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The CESM2 "Single Forcing" Large Ensemble Project is a publicly available set of climate model simulations useful for addressing the roles of individual forcings in historical and future climate change. This simulations use the same model and forcings as the CESM2 Large Ensemble Project and, therefore, can be used to parse the relative roles of different forcings in responses found in that ensemble where all forcings are applied together. The ensemble members are initialized from 1850 from the same initial conditions that were used to initialize the "macro" members of the CESM2 Large Ensemble and they extend to 2050, following CMIP6 historical forcings prior to 2015 and SSP3-7.0 forcings, thereafter. Note that the smoothed biomass burning emissions that were used in the second 50 members of the CESM2 large ensemble are used, so these simulations should be compared with the second 50 members of the CESM2 large ensemble. Four primary ensembles are available in which different forcings are time evolving while all other forcings are held fixed at 1850's values, that is, the "only" method is used. Note that this differs from the CESM1 Large Ensemble which used the "all-but-one" method where all forcings were evolving except the one of interest. In the CESM2 ensembles, only the forcing of interest is evolving. Four ensembles are available using the following time-evolving forcings:

• GHG = only greenhouse gases evolving (15 members)
• AAER = Only anthropogenic aerosols evolving (20 members)
• BMB = Only biomass burning aerosols evolving (15 members)
• EE = everything else evolving i.e., all forcings other than those that are time evolving in GHG, AAER or BMB are time evolving. Greenhouse gases and anthropogenic and biomass burning aerosols are held fixed (15 members)

Note that by "anthropogenic aerosols" here we refer to all industrial, agricultural, domestic and transport related emissions and acknowledge that this does not include any anthropogenic influences on biomass burning, which is instead present in the BMB ensemble. Each forcing that is time evolving in the CESM2 Large Ensemble is time evolving in one of these four sub-ensembles to allow additivity to be tested. As discussed in the release paper cited below, substantial non-linearities are present in the CESM2 Single Forcing Large Ensemble. As part of the investigation into this non-linearity, an additional ensemble was performed which was initialized in 1920 of the CESM2 Large Ensemble members and run with all forcings except anthropogenic aerosols i.e., following the same "all-but-one" approach that was used in CESM1. This demonstrated that there is considerable sensitivity of the anthropogenic aerosol forced response to the method used i.e., "all-but-one" versus "only". We have, therefore, expanded this ensemble to a 10 member ensemble, referred to as xAER, so that any sensitivity of the anthropogenic aerosol influence to the method used can be tested.

xAER = Everything time evolving except anthropogenic aerosols (10 members)

Datasets used in the creation of original figures of Bacmeister et al. JAMES (2020). CO2 increase experiments using the Community Earth System Model (CESM): Relationship to climate sensitivity and comparison of CESM1 to CESM2.

We examine the response of the Community Earth System Model versions 1 and 2 (CESM1 and CESM2) to abrupt quadrupling of atmospheric CO2 concentrations (4xCO2) and to 1% annually increasing CO2 concentrations (1% CO2). Different estimates of equilibrium climate sensitivity (ECS) for CESM1 and CESM2 are presented. All estimates show that the sensitivity of CESM2 has increased by 1.5K or more over that of CESM1. At the same time the transient climate response (TCR) of CESM1 and CESM2 derived from 1% CO2 experiments has not changed significantly - 2.1K in CESM1 and 2.0K in CESM2. Increased initial forcing as well as stronger shortwave radiation feedbacks are responsible for the increase in ECS seen in CESM2. A decomposition of regional radiation feedbacks and their contribution to global feedbacks shows that the Southern Ocean plays a key role in the overall behavior of 4xCO2 experiments, accounting for about 50% of the total shortwave feedback in both CESM1 and CESM2. The Southern Ocean is also responsible for around half of the increase in shortwave feedback between CESM1 and CESM2, with a comparable contribution arising over tropical ocean. Experiments using a thermodynamic slab-ocean model (SOM) yield estimates of ECS that are in remarkable agreement with those from fully-coupled earth system model (ESM) experiments for the same level of CO2 increase. Finally, we show that the similarity of TCR in CESM1 and CESM2 masks significant regional differences in warming that occur in the 1% CO2 experiments for each model.

This is a 16 member ensemble of simulations with CESM2 under the SSP2-4.5 forcing scenario from 2015 to 2100. These simulations can be compared with the CESM2 Large Ensemble and provide the opportunity to compare and contrast change under a lower forcing scenario. One difference from the official CMIP6 SSP2-4.5 forcing is that slightly modified biomass burning emissions are used at the beginning of the simulation. As is discussed in the CESM2 Large Ensemble reference paper (Rodgers et. al. 2021), the second 50 members of the CESM2 Large Ensemble use smoothed biomass burning emissions over the GFED era of the late 20th/early 21st centuries. While the GFED emissions were not prescribed in the SSP scenario, there is a minor effect of the smoothing into the first years of the SSP scenario and these simulations have been branched from historical simulations that used the smoothed biomass burning emissions. As such, this medium ensemble is complementary to the second 50 member of the CESM2 Large Ensemble.

For more information about this ensemble visit the CESM CVCWG CESM2 SSP2-4.5 Ensemble website.

This is a 15 member ensemble of simulations with CESM2 under the SSP5-8.5 forcing scenario from 2015 to 2100. Note, SSP5-8.5 is not considered a likely scenario - it is a high emissions scenario. These simulations can be compared with the CESM2 Large Ensemble and provide the opportunity to compare and contrast climate change under a lower forcing scenario. One difference from the official CMIP6 SSP5-8.5 forcing is that slightly modified biomass burning emissions are used at the beginning of the simulation. As is discussed in the CESM2 Large Ensemble reference paper (Rodgers et. al. 2021), the second 50 members of the CESM2 Large Ensemble use smoothed biomass burning emissions over the GFED era of the late 20th/early 21st centuries. While the GFED emissions were not prescribed in the SSP scenario, there is a minor effect of the smoothing into the first years of the SSP scenario and these simulations have been branched from historical simulations that used the smoothed biomass burning emissions. As such, this medium ensemble is complementary to the second 50 member of the CESM2 Large Ensemble.

For more information about this ensemble visit the CESM CVCWG CESM2 SSP5-8.5 Ensemble website.

