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Update README.md
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azadeh-gh authored Feb 21, 2024
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Expand Up @@ -7,11 +7,11 @@ This tool automates the estimation of observation error parameters. It consists

1. Compute mean cloud amount and first guess standard deviation.
2. Generate four plots:
- Mean cloud amount vs. first guess departure standard deviation
- Standard deviation of FG departures in each channel as a function of mean cloud amount: (clw_guess + clw_obs)/2
- Number of observations in each defined bin of mean cloud amount
- Un-normalized and normalized first guess departure
- Histogram of un-normalised and also normalised FG departures in each channel
- Histogram of Errors
3. Compute error parameters (`error_cld`, `error_clr`, `clw_clr`, and `clw_cld`) and create CSV files for each channel.
3. Estimate error parameters (`error_cld`, `error_clr`, `clw_clr`, and `clw_cld`) and create CSV files for each channel.

## Usage
Before running the script, the user needs to specify certain parameters in `run_error_model_estimate.sh`:
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