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At least 199 records · Page 11

Fast-Time Simulation for Evaluating the Impact of Estimated Flight Ready Time Uncertainty on Surface Metering

NASA has been developing and demonstrating new concepts and technologies for Integrated Arrival, Departure, and Surface (IADS) traffic management capabilities under the Airspace Technology Demonstration 2 (ATD-2) project. One of the IADS capabilities in the ATD-2 project is surface metering enabled by a tactical surface scheduler to provide controllers with the pushback advisories for departures at gates. The tactical surface scheduler uses the estimated flight ready times provided by airlines, called Earliest Off-Block Times (EOBTs), as input to calculate the target off-block times for pushback advisories. However, the EOBTs are often inaccurate and deviate from the actual flight ready times, which may reduce the benefits of surface metering. In this paper, a linear regression model is developed to model the EOBT uncertainty distribution over time based on actual EOBT data collected at Charlotte airport. This EOBT model is integrated with a tactical surface scheduler and a fast-time simulation tool. To evaluate the impact of the EOBT accuracy on airport surface operations, fast-time simulations are implemented for selected traffic scenarios under different levels of modelled EOBT accuracy. The simulation results show that the EOBT uncertainty affects several performance metrics related to the surface metering, such as gate hold, taxi time reduction, and target takeoff time predictability, which in turn influences ATD-2's scheduler performance.

tactical surface scheduler↗

Global Aerosol Direct Radiative Effect From CALIOP and C3M

Aerosols are responsible for the largest uncertainties in current estimates of climate forcing. These uncertainties are due in part to the limited abilities of passive sensors to retrieve aerosols in cloudy skies. We use a dataset which merges CALIOP observations together with other A-train observations to estimate aerosol radiative effects in cloudy skies as well as in cloud-free skies. The results can be used to quantify the reduction of aerosol radiative effects in cloudy skies relative to clear skies and to reduce current uncertainties in aerosol radiative effects.

Winker, Dave↗

Global Aerosol Direct Radiative Effect from CALIOP and C3M

Aerosols are responsible for the largest uncertainties in current estimates of climate forcing. These uncertainties are due in part to the limited abilities of passive sensors to retrieve aerosols in cloudy skies. We use a dataset which merges CALIOP observations together with other A-train observations to estimate aerosol radiative effects in cloudy skies as well as in cloud-free skies. The results can be used to quantify the reduction of aerosol radiative effects in cloudy skies relative to clear skies and to reduce current uncertainties in aerosol radiative effects.

Winker, Dave↗

Electron beam fluorescence measurements in the Boeing hypersonic shock tunnel

The Calspan electron beam fluorescence (EBF) measurement system is described along with the results of measurements made in hypersonic flow. Numerous self-emitting metallic species were identified, many of which may be associated with an aging/erosion process within the B30HST. Because there were only 16 tunnel runs, it was only possible to obtain spectral measurements over a limited range of wavelengths and time sampling periods. Many spectral features of the flow remain uninvestigated. Because flow self-emission is important to all optical diagnostic techniques, it is recommended that additional spectral studies by performed. The three electron beam-excited species that were identified are nitrogen, helium, and nitric oxide. The high metallic radiation background interfered with attempts to obtain the time-wise variation of N2 density and He radiation with the optical fiber/PMT channels. In the case of the N2 density measurements the result of interference was increased uncertainty. Unfortunately, the interference caused the time-wise He measurements to fail completely. It is recommended that the electron beam be modulated to provide discrimination against the background radiation in future N2 density measurements. Careful data reduction produced useful measurements of N2 vibrational temperature, even though the high background from metallic species significantly increased measurement uncertainty. Perhaps the recommended additional spectral studies would reveal N2(+) First Negative System band-pair regions having less background. Detection of the He arrival was easily accomplished with the spectrometer/array detector system. Because of this, it is recommended that this means of detecting He arrival be used in the future. With proper calibrations of the system an He number density could be obtained. Although the flow conditions were out of limits for the run in which the NO spectrum was recorded, the usefulness of the NO spectrum for determination of free-stream rotational temperature was demonstrated and should be exploited in future experiments. Indeed, based on the strong NO signals, it is recommended that lower resolution NO spectra be obtained to provide a measure of NO vibrational temperature in the same manner that the N2 temperature was obtained.

