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Characterized by similar-to-today CO2 (∼400 ppm) and surface temperatures approximately 3°–4°C warmer than the preindustrial, the mid-Pliocene warm period (mPWP) has often been used as an analog for modern CO2-driven climate change and as a constraint on the equilibrium climate sensitivity (ECS). However, model intercomparison studies suggest that non-CO2boundary conditions—such as changes in ice sheets—contribute substantially to the higher global mean temperatures and strongly shape the pattern of sea surface warming during the mPWP. Here, we employ a set of CESM2 simulations to quantify mPWP effective radiative forcings, study the role of ocean circulation changes in shaping the patterns of sea surface temperatures, and calculate radiative feedbacks during the mPWP. We find that the non-CO2boundary conditions of the mPWP, enhanced by changes in ocean circulation, contributed to larger high-latitude warming and less-stabilizing feedbacks relative to those induced by CO2alone. Accounting for differences in feedbacks between the mPWP and the modern (greenhouse gas–driven) climate provides stronger constraints on the high-end of modern-day ECS. However, a quantification of the forcing of non-CO₂boundary condition changes combined with the distinct radiative feedbacks that they induce suggests that Earth system sensitivity may be higher than previously estimated. 

Temperature is the key variable in the study of climate changes in the past and future. Most previous studies on past temperature reconstructions, however, have focused on the mean annual temperature (MAT). Here, focusing on the seasonal temperature reconstructions in the Northern Hemisphere extratropics during the Holocene period, we show that the change in seasonal cycle of temperature reconstructions is severely underestimated in comparison with the expectation from present observations. Our study highlights the current uncertainty in seasonal temperature reconstructions in the Holocene, with an implication that the MAT simulation in current climate models may not be much biased. 

This dataset originates from a new CESM2 CAM6 perturbed parameter ensemble (PPE) designed to explore climate and hydroclimate dynamics under a wide range of sea surface temperature (SST) conditions. The SST varies from 4 degrees Celsius colder to 16 degrees Celsius warmer than preindustrial levels, encompassing a broad spectrum of mean temperatures spanning the past 65 million years. This dataset offers valuable insights into climate and hydroclimate responses, as well as weather and climate extremes under diverse conditions.The dataset includes results from nine PPE simulations with different SST scenarios: preindustrial (PREI), 4K cooler (M04K), and 4K, 8K, 12K, and 16K warmer (P04K to P16K). For SSTs exceeding 8K warming, sea ice was removed to improve numerical stability. Each PPE set consists of 250 ensemble members, with 45 parameters related to microphysics, convection, turbulence, and aerosols perturbed using Latin Hypercube Sampling. An additional simulation with default parameter settings brings the total to 251 simulations, each running for five years using CAM6.3 (https://github.com/ESCOMP/CAM/tree/cam6_3_026; with additional paleo modifications).Post-processing converted the data into compressed NetCDF-4 format. All 251 runs were concatenated using ncecat to minimize the number of files. For example, the following file contains monthly surface temperature data from the preindustrial PPE: f.c6.F1850.f19_f19.paleo_ppe.sst_prei.ens251/atm/proc/tseries/month_1/f.c6.F1850.f19_f19.paleo_ppe.sst_prei.ens251.cam.h0.TS.000101-000512.ncA detailed variable list [https://rda.ucar.edu/OS/web/datasets/d651038/docs/detailed_vars.txt] can be found in the Documentation Tab.Parameter values are provided in the PPE Parameter File. More details can be found in the paper: Zhu et al. (2025). Investigating the State Dependence of Cloud Feedback Using a Suite of Perturbed Parameter Ensembles, Journal of Climate. 

Abstract The state dependence of cloud feedback—its variation with the mean state climate—has been found in many paleoclimate and contemporary climate simulations. Previous results have shown inconsistencies in the sign, magnitude, and underlying mechanisms of state dependence. To address this, we utilize a perturbed parameter ensemble (PPE) approach with fixed sea surface temperature (SST) in the Community Atmosphere Model, version 6. Our suites of PPEs span a wide range of global mean surface temperatures (GMSTs), with spatially uniform SST perturbations of −4, 0, 4, 8, 12, and 16 K from the preindustrial. The results reveal a nonmonotonic variation with GMSTs: Cloud feedback increases under both cooler and warmer-than-preindustrial conditions, with a rise of ∼0.1 W m⁻²K⁻¹under a 4-K colder climate and ∼0.4 W m⁻²K⁻¹under a 12-K warmer climate. This complexity arises from differing cloud feedback responses in high and low latitudes. In high latitudes, cloud feedback consistently rises with warming, likely driven by a moist adiabatic mechanism that influences cloud liquid water. The low-latitude feedback increases under both cooler and warmer conditions, likely influenced by changes in the lower-tropospheric stability. This stability shift is tied to nonlinearity in thermodynamic responses, particularly in the tropical latent heating, alongside potential state-dependent changes in tropical circulations. Under warmer-than-preindustrial conditions, the increase in cloud feedback with warming is negatively correlated with its preindustrial value. Our PPE approach takes the model parameter uncertainty into account and emphasizes the critical role of state dependence in understanding past and predicting future climates. Significance StatementThis study focuses on how cloud feedback—one of the most uncertain aspects of climate change—varies as global temperatures rise. We found that the cloud feedback decreases at first with warming and then increases, showing significant variation. This complexity stems from nonlinear thermodynamics, such as the Clapeyron–Clausius relationship, which describes how temperature affects moisture in the atmosphere. Our results indicate that the cloud feedback depends on the level of global warming, which is a significant factor rooted in fundamental physics. Recognizing this dependence is important for studies that aim to interpret past climates and predict future climate changes. 

