HadSST4 provides monthly SST anomalies on a 5°x5° grid for 1850-present. The anomalies are derived from a 30-year climatology spanning 1961-90. Coverage is global but there is no interpolation; Thus, missing data occur in the final product. This means that uncertainties due to limited spatial coverage and systematic errors are relatively easy to identify compared with interpolated SST products; it also minimizes the loss of variance in SST anomalies that occurs in interpolated products. The primary input data to HadSST4 are from ICOADS release 3.0. Bias adjustments to the ICOADS SSTs account for changes in measurement methods (e.g. engine room intake, bucket measurements, or buoy data). These adjustments are carried forward to the present. Uncertainties in these adjustments have complex spatial and temporal dependencies. The uncertainties are represented in an ensemble of 200 realizations of the data set. This allows the spatial and temporal characteristics of the uncertainties and their effects on climate signals to be explored. In addition to the ensemble, a median estimate is provided. Additional uncertainty arises from local measurement errors and local sampling errors; these errors are represented as gridded fields. Correlated measurement errors are represented in error-covariance matrices. Unadjusted raw data are provided but their use for climate studies is discouraged.
Derivative products: HadSST4 is used in the HadCRUT5 global combined land-ocean surface temperature data set. It has also been used in the Cowtan & Way global combined land-ocean surface temperature data set and will likely also be used in a forthcoming version of the Berkeley Earth global land-ocean data set.
The following was contributed by Dr. John Kennedy, in September, 2019:
Summary
HadSST.4.0.0.0 (the Hadley Centre Sea-Surface Temperature data set version 4, Kennedy et al. 2019) is a gridded data set of sea-surface temperature anomalies (that is, temperature difference from the 1961-1990 average) from January 1850 to December 2018. The monthly grids have a resolution of 5° latitude by 5° longitude. HadSST.4.0.0.0 is based on quality-controlled in situ measurements of sea-surface temperature from the International Comprehensive Ocean Atmosphere Data Set (ICOADS) release 3.0. It is updated using ship and moored buoy data from ICOADS release 3.0.1 and drifting buoy data provided by the Copernicus Marine Environment Monitoring Service. In situ measurements are those made at the surface by ships, drifting buoys and moored buoys. Ship measurements are made using a variety of methods and adjustments have been applied to the data to minimise the impact of artificial variability caused by changes in instrumentation. Uncertainties associated with bias adjustments, measurement errors and sampling error have been estimated and are provided with the data. Grid-box SST anomalies are only estimated in those grid boxes that contain observations. Consequently, the data set is not globally complete.
What are the key strengths of this data set?
What are the key limitations of this data set?
What are the typical research applications of this data set?
What are the most common mistakes that users encounter when processing or interpreting these data?
What are some comparable data sets, if any?
How is uncertainty characterized in these data?
Were corrections made to account for changes in observing systems or practices, sampling density, satellite drift, or similar issues?
How useful are these data for characterizing means as well as extremes?
How do I best compare these data with model output?
It depends on what you are doing. There are two main things to bear in mind.
First, there are gaps in the data and the gaps are not randomly-distributed in time. Early in the record and during the two World Wars, the coverage is very sparse. Some analyses have accounted for this by masking the model output to have a similar coverage to that of the observations.
Second, there are uncertainties in the data. The data set has been presented as an ensemble of 200 data sets that characterise the uncertainties in the bias adjustments and, used together with separate fields of uncertainties associated with other measurement and sampling errors, these provide information about the estimated total uncertainty in the gridded fields.
The idea behind providing an ensemble was that it would be relatively easy to assess the sensitivity of an analysis to observational uncertainty by re-running the analysis on some, or all, of the observational ensemble. We very much welcome feedback from users on this general approach of using ensembles of observational data sets.
Are there spurious (non-climatic) features in the temporal record?
Probably. Although every effort has been made to minimise the effects of known changes in measurement methods, information concerning how measurements were made is limited. An attempt to quantify the uncertainty has made, but the period between 1935 and 1970 is particularly problematic as there were large, but poorly-documented changes in the way that measurements were made as well as discontinuities in the data sources used to form the ICOADS data base. It is recommended that users test their analyses using a range of long-term SST data sets in order to get a broader understanding of the uncertainties.
How do I access these data?
Data are available from https://www.metoffice.gov.uk/hadobs/hadsst4/data/download.html
How frequently are the data updated?
The data set is not currently being updated (it runs from January 1850 to December 2018), but monthly updates will commence in early 2020 typically with a two week lag.##
Kennedy, J. J., Rayner, N. A., Atkinson, C. P., & Killick, R. E. ( 2019). An ensemble data set of sea‐surface temperature change from 1850: the Met Office Hadley Centre HadSST.4.0.0.0 data set. Journal of Geophysical Research: Atmospheres, 124. https://doi.org/10.1029/2018JD029867
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Kennedy, John & National Center for Atmospheric Research Staff (Eds). Last modified 14 Jan 2021. "The Climate Data Guide: SST data: HadSST4." Retrieved from https://climatedataguide.ucar.edu/climate-data/sst-data-hadsst4.
Funding: NSF | National Science Foundation
Based at: NCAR | National Center for Atmospheric Research
A Project of: Climate Analysis Section in Climate and Global Dynamics Laboratory
Created by: Climate Data Guide PIs and Staff