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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment (BASE-ASIA)

Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth's radiation and water budget. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds from the soil to the atmosphere; the hydrological cycle (i.e., run off and evaporation); land surface reflectivity and emissivity; as well as ecosystem biodiversity and stability. Analyses from satellite measurements reveal that smoke is frequently present solar (emitted thermal) radiation from clouds due to smoke aerosols can be reduced (enhanced) by as much as 100 (20) W/sq m over the month of March 2000. In addition, the reduction in cloud spectral reflectance at 670 run is large enough to lead to significant errors in retrieving cloud properties (e.g., optical thickness and effective radius) from satellite measurements. The fresh water distribution in this region is highly dependent on monsoon rainfall; in fact, the predictability of the tropical climate system is much reduced during the boreal spring. Estimating the burning fuel (e.g., bark, branches, and wood), an important part of studying regional carbon cycle, may rely on utilizing a wide range of distinctive spectral features in the shortwave and longwave regions. Therefore, to accurately assess the impact of smoke aerosols in this region requires continuous observations from satellites, aircraft, networks of ground-based instruments and dedicated field experiments. A new initiative will be proposed and discussed.

Tsay, Si-Chee↗
NASA NTRS2015

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar↗
NASA NTRS1996

Development of a Large Scale, High Speed Wheel Test Facility

Draper Laboratory, with its internal research and development budget, has for the past two years been funding a joint effort with the Massachusetts Institute of Technology (MIT) for the development of a large scale, high speed wheel test facility. This facility was developed to perform experiments and carry out evaluations on levitation and propulsion designs for MagLev systems currently under consideration. The facility was developed to rotate a large (2 meter) wheel which could operate with peripheral speeds of greater than 100 meters/second. The rim of the wheel was constructed of a non-magnetic, non-conductive composite material to avoid the generation of errors from spurious forces. A sensor package containing a multi-axis force and torque sensor mounted to the base of the station, provides a signal of the lift and drag forces on the package being tested. Position tables mounted on the station allow for the introduction of errors in real time. A computer controlled data acquisition system was developed around a Macintosh IIfx to record the test data and control the speed of the wheel. This paper describes the development of this test facility. A detailed description of the major components is presented. Recently completed tests carried out on a novel Electrodynamic (EDS) suspension system, developed by MIT as part of this joint effort are described and presented. Adaptation of this facility for linear motor and other propulsion and levitation testing is described.

Kondoleon, Anthony↗
DOE OSTI2014

A New Approach for Reducing Uncertainty in Biospheric CO 2 Flux

In the 2010 Global Carbon Project Report it was estimated that the terrestrial biosphere sequesters 2.4 Pg of anthropogenic carbon emissions per year although the uncertainty on that value is undoubtedly high as no error bars were given. As man-made emissions of CO 2 continue to increase unabated in the atmosphere, quantifying the fate of these anthropogenic sources requires both knowing the magnitude and uncertainty of background, natural CO 2 fluxes. Thus, reducing uncertainty in biospheric CO 2 flux measurements will not only give us direct, accurate observations for future carbon accounting and climate treaties but also indirectly help us quantify anthropogenic emissions for the same purposes. In conjuncture with ecosystem models or remote-sensing techniques, these measurements also provide accurate constraints on global and continental terrestrial CO 2 budgets. With the motivation stated above, we designed and executed a three-year Laboratory Directed Research and Development (LDRD) project with the aim of reducing the uncertainty in eddy-covariance biospheric CO 2 flux. Reducing uncertainty was approached in two ways. The first utilized nontraditional eddy covariance instrumentation to identify and characterize atmospheric flows above and within the plant canopy. Here, atmospheric laser detection and ranging (lidar) instrumentation were used to capture unique flow features at night which may explain erroneous or anomalous carbon fluxes. The second approach utilized a multi-layer, 3rd order closure canopy-atmosphere model to simulate fluxes at each field site. Three sites were chosen for field instrument deployment and modeling. These included the Wind River AmeriFlux tower in Washington State and the Tonzi AmeriFlux and Diablo AmeriFlux towers in northern California. These sites represent some of the extremes in the biological and meteorological conditions over which eddy covariance techniques are used. Wind River is a multi-layered, 60-m tall seasonal rainforest, Diablo is a 1-m tall grassland with a very short growing season, and Tonzi is a 2- layered savannah canopy with complex ecohydrology. All three are surrounded by complex terrain in varying degrees. The towers provided very different test sites for validating the UC Davis Advanced Canopy Atmosphere Soil Algorithm (ACASA) model. Such validation gives promise that the model can be used to independently verify and gap-fill biospheric CO 2 measurements from the network of ~ 550 global flux towers for future greenhouse gas emissions monitoring and verification studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The CMIP6 Sea-Ice Model Intercomparison Project (SIMIP): Understanding sea ice through climate-model simulations

