Measurement · Meteorology & Sea State · °C

Air temperature

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).

key air_temp_c series air_temp_c

28,100
values: 28,100
sampling events: 2016–2022
years: 1
dataset: surface
depth: Jan · Feb · Mar · Apr · May · Jul · Aug · Oct · Nov
seasons

Heads-up The air_temp_c series from Underway Meteorological (METS) carries no flag at this grain, so its values cannot be screened this way.

Measured in

Underway Meteorological (METS) 28,100 values · 28,100 sampling events · 2016–2022 · surface · 97 grid cells · 20 cruises

series air_temp_c · source column air_temp_c no flag at this grain no P01 concept

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 -50 … 60 °C for air_temp_c; a value outside it is dropped at the ingest (drop_out_of_bounds()).
observed: Underway Meteorological (METS) air_temp_c 1.612 · median 15.79 · 25.22 °C (5th–95th percentile 12.65–19.2)
flags: Underway Meteorological (METS) air_temp_c carries no quality code at the release grain; qual_ok keeps all 28,100.
baseline: No climatology row is built for this measurement, so the Explorer draws values, not anomalies.

Ways in

Explorermaps, sections and time series of this measurement — opens prefilled
https://calcofi.io/explore/?var=air_temp_c
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+%27air_temp_c%27+LIMIT+100%3B
ERDDAP · Underway Meteorological (METS)CalCOFI's own server, the Underway Meteorological (METS) table constrained to this series
https://erddap.calcofi.io/erddap/tabledap/calcofi_mets.html?&measurement_type=%22air_temp_c%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 = 'air_temp_c'
```

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

Python

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

This page as data

JSONthis measurement's entry of the release record, verbatim
https://calcofi.io/measurements/air_temp_c.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 — Underway Meteorological (METS). The Explorer's Share → Cite writes it for the view you make.