dapper.met.adapters.era5

ERA5-Land adapter implementation.

Classes

ERA5Adapter()

ERA5-Land → ELM adapter.
class dapper.met.adapters.era5.ERA5Adapter[source]

Bases: BaseAdapter

ERA5-Land → ELM adapter.

This adapter implements the BaseAdapter interface for ERA5-Land hourly data. It handles source-specific details—file discovery, unit conversions, humidity diagnostics, renaming to ELM short names, and nonnegativity enforcement, so the upstream Exporter can remain source-agnostic.

Responsibilities

  • discover_files: Find CSV shards in a directory and infer the overall (start_year, end_year) using their date coverage.

  • normalize_locations: Validate and normalize the locations table (adds lon_0-360, ensures/creates zone, stable sorting).

  • id_column_for_csv: Declare the identifier column name in the input CSVs. For ERA5 we require gid.

  • preprocess_shard: Convert one merged shard (CSV rows joined to locations) into canonical ELM columns. Steps include:

    1. time filtering and optional “noleap” removal of Feb 29

    2. ERA5→ELM unit conversions (e.g., J/hr/m² → W/m², m/hr → mm/s)

    3. optional humidity computation (RH/Q) if temperature, dewpoint, and surface pressure are available

    4. renaming raw ERA5 fields to ELM short names via a mapping

    5. clipping canonical nonnegative variables

    6. returning only required columns in a deterministic order

  • required_vars: Report the canonical ELM variable names required for the requested output format.

  • pack_params: Provide robust (add_offset, scale_factor) for a canonical ELM variable, given optional data to tune ranges.

Notes

  • Humidity computation is performed only when temperature_2m, dewpoint_temperature_2m, and surface_pressure are present.

  • Precipitation conversion uses m/hr → mm/s via division by 3.6.

DRIVER_TAG = 'ERA5'
SOURCE_NAME = 'ERA5-Land hourly reanalysis'
discover_files(csv_directory, calendar)[source]

Discover ERA5 CSV shards in a directory and infer the inclusive year range.

id_column_for_csv(df_csv, id_col)[source]

Return the required identifier column name expected in ERA5 CSV shards (“gid”).

pack_params(elm_var, data=None)[source]

Return (add_offset, scale_factor) used to pack a variable for NetCDF output.

preprocess_shard(df_merged, start_year, end_year, calendar, dformat)[source]

  1. Filter time & handle no-leap

  2. Apply ERA5 → ELM unit conversions

  3. Compute humidities (if columns available)

  4. Rename columns to canonical ELM names using RAW_TO_ELM

  5. Clip canonical nonnegative variables

  6. Return only the canonical vars required by elm_required_vars(dformat), plus LONGXY/LATIXY/time/gid/zone (coords/meta).

required_vars(dformat)[source]

Return the canonical ELM variables required for the requested output format.