Simulating the warmth and equability of past hothouse climates has been a challenge since the inception of paleoclimate modeling. The newest generation of Earth system models (ESMs) has shown substantial improvements in the ability to simulate the early Eocene global mean surface temperature (GMST) and equator-to-pole gradient. Results using the Community Earth System Model suggest that parameterizations of atmospheric radiation, convection, and clouds largely determine the Eocene GMST and are responsible for improvements in the new ESMs, but they have less direct influence on the equator-to-pole temperature gradient. ESMs still have difficulty simulating some regional and seasonal temperatures, although improved data reconstructions of chronology, spatial coverage, and seasonal resolution are needed for more robust model assessment. Looking forward, key processes including radiation and clouds need to be benchmarked and improved using more accurate models of limited domain/physics. Earth system processes need to be better explored, leveraging the increasing ESM resolution and complexity. 

Abstract. Paleoclimate reconstructions of the Early Eocene provide important data constraints on the climate and hydrologic cycle under extreme warm conditions. Available terrestrial water isotope records have been primarily interpreted to signal an enhanced hydrologic cycle in the Early Eocene associated with large-scale warming induced by high atmospheric CO2. However, orbital-scale variations in these isotope records have been difficult to quantify and largely overlooked, even though orbitally driven changes in solar irradiance can impact temperature and the hydrologic cycle. In this study, we fill this gap using water isotope–climate simulations to investigate the orbital sensitivity of Earth's hydrologic cycle under different CO2 background states. We analyze the relative difference between climatic changes resulting from CO2 and orbital changes and find that the seasonal climate responses to orbital changes are larger than CO2-driven changes in several regions. Using terrestrial δ18O and δ2H records from the Paleocene–Eocene Thermal Maximum (PETM), we compare our modeled isotopic seasonal range to fossil evidence and find approximate agreement between empirical and simulated isotopic compositions. The limitations surrounding the equilibrated snapshot simulations of this transient event and empirical data include timing and time interval discrepancies between model and data, the preservation state of the proxy, analytical uncertainty, the relationship between δ18O or δ2H and environmental context, and vegetation uncertainties within the simulations. In spite of the limitations, this study illustrates the utility of fully coupled, isotope-enabled climate models when comparing climatic changes and interpreting proxy records in times of extreme warmth. 

Abstract. The effects of anthropogenic warming on the hydroclimate of California are becoming more pronounced with the increased frequency of multi-year droughts and flooding. As a past analog for the future, the Paleocene–Eocene Thermal Maximum (PETM) is a unique natural experiment for assessing global and regional hydroclimate sensitivity to greenhouse gas warming. Globally, extensive evidence (i.e., observations and climate models with high pCO2) demonstrates hydrological intensification with significant variability from region to region (i.e., drier or wetter, greater frequency, and/or intensity of extreme events). Central California (paleolatitude ∼ 42° N), roughly at the boundary between dry subtropical highs and mid-latitude low-pressure systems, would have been particularly susceptible to shifts in atmospheric circulation and precipitation patterns/intensity. Here, we present new observations and climate model output on regional/local hydroclimate responses in central California during the PETM. Our findings, based on multi-proxy evidence within the context of model outputs, suggest a transition to an overall drier climate punctuated by increased precipitation during summer months along central coastal California during the PETM. 

Abstract. The effects of anthropogenic warming on the hydroclimate of California are becoming more pronounced, with increased frequency of multi-year droughts and flooding. As a past analog for the future, the Paleocene-Eocene Thermal Maximum (PETM) is a unique natural experiment for assessing global and regional hydroclimate sensitivity to greenhouse gas warming. Globally, extensive evidence (i.e., observations, climate models with high pCO2) demonstrates hydrological intensification with significant variability from region to region (i.e., dryer or wetter, or greater frequency and/or intensity of extreme events). Central California (paleolatitude ~42° N), roughly at the boundary between dry subtropical highs and mid-latitude low pressure systems, would have been particularly susceptible to shifts in atmospheric circulation and precipitation patterns/intensity. Here, we present new observations and climate model output on regional/local hydroclimate responses in central California during PETM. Our findings based on multi-proxy evidence within the context of model output suggest a transition to an overall drier climate punctuated by increased precipitation during summer months along the central coastal California during the PETM. 

Here, we show that the Last Glacial Maximum (LGM) provides a stronger constraint on equilibrium climate sensitivity (ECS), the global warming from increasing greenhouse gases, after accounting for temperature patterns. Feedbacks governing ECS depend on spatial patterns of surface temperature (“pattern effects”); hence, using the LGM to constrain future warming requires quantifying how temperature patterns produce different feedbacks during LGM cooling versus modern-day warming. Combining data assimilation reconstructions with atmospheric models, we show that the climate is more sensitive to LGM forcing because ice sheets amplify extratropical cooling where feedbacks are destabilizing. Accounting for LGM pattern effects yields a median modern-day ECS of 2.4°C, 66% range 1.7° to 3.5°C (1.4° to 5.0°C, 5 to 95%), from LGM evidence alone. Combining the LGM with other lines of evidence, the best estimate becomes 2.9°C, 66% range 2.4° to 3.5°C (2.1° to 4.1°C, 5 to 95%), substantially narrowing uncertainty compared to recent assessments.