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Figure: Flowchart of the satellite and near space platform simulator.

Orbit Simulator for Satellite and Near Space Platforms

ESSIC/CISESS Scientists Likun Wang, Ross Hoffman and Kayo Ide have a new manuscript accepted for publication at the Journal of Atmospheric and Oceanic Technology titled “Orbit Simulator for Satellite and Near Space Platforms Supporting Observing System Simulation Experiments”.

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Figure. The 6 × 6 km2 Howland forest area in Maine: (A) the true color image obtained by the EO-1 Hyperion on March 5, 2014 (DOY 64) at a spatial resolution of 30 m; and maps of (B) snow cover fraction (SNOWCF); (C) surface water cover fraction (WaterBodyCF); (D)soil cover fraction (SOILCF); (E) vegetation cover fraction (VGCF); (F) fAPARcanopy; (G) fAPARchl; (H) fAPARnon-chl.

An Evergreen Forest Ecosystem from Satellites

ESSIC/CISESS Scientist Qingyuan Zhang has a new article to be published in International Journal of Applied Earth Observation and Geoinformation that characterizes the seasonally snow-covered Howland boreal forest ecosystem in Maine, USA with satellite images.

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Figure: This is a precipitation event on 29 August 2020 over the Pacific Ocean near the lower California peninsula. (a) the cross-track radiometer precipitation data, (b) the conical scanning radiometer precipitation data, (c) the reference data for the event, and (d) the “morphed” radiometer precipitation data. The box shows the area of improvement due to morphing.

Improving Satellite Precipitation Retrieval

ESSIC/CISESS Scientists Yalei You, John Xun Yang, and Jun Dong have a new article on using “morphing” to improve rain data from cross-track scanning radiometers. The paper, titled “Improving Cross-track Scanning Radiometers’ Precipitation Retrieval over Ocean by Morphing”, is in press at the Journal of Hydrometeorology.

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