Global analysis of night marine air temperature and its uncertainty since 1880: the HadNMAT2 Dataset
An updated version of the Met Office Hadley Centre's monthly night marine air temperature dataset is presented. It is available on a 5? latitude-longitude grid from 1880 as anomalies relative to 1961-1990 calendar-monthly climatological average night marine air temperature (NMAT). Adjustments a...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
2013-02-16.
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| Subjects: | |
| Online Access: | Get fulltext |
| Summary: | An updated version of the Met Office Hadley Centre's monthly night marine air temperature dataset is presented. It is available on a 5? latitude-longitude grid from 1880 as anomalies relative to 1961-1990 calendar-monthly climatological average night marine air temperature (NMAT). Adjustments are made for changes in observation height; these depend on estimates of the stability of the near surface atmospheric boundary layer. In previous versions of the dataset, ad hoc adjustments were also made for three periods and regions where poor observational practice was prevalent. These adjustments are re-examined. Estimates of uncertainty are calculated for every grid box and result from: measurement errors; uncertainty in adjustments applied to the observations; uncertainty in the measurement height and under-sampling. The new dataset is a clear improvement over previous versions in terms of coverage because of the recent digitization of historical observations from ships' logbooks. However, the periods prior to about 1890 and around World War 2 remain particularly uncertain and sampling is still sparse in some regions in other periods. A further improvement is the availability of uncertainty estimates for every grid box and every month. Previous versions required adjustments that were dependent on contemporary measurements of sea surface temperature (SST); to avoid these, the new dataset starts in 1880 rather than 1856. Overall agreement with variations of SST is better for the updated dataset than for previous versions, maintaining existing estimates of global warming and increasing confidence in the global record of temperature variability and change. |
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