Price, Linwood L.↗

Performance study of galactic cosmic ray shield materials

The space program is faced with two difficult radiation protection issues for future long-term operations. First, retrofit of shield material or conservatism in shield design is prohibitively expensive and often impossible. Second, shielding from the cosmic heavy ions is faced with limited knowledge on the physical properties and biological responses of these radiations. The current status of space shielding technology and its impact on radiation health is discussed herein in terms of conventional protection practice and a test biological response model. The impact of biological response on the selection of optimum materials for cosmic ray shielding is presented in terms of the transmission characteristics of the shield material. Although the systematics of nuclear cross sections are able to demonstrate the relation of exposure risk to shield-material composition, the current uncertainty in-nuclear cross sections will not allow an accurate evaluation of risk reduction. This paper presents a theoretical study of risk-related factors and a pilot experiment to study the effectiveness of choice of shield materials to reduce the risk in space operations.

Kim, Myung-Hee Y.↗

Advanced Turboprop Transport Aircraft Modeling for the Electrified Powertrain Flight Demonstration Project

The objective of this study is to establish models for state of the art, representative regional non-electrified turboprop configurations in the 19 to 50 passenger capability range and assess performance impacts from advanced aircraft technologies. Two of these models will serve as reference baseline configurations for comparison to electrified aircraft propulsion (EAP) demonstrator concepts for the Electrified Powertrain Flight Demonstration (EPFD) project. The other two non-electrified configurations will primarily assess the impacts of advanced technologies on fuel consumption and CO₂ emissions. This paper details an aircraft synthesis and performance analysis approach using the General Aviation Synthesis Program (GASP) which is used to establish baseline performance capabilities, calibrate airplane and engine models using published manufacturer data and conduct technology sensitivity studies. Advanced technologies are selected from the categories of propulsion, aerodynamics, and flight systems. A GASP-Monte Carlo simulation framework for uncertainty propagation is used to obtain performance distributions of the expected fuel burn, weight reduction and CO₂ emissions reductions from advanced aircraft technologies. Significant fuel burn savings from application of aerodynamics and propulsion technologies was observed.

Dahlia D.V. Pham↗

Characterization and Uncertainty Analysis of a Reference Pressure Measurement System for Wind Tunnels

This paper presents the calibration results and uncertainty analysis of a high-precision reference pressure measurement system currently used in wind tunnels at the NASA Langley Research Center (LaRC). Sensors, calibration standards, and measurement instruments are subject to errors due to aging, drift with time, environment effects, transportation, the mathematical model, the calibration experimental design, and other factors. Errors occur at every link in the chain of measurements and data reduction from the sensor to the final computed results. At each link of the chain, bias and precision uncertainties must be separately estimated for facility use, and are combined to produce overall calibration and prediction confidence intervals for the instrument, typically at a 95% confidence level. The uncertainty analysis and calibration experimental designs used herein, based on techniques developed at LaRC, employ replicated experimental designs for efficiency, separate estimation of bias and precision uncertainties, and detection of significant parameter drift with time. Final results, including calibration confidence intervals and prediction intervals given as functions of the applied inputs, not as a fixed percentage of the full-scale value are presented. System uncertainties are propagated beginning with the initial reference pressure standard, to the calibrated instrument as a working standard in the facility. Among the several parameters that can affect the overall results are operating temperature, atmospheric pressure, humidity, and facility vibration. Effects of factors such as initial zeroing and temperature are investigated. The effects of the identified parameters on system performance and accuracy are discussed.

