General
marine-carbonate-chemistry - Claude MCP Skill
Solves seawater carbonate chemistry with PyCO2SYS for chemical oceanography, ocean acidification, and marine carbon-cycle research. Use for paired total alkalinity, dissolved inorganic carbon, pH, or seawater pCO2/fCO2 measurements; carbonate speciation; aragonite and calcite saturation; Revelle factors; lab-to-in-situ temperature and pressure corrections; and measurement uncertainty propagation. Applies to carbonate-system calculations, not general aqueous speciation or air-sea gas-flux estimation.
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Documentation
SKILL.md# Marine Carbonate Chemistry Turn two independent seawater carbonate measurements into a reproducible speciation table, mineral saturation estimates, and a record of the calculation assumptions. Targets **PyCO2SYS 1.8.3.4**, tested with Python 3.13 and NumPy 2.5.3. As reviewed on 2026-10-01, this remains the stable PyPI release. The [v2 documentation](https://mvdh.xyz/PyCO2SYS/) is for a beta with breaking changes; use the v1 documentation for this pin. ## When to use - Analyze bottle samples, shipboard carbonate measurements, or acidification experiments. - Calculate total-scale pH, seawater pCO2/fCO2, carbonate ion, aragonite/calcite saturation state, or the Revelle factor from a valid measured pair. - Convert a system determined at laboratory conditions to specified ocean conditions. - Quantify how stated measurement uncertainties affect the calculated results. This workflow concerns seawater carbonate equilibria. Freshwater, porewaters with substantial uncharacterized alkalinity, brines outside the selected calibration range, and reaction/transport models require additional chemistry and validation. Do not infer an air-sea flux or atmospheric carbon removal from a carbonate equilibrium alone. ## Establish the measurement contract Before running a solver, identify the two measured variables, their units, quality flags, and their temperature/pressure basis. Retain a separate source table containing station, depth, timestamps, methods, reference materials, and original QC codes, joined by sample ID. Do not turn missing values or rejected measurements into zero. | Quantity | Required convention | |---|---| | Total alkalinity (TA), DIC, nutrients | micromol per **kg seawater**, not per litre or kg water | | Salinity | Practical Salinity, not Absolute Salinity in g/kg | | Temperature | In-situ/measurement temperature in degrees Celsius, not potential or Conservative Temperature | | Pressure | Sea pressure in dbar; surface sample is 0, not 1 atmosphere | | pH | Declared total, seawater, free, or NBS scale, at the declared measurement conditions | | pCO2 / fCO2 | Seawater partial pressure / fugacity in microatm; these are distinct quantities | TA and DIC remain constant during the solver's temperature/pressure conversion for a closed sample. pH and gas parameters change. Two inputs measured at different conditions cannot simply share one `temperature` value. Establish a consistent measurement basis first. Temperature correction does not repair sample changes caused by gas exchange, biology, evaporation, or mineral dissolution/precipitation. Use two independent carbonate parameters. pCO2 plus fCO2 is not an independent pair. Three or more measurements enable an overdetermination check: solve independent pairs and compare predicted versus measured third parameters, including their uncertainty. Do not average inconsistent solutions to hide a calibration or scale mismatch. ## Install Create a dedicated environment in the user's working directory: ```bash uv venv --python 3.13 .venv uv pip install --python .venv/bin/python "PyCO2SYS==1.8.3.4" "numpy==2.5.3" ``` On Windows the environment's interpreter is `.venv/Scripts/python.exe`. The commands below use the POSIX interpreter path. Set the shell variable `SKILL_DIR` to this installed skill's directory. Keep inputs and generated outputs in the working directory. ## Workflow 1. **Prepare paired measurements.** Use the schema in [references/input-and-results.md](references/input-and-results.md). Resolve units and quality flags before creating the input file. Supply phosphate and silicate explicitly; zero is an assumption to justify, not a missing-data code. 2. **Choose equilibrium constants.** Read [references/chemistry-decisions.md](references/chemistry-decisions.md) for pH scales, carbonic-acid constants, borate, saturation interpretation, and uncertainty limits. Match the study's validated convention and report it. The helper supports carbonic-acid options 10 and 15; other systems require a separately verified direct PyCO2SYS call. 3. **Solve with `scripts/solve_carbonate.py`.