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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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Figure A

Machine Learning-Based Estimation of Tropical Cyclone Intensity from Advanced Technology Microwave Sounder Using a U-Net Algorithm

ESSIC/CISESS scientists Yong-Keun Lee and Christopher Grassotti are co-authors on a new paper in Remote Sensing led by first author Zichao Liang, a student who interned with the MiRS team during the summer of 2023. NOAA scientists Lin Lin and Quanhua Liu also co-authored the paper. The paper, titled “Machine Learning-Based Estimation of Tropical Cyclone Intensity from Advanced Technology Microwave Sounder Using a U-Net Algorithm”, assesses the use of the U-Net model to estimate surface wind speed and surface pressure over pure ocean conditions.

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Figure 1. The local perturbations in observed microwave brightness temperatures from an ascending orbit of (a) MetOp-B AMSU-A channel 14, (b) MetOp-C AMSU-A channel 14, a descending orbit of (c) NOAA-20 ATMS channel 15, and (d) SNPP ATMS channel 15 on January 15, 2022. The black triangle at the center for each panel is the Tonga volcano location. The outermost black-curved lines from the Tonga volcano location correspond to a phase speed of 330 m/s assuming that the perturbation has been generated at the time and location of initial volcanic eruption. From the 2nd outermost black-curved lines to the innermost lines, the phase speeds are 300, 270, and 230 m/s, respectively. The time information in each panel indicates the approximate observation time for the Lamb wave (between 300 m/s and 330 m/s indicated by black right-pointing triangles) and for the lead gravity wave (between 230 m/s and 270 m/s indicated by red right-pointing triangles). Red dots indicate the pixels where the brightness temperature perturbation is larger than 1.2 K.

Satellite Microwave Observations of the Hunga Tonga Eruption’s Atmospheric Waves

ESSIC/CISESS scientists Yong-Keun Lee and Christopher Grassotti are authors on a new paper in Geophysical Research Letters describing the first attempt to perform a detailed analysis of the stratospheric impact of the eruption from satellite microwave observations. The other authors on the paper are Neil Hindley from University of Bath and Quanhua (Mark) Liu from NOAA’s Center for Satellite Applications and Research.

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Fig 1. The retrieved total precipitable water (TPW) and temperature (500 mb) from TROPICs are in good agreement with ECMWF analysis.

Atmospheric Sounding from the CubeSat TROPICS Mission

ESSIC/CISESS scientists John Xun Yang, Yong-Keun Lee, and Christopher Grassotti are co-authors on a new paper titled “Atmospheric humidity and temperature sounding from the CubeSat TROPICS mission: Early performance evaluation with MiRS” in Remote Sensing of Environment.

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Figure: Total transmittance from surface to satellite (black line). The red line is the accumulated CRTM radiance Jacobian to ozone profile. Symbol “c” is the position at 331 nm used to estimate surface reflectance. The symbol “o” are the two channels, that we propose, to estimate the surface reflectance. The surface reflectance for other channels is either interpolated or extrapolated from the two reflectance at 347.6 nm and 371.8 nm.

UV Surface Reflectance from OMPS Nadir Mapper (NM) Radiance—Simulation and Assimilation

ESSIC/CISESS scientists Christopher Grassotti and Xingming Liang are co-authors in a recently published study that documents the first ultraviolet radiance assimilation for atmospheric ozone in the troposphere and stratosphere. The paper, titled “Experimental OMPS Radiance Assimilation through One-Dimensional Variational Analysis for Total Column Ozone in the Atmosphere”, was published in Remote Sensing and includes co-authors from the NOAA/NESDIS Center for Satellite Applications and Research.

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Acid Rain Scenes from Great Smoky Mountains National Park - Clingmans Dome

A Study of Two Impactful Heavy Rainfall Events

Several ESSIC/CISESS scientists including Malarvizhi Arulraj, Jifu Yin, Christopher Grassotti, Veljko Petkovic collaborated on a multi-author, two-part study led by Douglas Miller, Professor of Atmospheric Sciences at the University of North Carolina, Asheville.

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