GribStream Blog
NOAA CCPA 1-hour precipitation analysis is now on GribStream
GribStream now serves NOAA's one-hour Climatologically Calibrated Precipitation Analysis on the CONUS NDGD 2.5 km grid for verification, hydrology, event review, and model evaluation.
We added NOAA's Climatologically Calibrated Precipitation Analysis to GribStream as ccpa1hndgd25, a one-hour precipitation analysis over CONUS on the NDGD 2.5 km grid.
CCPA is not another forecast. It is an analysis product, so the main question it answers is what precipitation was analyzed over the previous hour. That makes it a useful truth field for QPF verification, rainfall event review, hydrologic monitoring, model evaluation, and machine-learning workflows that need recent precipitation on a consistent grid.
Why CCPA matters
Precipitation is one of the hardest fields to verify cleanly. Radar-only estimates can have artifacts, gauge-only products can be too sparse for convective detail, and raw model precipitation is forecast guidance rather than an observed reference. CCPA was built to help with that middle ground.
NOAA's EMC description of CCPA emphasizes the combination of high-resolution multi-sensor QPE with gauge-based climatological calibration. The goal is a precipitation analysis that keeps useful spatial and temporal structure while reducing longer-term bias. That is why CCPA shows up in forecast verification, bias correction, downscaling, hydrology, and National Blend of Models work.
What is available
The new GribStream dataset is:
- CCPA 1-hour NDGD 2.5 km:
ccpa1hndgd25
It currently exposes one primary field:
APCP: one-hour accumulated precipitation
The product is most useful when paired with forecast datasets:
- compare analyzed precipitation against HRRR or HRRR sub-hourly for storm-scale verification
- compare against NBM for blended QPF evaluation
- combine with URMA when you need surface-condition actuals and precipitation analysis in the same workflow
- use GFS or RAP as larger-scale forecast context
Practical uses
CCPA is a good fit for:
- rainfall dashboards that need recent analysis instead of forecast totals
- QPF scorecards and model drift monitoring
- hydrology and flood-review workflows
- storm-event reconstruction
- precipitation feature engineering for ML models
- quality control for customer-facing weather products
The key difference from forecast guidance is interpretation. With CCPA, the valid time is an analyzed precipitation accumulation period. In other words, it belongs in the same mental bucket as verification and event review, not deterministic future prediction.