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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

OCI Geolocation Evaluation and Refinement Using Landsat Control Points

The Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission is NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer, Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. The geolocation processing is performed for OCI using spacecraft navigation data and an instrument geometry model. To evaluate the geolocation accuracy for OCI and develop refinements to the processing methods, control point matching using Landsat data has been implemented as a step in the operational processing of OCI data at the Science Data Segment. This processing provides between 200 and 300 high-quality matchups per day with good global and geometric distribution, allowing rapid evaluation of the OCI geolocation accuracy. The results provided an early indication of the overall quality of the geolocation processing and of specific aspects needing improvement. A standard set of granules was identified to support rapid implementation and testing of geolocation refinements, and this approach has been highly successful in improving the geolocation processing accuracy to meet the science requirements. The evaluation will continue throughout the mission to ensure the ongoing accuracy of geolocation. This paper describes the control point matching methodology, the approach to development of the geolocation processing refinements, and the recent results.

PACE↗
DOE OSTI2016

THE HERSCHEL ORION PROTOSTAR SURVEY: SPECTRAL ENERGY DISTRIBUTIONS AND FITS USING A GRID OF PROTOSTELLAR MODELS

We present key results from the Herschel Orion Protostar Survey: spectral energy distributions (SEDs) and model fits of 330 young stellar objects, predominantly protostars, in the Orion molecular clouds. This is the largest sample of protostars studied in a single, nearby star formation complex. With near-infrared photometry from 2MASS, mid- and far-infrared data from Spitzer and Herschel , and submillimeter photometry from APEX, our SEDs cover 1.2–870 μ m and sample the peak of the protostellar envelope emission at ∼100 μ m. Using mid-IR spectral indices and bolometric temperatures, we classify our sample into 92 Class 0 protostars, 125 Class I protostars, 102 flat-spectrum sources, and 11 Class II pre-main-sequence stars. We implement a simple protostellar model (including a disk in an infalling envelope with outflow cavities) to generate a grid of 30,400 model SEDs and use it to determine the best-fit model parameters for each protostar. We argue that far-IR data are essential for accurate constraints on protostellar envelope properties. We find that most protostars, and in particular the flat-spectrum sources, are well fit. The median envelope density and median inclination angle decrease from Class 0 to Class I to flat-spectrum protostars, despite the broad range in best-fit parameters in each of the three categories. We also discuss degeneracies in our model parameters. Our results confirm that the different protostellar classes generally correspond to an evolutionary sequence with a decreasing envelope infall rate, but the inclination angle also plays a role in the appearance, and thus interpretation, of the SEDs.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Preliminary Error Budget for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) plans to observe climate change trends over decadal time scales to determine the accuracy of climate projections. The project relies on spaceborne earth observations of SI-traceable variables sensitive to key decadal change parameters. The mission includes a reflected solar instrument retrieving at-sensor reflectance over the 320 to 2300 nm spectral range with 500-m spatial resolution and 100-km swath. Reflectance is obtained from the ratio of measurements of the earth s surface to those while viewing the sun relying on a calibration approach that retrieves reflectance with uncertainties less than 0.3%. The calibration is predicated on heritage hardware, reduction of sensor complexity, adherence to detector-based calibration standards, and an ability to simulate in the laboratory on-orbit sources in both size and brightness to provide the basis of a transfer to orbit of the laboratory calibration including a link to absolute solar irradiance measurements. The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those in the IPCC Report. A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO Project will implement a spaceborne earth observation mission designed to provide rigorous SI traceable observations (i.e., radiance, reflectance, and refractivity) that are sensitive to a wide range of key decadal change variables, including: 1) Surface temperature and atmospheric temperature profile 2) Atmospheric water vapor profile 3) Far infrared water vapor greenhouse 4) Aerosol properties and anthropogenic aerosol direct radiative forcing 5) Total and spectral solar irradiance 6) Broadband reflected and emitted radiative fluxes 7) Cloud properties 8) Surface albedo There are two methods the CLARREO mission will rely on to achieve these critical decadal change benchmarks: direct and reference inter-calibration. A quantitative analysis of the strengths and weaknesses of the two methods has led to the recommended CLARREO mission approach. The project consists of two satellites launched into 90-degree, precessing orbits separated by 90 degrees. The instrument suite receiver on each spacecraft includes one emitted infrared spectrometer, two reflected solar spectrometers: dividing the spectrum from ultraviolet through near infrared, and one global navigation receiver for radio occultation. The measurements will be acquired for a period of three years minimum, with a five-year lifetime goal, enabling follow-on missions to extend the climate record over the decades needed to understand climate change. The current work concentrates on the reflected solar instrument giving an overview of its design and calibration approach. The calibration description includes the approach to achieving an SI-traceable system on orbit. The calibration overview is followed by a preliminary error budget based on techniques currently in place at the National Institute of Standards and Technology (NIST).

