Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.4)

Calvert, Bruce

Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.4)

Calvert, Bruce

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amplification bias-correction climate change El Niño observational data sea ice Temperature

Summary: HadCRU_MLE_v1.4 is a dataset of monthly gridded surface temperatures for the Earth during the instrumental period (since 1850). The name ‘HadCRU_MLE_v1.4’ reflects the dataset’s use of maximum likelihood estimation and observational data primarily from the Met Office Hadley Centre and the Climate Research Unit of the University of East Anglia. Source datasets used to create HadCRU_MLE_v1.4 include land surface air temperature anomalies of non-infilled HadCRUT5, exposure bias adjustments of Wallis et al. (2024), sea surface temperature anomalies of HadSST4, sea ice coverage of HadISST2, the surface temperature climatology of Jones et al. (1999), the sea surface temperature climatology of HadSST3, land mask data of OSTIAv2, surface elevation data of GMTED2010, and climate model output of CCSM4 for a pre-industrial control scenario. HadCRU_MLE_v1.4 was generated using information from the Met Office Hadley Centre, the Climate Research Unit of the University of East Anglia, the E.U. Copernicus Marine Service, the U.S. Geological Survey, and the University Corporation of Atmospheric Research. Results of sensitivity tests using alternate sea ice source datasets from the Japanese Meteorological Agency (COBE-SST3) and the National Snow and Ice Data Center (modified G10010v2 appended with G02202v6) are also available.

The primary motivation to develop HadCRU_MLE_v1.0 was to better account for spatially nonuniform warming across the planet. HadCRU_MLE_v1.0 better accounts for nonuniform warming by fitting an amplification function to observations to better account for spatially nonuniform warming trends, and by using differences in temperature climatologies and temperature anomalies between open sea and sea ice regions to better account for the impacts of changes in sea ice concentrations. These improvements, as described in “Improving global temperature datasets to better account for non-uniform warming” (https://doi.org/10.1002/qj.4791), increased the estimate of global mean surface temperature change during the instrumental period. HadCRU_MLE_v1.4 has additional improvements compared to HadCRUT5 Analysis, including correcting for a small underestimation of LSAT warming between 1961 and 1990, taking advantage of temporal correlations of observations, taking advantage of correlations between land and open sea observations, and better treatment of the El Niño Southern Oscillation.

HadCRU_MLE_v1.4 includes mean surface temperature anomalies for each month from 1850 to 2025 and for each 5° latitude by 5° longitude grid cell. The maximum likelihood estimation approach allows for the estimated field of surface temperature anomalies to be temporally and spatially complete for the entire instrumental period and for the entire surface of the Earth. A 5° by 5° gridded 1961-1990 temperature climatology for HadCRU_MLE_v1.4 is available, although caution is advised when interpreting this temperature climatology since the source datasets used for temperature climatologies do not correspond perfectly with the source datasets used for temperature anomalies. Other information of HadCRU_MLE_v1.4 is available, including model parameters, the estimated amplification function, the internal variability pattern, the land area fractions, and the impacts of sea ice concentrations and the El Niño Southern Oscillation on surface temperature anomalies.

HadCRU_MLE_v1.4 is an annual update to extend HadCRU_MLE until the end of 2025. The median estimate of the change in global mean surface temperature change from 1850-1900 to 2025 is 1.52 °C, with a 95% confidence interval of [1.42,1.62] °C. Future versions of HadCRU_MLE may become available to extend the temporal coverage beyond 2025.
Project: HadCRU_MLE (Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit)
Contact: Mr. Bruce T. T. Calvert (
brucetcalvert@nullgmail.com
0000-0002-1124-9632)
Spatial Coverage: Longitude -180 to 180 Latitude -90 to 90
Temporal Coverage: 1850-01-01 to 2025-12-31 (gregorian)
Use constraints: Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/)
Data Catalog: World Data Center for Climate
Format: NetCDF, ascii
Status: metadata only
Creation Date: 2026-03-05
Review Date: 2026-03-10
Previous Version(s): doi:10.26050/WDCC/HadCRU_MLE_v1
hdl:21.14106/e73d7f7f5710c90a407f6723f523596697c56c3d
doi:10.26050/WDCC/HadCRU_MLE_v1.2
doi:10.26050/WDCC/HadCRU_MLE_v1.3

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Cite as: Calvert, Bruce (2026). Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.4). World Data Center for Climate (WDCC) at DKRZ. https://www.wdc-climate.de/ui/entry?acronym=HadCRU_MLE_v1.4

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Contact type	Person	ORCID	Organization
Contact	Mr. Bruce T. T. Calvert	0000-0002-1124-9632	-
Author	Mr. Bruce T. T. Calvert	0000-0002-1124-9632	-
Investigator	Mr. Bruce T. T. Calvert	0000-0002-1124-9632	-

