
    • Identification of features such as mesocyclones and tornadoes.
  • Role of lighting and color schemes in data interpretation and presentation.

Animation and Simulation Results

  • Demonstrations of thunderstorm simulations, including turbulence and storm behavior.
  • Observational features like above-anvil cirrus plumes linked to storm strength.
  • Importance of accurate visualization in scientific understanding.

Conclusion

  • Emphasis on the scientific value of high-resolution modeling and visualization in atmospheric science.
  • Dr. Orff invites questions and further discussion on the topics presented.