‘Heat stored in the Earth system: Where does the energy go?’ contains a consistent long-term Earth system heat inventory over the period 1960-2018. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. This Earth Energy Imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory, and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2018. Changes in version 2: a) uncertainties have been added and updated in the netcdf file b) Ocean heat content > 2000m depth: update of one time series, and thus revised ensemble mean c) Atmospheric heat content: update of the time series as received by experts on the 29/05/2020 d) Available heat cyropshere: update of the time series as received by experts on the 27/05/2020. e) some attributes have been added for more details.

The dataset ‘Heat stored in the Earth system: Where does the energy go?’ contains a consistent long-term Earth system heat gain over the past 58 years. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. This Earth Energy Imbalance (EEI) is a fundamental metric of climate change. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory, and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2018.

The Bias Corrected CESMv1 data for current (2006-2015) and future (2091-2100) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature, relative humidity, wind speed, total precipitation, mean surface shortwave flux, top-of-atmosphere outgoing longwave radiation, mean surface latent and sensible heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 60 files (10 variables x 3 temporal resolutions x 2 periods packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x30, and 369x369x12 data points, respectively. The entire dataset is about 100 GB in size. The WRF version used for this project is WRF 3.8.1. . The WRF-ARW source codes and suitable tutorials are available free to users as an open-source model in the NCAR’s https://www2.mmm.ucar.edu/wrf/users/download/get_sources.html website.

The Bias Corrected CESMv1 data for mid-century (2041-2050) for RCP8.5 emission scenario at coarser resolution has been downscaled to 10km resolution over India using the Weather Research and Forecasting (WRF) model. The climate variables included are 2m Temperature (t2m), relative humidity (rh), wind speed (wspd), total precipitation (prec), mean surface shortwave flux (sw), top-of-atmosphere outgoing longwave radiation (lw), mean surface latent (lhf) and sensible (shf) heat fluxes along with the latitude, longitude, and time information. The dataset covers the Indian National Territory region at a 369 x 369 grid. The data is available at three temporal resolutions: Daily TS, Monthly TS, and Monthly Climatology. The dataset has been structured into a total of 30 files (10 variables x 3 temporal resolutions) packed in self-explanatory NetCDF format. The daily, monthly, and monthly climatology files contain 369x369x3650, 369x369x30, and 369x369x12 data points, respectively. The entire dataset is about 30 GB in size. The precipitation files in the older version contained hourly accumulated values for every day. This version contains the correct daily accumulated, monthly accumulated and monthly climatology precipitation data.