This study isolates the influence of sea ice mean state on pre-industrial climate and transient 1850-2100 climate change within a fully coupled global model: The Community Earth System Model version 2 (CESM2). The CESM2 sea ice model physics is modified to increase surface albedo, reduce surface sea ice melt, and increase Arctic sea ice thickness and late summer cover. Importantly, increased Arctic sea ice in the modified model reduces a present-day late-summer ice cover bias. Of interest to coupled model development, this bias reduction is realized without degrading the global simulation including top of atmosphere energy imbalance, surface temperature, surface precipitation, and major modes of climate variability. The influence of these sea ice physics changes on transient 1850-2100 climate change is compared within a large initial condition ensemble framework. Despite similar global warming, the modified model with thicker Arctic sea ice than CESM2 has a delayed and more realistic transition to a seasonally ice free Arctic Ocean. Differences in transient climate change between the modified model and CESM2 are challenging to detect due to large internally generated climate variability. In particular, two common sea ice benchmarks, sea ice sensitivity and sea ice trends, are of limited value for comparing models with similar global warming. More broadly, these results show the importance of a reasonable Arctic sea ice mean state when simulating the transition to an ice-free Arctic Ocean in a warming world. Additionally, this work highlights the importance of large initial condition ensembles for credible model-to-model and observation-model comparisons.

The CESM2 with CMIP5 forcing is a set of climate model simulations intended to disentangle the role of forcing versus model structure between CESM2 and CESM1 for pre-industrial, 20th and 21st centuries simulations.

The CESM2 has considerable changes relative to the CESM1 both in the model structure and in the forcing. In order to understand these changes and their impact on climate variability and change, simulations with CESM2 but with a forcing similar to CESM1 were performed.

Simulations include a 500-year pre-industrial run and two 15-member ensembles forced by historical/RCP8.5 datasets.

Due to computational constraints, only a single historical ensemble member runs from 1850-1920. The remaining members were branched in 1920 from the first member.

The forcing in these simulations is comparable to forcing used in the CESM1 Large Ensemble Simulations.

The model code and case setups for the CESM2 CMIP5 Forcing Experiments can be found on github.

This dataset includes ensemble prediction experiments using the CESM2 model. These are "perfect model prediction experiments" in which the simulations are initialized with nearly identical conditions from CESM2 simulations in the year 2030 and then integrated forward for two years. Ensemble prediction sets are initialized on January 1, March 1, May 1, July 1, September 1, and November 1. Five different initial conditions, taken from five different CESM2 simulations, are used for each initialization timing and 15 members are simulated for each of the five initial states. These 15 members differ with a micro-perturbation to the initial atmospheric temperature. Thus, for each initialization timing set (i.e. January 1, 2030) there are 75 total ensemble members (15 members for 5 initial states). These experiments can be used to assess the inherent initial-value predictability characteristics of the earth system as simulated by CESM2.

This dataset includes ensemble prediction experiments using the CESM2 model. These are "perfect model prediction experiments" in which the simulations are initialized with nearly identical conditions from CESM2 historical simulations in the year 2010 and then integrated forward for two years. Ensemble prediction sets are initialized on January 1, March 1, May 1, July 1, September 1, and November 1. Five different initial conditions, taken from five different CESM2 historical simulations, are used are each initialization timing and 15 members are simulated for each of the five initial states. These 15 members differ with a micro-perturbation to the initial atmospheric temperature. Thus, for each initialization timing set (i.e. January 1, 2010) there are 75 total ensemble members (15 members for 5 initial states). These experiments can be used to assess the inherent initial-value predictability characteristics of the earth system as simulated by CESM2.

The efficiency of marine cloud brightening in cooling Earth's surface temperature is investigated by using a medium ensemble of simulations with the Community Earth System Model version 2 (CESM2). Various cloud seeding schemes based on susceptibility are examined to determine what area extent will be required to induce 1.5 degrees C cooling under SSP2-4.5. The results indicate that cloud seeding over 5% of the ocean area is capable of achieving this goal. Under this seeding scheme, cloud seeding is mainly deployed over lower latitudes where strong surface temperature and precipitation responses are induced. The simulations also reveal that the 5% cloud seeding scheme reduces precipitation over the ocean, but enhances precipitation over land, with an overall reduction in global precipitation.

Previous modeling studies indicate that even though marine cloud brightening under a susceptibility-based strategy is effective in reducing the global average surface temperature, it can induce several highly undesirable outcomes. Under such marine cloud brightening intervention, a La Nina-like sea-surface temperature response is triggered with cooling mostly confined within lower latitudes. It is likely to pose a threat to disrupt the El Nino Southern Oscillation.

A different cloud seeding strategy is explored to alleviate such undesirable outcomes. It is hypothesized that deployment of marine cloud brightening over broader regions with low susceptibility to cloud seeding might induce cooling more evenly distributed over the globe, and hence exert much weaker regional forcing on the climate system. This hypothesis is tested with the Community Earth System Model, version 2 (CESM2). Our simulations with CESM2 reveal that this new strategy indeed alleviates the highly undesirable outcomes previously found.

The CESM2 SSP2-4.5 ensemble simulations can be accessed at https://doi.org/10.26024/j23t-pc83.

The Transient Last Interglacial dataset contains output from the TransientLIG simulation from 127,000 to 119,000 years before present (127 - 119 ka). This simulation is with the CESM2.1 at the FV1_gx1v6 resolution coupled to CISM2 at 4 km resolution for Greenland. The ice sheet model and the orbital parameters over time (eccentricity, obliquity, and precession) are accelerated - advancing 5 years for each CESM2 year. In CAM6, the surface elevation over Greenland is updated every 10 atmosphere years. Offline coupling of BIOME4 distributions every 500 ice-sheet years allows for incorporation of quasi-dynamic vegetation changes [U.S. Geological Survey data release, https://doi.org/10.5066/P9RPB5KD]. All other forcings (GHGs, aerosols, land-ocean configuration) are kept constant during the TransientLIG simulation.

The dataset also includes a sensitivity simulation (NoBiome) from 127 - 121 ka illustrating the effects of vegetation. This simulation retains the preindustrial no-Anthro vegetation distribution adopted in the CMIP6-PMIP4 127 ka and 6ka equilibrium simulations with CESM2.1 at the FV1_gx1v6 resolution.

The TransientLIG and NoBiome simulations are initialized from the CMIP6-PMIP4 lig127ka simulation with CESM2 [http://doi.org/10.22033/ESGF/CMIP6.7673]. The simulations adopted the initial state of the GrIS from the CESM2-CISM2 JG/BG spinup under pre-industrial climate forcing [https://doi.org/10.26024/4gt3-9r10].

This dataset contains processed data from the CESM2 single forcing large ensemble experiments as well as some CESM2 emissions files that are necessary for reproducing the figures in Simpson et al (2023) "The CESM2 Single Forcing Large Ensemble and Comparison to CESM1: Implications for Experimental Design", Journal of Climate.

