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Friday, August 14, 2026

The 2025 Global Carbon Budget

CISESS Scientist Annika Jersild and other members of the international carbon cycle research community present a “living data” update on the global carbon budget, the 14th such update published in the journal Earth System Science Data. Her CISESS Project is funded by the NOAA Global Ocean Monitoring and Observing program (GOMO).
Friday, August 7, 2026

CISESS Scientists at the International Coral Reef Symposium

CISESS Scientists Rebecca Wenker and Rasheeda Alexander attended the 16th International Coral Reef Symposium (ICRS) in Auckland, New Zealand, from 19–24 July 2026, representing the NOAA NCEI Digital Corals team. Both presented posters about their work with NCEI on NOAA’s Coral Reef Monitoring Program Data Archive.

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Raspberry Pi Lightning Camera Network

CISESS Lightning Camera Network Seed Grant Results

CISESS Scientist Daile Zhang, with the help of her student interns Dominic Brooks, Alex Friedman and Samantha Smith, has designed and built a Raspberry Pi camera network for high-speed lightning video observation. Four Raspberry Pi Cameras were set up in Maryland, two in Arizona and one in Oklahoma.

 
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Virtual Reality

CISESS Virtual Reality Seed Grant Results

The goal of CISESS Scientists Guangyang Fang and Joseph Patton’s Seed Grant project was to develop a Virtual Reality (VR) tool that allows researchers and forecasters to interpret 3-D weather and climate datasets on a sphere more intuitively and efficiently. They redesigned their earlier user interface to make it easier to use – this effort was led by undergraduate interns Damian Figuero and Ashmita Pyne.

 
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Emulated Microwave Brightness Temperature

CISESS Passive Microwave Emulator Seed Grant Results

CISESS Scientists Veljko Petkovic and Malarvizhi Arulraj, with the help of PhD student, Vesta Gorooh, completed their CISESS Seed Grant used the GOES-R Advanced Baseline Imager to achieve highly accurate and location-specific information on clouds by approximating of passive microwave (PMW) observations using artificial intelligence/machine learning.

 
 
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