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GEE Python API and CHIRPS: Analyzing precipitation in Buenos Aires - Part 2

Project Overview In this post, we continue our exploration of the 2023 severe drought in Buenos Aires province, Argentina. In our previous post, we used the CHIRPS dataset to analyze the extent and impact of the drought. Now, we’ll take our analysis a step further by extracting time series data from specific coordinates within the affected region. To ensure that you can follow along and reproduce the results, all the code used in this analysis is available in my GitHub repository.

Thursday, August 15, 2024 Read
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GEE Python API and CHIRPS: Analyzing precipitation in Buenos Aires - Part 1

Project Overview Welcome back! In this post, we’ll delve into the severe drought that affected Buenos Aires Province in Argentina, in 2023, using the CHIRPS dataset and the Google Earth Engine (GEE) Python API. As detailed in the GEE catalog, CHIRPS—short for Climate Hazards Group InfraRed Precipitation with Station data—is a 30+ year quasi-global rainfall dataset. This dataset integrates satellite imagery with in-situ station data at a 0.05° resolution to generate gridded rainfall at daily temporal resolution.

Tuesday, July 30, 2024 Read
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  • marcenarojuanmartin@gmail.com
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  • Juan Martín Marcenaro

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