Thome, Kurtis↗
NASA NTRS2019

Deep Learning Emulation of Atmospheric Correction for Geostationary Sensors

New generation geostationary satellites make reflectance observations available at a continental scale with unprecedented spatiotemporal resolution and spectral range. Generating Earth monitoring products from these observations requires retrieval of the basic parameter, surface reflectance (SR), by atmospheric correction (AC). Algorithms for atmospheric correction, including Multi-Angle Implementation of Atmospheric Correction (MAIAC), are adapted for each sensor and are too computationally complex to be run in real time, relying instead on look-up tables with precomputed values. Machine learning methods, including convolutional neural networks, have demonstrated performance in learning complex, nonlinear mappings and extracting insight from high-dimensional remote sensing data. In this work, we present a deep learning emulator of MAIAC to retrieve both SR and cloud products. Using this adaptation of deep learning-based emulation to remote sensing, we demonstrate stable SR retrieval over a variety of land covers and viewing conditions and accurate cloud detection. Further, a comparison of computation time suggests emulation as a compelling alternative for expensive physical simulation, especially for applications benefited by near-real time data, such as agricultural management and disaster response.

Duffy, Kate↗
NASA NTRSDate not supplied

The Crustal Dynamics Data Information System (CDDIS) – Updates and Future Developments

As earth observing services and techniques have flourished, data and products have exponentially grown, like the proliferation of Global Navigation Satellite System (GNSS) stations capable of providing real-time data, Satellite Laser Ranging (SLR) stations shifting to kHz lasers, and Very-Long-Baseline Interferometry (VLBI)’s implementation of VLBI Global Observing System (VGOS) telescopes. The CDDIS is continually evolving to fulfill the new storage, quality check, and latency requirements that these changes bring, as well as meet new standards such as the shift toward FAIR and open science. These have shaped how the CDDIS develops new software and resources. Beginning next year, the CDDIS will begin to transition their data and products to the Amazon Web Services (AWS) cloud, beginning with DORIS data. This poster will highlight the CDDIS’s recently updated processing system, new data and products available, and future work.

Justine Woo↗
NASA NTRSDate not supplied

Standalone Hazard Evaluation and Refinement From Instrument Findings (S.H.E.R.I.F.)

The Standalone Hazard Evaluation From Instrument Findings or SHERIF is a set of novel algorithms and associated framework designed to support the generation of Digital Elevation Maps (DEMs) from multiple LiDAR scans and perform Hazard Detection (HD) and Safe Site Selection with minimal input from other onboard systems. SHERIF can employ several techniques to perform Point Cloud registration(PCR) on disparate LiDAR scans of a planetary surface to generate a DEM which evolves over the course of a trajectory, with a flow designed to enable robustness. The framework also supports a variety of Hazard Detection and Safe Site Selection algorithms which can be run on the evolving DEM being produced. SHERIF features a robust and modular construction, allowing the user a high degree of flexibility in selecting and implementing whichever PCR and HD/SSL algorithms they may prefer, while maintaining the data products and sensor independence of the core SHERIF framework. SHERIF was recently tested in a hardware in the loop simulation at NASA JSC.

Entry Descent and Landing Guidance Navigation Cont↗
DOE OSTI2017

OpenRBC: A Fast Simulator of Red Blood Cells at Protein Resolution

We present OpenRBC, a coarse-grained molecular dynamics code, which is capable of performing an unprecedented in silico experiment—simulating an entire mammal red blood cell lipid bilayer and cytoskeleton as modeled by multiple millions of mesoscopic particles—using a single shared memory commodity workstation. To achieve this, we invented an adaptive spatial-searching algorithm to accelerate the computation of short-range pairwise interactions in an extremely sparse three-dimensional space. The algorithm is based on a Voronoi partitioning of the point cloud of coarse-grained particles, and is continuously updated over the course of the simulation. The algorithm enables the construction of the key spatial searching data structure in our code, i.e., a lattice-free cell list, with a time and space cost linearly proportional to the number of particles in the system. The position and the shape of the cells also adapt automatically to the local density and curvature. The code implements OpenMP parallelization and scales to hundreds of hardware threads. It outperforms a legacy simulator by almost an order of magnitude in time-to-solution and >40 times in problem size, thus providing, to our knowledge, a new platform for probing the biomechanics of red blood cells.