Amer, Tahani↗

Assessment of Axial Wave Number and Mean Flow Uncertainty on Acoustic Liner Impedance Education

A key parameter in designing and assessing advanced broadband acoustic liners to achieve the current and future noise reduction goals is the acoustic impedance presented by the liner. This parameter, intrinsic to a specific liner configuration, is dependent on sound pressure level and grazing flow velocity. Current impedance eduction approaches have, in general, provided excellent results and continue to be employed throughout the acoustic liner community. However, some recent applications have indicated a possible dependence of the educed impedance on the direction of incident waves relative to the mean flow. The purpose of the current study is to investigate this unexpected behavior for various impedance eduction methods based on the Pridmore-Brown and convected Helmholtz equations. Specifically, the effects of flow profile and axial wavenumber uncertainties on educed impedances for upstream and downstream sources are investigated. The uniform flow results demonstrate the importance of setting a correct Mach number value in obtaining consistent educed impedances for upstream and downstream sources. In fact, the consistency of results over the two source locations was greatly improved by a slight modification of the uniform flow Mach number. In addition, uncertainty in educed axial wavenumber was also illustrated to correlate well with differences in the educed impedances, even with modified uniform flow Mach number. Finally, while less straightforward than in the uniform flow case, it appears that modification of the mean flow profile may also improve consistency of results for upstream and downstream results when shear flow is included.

Nark, Douglas M.↗

A STATISTICAL OPTIMIZING NAVIGATION PROCEDURE FOR SPACE FLIGHT

In a typical self-contained space navigation system, celestial observation data are gathered and processed to produce estimated velocity corrections. The results of this paper provide a basis for determining the best celestial measurements and the proper time s to implement velocity corrections. Fundamental to the navigation system is a procedure for processing celestial measurement data which permits incorporation of each individual measurement as it is made in order to provide an improved estimate of position and velocity. In order to "optimize" the navigation, a statistical evaluation of a number of alternative courses of action is made. The various alternatives, which form the basis of a decision process, concern the following: 1) which star and planet combination provides the "best" available observation; 2) whether the best observation gives a sufficient reduction in the predicted target error to warrant making the measurement; and 3) whether the uncertainty in the indicated velocity correction is a small enough percentage of the correction itself to justify an engine re-start and propellant expenditure. Numerical results are presented which illustrate the effectiveness of this approach to the space navigation problem.

NAVIGATION↗

Design and test of three active flutter suppression controllers

Three flutter suppression control law design techniques are presented. Each uses multiple control surfaces and/or sensors. The first uses linear combinations of several accelerometer signals together with dynamic compensation to synthesize the modal rate of the critical mode for feedback to distributed control surfaces. The second uses traditional tools (pole/zero loci and Nyquist diagrams) to develop a good understanding of the flutter mechanism and produce a controller with minimal complexity and good robustness to plant uncertainty. The third starts with a minimum energy Linear Quadratic Gaussian controller, applies controller order reduction, and then modifies weight and noise covariance matrices to improve multi-variable robustness. The resulting designs were implemented digitally and tested subsonically on the Active Flexible Wing (AFW) wind tunnel model. Test results presented here include plant characteristics, maximum attained closed-loop dynamic pressure, and Root Mean Square control surface activity. A key result is that simultaneous symmetric and antisymmetric flutter suppression was achieved by the second control law, with a 24 percent increase in attainable dynamic pressure.

