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Processing PACE data with Python get a polarized hyperspectral view of the Earth

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Processing PACE data with Python get a polarized hyperspectral view of the Earth
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34
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Abstract
PACE, the NASA Plankton, Aerosol, Clouds and ocean Ecosystem satellite was launched in February 2024 and carries three scientific instruments. The Ocean Color Instrument takes hyperspectral data at a 1 km x 1 km resolution and 2-day global coverage with very high radiometric accuracy. The two multiangle polarimeters, HARP2 and SPEXone, yield polarized data at a 5 km x 5 km resolution. HARP2 has 10-60 viewing angles at 4 spectral bands, while SPEXone (developed in the Netherlands) takes hyperspectral data at 5 viewing angles. Together, these instruments generate an unprecedented dataset that enables the characterization of ocean, land, clouds and the atmosphere. This tutorial aims to give the audience a jump-start into using data from the PACE mission using Python notebooks. We will explore Level-1 data (calibrated radiometry and multi-angle polarimetry) to create (hyperspectral) images of the Earth and look at Level-2 data and beyond in order to view higher level geophysical products, such as maps of atmospheric properties (e.g. aerosol and clouds), oceanic properties (e.g. phytoplankton), and land (e.g. vegetation).