Biophysics↗
DOE OSTI2021

Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.

consistent stream ordering↗
DOE OSTI2015

Toward Interactive Scenario Analysis and Exploration

As Modeling and Simulation (M&S) tools have matured, their applicability and importance have increased across many national security challenges. In particular, they provide a way to test how something may behave without the need to do real world testing. However, current and future changes across several factors including capabilities, policy, and funding are driving a need for rapid response or evaluation in ways that many M&S tools cannot address. Issues around large data, computational requirements, delivery mechanisms, and analyst involvement already exist and pose significant challenges. Furthermore, rising expectations, rising input complexity, and increasing depth of analysis will only increase the difficulty of these challenges. In this study we examine whether innovations in M&S software coupled with advances in ''cloud'' computing and ''big-data'' methodologies can overcome many of these challenges. In particular, we propose a simple, horizontally-scalable distributed computing environment that could provide the foundation (i.e. ''cloud'') for next-generation M&S-based applications based on the notion of ''parallel multi-simulation''. In our context, the goal of parallel multi- simulation is to consider as many simultaneous paths of execution as possible. Therefore, with sufficient resources, the complexity is dominated by the cost of single scenario runs as opposed to the number of runs required. We show the feasibility of this architecture through a stable prototype implementation coupled with the Umbra Simulation Framework [6]. Finally, we highlight the utility through multiple novel analysis tools and by showing the performance improvement compared to existing tools.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

AERACEPT (Aerosol Rapid Analysis Combined Entry Probe/sonde Technology): Enabling Technology for Missions to the Venus Clouds

AERACEPT (AErosol Rapid Analysis Combined Entry Probe/sonde Technology) is an early-stage technology allowing a single aeroshell body to act as both an entry vehicle and aerosol-sampling passive descent sonde. AERACEPT does not require heat shield separation, deployable parachutes, or descent control, thus reducing the mass, volume, and complexity of planetary aerosol sampling. AERACEPT is particularly well suited for a Venus mission, where the particles of greatest interest are within the subsonic descent regime. AERACEPT uses the aeroshell’s own velocity to drive aerosol capture and separation through a series of embedded inlets. It takes advantage of recently developed thermal protection materials (3D-CC and HEEET) in combination with heritage aerosol sampling technologies from both planetary and airborne science (high-speed inlets and particle separation). The trade space for a given descent trajectory includes the particle capture efficiency for a given size, the bias introduced in the sampled particle size and concentration distributions, and the thermal alteration experienced by the particles during their brief exposure to the internal flow environment. AERACEPT is included in the Nephele mission concept study for a small spacecraft targeting the Venus middle and lower cloud layers. Nephele complements larger missions targeting Venus atmospheric gas analysis, such as DAVINCI and Venera-D, by specifically targeting cloud and haze particles. Because of the short lifetime of the probe in the lower atmosphere, Nephele requires a fast cadence of analysis of the captured particles, and includes the VOLTR dual optical spectrometer (SERS/LIBS) as part of its notional payload. Preliminary modeling based on the Nephele trajectory at 63 km to 39 km indicates AERACEPT can limit sample heating to 30-60 K above ambient. A modified particle tracking model has been implemented to estimate capture efficiency of particles larger than 0.1 µm and total sample volume as part of an inlet and interal flow path geometry trade study. Further modeling and empirical testing is underway to improve these estimates.

AERACEPT↗
DOE OSTI2019

Description of the ARM Large-Scale Forcing Data from the Constrained Variational Analysis (VARANAL) Version 2

This technical report represents an update of the previous technical report written by Zhang et al., which described the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility constrained variational analysis (VARANAL) that is used to develop the large-scale forcing data for driving single-column models (SCMs), cloud-resolving models (CRMs), and large-eddy simulation models (LES). The VARANAL algorithm was originally developed by Zhang and Lin and Zhang et al. at Stony Brook University and was migrated to the Lawrence Livermore National Laboratory (LLNL) as the ARM operational objective analysis system in May 1999. Since then, the algorithm has been evolved with time along with the availability of new observations and techniques to meet various modeling needs. Major updates include: 1. The method used to develop multi-year continuous forcing data, 2. The incorporation of eddy correlation flux measurement system (ECOR) turbulent fluxes into the analysis, and 3. Improvements to the workflow (e.g., implementing part of the code into the ARM Data Integrator [ADI]) to increase efficiency. The ARM large-scale forcing data have been widely used for SCM/CRM/LES to understand and improve physical processes in models. Zhang et al. has provided a comprehensive review of the SCM concept, early efforts to derive forcing data for SCM studies, efforts of the ARM constrained variational analysis, and previous SCM studies using ARM cases. This technical report focuses on the constrained variational analysis algorithm and the introduction of the ARM VARANAL products. We also extended the VARANAL algorithm into a three-dimensional constrained variational analysis (3DCVA) and designed an ensemble framework to address the forcing uncertainty. The 3D large-scale forcing data are released as another datastream named “varanal3d”. Please refer to the ARM varanal3d technical report for more information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Demonstration of a MOT in a sub-millimeter membrane hole