The CESM2 Large Ensemble consists of 100 members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Two separate sets of biomass burning emissions forcing files were used within the ensemble. Members 1-50 were forced with CMIP6 protocols identical to those used in Danabasoglu et al. (2020) in the paper for CESM2. For members 51-100, the most relevant species for biomass burning fluxes from the CMIP6 protocols were smoothed with an 11-year running mean filter, impacting the fluxes over the years 1990-2020.

The CESM2 Large Ensemble uses a combination of different oceanic and atmospheric initial states to create ensemble spread as follows:

Members 1-10: These begin from years 1001, 1021, 1041, 1061, 1081, 1101, 1121, 1141, 1161, and 1181 of the 1400-year pre-industrial control simulation. This segment of the control simulation was chosen to minimize drift.

Members 11-90: These begin from 4 pre-selected years of the pre-industrial control simulation based on the phase of the Atlantic Meridional Overturning Circulation (AMOC). For each of the 4 initial states, there are 20 ensemble members created by randomly perturbing the atmospheric temperature field on the order of -14K. The chosen start dates (model years 1231, 1251, 1281, and 1301) sample AMOC and Sea Surface Height (SSH) in the Labrador Sea at their maximum, minimum and transition states.

Members 91-100: These begin from years 1011, 1031, 1051, 1071, 1091, 1111, 1131, 1151, 1171, and 1191 of the 1400-year pre-industrial control simulation. This set includes the extensive "MOAR" output, which can be used to drive regional climate models.

The initialization design allows assessment of oceanic (AMOC) and atmospheric contributions to ensemble spread, and the impact of AMOC initial-condition memory on the global earth system.

SMYLE (Seasonal-to-MultiYear Large Ensemble) is an initialized prediction system using CESM2. It consists of fully coupled initialized hindcast simulations using CESM2 component models at nominal 1 degree horizontal resolution. Hindcasts are initialized from historical reconstructions (SMYLE-FOSI for ocean and sea-ice; SMYLE-landonly for land; and JRA55 reanalysis for atmosphere) and then integrated forward 24-months. Initialization occurs quarterly (1st of each month of February, May, August, and November) for each year between 1970-2019. The ensemble size is 20 for each start date, with ensemble spread introduced through a random field perturbation applied to the atmospheric initial conditions. The SMYLE data release also includes the historical reconstructions used to initialize the ocean, sea ice, ocean biogeochemistry, and land components (SMYLE-FOSI and SMYLE-landonly).

The US National Center for Atmospheric Research partnered with the IBS Center for Climate Physics in South Korea to generate the CESM2 Large Ensemble which consists of 100 ensemble members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Data sets from this ensemble were made downloadable via the Climate Data Gateway on June 14, 2021. NCAR has copied a subset (currently ~500 TB) of CESM2 LENS data to Amazon S3 as part of the AWS Public Datasets Program. To optimize for large-scale analytics we have represented the data as ~275 Zarr stores format accessible through the Python Xarray library. Each Zarr store contains a single physical variable for a given model run type and temporal frequency (monthly, daily).

The Marine Biogeochemistry Library (MARBL) is a prognostic ocean biogeochemistry model that simulates marine ecosystem dynamics and the coupled cycles of carbon, nitrogen, phosphorus, iron, silicon, and oxygen.

MARBL is a component of the Community Earth System Model (CESM); it supports flexible ecosystem configuration of multiple phytoplankton and zooplankton functional types; it is also portable, designed to interface with multiple ocean circulation models. Here, we present scientific documentation of MARBL, describe its configuration in CESM2 experiments included in the Coupled Model Intercomparison Project version 6 (CMIP6), and evaluate its performance against a number of observational datasets.

The model simulates present-day air-sea CO2 flux and many aspects of the carbon cycle in good agreement with observations. However, the simulated integrated uptake of anthropogenic CO2 is weak, which we link to poor thermocline ventilation, a feature evident in simulated chlorofluorocarbon distributions. This also contributes to larger-than-observed oxygen minimum zones. Moreover, radiocarbon distributions show that the simulated circulation in the deep North Pacific is extremely sluggish, yielding extensive oxygen depletion and nutrient trapping at depth.

Surface macronutrient biases are generally positive at low latitudes and negative at high latitudes. CESM2 simulates globally-integrated net primary production (NPP) of 48 PgC/yr and particulate export flux at 100m of 7.1 PgC/yr. The impacts of climate change include an increase in globally-integrated NPP, but substantial declines in the North Atlantic.

Particulate export is projected to decline globally, attributable to decreasing export efficiency associated with changes in phytoplankton community composition.

This dataset contains the more frequently-used variables from the DECK (Diagnostic, Evaluation and Characterization of Klima), the Coupled Model Intercomparison Project phase 6 (CMIP6) historical, and the Paleoclimate Modelling Intercomparison Project phase 4 (PMIP4) Last Glacial Maximum simulations using the Paleoclimate-Calibrated Community Earth System Model version 2 (CESM2).

The Community Earth System Model Version 2 (CESM2) has a Equilibrium Climate Sensitivity (ECS) of 5.3K. ECS is an emergent property of both climate feedbacks and aerosol forcing. The increase in ECS over the previous version (CESM1) is the result of cloud feedbacks. Interim versions of CESM2 had a land model which damped ECS. Part of the ECS change results from evolving the model configuration to reproduce the long term trend of global and regional surface temperature over the 20th century in response to climate forcings. Changes made to reduce sensitivity to aerosols also impacted cloud feedbacks, which significantly influence ECS. CESM2 simulations compare very well to observations of present climate. It is critical to understand whether the high ECS, outside the best estimate range of 1.5 to 4.5K, is plausible.

We examine results from two transient modeling experiments that simulate the Last Interglacial period (LIG) using the state-of-the-art Community Earth System Model (CESM2), with a focus on climate and ocean changes relevant to the possible collapse of the Antarctic ice sheet. The experiments simulate the early millennia of the LIG warm period using orbital forcing, greenhouse gas concentrations and vegetation appropriate for 127ka; in the first case (127ka) no other changes are made; in the second case (127kaFW), we include a 0.2 Sv freshwater forcing in the North Atlantic. Both are compared with a pre-industrial control simulation (piControl). In the 127ka simulation, the global average temperature is only marginally warmer (0.004 degrees C) than in the piControl. When freshwater forcing is added (127kaFW), there is surface cooling in the NH and warming in the SH, consistent with the bipolar seesaw effect. Near the Antarctic ice sheet, the 127ka simulation generates notable ocean warming (up to 0.4 degrees C) at depths below 200 m compared to the piControl. In contrast, the addition of freshwater in the North Atlantic in the 127kaFW run results in a multi-century subsurface ocean cooling that rebounds slowly over multiple millennia near the Antarctic ice sheet. These results have implications for the thermal forcing (and thereby mass balance) of the Antarctic Ice Sheet. We explore the physical processes that lead to this result and discuss implications for climate forcing of Antarctic ice sheet mass loss during the LIG.

