The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022).

The file “GCOS_EHI_1960-2020_Cryosphere_Heat_Content_data.nc” presents an updated estimate of the global cryosphere heat uptake from 1960-2020. The cryosphere heat uptake sums the energy change associated with changes in Arctic and Antarctic sea ice, glaciers and the Greenland and Antarctic Ice Sheets. This represents an update to the record described in von Schuckmann et al. (2020) with the inclusion of observationally-based estimates for recent Arctic sea-ice change, and the data are used in von Schuckmann et al. (2022).

The file “GCOS_EHI_1960-2020_Inland_Water_Heat_Content_data.nc” presents an updated estimate of the global heat storage within natural lakes and artificial reservoirs for the period 1960-2020. Several improvements have been implemented in comparison with Vanderkelen et al. (2020): new approach to estimate lake volume, new lake models considered, and an extension of the analysis period. The data are used in von Schuckmann et al. (2022).

The file “GCOS_EHI_1960-2020_Atmosphere_Heat_Content_data.nc” presents an updated estimate of the atmospheric heat content (AHC) from 1960-2020 calculated using observational data and reanalyses. The estimate is given for the AHC relative to 1960. This represents an update to the record described in von Schuckmann et al. (2020) with the ENSO signal removed. The data are used in von Schuckmann et al. (2022).

The file “GCOS_EHI_1960-2020_Permafrost_Heat_Content_data.nc” presents the first estimate of permafrost heat storage within the Arctic region for the period 1960-2020. A perturbed parameter ensemble of simulations using the CryoGridLite permafrost model and climate forcings from the ERA-Interim reanalysis (1979-2020) and the Mk3L climate system model (500 CE -1979) allow to estimate the latent heat flux due to phase change in the subsurface from the surface to 550 m of depth. This ensemble of simulations allows to retrieve the uncertainty due to the unknown distribution of ground ice in the Arctic. More info: ESSOAr preprint server, https://doi.org/10.1002/essoar.10511600.1. The data are described in Nitzbon et al. (2022), and used in von Schuckmann et al. (2022).

The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022). This version includes an update of continental heat content uncertainty, where the standard deviation has been corrected from the precedent version to consider properly the value from permafrost heat storage uncertainty.