A better understanding of the role of sea ice for the changing climate of our planet is the central aim of the diagnostic Coupled Model Intercomparison Project 6 (CMIP6)-endorsed Sea-Ice Model Intercomparison Project (SIMIP). To reach this aim, SIMIP requests sea-ice-related variables from climate-model simulations that allow for a better understanding and, ultimately, improvement of biases and errors in sea-ice simulations with large-scale climate models. This then allows us to better understand to what degree CMIP6 model simulations relate to reality, thus improving our confidence in answering sea-ice-related questions based on these simulations. Furthermore, the SIMIP protocol provides a standard for sea-ice model output that will streamline and hence simplify the analysis of the simulated sea-ice evolution in research projects independent of CMIP. To reach its aims, SIMIP provides a structured list of model output that allows for an examination of the three main budgets that govern the evolution of sea ice, namely the heat budget, the momentum budget, and the mass budget. Furthermore, we explain the aims of SIMIP in more detail and outline how its design allows us to answer some of the most pressing questions that sea ice still poses to the international climate-research community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Best Practices of Uncertainty Estimation for the National Solar Radiation Database (NSRDB 1998-2015): Preprint

It is essential to apply a traceable and standard approach to determine the uncertainty of solar resource data. Solar resource data are used for all phases of solar energy conversion projects, from the conceptual phase to routine solar power plant operation, and to determine performance guarantees of solar energy conversion systems. These guarantees are based on the available solar resource derived from a measurement station or modeled data set such as the National Solar Radiation Database (NSRDB). Therefore, quantifying the uncertainty of these data sets provides confidence to financiers, developers, and site operators of solar energy conversion systems and ultimately reduces deployment costs. In this study, we implemented the Guide to the Expression of Uncertainty in Measurement (GUM) 1 to quantify the overall uncertainty of the NSRDB data. First, we start with quantifying measurement uncertainty, then we determine each uncertainty statistic of the NSRDB data, and we combine them using the root-sum-of-the-squares method. The statistics were derived by comparing the NSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network, National Renewable Energy Laboratory's Solar Radiation Research Laboratory, and the Atmospheric Radiation Measurement program's Southern Great Plains Central Facility, in Billings, Oklahoma. The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals. Varying time averages assist to capture the temporal uncertainty of the specific modeled solar resource data required for each phase of a solar energy project; some phases require higher temporal resolution than others. Overall, by including the uncertainty of measurements of solar radiation made at ground stations, bias, and root mean square error, the NSRDB data demonstrated expanded uncertainty of 17 percent - 29 percent on hourly and an approximate 5 percent - 8 percent annual bases.

