Data and code for: Hidden Markov model identifies four phytoplankton regimes associated with seasonal forcing and monsoon disturbance at a coastal station in Jinhae Bay, Korea

Complete data and code supporting the manuscript submitted to Limnology and Oceanography (LO-26-0267). Contents: raw and processed daily HPLC pigment and environmental data; the frozen-state R pipeline (Gaussian HMM fitted from a single prespecified 15-seed multi-start set; biomass emission variable = log10[TChl-a + fucoxanthin + peridinin]; CZM zero replacement via zCompositions; CLR-PCA); fitted model objects; the decoded regime sequence and posterior probabilities; state-number selection (AIC/BIC/ICL, k=1-6) under both a single-sequence and a gap-aware (seven-segment) specification, with k=4 vs k=5 cross-tabulation, fifth-state profile, and k=5 robustness of transitions/dwell; per-state (within-state) conditional-independence matrices; CLR transformation-sensitivity; parametric bootstrap; below-detection (censored) sensitivity; per-pigment non-detection counts; figure code; Supplementary Tables S1-S8. Reproducibility (this version): project-root-relative paths (00_paths.R, no absolute paths), a single master runner (run_all.R), an automated value-check (verify_values.R) with a clean-run log (CLEAN_RUN_LOG.txt), and a machine-restorable environment (renv.lock, R 4.5.2). One command from the repository root regenerates the principal tables and values and passes the automated checks (see README.md). Funding: National Research Foundation of Korea (NRF) grants RS-2026-25468730 and RS-2026-25550603.