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

Calvert, Bruce

ExperimentDOI
amplificationbias-correctionclimate changeEl Niñoobservational datasea iceTemperature
Summary
HadCRU_MLE_v1.2 is a dataset of monthly gridded surface temperatures for the Earth during the instrumental period (since 1850). The name ‘HadCRU_MLE_v1.2’ 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_v1.2 include land surface air temperature anomalies of non-infilled HadCRUT5, 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_v1.2 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-SST2) and the National Snow and Ice Data Center (modified G10010v2 appended with G02202v4) 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 increased the estimate of global mean surface temperature change during the instrumental period. HadCRU_MLE_v1.2 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.
To support publication of the referenced research article in the Quarterly Journal of the Royal Meteorological Society, HadCRU_MLE_v1.2 was created to respond to suggestions by peer reviewers, including extended coverage until the end of 2023 and additional sensitivity tests.

HadCRU_MLE_v1.2 includes mean surface temperature anomalies for each month from 1850 to 2023 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_v1.2 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_v1.2 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.

Future versions of HadCRU_MLE may become available to extend the temporal coverage beyond 2023.
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 2023-12-31 (gregorian)
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Size
18.14 GiB (19475439507 Byte)
Format
NetCDF, ascii
Status
completely archived
Creation Date
Future Review Date
2034-03-04
Previous Version(s)
doi:10.26050/WDCC/HadCRU_MLE_v1
hdl:21.14106/e73d7f7f5710c90a407f6723f523596697c56c3d
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Cite as
Calvert, Bruce (2024). Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.2). World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/HadCRU_MLE_v1.2

BibTeX RIS
Description
The quality of HadCRU_MLE_v1.2 has been approved by Bruce T. T. Calvert on February 19, 2024. HadCRU_MLE_v1.2 is a further derived product (classifying as a level 4 data processing level) derived from various source datasets, including land surface air temperature anomalies of HadCRUT5, sea surface temperature anomalies of HadSST4, sea ice coverage of HadISST2, land mask data of OSTIAv2, the surface temperature climatology of Jones et al. (1999), the sea surface temperature climatology of HadSST3, surface elevation data of GMTED2010, and climate model output of CCSM4 for a pre-industrial control simulation. Sensitivity tests of HadCRU_MLE_v1.2 use alternate sea ice source datasets (COBE-SST2, G10010v2, and G02202v4). These source datasets either have had extensive quality control or are themselves further derived products based on source datasets that have had extensive quality control.
Description
Due to the maximum likelihood estimation approach used, the estimated field of surface temperature anomalies is temporally and spatially complete for the entire instrumental period and for the entire surface of the Earth. Other information of HadCRU_MLE_v1.2 is also spatially and temporally complete. As a result, there are no missing values in the dataset.
Description
Summary:
Findable: 6 of 7 level;
Accessible: 2 of 3 level;
Interoperable: 3 of 4 level;
Reusable: 5 of 10 level
Method
F-UJI online v3.1.0 automated
Method Description
Checks performed by WDCC. Metrics documentation: https://doi.org/10.5281/zenodo.6461229 Metric Version: metrics_v0.5
Result Date
2024-05-03
Result Date
2024-05-02
Description
1. Number of data sets is correct and > 0: passed;
2. Size of every data set is > 0: passed;
3. The data sets and corresponding metadata are accessible: passed;
4. The data sizes are controlled and correct: passed;
5. The spatial-temporal coverage description (metadata) is consistent to the data, time steps are correct and the time coordinate is continuous: passed;
6. The format is correct: passed;
7. Variable description and data are consistent: samples passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
Method Url
https://www.wdc-climate.de/docs/WDCC_User_Guide_Data_v1.pdf
Result Date
2024-05-02
Contact typePersonORCIDOrganization
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
-

Is cited by

[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

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 Hirahara, Shoji; Ishii, Masayoshi; Fukuda, Yoshikazu. (2014). Centennial-Scale Sea Surface Temperature Analysis and Its Uncertainty. doi:10.1175/jcli-d-12-00837.1
[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: 1. Measurement and sampling uncertainties. doi:10.1029/2010jd015218
[7] 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
[8] 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
[9] 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
[10] 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
[11] 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
[12] DOI Meier, W. N.; Fetterer, F.; Windnagel, A. K.; Stewart, S. (2021). NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice Concentration, Version 4. doi:10.7265/efmz-2t65
[13] 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

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

[Entry acronym: HadCRU_MLE_v1.2] [Entry id: 5275093]