Deep Purple Payload Qualifies for NASA Launch, Could Provide New Method for Real-Time Space-Domain Awareness
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This special issue of Nuclear Technology contains full-length, peer-reviewed papers describing the design work leading up to and the results of the Kilowatt Reactor Using Stirling TechnologY (KRUSTY) test. KRUSTY was the centerpiece of the National Aeronautics and Space Administration (NASA) Kilopower Project to design, build, and test a space nuclear reactor. This test was the first such test since the end of the Space Nuclear Auxiliary Power (SNAP) project at the end of the 1960s. In this issue, the introduction paper presents the goals of the Kilopower Project and the potential missions this reactor concept could serve in NASA. Kilopower was intended to serve both human exploration needs on planetary surfaces as well as science needs for deep-space exploration. The design work for the experiment by Poston and the power conversion development by Gibson present the pre-work required to perform the eventual KRUSTY test. A paper on regulatory analysis follows, to show the path used to gain approval of the proposed experiment. Then, the early zero-power critical experiments are presented by Sanchez and Grove. These experiments were essential data used to enhance model predictions prior to the high-temperature test. Next, Poston presents the three experiments (warm criticals) that increase the temperature in an incremental fashion prior to the final experiment. These experiments were used to achieve final regulatory approval of the final high-temperature experiment. The last paper by Poston presents the results of the steady-state and transient testing of the reactor at full power and at the design temperature. These results show that the reactor design and as-built experiment met all of the requirements that NASA had developed for the system. Any experiment of this magnitude was accomplished only because of the hard work and dedication of a large number of people at multiple institutions, including the NASA Glenn Research Center, NASA Marshall Space Flight Center, Y-12 National Security Site, Los Alamos National Laboratory, and the Nevada National Security Site prime contractor (formerly National Security Technologies and now the Mission Support and Test Services). The project was jointly funded by the Space Technology Mission Directorate at NASA and the Criticality Safety Program at the National Nuclear Security Administration (NNSA). A special thanks to Jerry McKamy and Angela Chambers at the NNSA and Lee Mason and Don Palac at NASA for their support and guidance. For the authors and multitude of staff that performed this work, the passion for space nuclear reactors was the key to making this experiment a reality.
The scientific focus here is interagency collaboration to support a National Aeronautics and Space Administration (NASA)-sponsored 2023 field campaign: Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS). IMPACTS objectives are to provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; study how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and improve snowfall remote-sensing interpretation and modeling to significantly advance predictive capabilities. The relevance to The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility's mission was to support the Interagency Council for Advancing Meteorological Services (ICAMS)’ objectives to enhance communication and coordination, and promote sharing, within and across agencies. NASA therefore requested to borrow ARM’s two-dimensional stereo probe (2DS) for possible use during the 2023 IMPACTS project. Additionally, this use of the 2DS could improve understanding of ARM 2DS measurements collected on previous field campaigns. The plan was to have the 2DS available for possible backup deployment on the NASA Lockheed Orion P-3 aircraft during the 2023 IMPACTS field project. NASA has a 2DS probe and the ARM 2DS is a hot swappable probe in case the project's 2DS fails. The 2DS is a critical probe and we had issues during a 2022 field project that prevented us from obtaining 2DS data on several flights. Hence, we wanted a hot swappable 2DS on stand-by. We have a data acquisition system, along with a backup data acquisition system for the 2DS, so we only needed the 2DS probe. David Delene was responsible for the use of the 2DS on the NASA P-3 aircraft. He has experience deploying the 2DS on several aircraft, including previously on the NASA P-3 in 2022. The team ensured that the aircraft wiring and deployment of the 2DS were completed correctly for the ARM 2DS.
Through a partnership between the U.S. National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA), this field campaign demonstrated first-of-its-kind hyperspectral microwave airborne measurements (Conical Scanning Millimeter-wave Imaging Radiometer [CoSMIR-H]). It was complemented by other passive (infrared, visible) and active (lidar) sensors onboard the NASA ER-2 aircraft. Serving as a future NASA planetary boundary-layer (PBL) mission prototype, the Westcoast and Heartland Hyperspectral Microwave Intensive Experiment (WH 2 yMSIE, formerly WHyMSIE) aimed to capture a wide variety of thermodynamic, moisture, and PBL regimes across a variety of surface types. The intensive operating period of the campaign spanned from October 22, 2024, through November 15, 2024, and included a large network of collaborators.