We examine results from two transient modeling experiments that simulate the Last Interglacial period (LIG) using the state-of-the-art Community Earth System Model (CESM2), with a focus on climate and ocean changes relevant to the possible collapse of the Antarctic ice sheet. The experiments simulate the early millennia of the LIG warm period using orbital forcing, greenhouse gas concentrations and vegetation appropriate for 127ka; in the first case (127ka) no other changes are made; in the second case (127kaFW), we include a 0.2 Sv freshwater forcing in the North Atlantic. Both are compared with a pre-industrial control simulation (piControl). In the 127ka simulation, the global average temperature is only marginally warmer (0.004 degrees C) than in the piControl. When freshwater forcing is added (127kaFW), there is surface cooling in the NH and warming in the SH, consistent with the bipolar seesaw effect. Near the Antarctic ice sheet, the 127ka simulation generates notable ocean warming (up to 0.4 degrees C) at depths below 200 m compared to the piControl. In contrast, the addition of freshwater in the North Atlantic in the 127kaFW run results in a multi-century subsurface ocean cooling that rebounds slowly over multiple millennia near the Antarctic ice sheet. These results have implications for the thermal forcing (and thereby mass balance) of the Antarctic Ice Sheet. We explore the physical processes that lead to this result and discuss implications for climate forcing of Antarctic ice sheet mass loss during the LIG.

A 10-member ensemble of CESM2 (1 degree spatial resolution) simulations in which time-evolving SST anomalies in the eastern tropical Pacific are nudged to observations (NOAA Extended Reconstruction Sea Surface Temperature version 5: ERSSTv5) during 1880-2019. In this way, the observed evolution of ENSO is maintained in each simulation (i.e. ENSO is the pacemaker), with the rest of the model's coupled climate system free to evolve. Note that only the SST anomalies, not the total SST, are nudged to observations, maintaining the model's mean state, including and model biases. In the East Pacific, the nudging is full strength between 15S and 15N and from the International Date Line to the American coast with a 5 degree latitude buffer region to the south and north where the strength of the relaxation is linearly reduced. West of the Date Line, the nudging mask takes the form of a wedge shape, tapering off in latitude toward the Maritime continent.

This is a 10-member ensemble of SSP2-4.5 simulations with CESM2 (WACCM6) that provide control simulations for the ARISE SAI (Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection) simulations. The first 5 members have the default CMIP6 output whereas the subsequent 5 ensemble members include additional output that matches the ARISE SAI output. Simulations go from 2015 to 2100 (for the first 5 ensemble members) and from 2015 through 2069 for the subsequent 5 ensemble members. All 3D data are on the original model levels (in timeseries format).

This dataset contains subseasonal-to-seasonal (S2S) hindcasts with CESM2 WACCM that were done in support of a NOAA project and also NCAR NSC project on Whole Atmosphere subseasonal predictability. These forecasts consist of 45-day long runs initialized every Monday from 1999 to 2019, 11 ensemble members for start dates between September and March (winter season). Output includes atmospheric, land, ocean and sea-ice variables. The project utilized both NOAA grant and core funding. NOAA did not require us to publish data, but as part of the NCAR mission (and core funded effort) we do need to put things out for the community and also to publish findings.

Atmospheric Forcing data, regridded from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) data and are both horizontally and vertically interpolated to the CESM2 standard 32 vertical model levels.

This dataset contains tropical cyclone (TCs) tracks in the CESM2 S2S reforecasts for the period of 2002 - 2019. We use the TempestExtremes tracking algorithm to detect and track TCs (or TC-like disturbances) on the CESM2 CAM6 native grid, utilizing all 11 ensemble members and 6-hourly output of near-surface winds, sea level pressure, and geopotential thickness between 200 and 500 hPa. D

Climate variations on seasonal-to-decadal (S2D) timescales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales an invaluable tool for policymakers and stakeholders. Such variations modulate the likelihood and intensity of extreme weather events including, tropical cyclones (TCs), heat waves, winter storms, atmospheric rivers (ARs), and floods, which have all been associated with (1) increases in human morbidity and mortality rates; (2) severe impacts on agriculture, energy use, and industrial activity; and (3) economic costs in the billions of dollars. Changes in prevailing climate patterns are also responsible for prolonged droughts, which can have profoundly negative effects on large segments of the world population. Enhancing our foreknowledge of climate variability on S2D time scales and understanding its influence on extreme weather events could help mitigate negative impacts on human and biological populations, making climate predictions an exceptionally important climate and social science frontier.

Over the past six years, our research team consisting of scientists at Texas A and M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed an unprecedented 10-member ensemble of Community Earth System Model (CESM) historical and future climate simulations at a TC-permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR). This CESM-HR ensemble was completed as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". This ensemble is particularly timely, following the April 2023 report entitled "Extreme Weather Risk in a Changing Climate: Enhancing Prediction and Protecting Communities" from the U.S. President's Council of Advisors on Science and Technology (PCAST). Indeed, this report made several recommendations on how climate science can support the provision of information about future risks from extreme weather and highlight the urgent need for high-resolution simulations to improve predictions of extreme weather events and guide risk management strategies. More specifically, the report recognized that high-resolution simulations, in the range of 10-25km horizontal resolution, would capture extreme events more accurately than typical low-resolution (approximately 100km) climate projections, and it goes on to recommend "a focused federal effort to provide estimates of the risk that a weather event of a given severity will occur in any location and year between now and mid-century". Our 10-member CESM-HR ensemble is able to meet some of the key aspects of this PCAST report.

The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al. 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al. 2012; Smith et al. 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al. 2011).

