Satellite-based Precipitation Estimates for Operational Hydrology

HydroLearn Satellite-based Precipitation Estimates for Operational Hydrology Satellite-based Precipitation Estimates for Operational Hydrology View Course Problem statement In much of the world the rain gauge network is sparse and weather radar does not exist, yet the forecast desk still has to answer the same question every morning: how much rain fell, and where? For many National Meteorological and Hydrological Services, satellite precipitation estimates are the only spatially complete rainfall picture available in near real time. Three operational families dominate that picture: NASA's GPM IMERG , the EUMETSAT H SAF precipitation products , and the NOAA Enterprise Rain Rate (the operational SCaMPR algorithm). They are built differently, cover different parts of the globe, arrive at different speeds, and are downloaded in different ways. This module gives you working command of all three: how each estimate is made, how to download each for your own bounding box with a scripted notebook, and how to compare whichever products cover your region on a common grid. One rule governs everything: this is a comparison, not an evaluation . No product here is treated as the truth; deciding which is closest to what actually fell would require independent reference observations, which this module deliberately does not use. Short description Learn the three major satellite precipitation families (GPM IMERG, H SAF, and the NOAA Enterprise Rain Rate / SCaMPR), download each for your own region with Python notebooks, and compare them on a common grid with difference maps, scatter plots, and hyetographs. You finish by writing a one-page satellite rainfall briefing for your area of responsibility. Audience Early-career forecasters and hydrometeorologists at National Meteorological and Hydrological Services in WMO project countries, especially where gauges and radar are sparse. Fundamentals level. Estimated effort About 1.5 to 2 hours total. Self paced. Section Estimated time About page 5 min Section 1, Introduction 5 min Section 2, Meet the products 35 to 40 min (includes Learning Activity 1) Section 3, Access and comparison 30 to 35 min (includes Learning Activity 2) Section 4, Authentic task 15 to 20 min Prerequisites Basic precipitation vocabulary (rain rate, accumulation, convective, stratiform). Python at Jupyter-notebook level (run cells, edit a few lines); no remote-sensing background required. Comfort with latitude-longitude bounding boxes. No data accounts are needed in advance; the module says which to create and when. What you will be able to do by the end Describe how IMERG, the H SAF products, and the Enterprise Rain Rate each turn satellite measurements into rain rates. State each product's grid, time step, coverage, latency, record start, and account requirement. Download a subset of each product for your bounding box with the module notebooks (Earthdata login, H SAF registration, anonymous AWS access). Regrid the available products to a common grid and compare amount, placement, and timing in difference-based language. Attribute the differences to physically plausible causes and recommend a monitoring practice for your region, with no accuracy verdicts, which would require reference data this module does not use. Course card image suggestion Three side-by-side maps of one day's rainfall total from IMERG, H SAF, and the Enterprise Rain Rate (or the available pair) over one bounding box, exported from Notebook 04, with the module title across the top. Credits Module developed by Mohamed Abdelkader (University of Iowa) for the WMO Project capacity-building activity. References are listed at the end of Sections 2 and 3.