Summer 2017 Data Analysis: Satellite Remote Sensing for Atmospheric Variables

Aug 12, 2023

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This report presents an analysis of summer 2017 data collected through satellite remote sensing, with a focus on atmospheric variables such as PBLH, RH, and scatterplots. The study explores the impact of PBLH on data quality and addresses issues related to unaligned Cimel and BAM measurements. The analysis also highlights the challenges associated with high RH values and provides insights into time series alignment. Polyfit regression is utilized to develop a PBLH model.

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Summer 2017 Data Analysis: Satellite Remote Sensing for Atmospheric Variables

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Presentation Transcript

Summer 2017 Data Skylar Smith
Here Is Where I’m At • Satellite Remote Sensing • Cimel and BAM unaligned • Scatterplots have low R value • Time Series only sometimes align • PBLH effect on data • RH too high causes problems