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Climate Data Records

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC)

NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

CDRs provide trustworthy information on how, where and to what extent the land, oceans, atmosphere, and ice sheets are changing. This information is used to manage natural resources and agriculture, measure environmental impacts on human health and community preparedness, and inform policy development and decision making for other sectors and interest groups.

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Operational Climate Data Records

NOAA operational CDRs are systematically generated, and routinely assessed for quality. The first step in establishing an operational CDR includes public posting of the source code that generated the CDR dataset, the dataset itself, and supporting documentation through a six-phase Research-to-Operations process that is described in the Developers Guidelines.

Fundamental

Fundamental CDRs are composed of sensor data (e.g. calibrated radiances, brightness temperatures) that have been improved and quality controlled over time, together with ancillary calibration data.

Thematic

Thematic CDRs address a geophysical variable that is often derived from a fundamental CDR(s), that are specific to various disciplines: Terrestrial, Oceanic, Atmospheric. Thematic CDRs are often generated by blending satellite observations, in-situ data, and/or model output.