14 SOLAR ENERGY↗
DOE OSTI2021

Implementation and Evaluation of a Unified Turbulence Parameterization Throughout the Canopy and Roughness Sublayer in Noah‐MP Snow Simulations

Abstract The Noah‐MP land surface model (LSM) relies on the Monin‐Obukhov (M‐O) Similarity Theory (MOST) to calculate land‐atmosphere exchanges of water, energy, and momentum fluxes. However, MOST flux‐profile relationships neglect canopy‐induced turbulence in the roughness sublayer (RSL) and parameterize within‐canopy turbulence in an ad hoc manner. We implement a new physics scheme (M‐O‐RSL) into Noah‐MP that explicitly parameterizes turbulence in RSL. We compare Noah‐MP simulations employing the M‐O‐RSL scheme (M‐O‐RSL simulations) and the default M‐O scheme (M‐O simulations) against observations obtained from 647 Snow Telemetry (SNOTEL) stations and two AmeriFlux stations in the western United States. M‐O‐RSL simulations of snow water equivalent (SWE) outperform M‐O simulations over 64% and 69% of SNOTEL sites in terms of root‐mean‐square‐error (RMSE) and correlation, respectively. The largest improvements in skill for M‐O‐RSL occur over closed shrubland sites, and the largest degradations in skill occur over deciduous broadleaf forest sites. Differences between M‐O and M‐O‐RSL simulated snowpack are primarily attributable to differences in aerodynamic conductance for heat underneath the canopy top, which modulates sensible heat flux. Differences between M‐O and M‐O‐RSL within‐canopy and below‐canopy sensible heat fluxes affect the amount of heat transported into snowpack and hence change snowmelt when temperatures are close to or above the melting point. The surface energy budget analysis over two AmeriFlux stations shows that differences between M‐O and M‐O‐RSL simulations can be smaller than other model biases (e.g., surface albedo). We intend for the M‐O‐RSL physics scheme to improve performance and uncertainty estimates in weather and hydrological applications that rely on Noah‐MP.

Meteorology & Atmospheric Sciences↗
NASA NTRS1989

On estimating total daily evapotranspiration from remote surface temperature measurements

A method for calculating daily evapotranspiration from the daily surface energy budget using remotely sensed surface temperature and several meteorological variables is presented. Vaules of the coefficients are determined from simulations with a one-dimensional boundary layer model with vegetation cover. Model constants are obtained for vegetation and bare soil at two air temperature and wind speed levels over a range of surface roughness and wind speeds. A different means of estimating the daily evapotranspiration based on the time rate of increase of surface temperature during the morning is also considered. Both the equations using our model-derived constants and field measurements are evaluated, and a discussion of sources of error in the use of the formulation is given.

Carlson, Toby N.↗
NASA NTRS2019

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

B. D. Loomis↗
NASA NTRS2019

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

Loomis, B. D.↗
NASA NTRS1977

TDRSS performance evaluation for TDRSS services using analytical simulation

An analytical simulation package which can predict bit error rate and tracking performance for nonlinear, bandlimited satellite links was developed for the Tracking and Data Relay Satellite System (TDRSS). It is based on analytical simulation, i.e., a combination of simulation techniques and analytical performance evaluation. This allows the use of a more realistic signal format than is possible with a purely analytical approach and maintains the advantage of short computation time on bandlimited, nonlinear channels with a noisy uplink. The link models and the main features of the program are described and an overview of the mathematical approach is given. Sample results of computer runs are provided for current power budgets and system design parameters for both forward and return links.

Braun, W. R.↗
NASA NTRS1992

A technique for global monitoring of net solar irradiance at the ocean surface. II - Validation

The generation and validation of the first satellite-based long-term record of surface solar irradiance over the global oceans are addressed. The record is generated using Nimbus-7 earth radiation budget (ERB) wide-field-of-view plentary-albedo data as input to a numerical algorithm designed and implemented based on radiative transfer theory. The mean monthly values of net surface solar irradiance are computed on a 9-deg latitude-longitude spatial grid for November 1978-October 1985. The new data set is validated in comparisons with short-term, regional, high-resolution, satellite-based records. The ERB-based values of net surface solar irradiance are compared with corresponding values based on radiance measurements taken by the Visible-Infrared Spin Scan Radiometer aboard GOES series satellites. Errors in the new data set are estimated to lie between 10 and 20 W/sq m on monthly time scales.