The CESM-HR ensemble experimental design follows a similar approach as the CESM LENS1 large ensemble. We started with a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions. The first ensemble member is branched at year 250 of the PI-CTRL simulation and then integrated forward from year 1850 to 2100 (Figure 1). Ensemble members 2-10 are subsequently started from the year 1920 of ensemble member 1 and integrated forward to 2100 (Figure 1). Spread in the ensemble is generated by applying round-off level perturbations in the atmospheric potential temperature initial conditions for members 2-10. All 10 members use the same specified external climate forcing. Following the CMIP5 protocol for the Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, historical forcing is used from 1920 to 2005 followed by the representative concentration pathway 8.5 (RCP 8.5) forcing from 2006 to 2100. RCP 8.5 is a high-emissions scenario and is frequently referred to as the "business as usual" scenario. It refers to the concentration of carbon that delivers global warming at an average of 8.5 W/m^2 across the planet by 2100. All 10 members produce a warming of approximately 4.5K at the end of 2100 in response to the applied historical and RCP 8.5 external forcing (Figure 1). The warming produced by CESM-HR is consistent with the warming from the standard low-resolution (approximately 1 degree) version of the model. The rate of warming simulated by CESM-HR over the observed period agrees very well with the observed rate of warming derived from the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (Figure 1).

Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Current predictions and projections of future sea-level changes are based on Coupled Model Intercomparison Project (CMIP) class climate model simulations. Although this class of models is capable of simulating global sea-level rise and its basic spatial patterns, they are unable to robustly and accurately predict or project future regional and local sea-level changes because of their limitations in representing complex coastline and bathymetry features and regional ocean circulations with their coarse (approximately 100 km) horizontal resolutions. More specifically, sea-level changes within the Gulf of Mexico are closely linked to changes in the Loop Current and its eddies, which cannot be resolved by these CMIP-class models.

To address this fundamental issue, we have completed a 10-member ensemble of simulations with the Community Earth System Model (CESM) at a Tropical Cyclone-permitting and ocean-mesoscale-eddy-rich horizontal resolution (hereafter simply referred to as CESM-HR). The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).

Following the protocol for the CMIP phase 5 (CMIP5) experiments, the representative concentration pathway 6.0 (RCP 6.0) was used to force the model from 2006 to 2100. RCP 6.0 represents a stabilization scenario, where the greenhouse gas emission rate is high initially, but total radiative forcing is stabilized after 2100 through the use of various technologies and strategies for reducing emissions. In this scenario, the specified amount of carbon concentration results in an average global radiative forcing increase of 6.0 W/m^2 by 2100. This CESM-HR ensemble was completed as part of our National Academy of Sciences (NAS) funded project entitled "Improving Prediction and Projection of Gulf of Mexico Sea-Level Changes Using Eddy-Resolving Earth System Models (iPOGS)". This effort is complementary to the 10-member ensemble of CESM-HR historical and future (with RCP 8.5 forcing) climate simulations produced by our National Science Foundation (NSF) funded project entitled "Understanding the role of mesoscale atmosphere-ocean interactions in seasonal-to-decadal climate prediction (MESACLIP)". Each RCP 6.0 simulation starts at the end of the corresponding historical simulation from MESACLIP, enabling the exploration of future projections associated with varying levels of mitigation and future greenhouse gas emissions. For example, Figure 1 shows the global-mean dynamical sea level (DSL) from simulations under different forcings. The stronger warming associated with the RCP 8.5 forcing results in an additional 10 cm rise in global-mean DSL by 2100 compared to that of the RCP 6.0 ensemble.

Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Climate variations on seasonal-to-decadal (S2D) timescales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales an invaluable tool for policymakers and stakeholders. Such variations modulate the likelihood and intensity of extreme weather events including, tropical cyclones (TCs), heat waves, winter storms, atmospheric rivers (ARs), and floods, which have all been associated with (1) increases in human morbidity and mortality rates; (2) severe impacts on agriculture, energy use, and industrial activity; and (3) economic costs in the billions of dollars. Changes in prevailing climate patterns are also responsible for prolonged droughts, which can have profoundly negative effects on large segments of the world population. Enhancing our foreknowledge of climate variability on S2D time scales and understanding its influence on extreme weather events could help mitigate negative impacts on human and biological populations, making climate predictions an exceptionally important climate and social science frontier.

Over the past six years, our research team consisting of scientists at Texas A&M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed an unprecedented 10-member ensemble of Community Earth System Model (CESM) historical and future climate simulations at a tropical cyclone-permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR). This CESM-HR ensemble was completed as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". This ensemble is particularly timely, following the April 2023 report entitled "Extreme Weather Risk in a Changing Climate: Enhancing Prediction and Protecting Communities" from the U.S. President's Council of Advisors on Science and Technology (PCAST). Indeed, this report made several recommendations on how climate science can support the provision of information about future risks from extreme weather and highlight the urgent need for high-resolution simulations to improve predictions of extreme weather events and guide risk management strategies. More specifically, the report recognized that high-resolution simulations, in the range of 10 to 25 km horizontal resolution, would capture extreme events more accurately than typical low-resolution (approximately 100 km) climate projections, and it goes on to recommend "a focused federal effort to provide estimates of the risk that a weather event of a given severity will occur in any location and year between now and mid-century". Our 10-member CESM-HR ensemble is able to meet some of the key aspects of this PCAST report.

The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke & Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).

The CESM-HR ensemble experimental design follows a similar approach as the CESM LENS1 large ensemble. We started with a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions. The first ensemble member is branched at year 250 of the PI-CTRL simulation and then integrated forward from year 1850 to 2100 (Figure 1). Ensemble members 2-10 are subsequently started from the year 1920 of ensemble member 1 and integrated forward to 2100 (Figure 1). Spread in the ensemble is generated by applying round-off level perturbations in the atmospheric potential temperature initial conditions for members 2-10. All 10 members use the same specified external climate forcing. Following the CMIP5 protocol for the Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, historical forcing is used from 1920 to 2005 followed by the representative concentration pathway 8.5 (RCP 8.5) forcing from 2006 to 2100. RCP 8.5 is a high-emissions scenario and is frequently referred to as the "business as usual" scenario. It refers to the concentration of carbon that delivers global warming at an average of 8.5 W/m^2 across the planet by 2100. All 10 members produce a warming of approximately 4.5K at the end of 2100 in response to the applied historical and RCP 8.5 external forcing (Figure 1). The warming produced by CESM-HR is consistent with the warming from the standard low-resolution (approximately 1 degree) version of the model. The rate of warming simulated by CESM-HR over the observed period agrees very well with the observed rate of warming derived from the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (Figure 1).

Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Climate variations on seasonal-to-decadal (S2D) timescales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales an invaluable tool for policymakers and stakeholders. Such variations modulate the likelihood and intensity of extreme weather events including, tropical cyclones (TCs), heat waves, winter storms, atmospheric rivers (ARs), and floods, which have all been associated with (1) increases in human morbidity and mortality rates; (2) severe impacts on agriculture, energy use, and industrial activity; and (3) economic costs in the billions of dollars. Changes in prevailing climate patterns are also responsible for prolonged droughts, which can have profoundly negative effects on large segments of the world population. Enhancing our foreknowledge of climate variability on S2D time scales and understanding its influence on extreme weather events could help mitigate negative impacts on human and biological populations, making climate predictions an exceptionally important climate and social science frontier.

