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IconlamSource

Classes:

  • IconlamSource –

    SChen: The IconlamSource from the output of ICON-LAM model minics the ERA5soure.

IconlamSource 

IconlamSource(source, bounds=None, index_pad=5, **kwargs)

Bases: NCSource

SChen: The IconlamSource from the output of ICON-LAM model minics the ERA5soure.

Note:

Various constants can have been set for this weather source which can impact later simulation workflows.

These constants include: MAX_LON_DIFFERENCE = 0.034 # SChen this is for 0.033 ICON-LAM grid The maximum longitude difference to accept between a grid cell's center and the coordinates to extract data for

MAX_LAT_DIFFERENCE = 0.034 # SChen this is for 0.033 ICON-LAM grid
    The maximum latitude difference to accept between a grid cell's center and the coordinates
        to extract data for

WIND_SPEED_HEIGHT_FOR_WIND_ENERGY = 100
    The suggested altitude of wind speed data to use for wind-energy simulations

WIND_SPEED_HEIGHT_FOR_SOLAR_ENERGY = 10
    The suggested altitude of wind speed data to use for wind-energy simulations

LONG_RUN_AVERAGE_WINDSPEED :
    <RESKit path>/weather/Era5Source/data/ERA5_wind_speed_100m_mean.tiff

    A path to a raster file with the long-time average wind speed in each grid cell
    * Can be used in wind energy simulations
    * Calculated at the height specified in `WIND_SPEED_HEIGHT_FOR_WIND_ENERGY`
    * Time range includes 1980 until the end of 2019 (the time of first calculation)
    * The averaging is performed globally

LONG_RUN_AVERAGE_WINDDIR :
    <RESKit path>/weather/Era5Source/data/ERA5_wind_direction_100m_mean.tiff

    A path to a raster file with the long-time average wind direction in each grid cell
    * Can be used in wind energy simulations
    * Calculated at the height specified in `WIND_SPEED_HEIGHT_FOR_WIND_ENERGY`
    * Time range includes 1980 until the end of 2019 (the time of first calculation)
    * The averaging is performed globally

LONG_RUN_AVERAGE_GHI :
    <RESKit path>/weather/Era5Source/data/ERA5_surface_solar_radiation_downwards_mean.tiff

    A path to a raster file with the long-time average global horizontal irradiance in
        each grid cell
    * Can be used in solar energy simulations
    * Calculated at the surface
    * Time range includes 1980 until the end of 2019 (the time of first calculation)
    * The averaging is performed globally

LONG_RUN_AVERAGE_DNI :
    <RESKit path>/weather/Era5Source/data/ERA5_total_sky_direct_solar_radiation_at_surface_mean.tiff

    A path to a raster file with the long-time average direct horizontal irradiance in
        each grid cell
    * Can be used in solar energy simulations
    * Calculated at the surface and on a horizontal plane (not DNI!)
    * Time range includes 1980 until the end of 2019 (the time of first calculation)
    * The averaging is performed globally
See Also

reskit.weather.MerraSource reskit.weather.SarahSource reskit.weather.Era5Source

Initialize a ERA5 style netCDF4 file source

Compared to the generic NCSource object, the following parameters are automatically set: * tz = None * time_name = "time" * lat_name = "latitude" * lon_name = "longitude" * flip_lat = True * flip_lon = False * time_offset_minutes = +30

Parameters:

  • path

    (str or list of str) –

    The path to the main data file(s) to load

    If multiple files are given, or if a directory of netCDF4 files is given, then it is assumed that all files ending with the extension '.nc' or '.nc4' should be managed by this object. * Be sure that all the netCDF4 files given share the same time and spatial dimensions!

  • bounds

    (Anything acceptable to geokit.Extent.load(), default: None ) –

    The boundaries of the data which is needed * Usage of this will help with memory management * If None, the full dataset is loaded in memory * The actual extent of the loaded data depends on the source's available data

  • index_pad

    (int, default: 5 ) –

    The padding to apply to the boundaries * Useful in case of interpolation * Units are in longitudinal degrees

  • verbose

    (bool) –

    If True, then status outputs are printed when searching for and reading weather data

  • forward_fill

    (bool) –

    If True, then missing data in the weather file is forward-filled * Generally, there should be no missing data at all. This option is only intended to catch the rare scenarios where one or two timesteps are missing

See Also

MerraSource SarahSource Era5Source

Methods:

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def __init__(self, source, bounds=None, index_pad=5, **kwargs):
    """Initialize a ERA5 style netCDF4 file source

    Compared to the generic NCSource object, the following parameters are automatically set:
        * tz = None
        * time_name = "time"
        * lat_name = "latitude"
        * lon_name = "longitude"
        * flip_lat = True
        * flip_lon = False
        * time_offset_minutes = +30


    Parameters
    ----------
    path : str or list of str
        The path to the main data file(s) to load

