MET Stat Use Case: FBIAS Across Models
This use case demonstrates how to run VCasT to compute FBIAS for precipitation forecasts using MET .stat files and a YAML configuration.
It uses a sample configuration file (cts.yaml) that filters and aggregates FBIAS across multiple models using APCP data.
Prerequisites
Before running the example, make sure VCasT is installed. Follow the installation steps in Quick Start Guide.
Run the Example
Clone the test repository:
git clone https://github.com/NOAA-GSL/VCasT-tests cd VCasT-tests/examples/MET/fbias_multiple_models
Run VCasT with the provided YAML file:
vcast cts.yamlThis will load and process the .stat files under the ./stats directory using the configuration options defined below.
YAML Configuration Explained
Below is the content of cts.yaml, which configures VCasT to:
Load categorical statistics (
line_type: cts)Focus on FBIAS for APCP forecasts
Filter by model, variable, threshold, lead time, and region.
Aggregate results by model and lead time
1input_stat_folder: ./stats
2line_type: cts
3date_column: "fcst_valid_beg"
4start_date: "2022-05-01_00:00:00"
5end_date: "2022-05-07_12:00:00"
6
7string_filters:
8 model: ["RRFS_GDAS_GF.SPP.SPPT_mem01", "RRFS_GDAS_GF.SPP.SPPT_mem02", "RRFS_GDAS_GF.SPP.SPPT_mem03", "RRFS_GDAS_GF.SPP.SPPT_mem04", "RRFS_GDAS_GF.SPP.SPPT_mem05",
9 "RRFS_GDAS_GF.SPP.SPPT_mem06", "RRFS_GDAS_GF.SPP.SPPT_mem07", "RRFS_GDAS_GF.SPP.SPPT_mem08", "RRFS_GDAS_GF.SPP.SPPT_mem09", "RRFS_GDAS_GF.SPP.SPPT_mem10"]
10 fcst_var: ["APCP_03"]
11 fcst_thresh: [">0.0"]
12 fcst_lead: ["00000", "030000", "060000", "090000", "120000", "150000", "180000", "210000", "240000", "270000", "300000", "330000", "360000"]
13 vx_mask: ["CONUS"]
14
15stat_vars: ["fbias"]
16
17reformat_file: false
18output_reformat_file: "./filtered_output.data"
19
20output_file: false
21output_plot_file: "./vars.data"
22
23aggregate: true
24group_by: ["model", "fcst_var", "fcst_lead"]
25output_agg_file: "./APCP_agg.data"
Output
Since both reformat_file and output_file are set to false, the only output in this example will be an aggregated result saved to APCP_agg.data.
You can modify the YAML to enable full data dumps as needed.