Over the past six years, our research team consisting of scientists at Texas A and M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed an unprecedented 10-member ensemble of Community Earth System Model (CESM) historical and future climate simulations at a TC-permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR). This CESM-HR ensemble was completed as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". This ensemble is particularly timely, following the April 2023 report entitled "Extreme Weather Risk in a Changing Climate: Enhancing Prediction and Protecting Communities" from the U.S. President's Council of Advisors on Science and Technology (PCAST). Indeed, this report made several recommendations on how climate science can support the provision of information about future risks from extreme weather and highlight the urgent need for high-resolution simulations to improve predictions of extreme weather events and guide risk management strategies. More specifically, the report recognized that high-resolution simulations, in the range of 10-25km horizontal resolution, would capture extreme events more accurately than typical low-resolution (approximately 100km) climate projections, and it goes on to recommend "a focused federal effort to provide estimates of the risk that a weather event of a given severity will occur in any location and year between now and mid-century". Our 10-member CESM-HR ensemble is able to meet some of the key aspects of this PCAST report.

The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al. 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al. 2012; Smith et al. 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al. 2011).

The CESM-HR ensemble experimental design follows a similar approach as the CESM LENS1 large ensemble. We started with a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions. The first ensemble member is branched at year 250 of the PI-CTRL simulation and then integrated forward from year 1850 to 2100 (Figure 1). Ensemble members 2-10 are subsequently started from the year 1920 of ensemble member 1 and integrated forward to 2100 (Figure 1). Spread in the ensemble is generated by applying round-off level perturbations in the atmospheric potential temperature initial conditions for members 2-10. All 10 members use the same specified external climate forcing. Following the CMIP5 protocol for the Coupled Model Intercomparison Project phase 5 (CMIP5) experiments, historical forcing is used from 1920 to 2005 followed by the representative concentration pathway 8.5 (RCP 8.5) forcing from 2006 to 2100. RCP 8.5 is a high-emissions scenario and is frequently referred to as the "business as usual" scenario. It refers to the concentration of carbon that delivers global warming at an average of 8.5 W/m^2 across the planet by 2100. All 10 members produce a warming of approximately 4.5K at the end of 2100 in response to the applied historical and RCP 8.5 external forcing (Figure 1). The warming produced by CESM-HR is consistent with the warming from the standard low-resolution (approximately 1 degree) version of the model. The rate of warming simulated by CESM-HR over the observed period agrees very well with the observed rate of warming derived from the Goddard Institute for Space Studies (GISS) Surface Temperature Analysis (Figure 1).

Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Over the past six years, our research team consisting of scientists at Texas A&M University (TAMU) and the U.S. National Science Foundation National Center for Atmospheric Research (NSF NCAR) has made major breakthroughs in advancing high-resolution global climate modeling and prediction. We have completed several thousand years of climate simulations at a tropical cyclone (TC) permitting and ocean-eddy-rich resolution (hereafter simply referred to as CESM-HR) as part of our NSF-funded project entitled "Understanding the Role of MESoscale Atmosphere-Ocean Interactions in Seasonal-to-Decadal CLImate Prediction (MESACLIP)". Among others, we completed a 500-year preindustrial control (PI-CTRL) simulation forced by a perpetual climate forcing that corresponds to the year 1850 conditions and a 10-member ensemble of historical and future transient climate simulations.

The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke & Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).

Here we release the nominal 1 degree low-resolution (LR) equivalent simulations based on the same CESM1.3 code base and using the same CAM5 Spectral Element (SE) dycore used in CESM-HR to permit an as-clean-as-possible comparison of the respective LR and HR simulations. CESM LR uses a nominal 1 degree grid in all its components.

Citation: The two papers linked below are the most appropriate references for these simulations. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2024) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre-industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. It also introduces the corresponding CESM LR experiments. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

Current predictions and projections of future sea-level changes are based on Coupled Model Intercomparison Project (CMIP) class climate model simulations. Although this class of models is capable of simulating global sea-level rise and its basic spatial patterns, they are unable to robustly and accurately predict or project future regional and local sea-level changes because of their limitations in representing complex coastline and bathymetry features and regional ocean circulations with their coarse (approximately 100 km) horizontal resolutions. More specifically, sea-level changes within the Gulf of Mexico are closely linked to changes in the Loop Current and its eddies, which cannot be resolved by these CMIP-class models.

To address this fundamental issue, we have completed two projections with the Community Earth System Model (CESM) at a Tropical Cyclone-permitting and ocean-mesoscale-eddy-rich horizontal resolution (hereafter simply referred to as CESM-HR). The CESM-HR configuration is based on an earlier CESM version, CESM1.3, with many additional modifications and improvements. CESM-HR uses a 0.25 degree grid in the atmosphere and land components and a 0.1 degree grid in the ocean and sea-ice components. The primary reason for using an older model version, instead of the latest CESM2, is that CESM2 does not support a high-resolution version per the decision by the CESM Scientific Steering Committee. The component models within CESM1.3 are the Community Atmosphere Model version 5 (CAM5; Neale et al., 2012), the Parallel Ocean Program version 2 (POP2; Danabasoglu et al., 2012; Smith et al., 2010), the Community Ice Code version 4 (CICE4; Hunke and Lipscomb, 2008), and the Community Land Model version 4 (CLM4; Lawrence et al., 2011).

Following the protocol for the CMIP phase 5 (CMIP5) experiments, the representative concentration pathway 2.6 (RCP 2.6) and representative concentration pathway 4.5 (RCP 4.5) were used to force the model from 2006 to 2100. RCP 2.6 represents a pathway where greenhouse gas emissions are strongly reduced. This scenario is a so-called "peak" scenario, which means it shows a level of radiative forcing by greenhouse gas emissions peaking by mid-century then returning to 2.6 W/m^2 by 2100. RCP 4.5 represents a stabilization scenario, which means the radiative forcing level stabilizes at 4.5 W/m^2 before 2100 by employing of a range of technologies and strategies for reducing greenhouse gas emissions. This CESM-HR ensemble was completed as part of our National Academy of Sciences (NAS) funded project entitled "Improving Prediction and Projection of Gulf of Mexico Sea-Level Changes Using Eddy-Resolving Earth System Models (iPOGS)". This effort is complementary to the 10-member ensemble of CESM-HR historical and future (with RCP 8.5 forcing) climate simulations produced by our National Science Foundation (NSF) funded project entitled "Understanding the role of mesoscale atmosphere-ocean interactions in seasonal-to-decadal climate prediction (MESACLIP)". The RCP 2.6 and 4.5 simulation starts at the end of the member #3 of the 10-member ensemble of historical simulation from MESACLIP, enabling the exploration of future projections associated with varying levels of mitigation and future greenhouse gas emissions. For example, Figure 1 shows the global-mean dynamical sea level (DSL) from simulations under different forcings. The stronger warming associated with the RCP 8.5 forcing results in an additional 10 cm rise in global-mean DSL by 2100 compared to that of the RCP 6.0 ensemble.