NASA and DOE have been developing concepts for lunar and Mars Fission Surface Power (FSP) systems for decades and have considered many different technologies and system variations. In 2023, three contractor teams completed Phase 1 conceptual design studies on a 40 kWe lunar FSP system in response to a modest set of NASA requirements and goals. A government team consisting of NASA Glenn Research Center (GRC), Los Alamos National Laboratory (LANL), and Idaho National Laboratory (INL) was formed to develop an independent design approach that adhered to the same requirements and goals posed to the contractor teams. GRC provided expertise, analysis, and design decisions for the power conversion, heat rejection, power management & distribution (PMAD), and mission integration. LANL and INL provided expertise, analysis, and design decisions for the reactor and shielding. The goal of the government study was to develop representative concepts that could be used in NASA architecture studies, guide government technology investments, and inform Phase 2 requirements definition. This paper provides a summary of the key technology options, system-level trades, and mission-level concept-of-operations.
The latest generation of geostationary satellites provide Earth observations similar to widely used polar-orbiting sensors but at intervals as frequently as every 5–10 min, making them ideal for studying the diurnal dynamics of land–atmosphere interactions. The NASA Earth Exchange (NEX) group created the GeoNEX datasets by collating data from several geostationary platforms, including GOES-16/17/18, Himawari-8/9, and GK-2A, and placing them on a common grid to facilitate use by the Earth science community. Here, we document the GeoNEX Coincident Ground Observations (GeCGO) dataset for terrestrial ecosystem studies and provide examples for its use. Currently, GeCGO provides GOES-16 Advanced Baseline Imager (ABI) data over a 10 km × 10 km area surrounding 1586 network sites across the Americas. GeCGO makes it easy to compare the time series of geostationary data with the diurnal ground observations, including carbon/water fluxes and aerosol optical depth, and is extensible to other regions. We also develop GeoNEXTools to facilitate analyses that require both GeoNEX data and other NASA satellite data. The objectives of this paper are to introduce GeCGO and GeoNEXTools and demonstrate their applications. First, we describe the details of GeCGO and GeoNEXTools. Second, we explain how GeCGO can be integrated with other satellite data. Finally, we showcase comparisons between GeCGO and observations from three ground-based networks. GeCGO is available at https://doi.org/10.25966/y5pe-xp41 (Hashimoto et al., 2025).
Aircraft electric fields from NASA's Lightning Instrument Package (LIP) were coupled with other airborne and ground-based, and in situ measurements to understand electrification in winter clouds that did not produce lightning. The measurements were made during seven research flights by a NASA ER-2 during the 2020 Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Observed total electric field magnitudes were as high as 80 V m -1 and variability in the electric field was observed along the flight path of the ER-2, indicating horizontal and/or vertical inhomogeneity in the cloud's electrical structure. X-band airborne radar data indicated 20-dBZ echo tops above 5 km in regions where electrification exceeded 10 V m -1 . In these regions, 85-GHz brightness temperatures (TB) from an airborne radiometer were lower than 265 K, with the lowest T B (~210 K) associated with ice scattering collocated with the strongest electric fields. In situ microphysical measurements from the NASA P-3 aircraft on February 7 indicated that regions near strong electric field contained supercooled water, rimed ice hydrometeors, ice water p- content as high as 1 g m -3 , liquid water content as high as 0.15 g m -3 , and supersaturation as high as 3.5%. Furthermore, these observations support the role of mixed phase microphysics in the generation of electric fields in clouds. In three case studies, ground based S-band polarimetric radar observed depolarization streaks in differential reflectivity near areas where the strongest electrification was observed. This observation reinforces the utility of depolarization streaks to identify areas of electrification prior to lightning occurrence.
NASA’s Space Technology Mission Directorate (STMD) intends to demonstrate a 10 kWe fission surface power (FSP) system on the surface of the Moon as part of a Capability Demonstration Mission. STMD tasked a joint NASA-DOE team to ‘outline an FSP reactor concept that can be readied for 2027 launch,’ and serves ‘as a pathfinder for future power modules for Mars.’ Tables 1 and 2 respectively list FSP performance requirements and design guidance provided for the study. DOE is the leading agency for the reactor module, reactor controls and radiation shielding, and shares joint responsibility for the overall FSP system. This report summarizes an analysis of alternative reactor classes and shielding configurations carried out by the DOE national laboratories. Representative reactor and shielding configurations were based on heritage and are in alignment with the industry initiatives. This report presents no recommendations on the appropriate choice of fuel or class of reactor that NASA should pursue. Instead the focus here is to provide a summary and findings of analyses carried out by DOE national laboratory personnel.
