Measurement · Physical Oceanography · °C · one key across 2 datasets

Temperature

Water temperature (QC'd)

NERC P01 TEMPPR01P06 units UPAA degCkey temperature series temperature · temperature_ave

1,575,364
values: 45,019
sampling events: 1949–2026
years: 2
datasets: 0–5,351 m
depth: every month
seasons

Measured in

Hydrographic Bottle 884,400 values · 35,389 sampling events · 1949–2021 · 0–5,351 m · 213 grid cells · 657 cruises

series temperature · source column t_deg_c · flag column t_qual 1.5 % flagged
CTD Cast Files 690,964 values · 9,630 sampling events · 1993–2026 · 1–3,630 m · 97 grid cells · 134 cruises

series temperature_ave · source column temp_ave sensor mean no flag at this grain
Average temperature

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 -2 … 40 °C for temperature · temperature_ave; a value outside it is dropped at the ingest (drop_out_of_bounds()).
observed: Hydrographic Bottle temperature 1.44 · median 10.07 · 31.14 °C (5th–95th percentile 4.7–18.2)
CTD Cast Files temperature_ave 1.508 · median 8.979 · 39.86 °C (5th–95th percentile 5.792–16.48)
flags: Hydrographic Bottle temperature t_qual on 13,047 of 884,400 rows: 0 170 · 1 118 · 2 135 · 3 104 · 4 53 · 5 129 · 6 11,756 · 7 7 · 8 575; qual_ok keeps 883,825. The codes are this dataset's own vocabulary, uninterpreted.
CTD Cast Files temperature_ave carries no quality code at the release grain; qual_ok keeps all 690,964.
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.

Related measurements

Bottle temperature btl_temperature · CTD Cast Files · 1993–2025 · 141,771 values · P01 TEMPPR01 the same quantity from the CTD files' own bottle samples — plausibly the same physical bottles, so merging them would count the bottle dataset twice

The same quantity from another platform or another kind of sample, each its own page and never merged into this one: a dataset's own bottle samples would count that dataset twice, an underway intake is not a cast, and a replicate is not a mean. The reason is the record's (related[].why).

Ways in

Explorermaps, sections and time series of this measurement — opens prefilled
https://calcofi.io/explore/?var=temperature
Explorer · a depth section vs normalthe newest cruise's section against the climatology baseline
https://calcofi.io/explore/?lens=section&var=temperature&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+IN+%28%27temperature%27%2C+%27temperature_ave%27%29+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=%22temperature%22
ERDDAP · CTD Cast FilesCalCOFI's own server, the CTD Cast Files table constrained to this series
https://erddap.calcofi.io/erddap/tabledap/calcofi_ctd-cast.html?&measurement_type=%22temperature_ave%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 = 'temperature'
--                    | 'temperature_ave'

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

Python

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

This page as data

JSONthis measurement's entry of the release record, verbatim
https://calcofi.io/measurements/temperature.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, CTD Cast Files. The Explorer's Share → Cite writes it for the view you make.