adding files related to NOA GFS poc

[balit-raibot]

Adding GFS Data of NOA for Data Commons POC

[gemini-code-assist]

Summary of Changes

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This pull request establishes the foundational data and configuration for a Proof of Concept (PoC) to integrate NOAA Global Forecast System (GFS) data into the system. It includes the raw GFS data, the necessary metadata and mapping files to process this data, and the resulting transformed output, along with the corresponding statistical variable definitions and schema.

Highlights

• Raw GFS Data Addition: Added a CSV file containing raw NOAA Global Forecast System (GFS) meteorological data for December 24, 2025, covering various atmospheric and surface parameters.
• Data Processing Configuration: Introduced metadata and parameter-value mapping files (noa_gfs_metadata.csv and noa_gfs_pvmap.csv) essential for processing and transforming the raw GFS data.
• Transformed Output Data: Generated a CSV file (noa_gfs_output.csv) with the GFS data transformed and mapped to Data Commons statistical variables and properties.
• Statistical Variable Definitions: Included MCF files (noa_gfs_output_stat_vars.mcf and noa_gfs_output_stat_vars_schema.mcf) that define the new statistical variables and their corresponding schema for the GFS dataset within the Data Commons framework.

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[gemini-code-assist]

Code Review

This pull request adds new files for importing NOAA GFS data as a proof-of-concept for Data Commons. While this is a valuable addition, I've identified several critical and high-severity issues in the generated files and configurations that should be addressed to ensure the data is imported correctly and the process is robust. Key issues include hardcoded values leading to data precision loss, incomplete and fragile TMCF definitions, malformed data in the output CSV, and stylistic issues in the MCF files.

[gemini-code-assist]

The TMCF file is incomplete and not robust for a general import process.

1. Missing Mappings: It's missing mappings for the level, latitude, and longitude columns from the CSV. These are important properties for the observations and should be included.
2. Hardcoded Times: referenceTime and validTime are hardcoded. While they are constant for this specific input file, this approach is fragile. If data from other times is processed, this will lead to incorrect data. These should be mapped from their respective columns in the CSV.

A corrected version would look like this:

Node: E:noa_gfs_output->E0
typeOf: dcs:StatVarObservation
observationDate: C:noa_gfs_output->observationDate
value: C:noa_gfs_output->value
observationAbout: C:noa_gfs_output->observationAbout
variableMeasured: C:noa_gfs_output->variableMeasured
unit: C:noa_gfs_output->unit
level: C:noa_gfs_output->level
latitude: C:noa_gfs_output->latitude
longitude: C:noa_gfs_output->longitude
referenceTime: C:noa_gfs_output->referenceTime
validTime: C:noa_gfs_output->validTime

Node: E:noa_gfs_output->E0
typeOf: dcs:StatVarObservation
observationDate: C:noa_gfs_output->observationDate
value: C:noa_gfs_output->value
observationAbout: C:noa_gfs_output->observationAbout
variableMeasured: C:noa_gfs_output->variableMeasured
unit: C:noa_gfs_output->unit
level: C:noa_gfs_output->level
latitude: C:noa_gfs_output->latitude
longitude: C:noa_gfs_output->longitude
referenceTime: C:noa_gfs_output->referenceTime
validTime: C:noa_gfs_output->validTime

[gemini-code-assist]

The observationDate is hardcoded to 2025, which leads to a loss of precision since the input data contains full timestamps. This should be derived from the Reference_Time column.

To fix this, you should:

1. Change this line to remove the observationDate mapping.
2. Add a new line to map Reference_Time to observationDate, for example:
   Reference_Time,observationDate,{Data},#Eval,"observationDate=format_date(Data, '%Y-%m-%d')"

S.No,observationAbout,country/USA