Northern California Fires in September 2020

  • Released Monday, December 9, 2024
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This visualization shows the lightning over California on August 16 and 17, 2020 that caused 38 separate fires to ignite. These eventually combined into the August Complex fire, the first recorded gigafire in California history, which burned until November 12 consuming 1,614 square miles (4,180 square kilometers). As the lightning fades, a series of images shows the smoke emanating from the fires on September 8 of that year. The visible smoke is followed by a series showing the Aerosol Optical Depth (a unitless quantitative metric of how much smoke is present in the atmosphere) as the smoke particles were transported across the Western US and Canada over a 10 day period.

The GeoXO satellite system will watch over the Western Hemisphere and will provide real-time, high-resolution visible and infrared imagery for monitoring Earth’s weather, ocean, and environment. This observing system will also deliver information that sophisticated climate-forecasting models use to predict weather patterns, including emerging patterns caused by climate change.

This visualization highlights how three instruments onboard a GeoXO satellite work in concert to provide data of environmental hazards more quickly than ever before, enabling faster response on the ground to these hazards.

  • GeoXO Lightning Mapper (LMX), improving on GOES-R’s visible/infrared imagery and lightning mapping capabilities, will detect, locate, and measure the intensity, duration, and extent of lightning flashes. LMX will improve current hazard detection, hurricane intensity prediction, wildfire detection and response, precipitation estimation, and aviation hazard mitigation capabilities.
  • The GeoXO Imager (GXI) will observe the Western Hemisphere and provide variable area imagery and information about Earth’s surface, such as vegetation, water, clouds, moisture, and smoke.
  • The GeoXO Atmospheric Composition instrument (ACX) will provide hourly observations of air pollutants emitted by transportation, power generation, industry, oil and gas extraction, volcanoes, and wildfires, as well as secondary pollutants generated from these emissions once they are in the atmosphere. By providing continuous observations and measurements of atmospheric composition, ACX data will improve air quality monitoring and forecasting as well as enable mitigation of health impacts from severe pollution and smoke events.
Using current satellite observations and forecast model data, this visualization shows how these capabilities of the GeoXO satellite will work together to monitor severe weather events, the resulting wildfires and the atmospheric impact from these events. This visualization shows the lightning over California on August 16 and 17, 2020 that caused 38 separate fires to ignite. These eventually combined into the August Complex fire, the first recorded gigafire in California history, which burned until November 12 consuming 1,614 square miles (4,180 square kilometers). As the lightning fades, a series of images shows the smoke emanating from the fires on September 8 of that year. The visible smoke is followed by a series showing the Aerosol Optical Depth (a unitless quantitative metric of how much smoke is present in the atmosphere) as the smoke particles were transported across the Western US and Canada over a 10 day period.

The visualization of lightning, smoke and Aerosol Optical Depth without the date, clock and colorbar overlay.

This image shows lightning detected over California on August 20, 2020.

This image shows lightning detected over California on August 20, 2020.

This image shows fires detected in California and Oregon on September 8, 2020 along with the smoke eminating from the fires.

This image shows fires detected in California and Oregon on September 8, 2020 along with the smoke eminating from the fires.

This image shows aerosol optical depth at 550 nm over California and Oregon on September 9, 2020.

This image shows aerosol optical depth at 550 nm over California and Oregon on September 9, 2020.

The overlay containing date, clock and colorbar with transparency.

The overlay containing date, clock and colorbar with transparency.

Credits

Please give credit for this item to:
NASA's Scientific Visualization Studio

This page was originally published on Monday, December 9, 2024.
This page was last updated on Tuesday, January 21, 2025 at 12:14 AM EST.

Datasets used

  • GLM L2 Lightning Detection Gridded Product (OR_GLM-L2-GLMF-M3_G17) [GOES 17: GOES R Series Geostationary Lightning Mapper]

    ID: 1223
    Type: Observed Data Sensor: GOES R Series Geostationary Lightning Mapper Dates used: Aug 16-17, 2020

    The Lightning Detection Gridded product generates fields starting from the GLM Lightning Detection Events, Groups, Flashes product. It consists of flash extent density, event density, average flash area, average group area, total energy, flash centroid density, and group centroid density.

    Credit: Rudlosky, Scott .2022. GOES-R Geostationary Lightning Mapper (GLM) Gridded Data Products OR_GLM-L2-GLMF-M3_G17. Dataset available online from the NASA Global Hydrometeorology Resource Center DAAC, Huntsville, Alabama, U.S.A. DOI: http://dx.doi.org/10.5067/GLM/GRID/DATA101

    This dataset can be found at: https://cmr.earthdata.nasa.gov/search/concepts/C2278812167-GHRC_DAAC.html

    See all pages that use this dataset

  • GeoColor (GeoColor) [GOES-17: Advanced Baseline Imager (ABI)]

    ID: 1225
    Type: Observed Data Sensor: Advanced Baseline Imager (ABI) Dates used: Aug 16-17, 2020; Aug 31 - Sep 8, 2020

    GeoColor is a multi-spectral algorithm using five channels from the Advanced Baseline Imager (ABI) along with some static ancillary data to approximate true color during the daytime and highlight high and low clouds at night.

    Credit: Steven D. Miller, Steven D. Miller, Curtis J. Seaman, Jeremy E. Solbrig

    This dataset can be found at: https://journals.ametsoc.org/view/journals/atot/37/3/JTECH-D-19-0134.1.xml

    See all pages that use this dataset

  • Simulated Aerosol Optical Depth from the CMAQ model (Simulated Aerosol Optical Depth from the CMAQ model)

    ID: 1235
    Type: Model Dates used: Sep 8, 2020 - Sep 18, 2020

    Credit: Jianping Huang

    This dataset can be found at: https://www.epa.gov/cmaq

    See all pages that use this dataset

Note: While we identify the data sets used on this page, we do not store any further details, nor the data sets themselves on our site.