As global warming is proceeding due to rising greenhouse gas concentrations, the Earth system moves towards climate states that challenge adaptation. Past Earth system states are offering possible modelling systems for the global warming of the coming decades. These include the climate of the mid-Pliocene (∼ 3 Ma), the last interglacial (∼ 129–116 ka) and the mid-Holocene (∼ 6 ka). The simulations for these past warm periods are the key experiments in the Paleoclimate Model Intercomparison Project (PMIP) phase 4, contributing to phase 6 of the Coupled Model Intercomparison Project (CMIP6). Paleoclimate modelling has long been regarded as a robust out-of-sample test bed of the climate models used to project future climate changes. Here, we document the model setup for PMIP4 experiments with EC-Earth3-LR and present the large-scale features from the simulations for the mid-Holocene, the last interglacial and the mid-Pliocene. Using the pre-industrial climate as a reference state, we show global temperature changes, large-scale Hadley circulation and Walker circulation, polar warming, global monsoons and the climate variability modes – El Niño–Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). EC-Earth3-LR simulates reasonable climate responses during past warm periods, as shown in the other PMIP4-CMIP6 model ensemble. The systematic comparison of these climate changes in past three warm periods in an individual model demonstrates the model's ability to capture the climate response under different climate forcings, providing potential implications for confidence in future projections with the EC-Earth model.

Large‐scale photovoltaic solar farms envisioned over the Sahara desert can meet the world's energy demand while increasing regional rainfall and vegetation cover. However, adverse remote effects resulting from atmospheric teleconnections could offset such regional benefits. We use state‐of‐the‐art Earth‐system model simulations to evaluate the global impacts of Sahara solar farms. Our results indicate a redistribution of precipitation causing Amazon droughts and forest degradation, and global surface temperature rise and sea‐ice loss, particularly over the Arctic due to increased polarward heat transport, and northward expansion of deciduous forests in the Northern Hemisphere. We also identify reduced El Niño‐Southern Oscillation and Atlantic Niño variability and enhanced tropical cyclone activity. Comparison to proxy inferences for a wetter and greener Sahara ∼6,000 years ago appears to substantiate these results. Understanding these responses within the Earth system provides insights into the site selection concerning any massive deployment of solar energy in the world's deserts.

The “Green Sahara” is a period when North Africa was characterized by vegetation cover and wetlands. To qualitatively identify the orbital‐climatic causation of the Green Sahara regime, we performed dynamic vegetation model (LPJ‐GUESS) simulations, driven by climate forcings from coupled general circulation model (EC‐Earth) simulations for the mid‐Holocene, in which the vegetation is prescribed to be either modern desert or artificially vegetated with a reduced dust load. LPJ‐GUESS simulates a vegetated Sahara covered by both herbaceous and woody vegetation types consistent with proxy reconstructions only in the latter scenario. Sensitivity experiments identify interactions required to capture the northward extension of vegetation. Increased precipitation is the main driver of the vegetation extent changes, and the temperature anomalies determine the plant functional types mainly through altered fire disturbance. Furthermore, the simulated vegetation composition also depends on the correct representation of soil texture in a humid environment like Green Sahara.

The Earth has seen El Niño-Southern Oscillation (ENSO)—the leading mode of interannual climate variability—for at least millennia and likely over millions of years. This paper reviews previous studies from perspectives of both paleoclimate proxy data (from traditional sediment records to the latest high-resolution oxygen isotope records) and model simulations (including earlier intermediate models to the latest isotope-enabled coupled models). It summarizes current understanding of ENSO’s past evolution during both interglacial and glacial periods and its response to external climatic forcings such as volcanic, orbital, ice-sheet and greenhouse gas forcings. Due to the intrinsic irregularity of ENSO and its complicated relationship with other climate phenomena, reconstructions and model simulations of ENSO variability are subject to inherent difficulties in interpretations and biases. Resolving these challenges through new data syntheses, new statistical methods, more complex climate model simulations as well as direct model-data comparisons can potentially better constrain uncertainty regarding ENSO’s response to future global warming.

Three transient National Center for Atmospheric Research Community Climate System Model, version 3 model simulations were analyzed to study the responses of El Niño–Southern Oscillation (ENSO) and the equatorial Pacific annual cycle (AC) to external forcings over the last 300,000 years. The time‐varying boundary conditions of insolation, greenhouse gases, and continental ice sheets, accelerated by a factor of 100, were sequentially added in these simulations. The simulated ENSO and AC amplitudes change in phase, and both have pronounced precession band variance (~21,000 years). The precession‐modulated slow (orbital time scales) ENSO evolution is dominated linearly by the change of the coupled ocean‐atmosphere instability, notably the Ekman upwelling feedback and thermocline feedback. In contrast, the greenhouse gases and ice sheet forcings (~100,000‐year cycles) are opposed to each other as they influence ENSO variability through changes in AC amplitude via a common nonlinear frequency entrainment mechanism. The acceleration technique could dampen and delay the precession signals below the surface ocean associated with ENSO intensity.