Rainfall Rate Algorithm
The amount of rain and the rate at which it is falling is important for flood forecasting as well as agricultural and water resource management. Rainfall rate is measured in millimeters per hour and expresses how har it is raining at the time of the observation. During drizzle, the rainfall rate is low (less than 1mm/hour) but during a down pour the rate is high (50 mm/hr or more.) Rain gauges on the ground can provide rainfall data, but only for that exact location. However, rain gauge locations are limited and rainfall can vary greatly over relatively short distances. For example, a small thunderstorm can produce an inch of rain in one location while no rain falls at all just a few miles away. Radars offer better coverage of rainfall than rain gauges but mountainous areas typically have poor radar coverage and the oceans have no coverage at all. GOES-R will provide rainfall data across the continental U.S. (or other area observed), even for areas without any rain gauges on the ground.
The Rainfall Rate/Quantitative Precipitation Estimate product provides a numerical value for the rate of rainfall in millimeters per hour at the instant the satellite observation was made for that location. The "location" is a 2 km (1.2 mile) square. These squares form a grid that is predefined and is the same for other ABI products.
A primary use of the product is as input for forecasts of stream flow and flooding.
Improvements and Benefits
The GOES-R will have four times the spatial resolution and take new images five times faster than the current system. This will contribute to better forecasts and warnings for floods, flash floods, and associated landslides. More accurate rainfall rates from areas with limited ground-based radar, for example mountainous headwaters and off-shore coastal storms, contributes to these improved forecasts and warnings
Proxy Hydroestimator Image, Europe
How does it work? - Algorithm
The processing combines GOES-R Advanced Baseline Imager (ABI) infrared images of the top of clouds with microwave data from other satellites to produce a better estimate of rainfall than is possible using only one of these sources.
How are the results compared to existing data? - Calibration and Validation
The fundamental challenge is that instantaneous measurements of rainfall rate are seldom available. The commonly used tipping-bucket rain gauges have inherent mechanical limitations that reduce the value of that data for validating the GOES-R data. Ground-based radar data that have been corrected for bias with rain gauge data provide the basis for GOES-R Rainfall Rate/Quantitative Prediction Estimate validation.
See the GOES-R ATBD page for the all ATBDs.