Closed csaybar closed 2 years ago
Hi @csaybar Can I confirm that the daily data users users/ryali93 is also something you are hosting? just want to make sure I wasn't missing out I know users/csaybar is you :) The page is now live and you can find it here. Let me know if all looks good and feel free to close the issue once confirmed. Thank you so much for contributing
Hi, @samapriya thanks for the super fast reply :)
Yes, unfortunately, the dataset surpasses the GEE asset quota (the max number of assets is 10k). Therefore, @ryali93 and I split the dataset and stored it together. Since we both will work with the dataset, there won't be any problem :)
Happy new year :partying_face:
Yeah I understand only new accounts have a limit of 50k older ones like ours had it at 10k, I am copying both of those into a joint collection and I should be able to combine it that way. Let me know if this is useful, if yes that I am happy to update the collection to the joint collection path.
projects/sat-io/open-datasets/rainpe/daily
Thank you again for contributing. Closing the issue now, will update the ticket when the collection merge is completed
Hi @samapriya yes that would be awesome. Thank you, let me know if I can help with something :100:
This combined asset is now completed @csaybar I can update the code and the description tomorrow to reflect it , hope this helps
projects/sat-io/open-datasets/rainpe/daily ===> 1 GB Total number of items in collection: 12783
I have updated the collection info, code link and the catalog to reflect the new collection
Thank u so much @samapriya it works perfectly from my side :).
High-resolution gridded precipitation dataset for Peruvian and Ecuadorian watersheds (1981-2015)
Dataset Name
RAIN4PE is a novel daily gridded precipitation dataset obtained by merging multi-source precipitation data (satellite-based Climate Hazards Group InfraRed Precipitation, CHIRP (Funk et al. 2015), reanalysis ERA5 (Hersbach et al. 2020), and ground-based precipitation) with terrain elevation using the random forest regression method. Furthermore, RAIN4PE is hydrologically corrected using streamflow data in catchments with precipitation underestimation through reverse hydrology. Hence, RAIN4PE is the only gridded precipitation product for Peru and Ecuador, which benefits from maximum available in-situ observations, multiple precipitation sources, elevation data, and is supplemented by streamflow data to correct the precipitation underestimation over páramos and montane catchments.
Currently included layers are:
Earth Engine Snippet: Annual mean
Sample Code: https://code.earthengine.google.com/35895dc6b3dda529d308673018cadced
Earth Engine Snippet: Monthly climatology
Sample Code: https://code.earthengine.google.com/5f88fb66ff5d9799c0bcd9ab7bccd200
Earth Engine Snippet: Monthly data
Sample Code: https://code.earthengine.google.com/3374b08b0eacaf0a4003d9098a4d56b3
Earth Engine Snippet: Daily data
Sample Code: https://code.earthengine.google.com/f62690ab93a65964ce753f080309e9eb
Resolution: 0.1° (or roughly 10km x 10km)
citation
When using the data please cite:
The data are supplementary material to:
License
This work is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy and redistribute the material in any medium or format, and to transform and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made.
Curated by: Cesar Aybar
Keywords: precipitation, streamflow, Peru, Ecuador, random forest, SWAT, reverse hydrology, satellite data, Earth observation, GIS.