Measurement · Physical Oceanography · %

Oxygen percent saturation

The registry carries no authored label for this measurement, so the name above is the canonical series' own description in metadata/measurement_type.csv (variable.csv holds the authored labels, five today).

NERC P01 OXYSZZ01P06 units UPCT %key oxygen_saturation series oxygen_saturation

690,745
values: 2,660
flagged: 26,995
sampling events: 1949–2021
years: 1
dataset: 0–5,351 m
depth: every month
seasons

Heads-up 2,660 of these 690,745 values (0.4 %) are flagged by their provider as questionable or bad. The Explorer, the climatology and its anomalies leave them out; do the same when you read the data yourself (cc_qual_ok_sql() in calcofi4r, qual_ok_sql() in calcofi4py).

Measured in

Hydrographic Bottle 690,745 values · 26,995 sampling events · 1949–2021 · 0–5,351 m · 210 grid cells · 558 cruises

series oxygen_saturation · source column o2sat · flag column o2satq 2,660 flagged · 0.4 %

One row per series, one cell per year, darker with more values — the same strip the front door draws per dataset and a species page draws per taxon. Each row is one dataset's own measurement_type; the label is written once, in the title above.

By depth

Values per depth band at the release grain, one thin bar per series. The bands are the record's own (0-10 … 2000+ m).

By month

Values per calendar month, one row per series: CalCOFI's quarterly cruises show as peaks in the months the ships sail.

Range & quality

bounds: The registry declares -1 … 250 % for oxygen_saturation; a value outside it is dropped at the ingest (drop_out_of_bounds()).
observed: Hydrographic Bottle oxygen_saturation -0.1 · median 54.5 · 214.1 % (5th–95th percentile 5.2–105.2)
flags: Hydrographic Bottle oxygen_saturation o2satq on 28,127 of 690,745 rows: 2 1,859 · 6 23,608 · 8 2,657 · 9 3; qual_ok keeps 688,085. The codes are this dataset's own vocabulary, uninterpreted.
baseline: A monthly climatology exists for this measurement (the release's climatology table: 1993–2013, dataset × grid cell × calendar month × 10 m bin), so the Explorer can draw anomalies against it rather than values.

Ways in

Explorermaps, sections and time series of this measurement — opens prefilled
https://calcofi.io/explore/?var=oxygen_saturation
Explorer · a depth section vs normalthe newest cruise's section against the climatology baseline
https://calcofi.io/explore/?lens=section&var=oxygen_saturation&anom=1
db-querySQL in your browser — the shell opens with this query
https://calcofi.io/db-query/?sql=SELECT+%2A+FROM+__TBL%3Aobs_env__+WHERE+measurement_type+%3D+%27oxygen_saturation%27+LIMIT+100%3B
ERDDAP · Hydrographic BottleCalCOFI's own server, the Hydrographic Bottle table constrained to this series
https://erddap.calcofi.io/erddap/tabledap/calcofi_bottle.html?&measurement_type=%22oxygen_saturation%22
Parquetobs_env is partitioned by measurement_type in the content-addressed store — resolved through the release catalog, never a path built by hand
```
SELECT * FROM read_json('…/v2026.09.10/catalog.json')
-- objects[] WHERE table = 'obs_env'
--   AND partition_value = 'oxygen_saturation'
```

library(calcofi4r)
con <- cc_get_db()                      # the promoted release
tbl(con, "obs_env") |> filter(measurement_type %in% c("oxygen_saturation"))

Python

import calcofi4py as cc
con = cc.cc_get_db()
con.sql("SELECT * FROM obs_env WHERE measurement_type IN ('oxygen_saturation')").df()

This page as data

JSONthis measurement's entry of the release record, verbatim
https://calcofi.io/measurements/oxygen_saturation.json

Read from measurements.json of release v2026.09.10, written at release by calcofi4db::build_measurements_catalog() beside taxa.json. The catalog's index is /measurements/; the JSON-LD on this page is a schema.org/DefinedTerm in the NERC P01 term set with a PropertyValue per series.

Cite

Cite the release; each dataset's own citation, licence and DOI are on its page — Hydrographic Bottle. The Explorer's Share → Cite writes it for the view you make.