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The Nanjing University of Information Science and Technology Earth System Model version 3 (NESM v3) has been developed, aiming to provide a numerical modeling platform for cross-disciplinary earth system studies, project future Earth's climate and environment changes, as well conduct subseasonal-to-seasonal prediction. While the previous model version NESM v1 simulates well the internal modes of climate variability, it has no vegetation dynamics and suffers considerable radiative energy imbalance at the top of the atmosphere and surface, resulting in large biases in the global mean surface air temperature, which limit its utility to simulate past and project future climate changes. The NESM v3 upgraded the atmospheric and land surface model components and improved physical parameterization and conservation of coupling variables. Here we describe the new version's basic features and how the major improvements were made. We demonstrate the v3 model's fidelity and suitability to address the global climate variability and change issues. The 500-year PI experiment shows negligible trends in the net heat flux at the top of atmosphere and the Earth surface. Consistently, the simulated global mean surface air temperature, land surface temperature and sea surface temperature (SST) are all in a quasi-equilibrium state. The conservation of global water is demonstrated by the stable evolution of the global mean precipitation, sea surface salinity (SSS) and sea water salinity. The sea ice extents (SIEs), as a major indication of high latitude climate, also maintain a balanced state. The simulated spatial patterns of the mean outgoing longwave radiation, SST, precipitation, SSS fields are realistic, but the model suffers from a cold bias in the North Atlantic, a warm bias in the Southern Ocean and associated deficient Antarctic sea ice area, as well as a delicate sign of the double ITCZ syndrome. The estimate radiative forcing of quadrupling carbon dioxide is about 7.24 W m-2, yielding a climate sensitivity feedback parameter of -0.98 W m-2 K-1, and the equilibrium climate sensitivity is 3.69 K. The transient climate response from the 1 pct/year increasing CO2 experiment is 2.16 K. The model's performance on internal modes and responses to external forcing during the historical period will be documented in an accompanying paper. [ABSTRACT FROM AUTHOR]

The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercomparison Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of PMIP (PMIP4). The past1000 transient simulations serve to investigate the response to (mainly) natural forcing under background conditions not too different from today, and to discriminate between forced and internally generated variability on interannual to centennial time scales. This manuscript describes the motivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents: orbital, solar, volcanic, land-use/land-cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849 CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 experiments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simulations have been divided into three tiers. A default forcing data set has been defined for the "tier-1" (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated "tier-2" simulations. Additional experiments ("tier-3") are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simulations. This manuscript outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instrumental data). [ABSTRACT FROM AUTHOR]