netcdf-analysis

name	netcdf-analysis
description	Reading and analyzing GLM NetCDF output with Python netCDF4 and pandas for RMSE evaluation.

NetCDF Analysis for GLM Output

Reading GLM Output

import netCDF4 as nc
import numpy as np
import pandas as pd

ds = nc.Dataset('output/output.nc')
temp = ds.variables['temp'][:]  # masked array [time, layers]
z = ds.variables['z'][:]        # height above bottom [time, layers]
time_var = ds.variables['time']
times = nc.num2date(time_var[:], time_var.units)

Extracting Temperature at Specific Depths

GLM uses variable layer heights. For each timestep:

lake_depth = 25  # from morphometry (crest_elev - min(H))
for t in range(len(times)):
    valid = ~temp[t].mask if hasattr(temp[t], 'mask') else np.ones(temp.shape[1], bool)
    depths_from_surface = lake_depth - z[t, valid]
    temps = temp[t, valid]
    # Interpolate to desired depth

RMSE Calculation

# Merge on exact datetime and rounded depth
# rmse = sqrt(mean((obs - sim) ** 2))

Key Notes

• GLM z is height from lake bottom; depth = lake_depth - z
• Round depths to nearest integer for matching
• Use exact datetime matching (no nearest-time)