As King et al succinctly write, “Collision between the Earth and small objects in the solar system are known to occur regularly, and can result in extinction-level events at their most energetic or more commonly widespread loss of life or economic destruction even for relatively low-energy impacts.” Currently, the JPL Sentry System and the NASA NEO Surveyor mission track, identify, and monitor potential asteroid threats. The JPL Sentry System4 is an automated collision monitoring system which scans the current asteroid catalog for potential impact trajectories with Earth. A 2017 study led by P. Tricarico titled “The near-Earth asteroid population from two decades of observations” analyzes the combined observations of nine leading asteroid surveys. The NASA NEO Surveyor mission seeks to identify 90% of near-Earth objects (NEO) with diameters greater than 140 meters (460 feet) within 10 years. The NEO Surveyor combines data from two infrared imaging detectors to measure NEO size, composition, shape, rotational state, and orbits. Recently, the NASA Double Asteroid Redirection Test (DART) mission successfully altered the orbit of asteroid moon Dimorphos in 2022. This demonstrated that orbit alteration is possible. Thus, collisions between the Earth and asteroids are both likely and demonstrate potential for great harm. There is ongoing work to identify, catalog, and track potential threats. However, when a threat is identified there is not yet a system in place to target the threatening asteroid and defend the planet from potentially existential threats. Building on the DART Mission, we explore a planetary defense system to mitigate asteroid threats.
Here we present the first results of our ongoing project conducting simultaneous multiwavelength observations of flares on nearby active M dwarfs. We acquired data of the nearby dM3.5e star EV Lac using five different observatories: NASA’s Transiting Exoplanet Survey Satellite (TESS), NASA’s Neil Gehrels Swift Observatory (Swift), NASA’s Neutron Interior Composition Explorer (NICER), the University of Hawaii 2.2-meter telescope (UH88), and the Las Cumbres Observatory Global Telescope (LCOGT) Network. During the ~25 days of TESS observations, we acquired three simultaneous UV/X-ray observations using Swift that total ~18 ks, 21 simultaneous epochs totaling ~98 ks of X-ray data using NICER, one observation (~3 hr) with UH88, and one observation (~3 hr) with LCOGT. We identified 56 flares in the TESS light curve with estimated energies in the range log E T (erg) = (30.5–33.2), nine flares in the Swift UVM2 light curve with estimated energies in the range log E UV (erg) = (29.3–31.1), 14 flares in the NICER light curve with estimated minimum energies in the range log E N (erg) = (30.5–32.3), and 1 flare in the LCOGT light curve with log E L (erg) = 31.6. We find that the flare frequency distributions (FFDs) of TESS and NICER flares have comparable slopes, β T = -0.67 ± 0.09 and β N = - 0.65 ± 0.19, and the FFD of UVOT flares has a shallower slope (β U = -0.38 ± 0.13). Furthermore, we do not find conclusive evidence for either the first ionization potential (FIP) or the inverse FIP effect during coronal flares on EV Lac.
Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June-October), aerosol particles reaching 3-5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ~350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ~100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.
To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.
To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.
FG Virginis is a δ Scuti variable star that was the target of several ground-based multisite photometric campaigns from 1992 to 2004. Over 75 pulsation frequencies were detected (Breger et al., Astron. Astrophys., 2005, 435, 955–965), more than for any other δ Sct star before the era of space photometry. FG Vir was observed for 52 days in 30-minute cadence photometry by the NASA Kepler spacecraft K2 mission in 2016, and for 23 days in 2-minute cadence photometry by the NASA TESS spacecraft in 2021. We present light curves and amplitude spectra obtained from these space missions. We find around 30 significant frequencies in the K2 data, and more than 100 significant frequencies in the TESS data. There is good correspondence between the first 10 or so highest-amplitude modes found in the K2 and TESS data and those found from the ground-based multisite campaigns, although the amplitude order is slightly different, indicating some stability in mode frequencies and amplitudes spanning 20 years. However, the 9th highest-amplitude mode of Breger et al. has moved down considerably in amplitude rank, while the 35th highest-amplitude mode has moved up to near the top ten as seen in both the K2 and TESS data. We find several low frequencies between 0.3 and 3 cycles per day in the TESS data that were not detected using the ground-based data. If low-frequency pulsations are confirmed, FG Vir would be classified as a δ Sct/γ Dor hybrid variable star. We also review stellar model results and some of the challenges for asteroseismology for this well-studied δ Sct star.
National Aeronautics and Space Administration (NASA) uses Radioisotope Power Systems (RPS) to power deep-space and planetary explorations such as Cassini-Huygens, Galileo, New Horizons, Mars Science Laboratory—Curiosity, and most recently Mars 2020--Perseverance. The Space Nuclear Power and Isotope Technologies (SNPIT) division, at Idaho National Laboratory (INL), fuels, tests, and delivers the RPS to ensure it can provide the electrical power needed to complete mission objectives. Some space crafts have instrumentation specifically designed to study the subject’s magnetic field or may have instruments that can be affected by magnetic fields produced by the RPS. Analyzing and measuring the RPS’s magnetic fields ensures the required thresholds are not exceeded and accurate data can be collected for the mission. Magnetics testing provides numerical values of the RPS’s magnetic field. During Magnetics testing at INL, the RPS is placed on a resistive load to simulate actual spacecraft load characteristics (voltage and current). During this simulation, magnetometers are used to measure the magnetic field of the RPS. Raw data is collected and then analyzed to ensure the field created by the RPS is below NASA thresholds or that the magnitude of the field is accounted for to ensure mission success.
The Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) is a NASA mission to characterize aerosol–cloud interactions over the western North Atlantic Ocean (WNAO). Such characterization requires understanding of life cycle, composition, transport pathways, and distribution of aerosols over the WNAO. This study uses the GEOS-Chem model to simulate aerosol distributions and properties that are evaluated against aircraft, ground-based, and satellite observations during the winter and summer field deployments in 2020 of ACTIVATE. Transport in the boundary layer (BL) behind cold fronts was a major mechanism for the North American continental outflow of pollution to the WNAO in winter. Turbulent mixing was the main driver for the upward transport of sea salt within and ventilation out of BL in winter. The BL aerosol composition was dominated by sea salt, which increased in the summer, followed by organics and sulfate. Aircraft in situ aerosol measurements provided useful constraints on wet scavenging in GEOS-Chem. The model generally captured observed features such as continental outflow, land–ocean gradient, and mixing of anthropogenic aerosols with sea salt. Model sensitivity experiments with elevated smoke injection heights to the mid-troposphere (versus within BL) better reproduced observations of smoke aerosols from the western US wildfires over the WNAO in the summer. Model analysis suggests strong hygroscopic growth of sea salt particles and their seeding of marine BL clouds over the WNAO (< 35° N). Future modeling efforts should focus on improving parameterizations for aerosol wet scavenging, implementing realistic smoke injection heights, and applying high-resolution models that better resolve vertical transport.
The rich history of observing system simulation experiments (OSSEs) does not yet include a well-established framework for using climate models. The need for a climate OSSE is triggered by the need to quantify the value of a particular measurement for reducing the uncertainty in climate predictions, which differ from numerical weather predictions in that they depend on future atmospheric composition rather than the current state of the weather. However, both weather and climate modeling communities share a need for motivating major observing system investments. Here, we outline a new framework for climate OSSEs that leverages the use of machine learning to calibrate climate model physics against existing satellite data. We demonstrate its application using NASA’s GISS-E3 model to objectively quantify the value of potential future improvements in spaceborne measurements of Earth’s planetary boundary layer. A mature climate OSSE framework should be able to quantitatively compare the ability of proposed observing system architectures to answer a climate-related question, thus offering added value throughout the mission design process, which is subject to increasingly rapid advances in instrument and satellite technology. Technical considerations include selection of observational benchmarks and climate projection metrics, approaches to pinpoint the sources of model physics uncertainty that dominate uncertainty in projections, and the use of instrument simulators. Community and policy-making considerations include the potential to interface with an established culture of model intercomparison projects and a growing need to economically assess the value-driven efficiency of social spending on Earth observations.
A neural network (NN) surrogate of the NASA GISS ModelE atmosphere (version E3) is trained on a perturbed parameter ensemble (PPE) spanning 45 physics parameters and 36 outputs. The NN is leveraged in a Markov Chain Monte Carlo (MCMC) Bayesian parameter inference framework to generate a second posterior constrained ensemble coined a “calibrated physics ensemble,” or CPE. The CPE members are characterized by diverse parameter combinations and are, by definition, close to top-of-atmosphere radiative balance, and must broadly agree with numerous hydrologic, energy cycle and radiative forcing metrics simultaneously. Global observations of numerous cloud, environment, and radiation properties (provided by global satellite products) are crucial for CPE generation. The inference framework explicitly accounts for discrepancies (or biases) in satellite products during CPE generation. We demonstrate that product discrepancies strongly impact calibration of important model parameter settings (e.g., convective plume entrainment rates; fall speed for cloud ice). Structural improvements new to E3 are retained across CPE members (e.g., stratocumulus simulation). Notably, the framework improved the simulation of shallow cumulus and Amazon rainfall while not degrading radiation fields, an upgrade that neither default parameters nor Latin Hypercube parameter searching achieved. Analyses of the initial PPE suggested several parameters were unimportant for output variation. However, many “unimportant” parameters were needed for CPE generation, a result that brings to the forefront how parameter importance should be determined in PPEs. From the CPE, two diverse 45-dimensional parameter configurations are retained to generate radiatively-balanced, auto-tuned atmospheres that were used in two E3 submissions to CMIP6.