Long‐term climate simulations are performed using the IITM Earth System Model version 2 (IITM‐ESMv2), a sequel to the earlier version (IITM‐ESMv1), to assess climate variability and change with a special focus on the South Asian monsoon. Substantial improvements are incorporated in IITM‐ESMv2 to obtain a radiatively balanced global climate modeling framework. The IITM‐ESMv2 includes time‐varying aerosol forcing and land‐use land‐cover changes. Multicentury simulations corresponding to preindustrial and present‐day conditions show major improvements in capturing key aspects of time‐mean atmosphere and ocean large‐scale circulation. Representations of the Atlantic Meridional Overturning Circulation and poleward ocean heat transport, and major global climate drivers are superior to ESMv1. Teleconnections of the South Asian monsoon with climate drivers such as the El‐Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are found to be more robust in IITM‐ESMv2, thus leading to improved simulation of South Asian monsoon and its variability. The IITM‐ESMv2 takes a novel pursuit from India to contribute in the Intergovernmental Panel for Climate Change (IPCC) sixth assessment report (AR6).

To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.

Large volcanic eruptions enhance the coupling between the El Niño–Southern Oscillation and Indian monsoon.

We introduce University of Texas - GLObal Building heights for Urban Studies (UT-GLOBUS), a dataset providing building heights and urban canopy parameters (UCPs) for more than 1200 city or locales worldwide. UT-GLOBUS combines open-source spaceborne altimetry (ICESat-2 and GEDI) and coarse-resolution urban canopy elevation data with a machine-learning model to estimate building-level information. Validation using LiDAR data from six U.S. cities showed UT-GLOBUS-derived building heights had a root mean squared error (RMSE) of 9.1 meters. Validation of mean building heights within 1-km² grid cells, including data from Hamburg and Sydney, resulted in an RMSE of 7.8 meters. Testing the UCPs in the urban Weather Research and Forecasting (WRF-Urban) model resulted in a significant improvement (55% in RMSE) in intra-urban air temperature representation compared to the existing table-based local climate zone approach in Houston, TX. Additionally, we demonstrated the dataset’s utility for simulating heat mitigation strategies and building energy consumption using WRF-Urban, with test cases in Chicago, IL, and Austin, TX. Street-scale mean radiant temperature simulations using the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model, incorporating UT-GLOBUS and LiDAR-derived building heights, confirmed the dataset’s effectiveness in modeling human thermal comfort in Baltimore, MD (daytime RMSE = 2.85°C). Thus, UT-GLOBUS can be used for modeling urban hazards with significant socioeconomic and biometeorological risks, enabling finer scale urban climate simulations and overcoming previous limitations due to the lack of building information.