Because precipitation is such a critical variable, it is vital that we understand the limitations of using the reanalysis precipitation products. This presentation demonstrates the use of the CREATE service to extract appropriate data using Earth System Grid Federation (ESGF) or THREDDS, and then analyze using the Earth Data Analysis Service (EDAS), and plot using standard plotting tools with examples from a collection of Jupyter notebooks.
Using tools and resources from the CREATE service, we will present some preliminary analyses of daily precipitation for the MRE3 and the individual reanalyses compared with daily Global Precipitation Climatology Project (GPCP), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR) and Integrated Multi-satellitE Retrievals for GPM (IMERG) data sets. We explore how best to compare the reanalysis precipitation rate with the latest observational data on a variety of time scales.