What problem does it solve? Running the BIOME-BGC terrestrial biogeochemistry model correctly requires deep operational knowledge: strict unit conventions (precipitation in cm not mm, VPD in Pa not kPa), a fragile keyword-section .ini format, and mandatory multi-century spinup before carbon fluxes are meaningful. This Skill packages that expertise so an AI agent can prepare inputs, execute spinup and normal runs, parse outputs, and recover from the model's known silent failure modes. ## Core Features & Use Cases - End-to-end pipeline tools: Six Python tools generate site .ini files, map AVHRR land cover to plant functional types and .epc files, convert VIC/CMFD forcing to BIOME-BGC meteorological format, run spinup with convergence monitoring, execute normal simulations, and parse daily/annual outputs. - Diagnostic recovery: 25+ diagnostic triplets map symptoms (e.g., GPP 10x too high, zero GPP, spinup never converging) to diagnoses and validated remedies, covering the model's most dangerous silent unit errors. - Validation and coupling guidance: Dag-based output definitions with cited validation conventions (NSE, PBIAS pass-bands), FLUXNET comparison guidance, and rules for coupling with VIC hydrology and LDNDC cropland models without double-counting ET. - Use Case: Simulate forest carbon budgets for a basin by running spinup then a transient run per grid cell, producing FLUXNET-comparable GPP, NPP, NEE, ET, LAI, and soil carbon outputs. ## Quick Start Ask the agent to run the bundled Missoula ENF example by first executing preflight_check.py, then running the spinup and normal BIOME-BGC simulations and parsing the daily output into an annual carbon summary.