Citation: The two papers linked below are the most appropriate references for the CESM-HR ensemble. To cite the dataset, use Chang et al. (2025). We ask that you also cite the dataset itself using the reference Castruccio et al. (2025) in any documents or publications using these data. Chang et al. (2020) describes the initial CESM-HR simulations, including the 500-year pre- industrial control simulation and the first 250-year historical and future climate simulation from 1850 to 2100. We would also appreciate receiving a copy of the relevant publications. This will help us to justify keeping the data freely available online in the future. Thank you!

In the next generation of the Community Atmosphere Model (CAM7), the model top will be raised and the vertical resolution will be increased. The model top will be approximately 80 km (compared to 40 km in older generations), and the grid spacing in the free troposphere and lower stratosphere will be reduced to about 500 m compared to around 1137m in older generations. In addition to this, extra levels will be added to the boundary layer and the lowest model level will be lowered. Overall, this "mid-top" version of CAM7 will have 93 levels. However, many other changes will also be present in CAM7 such as physics updates and the new spectral element dynamical core, making it challenging to identify the role of this enhanced resolution in changes between CAM7 and CAM6.

This dataset consists of a suite of simulations that use CAM6 physics and the finite volume dynamical core, but with CAM7's grid except for the changes to the levels in the boundary layer i.e., an 83 level model. The boundary layer levels are not changed because once those are changed, some additional tuning of the physical parameterizations is needed precluding a clean comparison and identification of the impact of vertical resolution. Only minimal changes to CAM6 physics have been applied to these simulations; the non-orographic gravity wave drag scheme was turned on, the upper boundary condition was changed such that any remaining gravity wave momentum flux is deposited at the model lid, and some minor tuning of the gravity wave drag settings was also performed to optimize the behavior of the QBO. These simulations can, therefore, be compared with existing CAM6 simulations to identify the impacts of this raising of the model lid and change to the resolution of the free troposphere and lower stratosphere. These simulations have an internally generated QBO and a relatively good representation of the stratospheric polar vortices and can be used to explore climate variability and change in the presence of those features.

The Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection simulations (ARISE-SAI-1.5) utilize a moderate emission scenario, introduce stratospheric aerosol injection at approximately 21 km in year 2035, and keep global mean surface air temperature near 1.5C above the pre-industrial value.

CESM2 (WACCM6) global output from all model components (atmosphere, ice, land, ocean) on monthly, daily and sub-daily frequencies. All atmospheric data is on the original CESM2 (WACCM6) grid (0.9 by 1.25 degrees). All data is in time-series, NetCDF format.

More details about this dataset (including information on reference simulations) can be found on the ARISE-SAI-1.5 CESM Community Project page linked below under Related Resources.

The relative importance of radiative feedbacks and emissions scenarios in controlling surface warming patterns is challenging to quantify across model generations. We analyze three variants of the Community Earth System Model (CESM) with differing equilibrium climate sensitivities (ECS) under identical CMIP5 historical and high-emissions scenarios. CESM1, our base model, exhibits Arctic-amplified warming with the least warming in the Southern Hemisphere middle latitudes. A variant of CESM1 with enhanced extratropical shortwave cloud feedbacks shows slightly increased late-21st Century warming at all latitudes. In the next-generation model, CESM2, global-mean warming is also slightly greater, but the warming is zonally redistributed in a pattern mirroring cloud and surface albedo feedbacks. However, if the nominally equivalent CMIP6 scenario is applied to CESM2, the redistributed warming pattern is preserved, but global-mean warming is significantly greater. These results demonstrate how model structural differences and scenario differences combine to produce differences in climate projections across model generations.

The CESM PlioMIP2 project, completed by Bette Otto-Bliesner, Ran Feng, and Esther Brady, is a set of published simulations contributing to Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) and Climate Model Intercomparison Project 6 (CMIP6). These simulations are carried out with three consecutive, standard versions of NCAR family models: CCSM4, CESM1.2 and CESM2, and feature the same boundary conditions derived from reconstructions by Pliocene Research, Interpretation and Synoptic Mapping project phase 4 (PRISM4), following the PlioMIP2 protocol. In addition, preindustrial runs with the same models, branched from the published preindustrial simulations, are also included for comparison purpose.

All simulations are performed with the atmosphere-ocean-land-sea ice coupled model configuration at the nominal 1-degree latitude/longitude for all components. Terrestrial biogeochemical carbon-nitrogen (CN) cycling is active in all simulations. Precursor land only spin-up simulations were carried out to derive initial conditions for the terrestrial biogeochemical components.

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.nc

A detailed variable list 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.

Atmospheric River Tracking Method Intercomparison Project (ARTMIP) Tier 2 Paleoclimate source data and developer catalogues. Each ARTMIP method/algorithm (named by the developer) submits a catalogue comprised of 0's (no AR exists) or 1's (yes AR exists) for each time slice, for each grid point, using output from CESM2 paleoclimate simulations for PreIndustrial, orbital forcing comparable to the Holocene at 10ka, and greenhouse forcing comparable to 21ka. LGM (Last Glacial Maximum). Each simulation has 30 years of data. Derived quantities required for algorithms, such as IVT or IWV, were computed by the ARTMIP project so that all methods use the same data.

This dataset contains subseasonal-to-seasonal (S2S) hindcasts with CESM2 in which certain components used climatological data.

This dataset includes two MJO case S2S hindcasts starting with a QBO neutral state. For each case, the pre-control experiment follows the standard CESM2 S2S hindcast protocol as free runs, while the QBO experiments are conducted with the stratosphere zonal means nudged to the sum of pre-control states and the QBO anomalies for the selected variable such as zonal wind, temperature, or both. The dataset is used to investigate the QBO impacts on MJO case hindcasts.

