Download Rainfall Data from 1981 to 2022 using Earth Engine

Visualize & Download monthly total Rainfall data (Rainfall Time series analysis) and export to Google Drive as a csv file using Google Earth Engine. Source code link: code.earthengi...
Download codes in text format: drive.google.c...
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Data Description:
Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) is a global high-resolution dataset of precipitation that combines satellite imagery with ground-based station observations. The CHIRPS dataset provides monthly, decadal (every ten days), and daily precipitation data at a resolution of approximately 5 kilometres.
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The CHIRPS dataset was developed by the Climate Hazards Group at the University of California, Santa Barbara, in collaboration with the United States Geological Survey (USGS). It is based on a combination of infrared satellite imagery from the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellite (GOES) system and ground-based station observations from a variety of sources, including national meteorological agencies and non-governmental organizations.
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The CHIRPS dataset is particularly useful for regions of the world where ground-based station observations are sparse or unreliable, as the satellite imagery provides an alternative source of data. Additionally, the dataset incorporates corrections for systematic biases in both the satellite and station data, resulting in more accurate precipitation estimates.
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The CHIRPS dataset is available for download from the Climate Hazards Group website and is updated on a daily basis. The dataset has been used in a wide range of applications, including drought monitoring, crop yield forecasting, and water resource management.
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[@alemayehumullatuadashio5350]

Thank you for the sharing.💯

[@TerraSpatial]

You're welcome! I'm glad I could help.👍

[@shawkatali3207]

Great video, thanks

[@TerraSpatial]

Thanks for your valuable comment

[@gamerchan8754]

Very good 👍

[@TerraSpatial]

Thank you

[@romulosantelices314]

Hello, the video is very interesting. I am working in an area of Chile and need to calculate climatic variables. I have a question about the Set visualization parameter: why is a max of 17 being used? Thank you in advance for clarifying my question. Best regards.

[@carolinrock-yn5ic]

Nice video

[@TerraSpatial]

Thanks a lot

[@A.G.channel]

FeatureCollection (Error)
Error in map(ID=512):
Image.reduceRegions: Need 1 bands for Reducer.mean, image has 0.

[@deboutcongolais4067]

Hello, thanks for sharing your knowledge. I am struggling to edit your code to filter a region, say Kampala region, instead of a country and get monthly precipitations. So far I have not been able to save the data in CSV. Any help?

[@toadfootns]

import shapefile of your region as asset and rename it to roi, thats the easiest way to do it... ofc delete or comment 1 part of code(// 1. Define countries boundary layer)
To vizualize it only on your region add .clip here: Map.addLayer(rainfall.mean().clip(roi), rainfall_Vis, 'Rainfall')

[@shawkatali3207]

@@toadfootnsThank you so much, worked for me

[@tofufa8903]

hi, may i know how can I modify it to get rainfall data for every country in the world and merge it into one dataset?

[@chiranjitsingha7787]

how to get the annual mean in this code.. ? could you please help