Christhilf, David M.↗

Pulse Detonation Rocket MHD Power Experiment

A pulse detonation research engine (MSFC (Marshall Space Flight Center) Model PDRE (Pulse Detonation Rocket Engine) G-2) has been developed for the purpose of examining integrated propulsion and magnetohydrodynamic power generation applications. The engine is based on a rectangular cross-section tube coupled to a converging-diverging nozzle, which is in turn attached to a segmented Faraday channel. As part of the shakedown testing activity, the pressure wave was interrogated along the length of the engine while running on hydrogen/oxygen propellants. Rapid transition to detonation wave propagation was insured through the use of a short Schelkin spiral near the head of the engine. The measured detonation wave velocities were in excess of 2500 m/s in agreement with the theoretical C-J velocity. The engine was first tested in a straight tube configuration without a nozzle, and the time resolved thrust was measured simultaneously with the head-end pressure. Similar measurements were made with the converging-diverging nozzle attached. The time correlation of the thrust and head-end pressure data was found to be excellent. The major purpose of the converging-diverging nozzle was to configure the engine for driving an MHD generator for the direct production of electrical power. Additional tests were therefore necessary in which seed (cesium-hydroxide dissolved in methanol) was directly injected into the engine as a spray. The exhaust plume was then interrogated with a microwave interferometer in an attempt to characterize the plasma conditions, and emission spectroscopy measurements were also acquired. Data reduction efforts indicate that the plasma exhaust is very highly ionized, although there is some uncertainty at this time as to the relative abundance of negative OH ions. The emission spectroscopy data provided some indication of the species in the exhaust as well as a measurement of temperature. A 24-electrode-pair segmented Faraday channel and 0.6 Tesla permanent magnet assembly were then installed on Marshall Space Flight Center's (MSFC's) rectangular channel pulse detonation research engine. Magnetohydrodynamic (MHD) electrical power extraction experiments were carried out for a range of load impedances in which cesium hydroxide seed (dissolved in methanol) was sprayed into the gaseous oxygen/hydrogen propellants. Positive power extraction was obtained, but preliminary analysis of the data indicated that the plasma electrical conductivity is lower than anticipated and the near-electrode voltage drop is not negligible. It is believed that the electrical conductivity is reduced due to a large population of negative OH ions. This occurs because OH has a strong affinity for capturing free electrons. The effect of near-electrode voltage drop is associated with the high surface-to-volume ratio of the channel (1-inch by 1-inch cross-section) where surface effects play a dominant role. As usual for MHD devices, higher performance will require larger scale devices. Overall, the gathered data is extremely valuable from the standpoint of understanding plasma behavior and for developing empirical scaling laws.

Litchford, Ron J.↗

Analysis of Strategic Conflict Management Approaches as Applied to Simulated UAM Operations

This report presents the results of a comparison analysis of candidate Strategic Conflict Management (SCM) strategies as applied to Urban Air Mobility (UAM) operations. The SCM strategies investigated included: no SCM, resource scheduling (RS), resource flow rates (FR), area-based flow rates (AR), and conflict detection and resolution (CR). The study evaluated each strategy against the same 3 levels of flight demand in a representative airspace construct for the Dallas/Fort Worth region. The study also accounted for different levels of uncertainty in operational planning and equivalent levels of trajectory following error. In the analysis, we compared the SCM strategies’ effectiveness in reducing the need for the tactical conflict management layer to act and looked at the metrics of unmitigated losses-of-separation (LOS), flight delays imposed by strategic planning, and throughput of the overall airspace. The study results indicated that the CR strategy was the most effective at reducing LOS and percentage of flights with LOS, even in the presence of trajectory error when uncertainty is accounted for in planning. Thus, if the objective is to reduce the number of actions that the tactical conflict management layer will have to take, in terms of conflicts that may need to be resolved, CR is the strategy to use. The FR strategy was found to be the worst at reducing LOS and percentage of flights with LOS. Thus, it is not very effective at reducing the actions required by a tactical conflict management layer. In the airspace tested, the demand was high enough to produce unacceptable levels of flight delay and reductions of throughput when the SCM strategies were implemented. This was especially evident at the higher levels of trajectory uncertainty and error. The need to account for expected levels of uncertainty becomes more and more important as the demand level increases and as the level of trajectory error increases. This is because the likelihood of flights with LOS increases as the density of operations increases and as the level of trajectory error increases. Accounting for uncertainty in the SCM strategies improves the strategy effectiveness with respect to LOS but increases delays and reduces throughput. Thus, there is a tradeoff between scalability and allowable levels of uncertainty. That is, we can implement an air traffic management construct that allows high levels of uncertainty, but we can expect that same system to have limits on scalability that may be evident even at small demand levels, such as those used in this study. Therefore, the results in this study indicate that an air traffic system should attempt to implement mechanisms appropriate for reducing uncertainty where possible in order to increase the chances for scalability. And this increased level of predictability of operations needs to be balanced with mechanisms for ensuring flexibility when operational conditions and plans need to change, even though those types of changes should be the exception rather than the rule under normal conditions. The study also introduced a trade space that could serve as a mechanism for selecting the appropriate SCM strategy in a trade-off between uncertainty and error, mean flight delay, and the LOS metrics (which this study equates to the potential for tactical conflict management actions). The optimal solution for a given airspace, demand level, and other factors, could likely be a combination of SCM strategies, although this study only compared the use of a single SCM strategy at a time. The CR strategy appeared to have the best opportunity for scalability by limiting the number of potential tactical actions to nearly zero.

