The primary goal of DCENT_MLE is to combine instrumental observations with physically realistic statistical models to produce maximum likelihood estimates of surface temperature anomalies and other physical
DCENT_MLE_v1.0 is a dataset of monthly gridded surface temperatures for the Earth during the instrumental period (since 1850). The name ‘DCENT_MLE_v1.0’ reflects the dataset’s use of maximum likelihood
Text File describing Updated Code of Maximum Likelihood Estimates of Temperatures using Data from the Hadley Centre and the Climate Research Unit (Version 1.2)
This text file describes minor modifications to the code of HadCRU_MLE_v1.2 (https://doi.org/10.26050/WDCC/HadCRU_MLE_v1.2) that were made after archiving the code, including to produce higher resolution
This additional information contains code and a folder structure that can be used to reproduce or update the DCENT_MLE_v1.0 dataset. The zip file contains a README text file with instructions on how to
Amplification Function of Maximum Likelihood Estimates of Temperatures using Data from the Dynamically Consistent Ensemble of Temperature (Version 1.0)
This dataset consists of the estimated amplification function of DCENT_MLE_v1.0. The amplification function varies by 5° latitudinal band, surface type (open sea vs land/ice), and calendar month. The amplification
This dataset includes global mean surface temperature anomalies for each year from 1850 to 2023. The impacts of sea ice concentrations and an internal variability pattern on surface temperature anomalies
Estimates of Measurement and Sampling Uncertainties of the Land Surface Air Temperature Anomalies of the Dynamically Consistent Ensemble of Temperature (Version 1.0)
This dataset consists of estimates of standard errors of combined measurement and sampling uncertainties of land surface air temperature anomalies, corresponding to the DCLSAT anomalies used in the estimation
This dataset is a mean surface temperature climatology for each calendar month and for each 5° latitude by 5° longitude grid cell of the Earth. The temperature climatology corresponds to the 1982-2014
This dataset includes local mean surface temperature anomalies for each month from 1850 to 2023 and for each 5° latitude by 5° longitude grid cell of the Earth. The impact of sea ice concentrations on
Internal Variability Patterns of Maximum Likelihood Estimates of Temperatures using Data from the Dynamically Consistent Ensemble of Temperature (Version 1.0)
This dataset consists of the gridded internal variability pattern used to estimate DCENT_MLE_v1.0 for each 5° latitude by 5° longitude grid cell of the Earth. The internal variability pattern corresponds well to the El Niño Southern Oscillation.
This dataset consists of the gridded land area fraction used to estimate DCENT_MLE_v1.0 for each 5° latitude by 5° longitude grid cell of the Earth.
The land area fraction is a derivative product based
This dataset consists of model parameters used to estimate the DCENT_MLE_v1.0 dataset. Users are encouraged to read the supporting information of “Improving global temperature datasets to better account
This dataset includes global mean surface temperature anomalies for each month from 1850 to 2023. The impacts of sea ice concentrations and an internal variability pattern on surface temperature anomalies
Time Series Text Files of Maximum Likelihood Estimates of Temperatures using Data from the Dynamically Consistent Ensemble of Temperature (Version 1.0)
Time series of DCENT_MLE_v1.0 are also available as text files. These time series include estimates of global mean surface temperature anomalies, and estimates of the impacts of sea ice concentrations