Skip to content

data.GHCNHourly

Global

Import path: earth2studio.data.GHCNHourly

View source on GitHub

Documentation

Bases: _GHCNBase

NOAA's Global Historical Climatology Network Hourly (GHCNh) is a global database of hourly surface observations that supersedes the Integrated Surface Database (ISD). It compiles observations from thousands of stations worldwide into a common data model with consistent CSV encoding.

Parameters:

  • stations (list[str]) –

    Station IDs in GHCN station format (11 characters), e.g. "USW00013874" for Atlanta Hartsfield-Jackson. Use GHCNHourly.get_stations_bbox to discover IDs by geographic area.

  • time_tolerance (TimeTolerance, default: timedelta64(10, 'm') ) –

    Time tolerance window for filtering observations. Accepts a single value (symmetric ± window) or a tuple (lower, upper) for asymmetric windows, by default np.timedelta64(10, 'm')

  • cache (bool, default: True ) –

    Cache data source on local memory, by default True

  • verbose (bool, default: True ) –

    Print download progress and missing data warnings, by default True

  • async_timeout (int, default: 600 ) –

    Time in sec after which download will be cancelled if not finished successfully, by default 600

  • async_workers (int, default: 16 ) –

    Maximum number of concurrent async fetch tasks, by default 16

  • retries (int, default: 3 ) –

    Number of retry attempts per failed fetch task with exponential backoff, by default 3

Warning

This is a remote data source and can potentially download a large amount of data to your local machine for large requests.

Note

To help get a list of possible station IDs, this class includes GHCNHourly.get_stations_bbox which accepts a lat-lon bounding box and will return known station IDs. For more information on the stations, users should consult the ghcnh-station-list.csv file accessible via GHCNHourly.get_station_metadata.

Note

Additional information on the data repository can be referenced here:

Example 
# Atlanta Hartsfield-Jackson airport
stations = GHCNHourly.get_stations_bbox((33, -85, 34, -84))
ds = GHCNHourly(stations, time_tolerance=timedelta(hours=1))
df = ds(datetime(2024, 1, 1, 12), ["t2m", "ws10m"])

__call__ 

__call__(
    time: datetime | list[datetime] | TimeArray,
    variable: str | list[str] | VariableArray,
    fields: str | list[str] | Schema | None = None,
) -> DataFrame

Function to get data.

Parameters:

  • time (datetime | list[datetime] | TimeArray) –

    Timestamps to return data for (UTC).

  • variable (str | list[str] | VariableArray) –

    String, list of strings or array of strings that refer to variables to return.

  • fields (str | list[str] | Schema | None, default: None ) –

    Fields to include in output, by default None (all fields).

Returns:

fetch async 

fetch(
    time: datetime | list[datetime] | TimeArray,
    variable: str | list[str] | VariableArray,
    fields: str | list[str] | Schema | None = None,
) -> DataFrame

Async function to get data.

Parameters:

  • time (datetime | list[datetime] | TimeArray) –

    Timestamps to return data for (UTC).

  • variable (str | list[str] | VariableArray) –

    String, list of strings or array of strings that refer to variables to return. Must be in the GHCNh lexicon.

  • fields (str | list[str] | Schema | None, default: None ) –

    Fields to include in output, by default None (all fields).

Returns:

available classmethod 

available(time: datetime | datetime64) -> bool

Check if the given date time is available for this data source.

Parameters:

Returns:

  • bool –

    If date time is available

Examples using earth2studio.data.GHCNHourly

Preview of StormCast-CONUS Score-Based Data AssimilationStormCast-CONUS Score-Based Data AssimilationRunning StormCast-CONUS with guided diffusion posterior sampling to assimilate observations.