Cites

[1] DOI Calvert, Bruce T. T. (2024). Improving global temperature datasets to better account for non‐uniform warming. doi:10.1002/qj.4791

Is new version of

[1] DOI Calvert, Bruce T. T. (2021). Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.0). doi:10.26050/WDCC/HadCRU_MLE_v1

[2] Calvert, Bruce T. T. (2021). Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.1). hdl:21.14106/e73d7f7f5710c90a407f6723f523596697c56c3d

[3] DOI Calvert, Bruce. (2024). Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.2). doi:10.26050/WDCC/HadCRU_MLE_v1.2

[4] DOI Calvert, Bruce. (2025). Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.3). doi:10.26050/WDCC/HadCRU_MLE_v1.3

Is derived from

[1] DOI Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.; Holland, Marika M.; Hunke, Elizabeth C.; Jayne, Steve R.; Lawrence, David M.; Neale, Richard B.; Rasch, Philip J.; Vertenstein, Mariana; Worley, Patrick H.; Yang, Zong-Liang; Zhang, Minghua. (2011). The Community Climate System Model Version 4. doi:10.1175/2011JCLI4083.1

[2] DOI Danielson, Jeffrey J.; Gesch, Dean B. (2011). Global multi-resolution terrain elevation data 2010 (GMTED2010). doi:10.3133/ofr20111073

[3] DOI Good, Simon; Fiedler, Emma; Mao, Chongyuan; Martin, Matthew J.; Maycock, Adam; Reid, Rebecca; Roberts-Jones, Jonah; Searle, Toby; Waters, Jennifer; While, James; Worsfold, Mark. (2020). The Current Configuration of the OSTIA System for Operational Production of Foundation Sea Surface Temperature and Ice Concentration Analyses. doi:10.3390/rs12040720

[4] DOI Jones, P. D.; New, M.; Parker, D. E.; Martin, S.; Rigor, I. G. (1999). Surface air temperature and its changes over the past 150 years. doi:10.1029/1999rg900002

[5] DOI Kennedy, J. J.; Rayner, N. A.; Smith, R. O.; Parker, D. E.; Saunby, M. (2011). Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 1. Measurement and sampling uncertainties. doi:10.1029/2010jd015218

[6] DOI Kennedy, J. J.; Rayner, N. A.; Smith, R. O.; Parker, D. E.; Saunby, M. (2011). Reassessing biases and other uncertainties in sea surface temperature observations measured in situ since 1850: 2. Biases and homogenization. doi:10.1029/2010jd015220

[7] DOI 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. doi:10.1029/2018jd029867

[8] DOI Morice, C. P.; Kennedy, J. J.; Rayner, N. A.; Winn, J. P.; Hogan, E.; Killick, R. E.; Dunn, R. J. H.; Osborn, T. J.; Jones, P. D.; Simpson, I. R. (2021). An Updated Assessment of Near‐Surface Temperature Change From 1850: The HadCRUT5 Data Set. doi:10.1029/2019jd032361

[9] DOI Osborn, T. J.; Jones, P. D.; Lister, D. H.; Morice, C. P.; Simpson, I. R.; Winn, J. P.; Hogan, E.; Harris, I. C. (2021). Land Surface Air Temperature Variations Across the Globe Updated to 2019: The CRUTEM5 Data Set. doi:10.1029/2019jd032352

[10] DOI Titchner, Holly A.; Rayner, Nick A. (2014). The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations. doi:10.1002/2013jd020316

[11] DOI Walsh, J. E.; Chapman, W. L.; Fetterer, F.; Stewart, S. (2019). Gridded Monthly Sea Ice Extent and Concentration, 1850 Onward, Version 2. doi:10.7265/jj4s-tq79

[12] DOI Ishii, Masayoshi; Nishimura, Akio; Yasui, Soichiro; Hirahara, Shoji. (2024). Historical High-Resolution Daily SST Analysis (COBE-SST3) with Consistency to Monthly Land Surface Air Temperature. doi:10.2151/jmsj.2025-002

[13] DOI Wallis, Emily J.; Osborn, Timothy J.; Taylor, Michael; Jones, Philip D.; Joshi, Manoj; Hawkins, Ed. (2024). Quantifying exposure biases in early instrumental land surface air temperature observations. doi:10.1002/joc.8401

[14] DOI Meier, W. N.; F. Fetterer; A. K. Windnagel; J. S. Stewart; Stafford, T. (2026). NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 6. doi:10.7265/b18j-z797

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Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit

[Entry acronym: HadCRU_MLE_v1.4] [Entry id: 5369812]