NOAA RTMA analysis, virtual
| ID |
noaa-rtma-analysis-virtual
|
| Spatial domain | Continental United States |
| Spatial resolution | 2.5 km |
| Time domain | 2017-05-02 00:00:00 UTC to Present |
| Time resolution | 1 hour |
STAC (browse) · validation report
The Real-Time Mesoscale Analysis (RTMA) is NOAA NCEP's analysis of near-surface weather conditions. It combines observations with a model background using two-dimensional variational assimilation.
Hourly near-surface analyses on the 2.5 km CONUS Western Expansion grid, from 2017-05-02 onward. This virtual dataset references NOAA's GRIB files and is optimized for spatial (map) access. It contains 13 analysis fields, with dimensions time, y, and x on the native Lambert Conformal Conic projection. Precipitation is not included.
Related Datasets
Examples
|
RTMA, RTMA-RU and URMA analyses (Github) |
|
RTMA, RTMA-RU and URMA analyses (Colab) |
import dynamical_catalog # dynamical-catalog>=0.8.0
ds = dynamical_catalog.open("noaa-rtma-analysis-virtual", chunks=None)
ds["temperature_2m"].sel(time="2025-01-01T00")import icechunk
import pystac
import xarray as xr
catalog = pystac.Catalog.from_file("https://stac.dynamical.org/catalog.json")
collection = catalog.get_child("noaa-rtma-analysis-virtual")
asset = collection.assets["icechunk-https"]
authorize = icechunk.containers_credentials({"s3://noaa-rtma-pds/": icechunk.s3_anonymous_credentials()})
repo = icechunk.Repository.open(
icechunk.http_storage(asset.href),
authorize_virtual_chunk_access=authorize,
)
session = repo.readonly_session("main")
ds = xr.open_zarr(session.store, chunks=None)
ds["temperature_2m"].sel(time="2025-01-01T00")Explore
Dimensions
| min | max | units | |
|---|---|---|---|
| time | 2017-05-02T00:00:00Z | Present | seconds since 1970-01-01 |
| x | -3271147.288 | 2681916.544 | m |
| y | -263797.503 | 3789568.485 | m |
Variables
Access a variable by its name (the bold identifier, e.g. ds["cloud_ceiling_height"]).
Dimensions: time × y × x
| variable | units |
|---|---|
cloud_ceiling_height
Ceiling (ceil)
|
m |
dew_point_temperature_2m
2 metre dewpoint temperature (2d)
|
degree_Celsius |
geopotential_height_surface
Geopotential height (gh)
|
m |
pressure_surface
Surface pressure (sp)
|
Pa |
specific_humidity_2m
Specific humidity (q)
|
1 |
temperature_2m
2 metre temperature (2t)
|
degree_Celsius |
total_cloud_cover_atmosphere
Total cloud cover (tcc)
|
percent |
visibility_surface
Visibility (vis)
|
m |
wind_direction_10m
10 metre wind direction (10wdir)Direction the wind blows from, clockwise from true north.
|
degree |
wind_gust_10m
Wind speed (gust) (gust)
|
m s-1 |
wind_speed_10m
10 metre wind speed (10si)
|
m s-1 |
wind_u_10m
10 metre U wind component (10u)Velocity along the model grid's x dimension, not eastward velocity.
|
m s-1 |
wind_v_10m
10 metre V wind component (10v)Velocity along the model grid's y dimension, not northward velocity.
|
m s-1 |
Details
License
Dataset licensed under CC BY 4.0.
Attribution and citation
NOAA NWS NCEP RTMA data processed by dynamical.org from NOAA Open Data Dissemination archives.
Or NOAA RTMA from dynamical.org.
Construction
Hourly RTMA analyses are represented as virtual references to NOAA's CONUS Western Expansion GRIB files, on their native 2345 by 1597 Lambert Conformal Conic grid. Each chunk contains one complete field at one analysis time. The 13 fields include temperature, dew point, specific humidity, surface pressure, terrain height, wind, cloud cover, ceiling, and visibility. Precipitation is not included.
Wind components are grid-relative; wind direction is relative to true north. Ceiling and visibility retain the source's finite values. Consult the validation report for their interpretation and historical limitations.
Source
Source files are provided by NOAA Open Data Dissemination in the public NOAA RTMA archive.
Data availability
The archive begins at 2017-05-02 00:00 UTC and updates hourly. Missing source files remain gaps. See the validation report for checked coverage, source-archive gaps, and the ceiling/visibility findings.
Storage
Storage for this dataset is generously provided by AWS Open Data.
Chunks
This dataset is stored in Zarr format, which splits each variable into a grid of chunks — the smallest unit read from storage. 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 |
|---|---|
| time | 1 (1 hour) |
| y | 1597 (4055.91 km) |
| x | 2345 (5955.6 km) |
| uncompressed | 28.6 MiB |
Validation report
Review the validation report for variable availability, missing data, known quirks, fill values, value distributions, and sample plots.