Strategic Conflict Management↗

Orbit determination accuracies using satellite-to-satellite tracking

The uncertainty in relay satellite sate is a significant error source which cannot be ignored in the reduction of satellite-to-satellite tracking data. Based on simulations and real data reductions, it is numerically impractical to use simultaneous unconstrained solutions to determine both relay and user satellite epoch states. A Bayesian or least squares estimation technique with an a priori procedure is presented which permits the adjustment of relay satellite epoch state in the reduction of satellite-to-satellite tracking data without the numerical difficulties introduced by an ill-conditioned normal matrix.

Vonbun, F. O.↗

Uncertainties in estimates of the risks of late effects from space radiation

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits. Published by Elsevier Ltd on behalf of COSPAR.

Non-NASA Center↗

Uncertainties in Estimates of the Risks of Late Effects from Space Radiation

The health risks faced by astronauts from space radiation include cancer, cataracts, hereditary effects, and non-cancer morbidity and mortality risks related to the diseases of the old age. Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Within the linear-additivity model, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain a Maximum Likelihood estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including ISS, lunar station, deep space outpost, and Mar's missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time, and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative objective's, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits.

Cucinotta, F. A.↗

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. This suite included a network of MEDLI2 Instrumented Sensor Plugs (MISPs). Each MISP was comprised of a cylinder made of Thermal Protection System (TPS) material with 1-3 embedded thermocouples (TCs), and it was flush mounted into the heatshield or backshell. Data from these in-depth TCs were used to reconstruct the aeroheating environment of the vehicle throughout entry. Surface heating was posed as an inverse problem, with the goal of estimating the surface heating by minimizing an objective function of the difference between MISP temperature measurements during flight and the temperature predictions derived from the Fully Implicit Ablation and Thermal response (FIAT) program. Given an aerothermal environment, FIAT calculates the material response and provides in-depth temperatures throughout the TPS material. To achieve the reverse, an internal tool called FIAT_Opt runs through multiple different environments until the output temperature at the TC depth closely matches the flight data. 95% confidence intervals on the reconstructed surface heating were obtained using Monte Carlo analysis, in which uncertainties in the thermocouple depth and the TPS material properties (e.g., density, thermal conductivity, heat capacity, emissivity) based on flight-lot material testing were included. A variance decomposition method using Sobol indices was employed to assess the sensitivity of the reconstructed peak heating to the TC placement and material property uncertainties. Variance decomposition was found to require tens of thousands of FIAT_Opt runs in order for the Sobol indices to converge. With a single FIAT_Opt run taking on the order of 40 minutes, the required number of computations would take months to complete, even if using multiple CPUs. To mitigate this problem, three machine learning models (ridge regression with cross-validation, random forest regression, and a deep neural network) were trained and tested using the 2000 Monte Carlo runs that were already completed. A subset of 1600 runs were used to train the model (i.e., training set), while the remaining 400 runs were used as the test set. The predictions from the deep neural network (DNN) on the test set showed nearly perfect agreement to the actual values computed with FIAT_Opt (R2 > 0.99). Using the DNN as a surrogate model, the variance decomposition using 50,000 runs was completed within minutes. The resulting Sobol indices showed that the reconstructed peak surface heating was most sensitive to the uncertainties in the thermal conductivity (ST = 0.37) and heat capacity (ST = 0.26). This method can be leveraged to provide requirements for material property measurements needed to improve the accuracy of surface heating prediction and ultimately lead to the reduction of design margins in the future. This presentation will include background on the MEDLI2 suite; the method used for inverse heating estimation; the way that material property uncertainties were accounted for using Monte Carlo analysis; a brief background on variance decomposition; the motivation for using machine learning in this context; how a neural network was trained on the data to enable variance decomposition in a fraction of the time; and the variance decomposition results for one of the MISPs.