        If multiple files are given, or if a directory of netCDF4 files is given, then it is assumed
        that all files ending with the extension '.nc' or '.nc4' should be managed by this object.
        * Be sure that all the netCDF4 files given share the same time and spatial dimensions!

    bounds : Anything acceptable to geokit.Extent.load(), optional
        The boundaries of the data which is needed
          * Usage of this will help with memory management
          * If None, the full dataset is loaded in memory
          * The actual extent of the loaded data depends on the source's
            available data

    index_pad : int, optional
        The padding to apply to the boundaries
          * Useful in case of interpolation
          * Units are in longitudinal degrees

    verbose : bool, optional
        If True, then status outputs are printed when searching for and reading weather data

    forward_fill : bool, optional
        If True, then missing data in the weather file is forward-filled
        * Generally, there should be no missing data at all. This option is only intended to
            catch the rare scenarios where one or two timesteps are missing

    See Also
    --------
    MerraSource
    SarahSource
    Era5Source
    """
    super().__init__(
        source=source,
        bounds=bounds,
        time_name="time",
        lat_name="lat",  # "latitude"
        lon_name="lon",  # "longitude"
        index_pad=index_pad,
        _max_lon_diff=self.MAX_LON_DIFFERENCE,
        _max_lat_diff=self.MAX_LAT_DIFFERENCE,
        tz=None,
        flip_lat=True,
        time_offset_minutes=0,  # 30 SChen
        **kwargs,
    )

sload_boundary_layer_height 

sload_boundary_layer_height()

Standard loader function for the variable 'boundary_layer_height' in meters from the surface

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_boundary_layer_height(self):
    """Standard loader function for the variable 'boundary_layer_height' in meters
    from the surface

    """
    return self.load("blh", "boundary_layer_height")

sload_direct_horizontal_irradiance 

sload_direct_horizontal_irradiance()

Standard loader function for the variable 'direct_horizontal_irradiance'

Automatically reads the variable "fdir" from the given ERA5 source and saves it as the variable 'direct_horizontal_irradiance' in the data library

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_direct_horizontal_irradiance(self):
    """Standard loader function for the variable 'direct_horizontal_irradiance'

    Automatically reads the variable "fdir" from the given ERA5 source and saves it as the
    variable 'direct_horizontal_irradiance' in the data library
    """
    return self.load("fdir", name="direct_horizontal_irradiance")

sload_elevated_wind_direction 

sload_elevated_wind_direction()

Standard loader function for the variable 'elevated_wind_direction'

Automatically reads the variables "wd" from the given ERA5 source and saves it as the variable 'elevated_wind_direction' in the data library

Where '' is the height specified by Era5Source.ELEVATED_WIND_SPEED_HEIGHT

The "wd" variable also needs to be precomputed from the raw variables "u" and "v" and made available in the raw dataset

TODO: Update function to also be able to handle raw ERA5 inputs for u & v

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_elevated_wind_direction(self):
    """Standard loader function for the variable 'elevated_wind_direction'

    Automatically reads the variables "wd<X>" from the given ERA5 source and saves
    it as the variable 'elevated_wind_direction' in the data library

    Where '<X>' is the height specified by `Era5Source.ELEVATED_WIND_SPEED_HEIGHT`

    The "wd<X>" variable also needs to be precomputed from the raw variables "u<X>"
        and "v<X>" and made available in the raw dataset

    TODO: Update function to also be able to handle raw ERA5 inputs for u & v
    """
    return self.load("wd100", "elevated_wind_direction")

sload_elevated_wind_speed 

sload_elevated_wind_speed()

Standard loader function for the variable 'elevated_wind_speed'

Automatically reads the variables "ws" from the given ERA5 source and saves it as the variable 'elevated_wind_speed' in the data library

Where '' is the height specified by Era5Source.ELEVATED_WIND_SPEED_HEIGHT

The "ws" variable also needs to be precomputed from the raw variables "u" and "v"

TODO: Update function to also be able to handle raw ERA5 inputs for u & v

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_elevated_wind_speed(self):
    """Standard loader function for the variable 'elevated_wind_speed'

    Automatically reads the variables "ws<X>" from the given ERA5 source and saves
    it as the variable 'elevated_wind_speed' in the data library

    Where '<X>' is the height specified by `Era5Source.ELEVATED_WIND_SPEED_HEIGHT`

    The "ws<X>" variable also needs to be precomputed from the raw variables "u<X>"
        and "v<X>"

    TODO: Update function to also be able to handle raw ERA5 inputs for u & v
    """
    return self.load("ws{}".format(self.ELEVATED_WIND_SPEED_HEIGHT), "elevated_wind_speed")

sload_global_horizontal_irradiance 

sload_global_horizontal_irradiance()

Standard loader function for the variable 'global_horizontal_irradiance'

Automatically reads the variable "ssrd" from the given ERA5 source and saves it as the variable 'global_horizontal_irradiance' in the data library

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_global_horizontal_irradiance(self):
    """Standard loader function for the variable 'global_horizontal_irradiance'

