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fix time bounds in daily and monthly statistics #399

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fix time bounds in daily and monthly statistics #399

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ac4a22e
fix time bounds in daily and monthly statistics
SarahAlidoost Dec 12, 2019
5d66f7b
Remove unnecessary time arguments, add notes in docstrings and docume…
SarahAlidoost Dec 13, 2019
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3 changes: 2 additions & 1 deletion doc/esmvalcore/preprocessor.rst
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Expand Up @@ -675,7 +675,8 @@ The ``_time.py`` module contains the following preprocessor functions:
Statistics functions are applied by default in the order they appear in the
list. For example, the following example applied to hourly data will retrieve
the minimum values for the full period (by season) of the monthly mean of the
daily maximum of any given variable.
daily maximum of any given variable. The representative time for statistics
is (hour=12:00) in daily periods and (day=15, hour=12:00) in monthly periods.

.. code-block:: yaml

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24 changes: 22 additions & 2 deletions esmvalcore/preprocessor/_time.py
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Expand Up @@ -184,7 +184,9 @@ def daily_statistics(cube, operator='mean'):
"""
Compute daily statistics.

Chunks time in daily periods and computes statistics over them;
Chunks time in daily periods and computes statistics over them.
The statistics are assigned to a specific time (hour=12:00) in
daily period;

Parameters
----------
Expand All @@ -207,14 +209,24 @@ def daily_statistics(cube, operator='mean'):

operator = get_iris_analysis_operation(operator)
cube = cube.aggregated_by(['day_of_year', 'year'], operator)

# Correct the time coordinate
cube.coord('time').points = cube.coord('time').units.date2num([
cell.point.replace(hour=12, minute=0)
for cell in cube.coord('time').cells()])

cube.coord('time').bounds = None
cube.coord('time').guess_bounds()
return cube


def monthly_statistics(cube, operator='mean'):
"""
Compute monthly statistics.

Chunks time in monthly periods and computes statistics over them;
Chunks time in monthly periods and computes statistics over them.
The statistics are assigned to a specific time (day=15, hour=12:00)
in monthly period;

Parameters
----------
Expand All @@ -237,6 +249,14 @@ def monthly_statistics(cube, operator='mean'):

operator = get_iris_analysis_operation(operator)
cube = cube.aggregated_by(['month_number', 'year'], operator)

# Correct the time coordinate
cube.coord('time').points = cube.coord('time').units.date2num([
cell.point.replace(day=15, hour=12, minute=0)
for cell in cube.coord('time').cells()])

cube.coord('time').bounds = None
cube.coord('time').guess_bounds()
return cube


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