Hannah Alpert↗

Spectral Correlation in MODIS Water-Leaving Reflectance Retrieval Uncertainty

Spectral remote sensing reflectance, Rrs(λ) (sr−1), is the fundamental quantity used to derive a host of bio-optical and biogeochemical properties of the water column from satellite ocean color measurements. Estimation of uncertainty in those derived geophysical products is therefore dependent on knowledge of the uncertainty in satellite-retrieved R rs . Furthermore, since the associated algorithms require R rs at multiple spectral bands, the spectral (i.e., band-to-band)error covariance in R rs is needed to accurately estimate the uncertainty in those derived properties. This study establishes a derivative-based approach for propagating instrument random noise, instrument systematic uncertainty, and forward model uncertainty into R rs as retrieved using NASA’s multiple-scattering epsilon (MSEPS) atmospheric correction algorithm, to generate pixel-level error covariance in R rs . The approach is applied to measurements from Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite and verified using Monte Carlo (MC) analysis. We also make use of this full spectral error covariance in R rs to calculate uncertainty in phytoplankton pigment chlorophyll-a concentration (chl a , mg/m 3 ) and diffuse attenuation coefficient of downwelling irradiance at 490 nm (K d (490), m -1 ). Accounting for the error covariance in R rs generally reduces the estimated relative uncertainty in chl a by ∼1-2% (absolute value) in waters with chl a < 0.25 mg/m 3 where the color index (CI) algorithm is used. The reduction is ∼5-10% in waters with chl a > 0.35 mg/m 3 where the blue-green ratio (OCX) algorithm is used. Such reduction can be higher than 30% in some regions. For K d (490), the reduction by error covariance is generally ∼2%, but can be higher than 20% in some regions. The error covariance in R rs is further verified through forward-calculating chl a from MODIS-retrieved and in situ R rs and comparing estimated uncertainty with observed differences. An 8-day global composite of propagated uncertainty shows that the goal of 35% uncertainty in chl a can be achieved over deep ocean waters (chl a ≤ 0.1 mg/m3). While the derivative-based approach generates reasonable error covariance in R rs some assumptions should be updated as our knowledge improves. These include the inter-band error correlation in top-of-atmosphere reflectance, and uncertainties in the calibration of MODIS 869 nm band, in ancillary data, and in the in situ data used for system vicarious calibration.

Ocean color↗

The Climate Response to Emissions Reductions due to COVID-19: Initial Results from CovidMIP

Many nations responded to the COVID-19 pandemic by restricting travel and other activities during 2020, resulting in temporarily reduced emissions of CO2, other greenhouse gases and ozone and aerosol precursors. We present the initial results from a coordinated Intercomparison, CovidMIP, of Earth system model simulations which assess the impact on climate of these emissions reductions. Twelve models performed multiple initial-condition ensembles to produce over 300 simulations spanning both initial condition and model structural uncertainty. We find model consensus on reduced aerosol amounts (particularly over southern and eastern Asia) and associated increases in surface shortwave radiation levels. However, any impact on near-surface temperature or rainfall during 2020-2024 is extremely small and is not detectable in this initial analysis. Regional analyses on a finer scale, and closer attention to extremes (especially linked to changes in atmospheric composition and air quality) are required to test the impact of COVID- 19-related emission reductions on near-term climate.

Chris D. Jones↗