mettoolbox.disaggregate.temperature

mettoolbox.disaggregate.temperature(method, source_units, min_max_time='fix', mod_nighttime=False, input_ts='-', start_date=None, end_date=None, dropna='no', clean=False, round_index=None, skiprows=None, index_type='datetime', names=None, print_input=False, target_units=None, max_delta=False, temp_min_col=None, temp_max_col=None, temp_mean_col=None, lat=None, lon=None, hourly=None)

Disaggregate daily temperature to hourly temperature.

For straight disaggregation the temperature units are not relevant, however other tools in mettoolbox require metric units. You can use source_units and target_units keywords to change units.

Input Data

Description

temp_min_col

Required column name or number representing the minimum daily temperature.

temp_max_col

Required column name or number representing the maximum daily temperature.

temp_mean_col

Optional column name or number representing the average daily temperature. Default is None and if None will be calculated as average of temp_min_col and temp_max_col.

Parameters:
  • method (str) –

    Disaggregation methods available for temperature.

    method

    Description

    sine_min_max

    Standard sine redistribution; preserves Tmin and Tmax but not Tmean.

    sine_mean

    Sine redistribution; preserves Tmean and the diurnal temperature range (Tmax – Tmin) but not Tmin and Tmax.

    mean_course_min_max

    Redistribute following a prescribed temperature course calculated from hourly observations; preserves Tmin and Tmax. Hourly CSV filename specified with the hourly keyword.

    mean_course_mean

    Redistribute following a prescribed temperature course calculated from hourly observations; preserves Tmean and the diurnal temperature range. Hourly CSV filename specified with the hourly keyword.

  • source_units (str) –

    If unit is specified for the column as the second field of a ‘:’ delimited column name, then the specified units and the ‘source_units’ must match exactly.

    Any unit string compatible with the ‘pint’ library can be used.

  • min_max_time (str) –

    min_max_time

    Description

    fix

    The diurnal course of temperature is fixed without any seasonal variations for sine method

    sun_loc

    The diurnal course of temperature is modelled based on sunrise, noon and sunset calculations for sine method.

    sun_loc_shift

    This option activates empirical corrections of the ideal course modelled by sun_loc for sine method. Hourly CSV filename specifiedwith the hourly keyword.

  • mod_nighttime (bool) – Allows one to apply a linear interpolation of night time values, which proves preferable during polar nights.

  • input_ts (str) –

    [optional though required if using within Python, default is ‘-’ (stdin)]

    Whether from a file or standard input, data requires a single line header of column names. The default header is the first line of the input, but this can be changed for CSV files using the ‘skiprows’ option.

    Most common date formats can be used, but the closer to ISO 8601 date/time standard the better.

    Comma-separated values (CSV) files or tab-separated values (TSV):

    File separators will be automatically detected.
    
    Columns can be selected by name or index, where the index for
    data columns starts at 1.
    

    Command line examples:

    Keyword Example

    Description

    –input_ts=fn.csv

    read all columns from ‘fn.csv’

    –input_ts=fn.csv,2,1

    read data columns 2 and 1 from ‘fn.csv’

    –input_ts=fn.csv,2,skiprows=2

    read data column 2 from ‘fn.csv’, skipping first 2 rows so header is read from third row

    –input_ts=fn.xlsx,2,Sheet21

    read all data from 2nd sheet all data from “Sheet21” of ‘fn.xlsx’

    –input_ts=fn.hdf5,Table12,T2

    read all data from table “Table12” then all data from table “T2” of ‘fn.hdf5’

    –input_ts=fn.wdm,210,110

    read DSNs 210, then 110 from ‘fn.wdm’

    –input_ts=’-’

    read all columns from standard input (stdin)

    –input_ts=’-’ –columns=4,1

    read column 4 and 1 from standard input (stdin)

    If working with CSV or TSV files you can use redirection rather than use –input_ts=fname.csv. The following are identical:

    From a file:

    command subcmd –input_ts=fname.csv

    From standard input (since ‘–input_ts=-’ is the default:

    command subcmd < fname.csv

    Can also combine commands by piping:

    command subcmd < filein.csv | command subcmd1 > fileout.csv

    Python library examples:

    You must use the `input_ts=...` option where `input_ts` can be
    one of a [pandas DataFrame, pandas Series, dict, tuple, list,
    StringIO, or file name].
    

