Skip to main content


The Meteorological Atmospheric Measurement Bolometer Array (MAMBA) is an all-sky infrared sensor designed to characterize atmospheric transmittance to support tactical and space sensors testing and operations. By continually and simultaneously monitoring atmospheric conditions, MAMBA enables superior weather situational awareness.

MAMBA (Meteorological Atmospheric Measurement Bolometer Array) is now in its third-generation design with improved sky coverage, resolution, and noise properties that is able to infer atmospheric transmittance to within a few percent. MAMBA provides day and night weather situational awareness for equipment that is sensitive to atmospheric transmission loss.

In 2017, MAMBA was demonstrated for the U.S. Naval Air Systems Command at Naval Air Station Patuxent River. It successfully completed all technical objectives in characterizing atmospheric transmittance.  Oceanit is now exploring beyond MAMBA's current mission, developing future possibilities as a tactical sensor.

The all-sky infrared camera combines an equiresolution optical design with a thermal detector and in-field blackbody calibration sources to provide uniform sensitivity and radiometric accuracy across the sky at a relatively low price point. This system combines a next generation thermal all-sky camera, a weather station, and an AI neural net trained on historic Radiosonde profiles.

Information is driven to the cloud and available for review. MAMBA continually and simultaneously monitors atmospheric conditions enabling industries that are sensitive to atmospheric transmission loss, such as Astronomy observation, Solar power cloud prediction, and Telecommunications to function more proficiently.

Oceanit is taking orders for MAMBA for delivery in 2018, making this game-changing technology available for the astronomical community. To place an advance order for MAMBA or for more information, contact us.

  • IR atmospheric transmittance
  • 24-hour cloud monitoring
  • Precipitable water vapor tracking
  • AI neural net trained on historic Radiosonde profiles