pvlib.forecast.GFS

class pvlib.forecast.GFS(resolution='half', set_type='best')[source]

Subclass of the ForecastModel class representing GFS forecast model.

Model data corresponds to 0.25 degree resolution forecasts.

Parameters
  • resolution (string, default 'half') – Resolution of the model, either ‘half’ or ‘quarter’ degree.

  • set_type (string, default 'best') – Type of model to pull data from.

dataframe_variables

Common variables present in the final set of data.

Type

list

model

Name of the UNIDATA forecast model.

Type

string

model_type

UNIDATA category in which the model is located.

Type

string

variables

Defines the variables to obtain from the weather model and how they should be renamed to common variable names.

Type

dict

units

Dictionary containing the units of the standard variables and the model specific variables.

Type

dict

Methods

__init__([resolution, set_type])

Initialize self.

cloud_cover_to_ghi_linear(cloud_cover, ghi_clear)

Convert cloud cover to GHI using a linear relationship.

cloud_cover_to_irradiance(cloud_cover[, how])

Convert cloud cover to irradiance.

cloud_cover_to_irradiance_campbell_norman(…)

Estimates irradiance from cloud cover in the following steps:

cloud_cover_to_irradiance_clearsky_scaling(…)

Estimates irradiance from cloud cover in the following steps:

cloud_cover_to_transmittance_linear(cloud_cover)

Convert cloud cover (percentage) to atmospheric transmittance using a linear model.

connect_to_catalog()

get_data(latitude, longitude, start, end[, …])

Submits a query to the UNIDATA servers using Siphon NCSS and converts the netcdf data to a pandas DataFrame.

get_processed_data(*args, **kwargs)

Get and process forecast data.

gust_to_speed(data[, scaling])

Computes standard wind speed from gust.

isobaric_to_ambient_temperature(data)

Calculates temperature from isobaric temperature.

kelvin_to_celsius(temperature)

Converts Kelvin to celsius.

process_data(data[, cloud_cover])

Defines the steps needed to convert raw forecast data into processed forecast data.

rename(data[, variables])

Renames the columns according the variable mapping.

set_dataset()

Retrieves the designated dataset, creates NCSS object, and creates a NCSS query object.

set_location(tz, latitude, longitude)

Sets the location for the query.

set_query_latlon()

Sets the NCSS query location latitude and longitude.

set_query_time_range(start, end)

param start

Must be tz-localized.

set_time(time)

Converts time data into a pandas date object.

uv_to_speed(data)

Computes wind speed from wind components.

Attributes

access_url_key

base_tds_url

catalog_url

data_format

units