CLASSnmat: A global night marine air temperature data set, 1880–2019. (31st July 2020)

• Record Type: Journal Article
• Authors: Cornes, Richard C.; Kent, Elizabeth.C.; Berry, David.I.; Kennedy, John J.
• Is Part Of: Geoscience data journal. Volume 7:Number 2(2020)
• Page Start: 170
• Page End: 184
• Publication Date: 2020-07-31
• Subjects: climate change -- global surface temperature -- marine -- NMAT -- observations; Earth sciences -- Research -- Periodicals; Earth sciences -- Data processing -- Periodicals; Earth sciences -- Documentation -- Periodicals; 550.28557
• DOI: 10.1002/gdj3.100
• Languages: English
• ISSNs: 2049-6060

Abstract

Abstract: A new data set of Night Marine Air Temperature (NMAT) is presented that builds on the HadNMAT2 data set, which was released in 2013. In a similar manner to HadNMAT2, the new data set (CLASSnmat) provides uninterpolated, monthly global values at a 5° resolution back to 1880. In addition to being extended to the end of 2019, four main developments are made in CLASSnmat: (1) the NMAT values are extracted from the most recent version of the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS Release 3) and a revised method of eliminating duplicated observations is used; (2) values of NMAT are adjusted to 2m and 20m heights in addition to the 10 m height used in HadNMAT2; (3) a refinement is made to the corrections necessary during World War 2, which uses more of the NMAT observations and hence results in a more extensive spatial coverage for this period than was possible in HadNMAT2; (4) an updated gridding method is used that allows for an improved propagation of uncertainty from the individual NMAT values through to the gridded estimates. In this paper, the method used to construct CLASSnmat (version 1.0.0.0) is described. Abstract : A new data set of Night Marine Air Temperature (NMAT) is presented that builds on the HadNMAT2 data set. In a similar manner to HadNMAT2, the new data set (CLASSnmat) provides monthly global values at 5° resolution back to 1880. Several improvements to the data processing and gridding methods are used in CLASSnmat, and a method has been developed to retain more observations during the Second World War period.