We present a new version of the Met Office Hadley Centre/Climatic Research Unit global surface temperature data set, HadCRUT5. HadCRUT5 presents monthly average near‐surface temperature anomalies, relative to the 1961–1990 period, on a regular 5° latitude by 5° longitude grid from 1850 to 2018. HadCRUT5 is a combination of sea‐surface temperature (SST) measurements over the ocean from ships and buoys and near‐surface air temperature measurements from weather stations over the land surface. These data have been sourced from updated compilations and the adjustments applied to mitigate the impact of changes in SST measurement methods have been revised. Two variants of HadCRUT5 have been produced for use in different applications. The first represents temperature anomaly data on a grid for locations where measurement data are available. The second, more spatially complete, variant uses a Gaussian process based statistical method to make better use of the available observations, extending temperature anomaly estimates into regions for which the underlying measurements are informative. Each is provided as a 200‐member ensemble accompanied by additional uncertainty information. The combination of revised input data sets and statistical analysis results in greater warming of the global average over the course of the whole record. In recent years, increased warming results from an improved representation of Arctic warming and a better understanding of evolving biases in SST measurements from ships. These updates result in greater consistency with other independent global surface temperature data sets, despite their different approaches to data set construction, and further increase confidence in our understanding of changes seen.

HadUK‐Grid is a new dataset of gridded climate observations for the UK produced by the Met Office Hadley Centre for Climate Science and Services. The dataset interpolates in situ observations to a regular grid using methods developed in a previous equivalent dataset that had been made available to users since 2002 through the UK Climate Projections project (UKCIP02, UKCP09). The new dataset differs from the existing one in a number of key respects: higher spatial resolution, longer time series for some variables, improved consistency with regard to the pre‐processing of station observations, the use of publicly‐accessible ancillary data sources, a revised calculation sequence for some variables and improved version control. This makes for a dataset that is more internally consistent, more traceable and more reproducible. The result is a dataset of key UK climate variables of up to 1 km resolution from 1862 for monthly rainfall, 1884 for monthly temperature, 1891 for daily rainfall, 1929 for monthly sunshine and a wider set of variables with start dates from the 1960s to support the need for national climate monitoring and climate research.

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Climatic Research Unit temperature (CRUTEM) is a gridded data set of monthly near-surface air temperature anomalies over the land surfaces of the world, running from 1850 to the present. We have undertaken the fifth major update (CRUTEM5.0) of this data set since it was first published in the 1980s, and here we describe the changes since the previous version (CRUTEM4.0) was published in 2012 (Jones et al., 2012). This is a collaborative project between the Climatic Research Unit (CRU), the Met Office Hadley Centre and the National Centre for Atmospheric Science (NCAS). The temperature anomalies from CRUTEM form the land component of the global land and marine surface temperature data set HadCRUT, with the Met Office Hadley Centre sea surface temperature (SST) data set HadSST providing the marine component. Currently, HadCRUT4 (Morice et al., 2012) comprises land air temperatures from CRUTEM4 and SST from HadSST3 (Kennedy et al, 2011a, 2011b); HadCRUT5 will combine the new land air temperature data set reported here with the recently-published HadSST4 (Kennedy et al., 2019). There have been several important developments since 2012 for understanding and improving global (land-only and land-and-marine) temperature datasets. First, there have been further data rescue, data compilation, and data homogeneity exercises at national, regional and global scales. Examples of the national and regional exercises are given later in this study where we describe the acquisition of new or improved data into the CRUTEM5.0 compilation. The International Surface Temperature Initiative (Rennie et al., 2014) and version 4 of the Global Historical Climatology Network (Menne et al., 2018) provide updated global compilations of daily or monthly temperatures. Second, there is now better understanding of the sources of bias in global land temperature datasets, such as urbanization (