Climatic Change

, Volume 31, Issue 2–4, pp 559–600 | Cite as

Marine surface temperature: Observed variations and data requirements

  • D. E. Parker
  • C. K. Folland
  • M. Jackson


Measurements of temperature at the ocean surface are an indispensible part of the Global Climate Observing System (GCOS). We describe the varying coverage of these measurements from the mid-nineteenth century through to the present era of satellite data, along with ongoing attempts to augment the available digitized data base. We next survey attempts to remove systematic biases from both sea surface temperature (SST) and marine air temperature (MAT) data and to combinein situ and satellite SSTs in a consistent manner. We also describe new or planned geographically complete climatologies of SST and night MAT for 1961-90. These are expected to be more reliable than existing climatologies in the Southern Ocean and other sparsely-observed areas. The new SST climatology has been used in the construction of an improved geographically-complete data set of sea ice and SST: the techniques used are briefly reviewed, as are other methods of analysis and assessment of worldwide SST.

We present global and regional time series of anomalies (i.e. deviations from reference climatology) of SST and night MAT for 1856 to 1994 constructed using the most complete data and best-estimate bias-corrections hitherto available. These series are compared with earlier published series, and are validated by means of comparisons with anomalies of air temperature from coastal and island stations. The sensitivity of the time series to imperfect coverage is assessed by means of frozen grid experiments. The results underscore the need for ongoing development of SST and MAT data bases within GCOS for the detection of climatic change, and for improved methods of analysis to optimally isolate the signals from incomplete data.


Southern Ocean Ongoing Development Island Station Indispensible Part Marine Surface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • D. E. Parker
    • 1
  • C. K. Folland
    • 1
  • M. Jackson
    • 1
  1. 1.Meteorological OfficeHadley CentreBracknell, BerksU.K.

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