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An Air Quality Model That Is Evolving with the Times

ESSIC Scientist Min Huang is first author on a new article published in Eos, the American Geophysical Union’s science magazine. The article, titled “An Air Quality Model That Is Evolving with the Times”, discusses how the Sulfur Transport and Deposition Model (STEM) continues to find new applications and value in environmental science and policy making.

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Figure 1. Biases of accumulated precipitation (mm) relative to the MRMS ground-based analysis of the five machine learning models studied during the period of 1 May to 30 September, 2022. Biases of the operational MiRS algorithm are also shown in the bottom right panel.

Using Machine Learning to Improve Microwave-Based Precipitation Estimates

ESSIC/CISESS scientist Chris Grassotti along with CIRA and NOAA researchers Shuyan Liu and Quanhua (Mark) Liu, recently published a paper in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing titled “Warm-Season Microwave Integrated Retrieval System (MiRS) Precipitation Improvement Using Machine Learning Methods”.

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Terrestrial Water Storage In 2023: A Review

Earlier this month, Nature Reviews Earth & Environment released their annual Climate Chronicles, a collection of their ‘Year in Review’ articles. In these pieces, leading experts outline the observed characteristics and changes to select climate metrics and policies over the course of the year, collectively documenting the state of the climate and its ongoing evolution.

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