| Spatial domain | Continental United States |
| Spatial resolution | 0.01 degrees (~1km) |
| Time domain | 2014-11-01 00:00:00 UTC to Present |
| Time resolution | 1 hour |
The NOAA Multi-Radar/Multi-Sensor System (MRMS) integrates data from multiple radars and radar networks, surface observations, numerical weather prediction (NWP) models, and climatology to generate seamless, high spatio-temporal resolution mosaics at low latency focused on hail, wind, tornado, quantitative precipitation estimations, convection, icing, and turbulence.
This analysis dataset is an archive of MRMS radar and multi-sensor precipitation and weather analyses over the contiguous United States (CONUS).
| Quickstart (Github) | |
| Quickstart (Colab) |
import dynamical_catalog # dynamical-catalog>=0.7.0
ds = dynamical_catalog.open("noaa-mrms-conus-analysis-hourly")
ds["precipitation_surface"].sel(time="2026-01-01T00", latitude=40, longitude=-90, method="nearest").compute()
| min | max | units | |
|---|---|---|---|
| latitude | 20.005 | 54.995 | degree_north |
| longitude | -129.995 | -60.005 | degree_east |
| time | 2014-11-01T00:00:00Z | Present | seconds since 1970-01-01 |
Access a variable by its name (the bold identifier, e.g. ds["categorical_precipitation_type_surface"]).
Dimensions: time × latitude × longitude
| variable | units |
|---|---|
categorical_precipitation_type_surface
Precipitation type (ptype)Surface precipitation type flag. -3=no coverage, 0=no precipitation, 1=warm stratiform rain, 3=snow, 6=convective rain, 7=rain mixed with hail, 10=cold stratiform rain, 91=tropical/stratiform rain mix, 96=tropical/convective rain mix.
|
1 |
flash_qpe_ffg_max_surface
FLASH QPE-to-FFG percentage maximum (FLASH_QPE_FFGMAX)Maximum percentage of Quantitative Precipitation Estimate (QPE) to Flash Flood Guidance (FFG) from the FLASH system. Percentage where values > 100 indicate QPE exceeds FFG. Available from October 2020 onward.
|
percent |
precipitation_pass_1_surface
Precipitation rate (prate)Average precipitation rate over the previous hour, pass 1 (lower latency, fewer gauges). Derived from MultiSensor_QPE_01H_Pass1. Available from October 2020 onward. Units equivalent to mm/s.
|
kg m-2 s-1 |
precipitation_pass_2_surface
Precipitation rate (prate)Average precipitation rate over the previous hour, pass 2 (higher latency, more gauges). Derived from MultiSensor_QPE_01H_Pass2. Available from October 2020 onward. Units equivalent to mm/s.
|
kg m-2 s-1 |
precipitation_radar_only_surface
Precipitation rate from radar (rdpr)Average radar-only precipitation rate over the previous hour (no gauge correction). Derived from RadarOnly_QPE_01H. Units equivalent to mm/s.
|
kg m-2 s-1 |
precipitation_surface
Precipitation rate (prate)Average precipitation rate over the previous hour. Derived from MultiSensor_QPE_01H_Pass2 from October 2020, GaugeCorr_QPE_01H before. If primary product is unavailable, falls back to MultiSensor_QPE_01H_Pass1 and then RadarOnly_QPE_01H. Units equivalent to mm/s.
|
kg m-2 s-1 |
Dataset licensed under CC BY 4.0.
NOAA NWS NCEP MRMS data processed by dynamical.org from NOAA NCEP, NOAA Open Data Dissemination and Iowa Mesonet archives.
Or NOAA MRMS from dynamical.org.
Use this dataset over the land areas of the contiguous United States. Radar-only and precipitation type variables contain NaN values beyond the range of US radar. precipitation_pass_1_surface and precipitation_pass_2_surface extend further into the ocean, but still contain NaN values in the southeast corner of the domain over the Atlantic.
precipitation_surface combines multiple MRMS products to minimize missing values. Despite this, some hours (particularly early in the record) contain NaN values where data is unavailable.
precipitation_pass_2_surface and precipitation_pass_1_surface are available starting 2020-10-15. For timestamps prior to this date, these variables are filled with NaN.
The source files this archive is constructed from are provided by NOAA Open Data Dissemination (NODD) and accessed from the AWS Open Data Registry. Operational data is additionally accessed from NCEP.
Storage for this dataset is generously provided by Source Cooperative, a Radiant Earth initiative. Icechunk storage generously provided by AWS Open Data.
This dataset is stored in Zarr format, which splits each variable into a grid of chunks — the smallest unit read from storage. Chunks are grouped into larger shards (the objects actually written to storage), which keeps the object count manageable for long-archive datasets. When possible, aligning your reads with this dataset's chunk grid can significantly improve data access speed.
The element count and coordinate span of this dataset:
| dimension | chunk | shard |
|---|---|---|
| time | 648 (27 days) | 648 (27 days) |
| latitude | 100 (1°) | 700 (7°) |
| longitude | 100 (1°) | 1400 (14°) |
| uncompressed | 24.7 MiB | 2.4 GiB |
The data values in this dataset have been rounded in their binary floating point representation to improve compression. See Klöwer et al. 2021 for more information on this approach. The exact number of rounded bits can be found in our reformatting code.