    Automatically reads the variable "ssrd" from the given ERA5 source and saves it as the
    variable 'global_horizontal_irradiance' in the data library
    """
    return self.load("ssrd", name="global_horizontal_irradiance")

sload_surface_air_temperature 

sload_surface_air_temperature()

Standard loader function for the variable 'surface_air_temperature'

Automatically reads the variable "t2m" from the given ERA5 source and saves it as the variable 'surface_air_temperature' in the data library

Temperature values are also converted from kelvin to degrees celsius

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_surface_air_temperature(self):
    """Standard loader function for the variable 'surface_air_temperature'

    Automatically reads the variable "t2m" from the given ERA5 source and saves it as the
    variable 'surface_air_temperature' in the data library

    Temperature values are also converted from kelvin to degrees celsius
    """
    return self.load("t2m", name="surface_air_temperature", processor=lambda x: x - 273.15)

sload_surface_dew_temperature 

sload_surface_dew_temperature()

Standard loader function for the variable 'surface_dew_temperature'

Automatically reads the variable "d2m" from the given ERA5 source and saves it as the variable 'surface_dew_temperature' in the data library

Temperature values are also converted from kelvin to degrees celsius

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_surface_dew_temperature(self):
    """Standard loader function for the variable 'surface_dew_temperature'

    Automatically reads the variable "d2m" from the given ERA5 source and saves it as the
    variable 'surface_dew_temperature' in the data library

    Temperature values are also converted from kelvin to degrees celsius
    """
    return self.load("d2m", name="surface_dew_temperature", processor=lambda x: x - 273.15)

sload_surface_pressure 

sload_surface_pressure()

Standard loader function for the variable 'surface_pressure'

Automatically reads the variable "sp" from the given ERA5 source and saves it as the variable 'surface_pressure' in the data library

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_surface_pressure(self):
    """Standard loader function for the variable 'surface_pressure'

    Automatically reads the variable "sp" from the given ERA5 source and saves it as the
    variable 'surface_pressure' in the data library
    """
    return self.load("sp", name="surface_pressure")

sload_surface_wind_speed 

sload_surface_wind_speed()

Standard loader function for the variable 'surface_wind_speed'

Automatically reads the variables "ws" from the given ERA5 source and saves it as the variable 'surface_wind_speed' in the data library

Where '' is the height specified by Era5Source.SURFACE_WIND_SPEED_HEIGHT

The "ws" variable also needs to be precomputed from the raw variables "u" and "v"

TODO: Update function to also be able to handle raw ERA5 inputs for u & v

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_surface_wind_speed(self):
    """Standard loader function for the variable 'surface_wind_speed'

    Automatically reads the variables "ws<X>" from the given ERA5 source and saves
    it as the variable 'surface_wind_speed' in the data library

    Where '<X>' is the height specified by `Era5Source.SURFACE_WIND_SPEED_HEIGHT`

    The "ws<X>" variable also needs to be precomputed from the raw variables "u<X>"
        and "v<X>"

    TODO: Update function to also be able to handle raw ERA5 inputs for u & v
    """
    return self.load("ws{}".format(self.SURFACE_WIND_SPEED_HEIGHT), "surface_wind_speed")

sload_wind_speed_at_100m 

sload_wind_speed_at_100m()

Standard loader function for the variable 'wind_speed_at_100m'

Automatically reads the variables "ws100" from the given ERA5 source and saves it as the variable 'wind_speed_at_100m' in the data library

The "ws100" variable also needs to be precomputed from the raw variables "u100" and "v100"

TODO: Update function to also be able to handle raw ERA5 inputs for u & v

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_wind_speed_at_100m(self):
    """Standard loader function for the variable 'wind_speed_at_100m'

    Automatically reads the variables "ws100" from the given ERA5 source and saves
    it as the variable 'wind_speed_at_100m' in the data library

    The "ws100" variable also needs to be precomputed from the raw variables "u100"
        and "v100"

    TODO: Update function to also be able to handle raw ERA5 inputs for u & v
    """
    return self.load("ws100", "wind_speed_at_100m")

sload_wind_speed_at_10m 

sload_wind_speed_at_10m()

Standard loader function for the variable 'wind_speed_at_10m'

Automatically reads the variables "ws10" from the given ERA5 source and saves it as the variable 'wind_speed_at_10m' in the data library

The "ws10" variable also needs to be precomputed from the raw variables "u10" and "v10"

TODO: Update function to also be able to handle raw ERA5 inputs for u & v

Source code in reskit/weather/IconlamSource/IconlamSource.py 
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def sload_wind_speed_at_10m(self):
    """Standard loader function for the variable 'wind_speed_at_10m'

    Automatically reads the variables "ws10" from the given ERA5 source and saves
    it as the variable 'wind_speed_at_10m' in the data library

    The "ws10" variable also needs to be precomputed from the raw variables "u10"
        and "v10"

    TODO: Update function to also be able to handle raw ERA5 inputs for u & v
    """
    return self.load("ws10", "wind_speed_at_10m")