Tag: yan zhou

Figure 3. Monthly TPW anomaly time series shown in red for ERA5 and blue for MiRS SNPP, 2012-2021. The straight lines are the linear regression fits. [a] is for global, [b] for Tropics, and [c] for mid-latitude regions, respectively.

Evaluation of Total Precipitable Water Trends From Reprocessed MiRS SNPP ATMS Observations

November 15, 2024

Figure 3. Monthly TPW anomaly time series shown in red for ERA5 and blue for MiRS SNPP, 2012-2021. The straight lines are the linear regression

A satellite orbits around the Earth in this moody shot

Zhou and Grassotti Published on Development of Machine Learning-Based Radiometric Bias Correction for MiRS

October 5, 2020

ESSIC/CISESS scientists Post-doctoral Associate Yan Zhou and Senior Faculty Specialist Chris Grassotti have recently published in article in Remote Sensing titled “Development of a Machine Learning-Based Radiometric Bias Correction for NOAA’s Microwave Integrated Retrieval System (MiRS)”.

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Last Updated: 6 December 2024

Tag: yan zhou

Evaluation of Total Precipitable Water Trends From Reprocessed MiRS SNPP ATMS Observations

Zhou and Grassotti Published on Development of Machine Learning-Based Radiometric Bias Correction for MiRS

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