Experiments using prescribed SST and ice forcing within CAM6 using the CESM2 (Community Earth System Model 2).

Note: The Tropical AMIP have a temporal range of 1880-2019, and the Global AMIP span 1880-2021.

These data are from a series of simulations documenting model developments that have been included in Community Land Model version 5 (CLM5) which is the default land component for the Community Earth System Model version 2 (CESM2). These data were generated to compare CLM5 to prior versions of CLM (CLM4 and CLM4.5) in land-only mode forced with several historical forcing datasets including GSWP3v1, CRUNCEPv7, and WATCH. Data include simulations with LAI prescribed from satellite phenology (SP) and simulations with prognostic vegetation state and active biogeochemistry (BGC). All simulations were completed at a resolution of 0.9 degrees latitude by 1.25 degrees longitude. Additional simulations were conducted to evaluate model sensitivities to land use and land cover change, active crop management, elevated concentrations of atmospheric CO2, and nitrogen enrichment. Raw data were post processed to generate single variable time series. In addition to standard monthly output, these data also include PFT-level, daily, and hourly data available for selected fields and simulations. Additional analyses were made using the CLM diagnostics package and International Land Model Benchmarking (ILAMB) package and available at the linked web sites.

Stratospheric Aerosol Geoengineering experiments have been produced by CESM2 (WACCM6). Two experiments have been performed following the CMIP6 WACCM6 SSP5-34-OS experiment as a baseline scenario with stratospheric sulfur injections to limit global warming to 1.5C or 2.0C above 1850-1900 conditions, called Geo SSP5-34-OS 1.5 and Geo SSP5-34-OS 2.0, respectively. A third experiment has been performed that follows CMIP6 WACCM6 SSP5-85 as a baseline and to limit global warming to 1.5 degrees C, called Geo SSP5-85 1.5. Sulfur injections were applied at four predefined latitudes, 30N, 15N, 15S, and 30S, to reach three surface temperature targets: global mean temperature, and inter-hemispheric and pole-to-equator temperature gradients using a feedback algorithm. All experiments have two ensemble members. More details can be found in the reference paper.

This dataset contains subseasonal-to-seasonal (S2S) hindcasts with CESM2 that were carried out as a community project and with community analysis in mind. These forecasts consist of 45-day long runs initialized every Monday from 1999 to 2019, 11 ensemble members. Output includes atmospheric, land, ocean and sea-ice variables (many requested by the community). These simulations are in support of the work done by the newly formed Earth System Predictability Working Group within CESM.

These CAM6 Data Assimilation Research Testbed (DART) Reanalysis data products are designed to facilitate a broad variety of research using NCAR's CESM2 models, ranging from model evaluation to (ensemble) hindcasting, data assimilation experiments, and sensitivity studies. They come from an 80 member ensemble reanalysis of the global troposphere and stratosphere using DART and CAM6 from CESM2.1. The data products represent the actual states of the atmosphere during 2 recent decades at a 1 degree horizontal resolution and 6 hourly frequency. Each ensemble member is an equally likely description of the atmosphere, and is also consistent with dynamics and physics of CAM6. Visit DART Reanalysis for details.

The Generalized Analog Regression Downscaling method Large Ensemble (GARD-LENS) dataset is comprised of daily precipitation, mean temperature, and temperature range over the Contiguous U.S., Alaska, and Hawaii at 12 km, 4 km, and 1 km resolutions, respectively. GARD-LENS downscales three CMIP6 global climate model large ensembles, CESM2, CanESM5, and EC-Earth3, totaling 200 ensemble members. GARD-LENS is the first downscaled SMILE (single model initial-condition large ensemble), providing information about the role of internal climate variability at high resolutions. GARD LENS uses GMET as a training dataset for the period 1980-2014, although Hawaii GMET data is only available for 1990-2014. The total dataset consists of 200 ensemble member files per region per variable (e.g., 200 files for t_mean for CONUS), for a total of 1800 files and a total dataset size of roughly 12 TB.

The 150-year record of this large ensemble dataset provides ample data for assessing trends and extremes and allows users to robustly assess internal variability, forced climate signals, and time of emergence at high resolutions. As the need for high resolution, robust climate datasets continues to grow, GARD-LENS will be a valuable tool for scientists and practitioners who wish to account for internal variability in their future climate analyses and adaptation plans.

The CESM Large Ensemble Project is a publicly available set of climate model simulations intended for advancing understanding of internal climate variability and climate change. All simulations are performed with the nominal 1-degree latitude/longitude version of the Community Earth System Model version 1 (CESM1) with CAM5.2 as its atmospheric component. The Large Ensemble Project includes a 40-member ensemble of fully-coupled CESM1 simulations for the period 1920-2100. Each member is subject to the same radiative forcing scenario (historical up to 2005 and RCP8.5 thereafter), but begins from a slightly different initial atmospheric state (created by randomly perturbing temperatures at the level of round-off error). The Large Ensemble Project also includes a set of multi-century control simulations with the atmosphere, slab-ocean, and fully-coupled versions of CESM1 under pre-industrial (1850) radiative forcing conditions (2600 years, 900 years and 1800 years in length, respectively). Details of these model simulations may be found in Kay et al. (2015).

In addition to the simulations above the CESM1 Single Forcing experiments are also available in this archive. The CESM1 Single Forcing Large Ensemble Project is a set of climate model simulations that are useful for addressing the individual roles of anthropogenic aerosols, greenhouse gases and land-use / land-cover in historical and future climate change. These simulations use the same model, forcing configuration and initialization protocol as the CESM1 Large Ensemble Project, but keep either industrial aerosols (AER), biomass burning aerosols (BMB), greenhouse gases (GHG) or land-use / land-cover (LULC) conditions fixed at 1920 while all other external anthropogenic and natural forcing factors evolve following historical and future (RCP8.5) scenarios. There are 3 sets of ensembles: XGHG (20 members, 1920-2080), XAER (20 members, 1920-2080), and XBMB (15 members, 1920-2029). All members are branched from the first member of the all forcing CESM1 Large Ensemble on January 1, 1920 by applying a small (order of 10-14 K) random noise perturbation to their initial atmospheric temperature fields. The impact of the withheld forcing factor can be deduced by subtracting the ensemble-mean of each X ensemble from the ensemble-mean of the original all forcing CESM1 Large Ensemble. Details of these three ensembles are provided in Deser et al. (2020). A 3 member ensemble (named AAER) that is complementary to the XAER has also been performed as discussed in Simpson et al. (2023). These simulations begin in 1850 and evolve under ONLY time varying industrial aerosols with the other forcings held fixed at 1850's values.