Chertock, Beth↗
NASA NTRS1987

Nimbus 7 earth radiation budget wide field of view climate data set improvement. I - The earth albedo from deconvolution of shortwave measurements

A deconvolution method for extracting the top of the atmosphere (TOA) mean, daily albedo field from a set of wide-FOV (WFOV) shortwave radiometer measurements is proposed. The method is based on constructing a synthetic measurement for each satellite observation. The albedo field is represented as a truncated series of spherical harmonic functions, and these linear equations are presented. Simulation studies were conducted to determine the sensitivity of the method. It is observed that a maximum of about 289 pieces of data can be extracted from a set of Nimbus 7 WFOV satellite measurements. The albedos derived using the deconvolution method are compared with albedos derived using the WFOV archival method; the developed albedo field achieved a 20 percent reduction in the global rms regional reflected flux density errors. The deconvolution method is applied to estimate the mean, daily average TOA albedo field for January 1983. A strong and extensive albedo maximum (0.42), which corresponds to the El Nino/Southern Oscillation event of 1982-1983, is detected over the south central Pacific Ocean.

Hucek, Richard R.↗
DOE OSTI2018

Applications of an Updated Atmospheric Energetics Formulation

As observations and atmospheric reanalyses have improved, the diagnostics that can be computed with confidence also increase. Accordingly, a new formulation of the energetics of the atmosphere is laid out, with a view to advancing diagnostic studies of Earth’s energy budget and flows. It is utilized to produce assessments of the vertically integrated divergences in both the atmosphere and ocean. Careful conservation of mass is required, with special attention given to the hydrological cycle and redistribution of mass associated with precipitation and evaporation, and a new method for ensuring this is developed. It guarantees that the atmospheric divergence is associated with moisture and precipitation, unlike previous methods. A new term, identified as associated with the enthalpy of precipitation, is included in a preliminary way. It is sensitive to the formulation, and the use of temperature in degrees Celsius instead of Kelvin greatly reduces errors and produces the extra term with values up to about ±5 W m −2 . New results for 2000 to 2016 are presented for the vertical-mean and annual-mean diabatic atmospheric heating, atmospheric moistening, and total atmospheric energy divergence. Results for the atmospheric divergence are combined with top-of-atmosphere radiation observations to deduce total surface energy fluxes. Along with estimates of changes in ocean heat content, the Atlantic Ocean meridional heat transports are recomputed for March 2000 through 2013. The new results are compared with previous estimates and an assessment is made of the effects of the new mass balance, change in temperature scale, and the extra precipitation enthalpy term.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Adaptive multi-index collocation for uncertainty quantification and sensitivity analysis

In this paper, we present an adaptive algorithm to construct response surface approximations of high-fidelity models using a hierarchy of lower fidelity models. Our algorithm is based on multiindex stochastic collocation and automatically balances physical discretization error and response surface error to construct an approximation of model outputs. This surrogate can be used for uncertainty quantification (UQ) and sensitivity analysis (SA) at a fraction of the cost of a purely high-fidelity approach. We demonstrate the effectiveness of our algorithm on a canonical test problem from the UQ literature and a complex multi-physics model that simulates the performance of an integrated nozzle for an unmanned aerospace vehicle. We find that when the input-output response is sufficiently smooth our algorithm produces approximations that can be up to orders of magnitude more accurate than single fidelity approximations for a fixed computational budget.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multi-Fidelity Scheme for Accelerating 4D Finite Element Analysis for Mircoreactors