  • start_date (str) –

    [optional, defaults to first date in time-series, input filter]

    The start_date of the series in ISOdatetime format, or ‘None’ for beginning.

  • end_date (str) –

    [optional, defaults to last date in time-series, input filter]

    The end_date of the series in ISOdatetime format, or ‘None’ for end.

  • dropna (str) –

    [optional, defauls it ‘no’, input filter]

    Set dropna to ‘any’ to have records dropped that have NA value in any column, or ‘all’ to have records dropped that have NA in all columns. Set to ‘no’ to not drop any records. The default is ‘no’.

  • clean

    [optional, default is False, input filter]

    The ‘clean’ command will repair a input index, removing duplicate index values and sorting.

  • round_index

    [optional, default is None which will do nothing to the index, output format]

    Round the index to the nearest time point. Can significantly improve the performance since can cut down on memory and processing requirements, however be cautious about rounding to a very course interval from a small one. This could lead to duplicate values in the index.

  • skiprows (list-like or integer or callable) –

    [optional, default is None which will infer header from first line, input filter]

    Line numbers to skip (0-indexed) if a list or number of lines to skip at the start of the file if an integer.

    If used in Python can be a callable, the callable function will be evaluated against the row indices, returning True if the row should be skipped and False otherwise. An example of a valid callable argument would be

    lambda x: x in [0, 2].

  • index_type (str) –

    [optional, default is ‘datetime’, output format]

    Can be either ‘number’ or ‘datetime’. Use ‘number’ with index values that are Julian dates, or other epoch reference.

  • names (str) –

    [optional, default is None, transformation]

    If None, the column names are taken from the first row after ‘skiprows’ from the input dataset.

    MUST include a name for all columns in the input dataset, including the index column.

  • target_units (str) –

    [optional, default is None, transformation]

    The purpose of this option is to specify target units for unit conversion. The source units are specified in the header line of the input or using the ‘source_units’ keyword.

    The units of the input time-series or values are specified as the second field of a ‘:’ delimited name in the header line of the input or in the ‘source_units’ keyword.

    Any unit string compatible with the ‘pint’ library can be used.

    This option will also add the ‘target_units’ string to the column names.

  • print_input

    [optional, default is False, output format]

    If set to ‘True’ will include the input columns in the output table.

  • tablefmt (str) –

    [optional, default is ‘csv’, output format]

    The table format. Can be one of ‘csv’, ‘tsv’, ‘plain’, ‘simple’, ‘grid’, ‘pipe’, ‘orgtbl’, ‘rst’, ‘mediawiki’, ‘latex’, ‘latex_raw’ and ‘latex_booktabs’.

  • temp_min_col (str, int) – The column name or number (data columns start numbering at 1) in the input data that represents the daily minimum temperature.

  • temp_max_col (str, int) – The column name or number (data columns start numbering at 1) in the input data that represents the daily maximum temperature.

  • temp_mean_col (str, int) – The column name or number (data columns start numbering at 1) in the input data that represents the daily mean temperature. If None will be estimated by the average of temp_min_col and temp_max_col.

  • lat (float) – The latitude of the station. Required if min_max_time is “sun_loc” or “sun_loc_shift”.

  • lon (float) – The longitude of the station. Required if min_max_time is “sun_loc” or “sun_loc_shift”.

  • hourly (str) – File name that contains the hourly time series of temperatures to use when method is “mean_course_min” or “mean_course_mean” or when max_delta is True.

  • max_delta (bool) – Uses maximum delta of hourly values for each month to constrain the disaggregated hourly temperature values. If set to True requires an hourly time-series filename specified with the hourly keyword.