pvlib.iotools.get_acis_mpe(latitude, longitude, start, end, map_variables=True, url='https://data.rcc-acis.org/GridData', **kwargs)[source]#

Retrieve estimated daily Multi-sensor Precipitation Estimates via the Applied Climate Information System (ACIS).

ACIS 2, 3 aggregates and provides access to climate data from many underlying sources. This function retrieves daily data from the National Weather Service’s Multi-sensor Precipitation Estimates (MPE) 1, a gridded precipitation model.

This dataset covers the contiguous United States, Mexico, and parts of Central America.

  • latitude (float) – in decimal degrees, between -90 and 90, north is positive

  • longitude (float) – in decimal degrees, between -180 and 180, east is positive

  • start (datetime-like) – First day of the requested period

  • end (datetime-like) – Last day of the requested period

  • map_variables (bool, default True) – When True, rename data columns and metadata keys to pvlib variable names where applicable. See variable VARIABLE_MAP.

  • url (str, default: ‘https://data.rcc-acis.org/GridData’) – API endpoint URL

  • kwargs – Optional parameters passed to requests.post.


  • data (pandas.DataFrame) – Daily precipitation [mm] data

  • metadata (dict) – Coordinates of the selected grid cell


requests.HTTPError – A message from the ACIS server if the request is rejected


The returned values are 24-hour aggregates, but the aggregation period may not be midnight to midnight in local time. Check the ACIS and MPE documentation for details.



Multisensor Precipitation Estimates


ACIS Gridded Data


ACIS Web Services


>>> from pvlib.iotools import get_acis_mpe
>>> df, meta = get_acis_mpe(40, -80, '2020-01-01', '2020-12-31')