Next-generation microreactors are currently being designed to be operated terrestrial and extraterrestrial for remote surface power production. These systems will provide an alternative source of carbon-free energy that is versatile and can be utilized for various applications. These applications of microreactors have prompted the usage of high-fidelity unstructured finite element (FE) based approaches to provide time-dependent solutions for multiple physics fields. Computing these high-fidelity (4-D) solutions for multiple design iterations, physics fields, and transient events requires an immense computational cost. These high-fidelity solutions are computational expensive and the cost can be reduced through the implementation of less accurate low-fidelity solutions. Unlike the current fleet of commercial nuclear reactors, these next-gen systems present challenges due to the material and physical limitations required. Due to these constraints, the brute force technique of parameterizing important system characteristics determines whether a design meets the project objective. A system such as a nuclear reactor could have thousands of design parameters that affect system performance. In order to analyze the entire parameter space of such a complex system would require millions of CPU hours and countless design iterations. This costly approach is not practical due to regulatory and budget limitations. In this proposal, an approach that utilizes hybrid high-fidelity and low-fidelity FE models to reduce the computational cost of evaluating these applications in 4-D will be presented. The accuracy of the high-fidelity model and the computational efficiency of the low-fidelity model are taken advantage of to produce a solution that closely resembles the full order high-fidelity solution. By utilizing an unconverged coarse FE mesh, operation limits such as temperature, structural loading, etc., can be evaluated in an accelerated fashion and then can be spatially interpolated onto a finer mesh. The resulting error arising from the coarse mesh can be mitigated with a discrepancy function that actively quantifies and corrects the error in the coarse solution. This discrepancy function can be periodically updated with high-fidelity calculations across the temporal domain thus requiring less iterations on the fine mesh. As a result, the computational cost can be reduced for the evaluation and design iteration of microreactors. The proposal for this research contains three sections: Section 2 provides a literature review, Section 3 outlines the methodology for the proposed multi-fidelity scheme, and Section 4 displays preliminary results of the proposed research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Comparison of methods to estimate aerosol effective radiative forcings in climate models

Abstract. Uncertainty in the effective radiative forcing (ERF) of climate primarily arises from the unknown contribution of aerosols, which impact radiative fluxes directly and through modifying cloud properties. Climate model simulations with fixed sea surface temperatures but perturbed atmospheric aerosol loadings allow for an estimate of how strongly the planet's radiative energy budget has been perturbed by the increase in aerosols since pre-industrial times. The approximate partial radiative perturbation (APRP) technique further decomposes the contributions to the direct forcing due to aerosol scattering and absorption and to the indirect forcing due to aerosol-induced changes in cloud scattering, amount, and absorption, as well as the effects of aerosols on surface albedo. Here we evaluate previously published APRP-derived estimates of aerosol effective radiative forcings from these simulations conducted in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and find that they are biased as a result of two large coding errors that – in most cases – fortuitously compensate. The most notable exception is the direct radiative forcing from absorbing aerosols, which is more than 40 % larger averaged across CMIP6 models in the present study. Correcting these biases eliminates the residuals and leads to better agreement with benchmark estimates derived from double calls to the radiation code. The APRP method – when properly implemented – remains a highly accurate and efficient technique for diagnosing aerosol ERF in cases where double radiation calls are not available, and in all cases it provides quantification of the individual contributors to the ERF that are highly useful but not otherwise available.

58 GEOSCIENCES↗
NASA NTRS1983

Possible effects of the El Chichon volcanic cloud on the radiation budget of the northern tropics

A series of calculations with a one-dimensional, time-marching, radiative-convective model are performed to assess the impact of the El Chichon volcanic cloud on the radiation budget of the northern tropics during the 6-month period following the injection of volcanic material into the stratosphere. Extensive measurement of the cloud obtained from airborne, spacecraft, and ground platforms were used to define the model parameters and to test the predictions of the model. The El Chichon cloud is predicted to have caused an increase in planetary albedo of 10 percent, a decrease in total solar radiation of 2-3 percent at the ground on cloudless days, and an increase in temperature of 3.5 K at the 24-km (30-mb) level. These predictions are compatible with relevant observations, within their respective error bars.

Pollack, J. B.↗