Abstract We demonstrate the generation of a cold-atom ensemble within a sub-millimeter diameter hole in a transparent membrane, a so-called “membrane MOT”. With a sub-Doppler cooling process, the atoms trapped by the membrane MOT are cooled down to 10 $$\upmu$$ μ K. The atom number inside the unbridged/bridged membrane hole is about $$10^4$$ 10 4 to $$10^5$$ 10 5 , and the $$1/e^2$$ 1 / e 2 -diameter of the MOT cloud is about 180 $$\upmu$$ μ m for a 400 $$\upmu$$ μ m-diameter membrane hole. Such a membrane device can, in principle, efficiently load cold atoms into the evanescent-field optical trap generated by the suspended membrane waveguide for strong atom-light interaction and provide the capability of sufficient heat dissipation at the waveguide. This represents a key step toward the photonic atom trap integrated platform (ATIP).

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1999

Validation of Surface Skin Temperature and Moisture Profiles Using Satellite Data

New validation techniques and metrics using satellite data have been developed to evaluate the quality of model-based estimates of surface skin temperature (Tg) and moisture profiles (q). The satellite data consist of clear sky outgoing long-wave radiation (CLR), broadband radiances from 8 to 12 mu (RadWn), brightness temperature centered around 10.8 mu (Tbb), and total precipitable water (TPW) from microwave radiometry. We show that CLR can be used to diagnose Tg. Furthermore, by using a combination of CLR and RadWn from CERES-TRMM measurements and TPW from SSM/I, we are able to identify errors in the moisture profile. Finally, three-hourly Tbb from the International Satellite Cloud Climatology Project can be used to evaluate the amplitude and diurnal variation of Tg. For purpose of illustration, Tg and q are evaluated from runs with an early version of the Goddard Earth Observing System Data Assimilation System (GEOS-2). It is found that, in general, Tg is too cold in the winter hemisphere and q is too wet in the upper atmosphere. In order to address these deficiencies, several improvements have been implemented into GEOS-2, including a Land-Surface-Model, a Moist Turbulence Scheme, and the assimilation of new TOVS retrievals. Preliminary results indicate positive impacts from each of these implementations.

Wu, Man Li C.↗
NASA NTRS2000

Magnetic Flux Compression Concept for Aerospace Propulsion and Power

The objective of this research is to investigate system level performance and design issues associated with magnetic flux compression devices for aerospace power generation and propulsion. The proposed concept incorporates the principles of magnetic flux compression for direct conversion of nuclear/chemical detonation energy into electrical power. Specifically a magnetic field is compressed between an expanding detonation driven diamagnetic plasma and a stator structure formed from a high temperature superconductor (HTSC). The expanding plasma cloud is entirely confined by the compressed magnetic field at the expense of internal kinetic energy. Electrical power is inductively extracted, and the detonation products are collimated and expelled through a magnetic nozzle. The long-term development of this highly integrated generator/propulsion system opens up revolutionary NASA Mission scenarios for future interplanetary and interstellar spacecraft. The unique features of this concept with respect to future space travel opportunities are as follows: ability to implement high energy density chemical detonations or ICF microfusion bursts as the impulsive diamagnetic plasma source; high power density system characteristics constrain the size, weight, and cost of the vehicle architecture; provides inductive storage pulse power with a very short pulse rise time; multimegajoule energy bursts/terawatt power bursts; compact pulse power driver for low-impedance dense plasma devices; utilization of low cost HTSC material and casting technology to increase magnetic flux conservation and inductive energy storage; improvement in chemical/nuclear-to-electric energy conversion efficiency and the ability to generate significant levels of thrust with very high specific impulse; potential for developing a small, lightweight, low cost, self-excited integrated propulsion and power system suitable for space stations, planetary bases, and interplanetary and interstellar space travel; potential for attaining specific impulses approaching 10 (exp 6) seconds, which would enable missions to the outer planets within ten years and missions at interstellar distances within fifty years.

