Add WRF diagnostics accessor plugin

[decadeneo]

Pull Request: Add WRF Diagnostics Accessor Plugin

Summary

This PR adds a comprehensive WRF diagnostics accessor plugin that bridges xwrf/xarray with wrf-python's raw computational APIs, providing seamless integration for calculating diagnostic variables from WRF model output.

Features

• Comprehensive diagnostics: Thermodynamic, dynamic, and surface variables
• xarray integration: Seamless use via accessor pattern (ds.wrf_diag.*)
• Automatic variable mapping: Handles WRF variable naming conventions
• Staggered grid support: Automatic destaggering for mass grid calculations
• Unit conversions: Built-in unit conversion support (K/°C, Pa/hPa)
• Dask support: Parallel processing for large datasets

Available Diagnostics

Thermodynamic Variables

• slp() - Sea level pressure
• rh() - Relative humidity
• tk() / tc() - Temperature (Kelvin/Celsius)
• eth() - Equivalent potential temperature
• td() - Dewpoint temperature
• pw() - Precipitable water

Dynamic Variables

• avo() - Absolute vorticity
• omega() - Omega (vertical pressure velocity)
• udhel() - Updraft helicity

Advanced Diagnostics

• dbz() - Radar reflectivity
• cape_2d() - CAPE, CIN, LCL, LFC
• cloudfrac() - Low/mid/high cloud fractions
• ctt() - Cloud top temperature

Surface Variables (2m and 10m)

• t2() / t2c() - 2m temperature (K/°C)
• rh2() - 2m relative humidity
• td2() - 2m dewpoint temperature
• q2() - 2m specific humidity
• psfc() - Surface pressure
• u10() / v10() - 10m U/V wind components
• wspd10() - 10m wind speed
• wdir10() - 10m wind direction

Usage Example

import xarray as xr
import xwrf  # Automatically registers wrf_diag accessor

# Load WRF output
ds = xr.open_dataset("wrfout_d01_2022-07-14_00:00:00")

# Calculate diagnostics
slp = ds.wrf_diag.slp()          # Sea level pressure
rh = ds.wrf_diag.rh()             # Relative humidity
t2 = ds.wrf_diag.t2()             # 2m temperature
rh2 = ds.wrf_diag.rh2()           # 2m relative humidity
wspd10 = ds.wrf_diag.wspd10()     # 10m wind speed
cape = ds.wrf_diag.cape_2d()      # CAPE and CIN (returns Dataset)

Changes

• Added xwrf/xwrf_diagnostics.py - New module with WRFDiagnosticsAccessor class
• Modified xwrf/__init__.py - Import xwrf_diagnostics to auto-register accessor

Dependencies

• Requires wrf-python >= 1.3 (soft dependency, graceful warning if not installed)
• Maintains compatibility with existing xwrf functionality

Testing

The plugin has been tested with WRF output files and handles:

• Variable name variations (WRF standard vs CF conventions)
• Staggered grid variables
• Missing optional variables
• Unit conversions
• Multi-file processing with dask

Notes

• The accessor is automatically available after importing xwrf
• All diagnostic methods return xarray DataArrays or Datasets with proper metadata
• Follows xwrf conventions for variable naming and attributes