** It validates the full input table, solves the pair, checks finite outputs and DIC species balance, then writes `carbonate.csv` and `provenance.json` into a new output directory. 4. **Review flags and consistency.** Inspect calibration-range and gas-pressure flags, carbonate balance, measured-third-parameter residuals when available, and controls. A successful solve does not validate the sample, constants, or measurement method. 5. **Report at the intended conditions.** Results ending `_out` describe the supplied output temperature/pressure. Unsuffixed results describe input conditions. Gas results retain the helper's uncorrected hydrostatic gas convention (see below). Include parameter pair, pH scale, units, constants, nutrient assumptions, uncertainty scope, software versions, and excluded/flagged samples with the result table. ## Worked example: closed-sample condition correction The following values are synthetic, not field observations. Save this as `samples.csv` in a working directory. The two samples differ only in DIC; the second represents a fixed-alkalinity CO2-addition comparison. Their measurements are at 25 C and 0 dbar; results are also requested at 10 C and 1000 dbar. ```csv sample_id,par1,par2,salinity,temperature,pressure,total_phosphate,total_silicate,temperature_out,pressure_out,u_par1,u_par2 baseline,2300,2000,35,25,0,0,0,10,1000,2,2 added_co2,2300,2100,35,25,0,0,0,10,1000,2,2 ``` Run from that working directory: ```bash .venv/bin/python "$SKILL_DIR/scripts/solve_carbonate.py" samples.csv \ --par1-type alkalinity --par2-type dic --k-carbonic 10 \ --output-dir carbonate-results ``` For the baseline, the tested version gives input-condition total pH **8.045886**, pCO2 **396.958 microatm**, and aragonite saturation **3.386201**. At the specified output conditions, total pH is **8.241241** and aragonite saturation **2.605691**. These rounded values are regression checks for this exact setup, not universal seawater benchmarks. With independent 2 micromol/kg uncertainties in TA and DIC only, `u_pH_total` is about **0.004580**. This excludes equilibrium-constant and other input uncertainty. Both rows carry `gas_pressure_correction_disabled_output`: the output pH and mineral saturation include pressure effects, but the reported pCO2/fCO2 do not include the hydrostatic corrections to CO2 solubility and fugacity. Do not compare those gas values directly with a pressure-corrected subsurface sensor measurement. For TA + measured pH, use `--par2-type ph --ph-scale total` only if the source explicitly identifies total-scale pH; replace `par2` and `u_par2` with the measured pH and its absolute standard uncertainty. A column named merely `pH` is insufficient to establish its scale. ## Uncertainty and interpretation Optional `u_` input columns contain absolute **one-standard-deviation** uncertainties. They propagate to total pH, pCO2, and aragonite saturation at each requested condition. The helper assumes independent errors and treats unlisted inputs/constants as exact. For covariance, constants uncertainty, or strongly nonlinear uncertainty, follow the decision guide and validate a tailored propagation instead of calling these outputs a complete uncertainty budget. Omega < 1 indicates thermodynamic undersaturation with respect to the named mineral. It does not establish a dissolution rate or an organism's response. A lower pH across unmatched samples is not by itself evidence of an anthropogenic acidification trend. ## Sources and validation boundary - [PyCO2SYS v1 arguments, units, settings, and result keys](https://pyco2sys.readthedocs.io/en/latest/co2sys_nd/) - [Uncertainty propagation](https://pyco2sys.readthedocs.io/en/latest/uncertainty/) - [Upstream validation](https://pyco2sys.readthedocs.io/en/latest/validate/) - [Stable release](https://github.com/mvdh7/PyCO2SYS/releases/tag/v1.8.3.4) - [Humphreys et al. (2022), PyCO2SYS v1.8](https://doi.org/10.5194/gmd-15-15-2022) Repository tests exercise the pinned solver, independent-pair round trips, carbon balance, pH-scale equivalence, condition correction, Revelle-factor derivatives, gas-pressure conventions, uncertainty quadrature, CSV errors, and the worked example. The helper calls the local `pyco2.sys` Python API; it has no HTTP endpoints or authentication. Tests establish software behavior, not independent field-data validation; upstream's validation page also contains historical examples, including a removed `pyco2.test` interface.
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Information
- Repository
- K-Dense-AI/claude-scientific-skills
- Author
- K-Dense-AI
- Last Sync
- 11/1/2026
- Repo Updated
- 11/1/2026
- Created
- 10/1/2026
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