Run3 glm metric validator

Data Preparation:

• Load field observations from field_temp_oxy.csv.
• Ensure observation datetime values are truncated or aligned to match the simulation's temporal resolution (e.g., setting minutes/seconds to zero if the simulation outputs daily/hourly values).

Merge Logic:

• Apply round().astype(int) to the depth values of both the simulation and observation datasets to ensure integer-based depth matching.
• Perform an inner join on the datetime and rounded_depth columns. No interpolation or nearest-neighbor matching is permitted for the final evaluation.

Metric Calculation:

• Overall RMSE: Calculate the Root Mean Square Error for all matched pairs.
• Annual Deep RMSE: Calculate RMSE for all matched pairs where rounded_depth $\ge 13$.
• Summer Deep RMSE: Calculate RMSE for matched pairs where rounded_depth $\ge 13$ and the month is June, July, August, or September (6-9).

Reporting:

• Save the results to /root/metrics.json using the keys: overall_rmse, annual_deep_rmse, summer_deep_rmse, overall_n_pairs, annual_deep_n_pairs, and summer_deep_n_pairs.