Example of Incorrect Output

Oct 13, 2025 by miodeya.com 95 views

Introduction

In the icenetv0.4.0_dev branch, the forecast_date variable is being computed differently, resulting in an incorrect output in the netCDF file. This issue affects both monthly and daily forecasts, causing the forecast_date to be saved as the initialisation date for each leadtime. In this article, we will explore the issue, provide an example of the incorrect output, and propose a simple fix to resolve the problem.

Understanding the Issue

The forecast_date variable is computed using the following code snippet:

forecast_date = date + relativedelta(days=lead_idx)

However, this code snippet is missing the dictionary unpacking operator **, which is necessary to correctly compute the forecast_date based on the frequency attribute of the ground_truth_ds_config.

Example of Incorrect Output

As an example, let's consider a monthly forecast with a leadtime of 1 month. The output should start with the date one month ahead of the initialisation date and increment by one month for each leadtime. However, due to the incorrect computation, the output is as follows:

array([['2024-07-31T00:00:00.000000000', '2024-07-31T00:00:00.000000000',
        '2024-07-31T00:00:00.000000000', '2024-07-31T00:00:00.000000000',
        '2024-07-31T00:00:00.000000000', '2024-07-31T00:00:00.000000000',
        '2024-07-31T00:00:00.000000000', '2024-07-31T00:00:00.000000000',
        '2024-07-31T00:00:00.000000000', '2024-07-31T00:00:00.000000000',
        '2024-07-31T00:00:00.000000000', '2024-07-31T00:00:00.000000000']],
      dtype='datetime64[ns]')

As we can see, the dates are all the same, which is the initialisation date.

Proposed Fix

To resolve this issue, we need to modify the code snippet to correctly compute the forecast_date based on the frequency attribute of the ground_truth_ds_config. We can do this by using the dictionary unpacking operator ** to unpack the frequency attribute into the relativedelta function. The corrected code snippet is as follows:

forecast_date = date + relativedelta(**{"{}s".format(ground_truth_ds_config.frequency.attribute): int(lead_idx)})

This code snippet will correctly compute the forecast_date based on the frequency attribute of the ground_truth_ds_config, resulting in the correct output.

Testing the Fix

To test the fix, we can use the following code snippet:

import netCDF4 as nc
import datetime as dt

# Load the netCDF file
nc_file = nc.Dataset('/data/hpcdata/users/jambyr/icenet4/scratch/pipeline.monthly/results/forecasts/prediction.aug24.north/2024-07-31/2024-07-31.nc', 'r')

# Get the forecast_date variable
forecast_date = nc_file.variables['forecast_date'][:]

# Print the forecast_date variable
print(forecast_date)

This code snippet will load the netCDF file and print the forecast_date variable. If the fix is correct, the output should be the correct dates starting from one month ahead of the initialisation date and incrementing by one month for each leadtime.

Conclusion

Q: What is the issue with the `forecast_date` variable in the `icenetv0.4.0_dev` branch?

A: The forecast_date variable is being computed incorrectly, resulting in an incorrect output in the netCDF file. Specifically, the code snippet is missing the dictionary unpacking operator **, which is necessary to correctly compute the forecast_date based on the frequency attribute of the ground_truth_ds_config.

Q: What is the expected output for the `forecast_date` variable?

A: The expected output for the forecast_date variable is a list of dates starting from one month ahead of the initialisation date and incrementing by one month for each leadtime.

Q: What is the current output for the `forecast_date` variable?

A: The current output for the forecast_date variable is a list of dates that are all the same, which is the initialisation date.

Q: How can I fix the issue with the `forecast_date` variable?

A: To fix the issue with the forecast_date variable, you can modify the code snippet to correctly compute the forecast_date based on the frequency attribute of the ground_truth_ds_config. The corrected code snippet is as follows:

forecast_date = date + relativedelta(**{"{}s".format(ground_truth_ds_config.frequency.attribute): int(lead_idx)})

Q: How can I test the fix for the `forecast_date` variable?

A: To test the fix for the forecast_date variable, you can use the following code snippet:

import netCDF4 as nc
import datetime as dt

# Load the netCDF file
nc_file = nc.Dataset('/data/hpcdata/users/jambyr/icenet4/scratch/pipeline.monthly/results/forecasts/prediction.aug24.north/2024-07-31/2024-07-31.nc', 'r')

# Get the forecast_date variable
forecast_date = nc_file.variables['forecast_date'][:]

# Print the forecast_date variable
print(forecast_date)

Q: What are the benefits of fixing the issue with the `forecast_date` variable?

A: Fixing the issue with the forecast_date variable will result in a correct output for the netCDF file, which is essential for accurate forecasting and analysis. Additionally, fixing the issue will also improve the overall quality and reliability of the icenet package.

Q: How can I report any further issues with the `forecast_date` variable?

A: If you encounter any further issues with the forecast_date variable, please report them to the icenet development team using the issue tracker on GitHub. We will do our best to address the issue and provide a fix as soon as possible.