Litchford, Ron J.↗
NASA NTRS2009

Variability of Marine Aerosol Fine-Mode Fraction and Estimates of Anthropogenic Aerosol Component Over Cloud-Free Oceans from the Moderate Resolution Imaging Spectroradiometer (MODIS)

In this study, we examine seasonal and geographical variability of marine aerosol fine-mode fraction (f(sub m)) and its impacts on deriving the anthropogenic component of aerosol optical depth (tau(sub a)) and direct radiative forcing from multispectral satellite measurements. A proxy of f(sub m), empirically derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 data, shows large seasonal and geographical variations that are consistent with the Goddard Chemistry Aerosol Radiation Transport (GOCART) and Global Modeling Initiative (GMI) model simulations. The so-derived seasonally and spatially varying f(sub m) is then implemented into a method of estimating tau(sub a) and direct radiative forcing from the MODIS measurements. It is found that the use of a constant value for fm as in previous studies would have overestimated Ta by about 20% over global ocean, with the overestimation up to 45% in some regions and seasons. The 7-year (2001-2007) global ocean average tau(sub a) is 0.035, with yearly average ranging from 0.031 to 0.039. Future improvement in measurements is needed to better separate anthropogenic aerosol from natural ones and to narrow down the wide range of aerosol direct radiative forcing.

Yu, Hongbin↗
NASA NTRS2003

Sensitivity Studies for Space-based Measurement of Atmospheric Total Column Carbon Dioxide Using Reflected Sunlight

A series of sensitivity studies is carried out to explore the feasibility of space-based global carbon dioxide (CO2) measurements for global and regional carbon cycle studies. The detection method uses absorption of reflected sunlight in the CO2 vibration-rotation band at 1.58 microns. The sensitivities of the detected radiances are calculated using the line-by-line model (LBLRTM), implemented with the DISORT (Discrete Ordinates Radiative Transfer) model to include atmospheric scattering in this band. The results indicate that (a) the small (approx.1%) changes in CO2 near the Earth's surface are detectable in this CO2 band provided adequate sensor signal-to-noise ratio and spectral resolution are achievable; (b) the radiance signal or sensitivity to CO2 change near the surface is not significantly diminished even in the presence of aerosols and/or thin cirrus clouds in the atmosphere; (c) the modification of sunlight path length by scattering of aerosols and cirrus clouds could lead to large systematic errors in the retrieval; therefore, ancillary aerosol/cirrus cloud data are important to reduce retrieval errors; (d) CO2 retrieval requires good knowledge of the atmospheric temperature profile, e.g. approximately 1K RMS error in layer temperature; (e) the atmospheric path length, over which the CO2 absorption occurs, must be known in order to correctly interpret horizontal gradients of CO2 from the total column CO2 measurement; thus an additional sensor for surface pressure measurement needs to be attached for a complete measurement package.

Mao, Jianping↗
DOE OSTI2015

Early-type eclipsing binaries with intermediate orbital periods

We analyze 221 eclipsing binaries (EBs) in the Large Magellanic Cloud with B-type main-sequence (MS) primaries (M{sub 1} ≈ 4–14 M{sub ⊙}) and orbital periods P = 20–50 days that were photometrically monitored by the Optical Gravitational Lensing Experiment. We utilize our three-stage automated pipeline to (1) classify all 221 EBs, (2) fit physical models to the light curves of 130 detached well-defined EBs from which unique parameters can be determined, and (3) recover the intrinsic binary statistics by correcting for selection effects. We uncover two statistically significant trends with age. First, younger EBs tend to reside in dustier environments with larger photometric extinctions, an empirical relation that can be implemented when modeling stellar populations. Second, younger EBs generally have large eccentricities. This demonstrates that massive binaries at moderate orbital periods are born with a Maxwellian “thermal” orbital velocity distribution, which indicates they formed via dynamical interactions. In addition, the age-eccentricity anticorrelation provides a direct constraint for tidal evolution in highly eccentric binaries containing hot MS stars with radiative envelopes. The intrinsic fraction of B-type MS stars with stellar companions q = M{sub 2}/M{sub 1} > 0.2 and orbital periods P = 20–50 days is (7 ± 2)%. We find early-type binaries at P = 20–50 days are weighted significantly toward small mass ratios q ≈ 0.2–0.3, which is different than the results from previous observations of closer binaries with P < 20 days. This indicates that early-type binaries at slightly wider orbital separations have experienced substantially less competitive accretion and coevolution during their formation in the circumbinary disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

Zhang, Weiyu [University of Leeds (United Kingdom)↗