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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 1,657 records · Page 92

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DOE OSTI2015

Short‐term time step convergence in a climate model

Abstract This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

mphys-surrogate-model

This repository contains python scripts for building and studying reduced-order-modeling representations of droplet coalescence for eventual use in atmospheric models. The included data are generated from high-fidelity superdroplet methods and are utilized by machine learning pipelines to build data-driven models of droplet size distributions that evolve under coalescence. This repository further includes scripts to determine prediction (uncertainty) intervals on the data-driven model products based on conformal prediction.

Katona, JonasE [Lawrence Livermore National Labora↗

DOE OSTI2020

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the U.S.

In this study, a process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the U.S. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation feature at 12, 25 and 50 km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 km and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency and intensity are found to be consistently underestimated in the Central U.S., particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while MCS precipitation area is too large and intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

FACETS Dynamical Downscaling Simulations over North America by the CAM-MPAS Variable-Resolution Model

Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through development of metrics and their demonstration on a hierarchy of downscaled climate datasets to quantify aspects of climate change projections that are credible, particularly for supporting decisions related to the energy-water-land nexus. As a part of this effort, we have produced a regional climate dataset using the Model for Prediction Across Scales coupled to the Community Atmosphere Model (CAM-MPAS). This global modeling framework is configured with variable-resolution meshes featuring higher resolutions over North America, as well as quasi-uniform resolution meshes across the globe. The variable-resolution configurations allow fine-scale features to be better resolved inside the refinement and interact with global-scale circulations. The dataset includes multiple uniform- (240km and 120km) and variable-resolution (200-50km, 100-25km, and 46-12km) simulations that are designed to be compatible with other regional climate simulations that contribute to the hierarchy of downscaled climate datasets of the project. Furthermore, the dataset consists of simulations for both the present-day (1989-2010) and future (2079-2100) climate and post-processing of the model output has been coordinated across the project for consistency to facilitate common analysis across the hierarchy of datasets. Altogether, this CAM-MPAS model dataset provides a unique opportunity to assess the influence of resolutions and modeling framework on model credibility and climate change projection.

Sakaguchi, Koichi↗

DOE OSTI2021

Using radar observations to evaluate 3-D radar echo structure simulated by the Energy Exascale Earth System Model (E3SM) version 1

Abstract. The Energy Exascale Earth System Model (E3SM) developed by the Department of Energy has a goal of addressing challenges in understanding the global water cycle. Success depends on correct simulation of cloud and precipitation elements. However, lack of appropriate evaluation metrics has hindered the accurate representation of these elements in general circulation models. We derive metrics from the three-dimensional data of the ground-based Next-Generation Radar (NEXRAD) network over the US to evaluate both horizontal and vertical structures of precipitation elements. We coarsened the resolution of the radar observations to be consistent with the model resolution and improved the coupling of the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) and E3SM Atmospheric Model Version 1 (EAMv1) to obtain the best possible model output for comparison with the observations. Three warm seasons (2014–2016) of EAMv1 simulations of 3-D radar reflectivity features at an hourly scale are evaluated. A general agreement in domain-mean radar reflectivity intensity is found between EAMv1 and NEXRAD below 4 km altitude; however, the model underestimates reflectivity over the central US, which suggests that the model does not capture the mesoscale convective systems that produce much of the precipitation in that region. The shape of the model-estimated histogram of subgrid-scale reflectivity is improved by correcting the microphysical assumptions in COSP. Different from previous studies that evaluated modeled cloud top height, we find the model severely underestimates radar reflectivity at upper levels – the simulated echo top height is about 5 km lower than in observations – and this result is not changed by tuning any single physics parameter. For more accurate model evaluation, a higher-order consistency between the COSP and the host model is warranted in future studies.

58 GEOSCIENCES↗

NASA NTRS1963

EVALUATION OF TIROS INFRARED DATA

Comparison of tiros ii satellite infrared measurements with the outgoing flux computed from atmospheric models

ATMOSPHERIC RADIATION↗

NASA NTRS1973

Multiple scattering theory of radiative transfer in inhomogeneous atmospheres.

In this paper we treat the multiple scattering theory of radiative transfer in plane-parallel inhomogeneous atmospheres. The treatment presented here may be adopted to model atmospheres characterized by an optical depth dependent coherent scattering phase function. For the purpose of illustration we consider the semi-infinite medium in which the absorption property of the atmosphere is characterized by an exponential function. The methodology employed here is the extension of the case treated previously by the author for homogeneous atmospheres.

Kanal, M.↗

NASA NTRS1974

UCLA International Conference on Radiation and Remote Probing of the Atmosphere, University of California, Los Angeles, Calif., August 28-30, 1973, Proceedings

Approaches for solving multiple scattering problems in planetary atmospheres are considered along with the solution of the radiative transfer theory problems by the Monte Carlo method, the radiative transfer of visible radiation in turbid atmospheres, aspects of scattering and absorption from poly-dispersed aerosols, and multiple scattering in cloud layers. Other subjects discussed include particulate sizes from polarization measurements, lidar observations of atmospheric particulate content, methods of calculating infrared transfer, molecular absorption parameters in atmospheric modelling, and infrared remote sounding. The influence of the atmosphere on spectral radiance and contrasts of natural formations measured from space is investigated and analytical results for radiative transfer in thick atmospheres are presented. Individual items are announced in this issue.

Kuriyan, J. G.↗

NASA NTRS1988

Sampling data for OSSEs

An OSSE should for the sake of realism incorporate at least some of the high-frequency, small-scale phenomena that are suppressed by atmospheric models; these phenomena should be present in the realistic atmosphere sampled by all observing sensor systems whose data are being used. Errors are presently generated for an OSSE in a way that encompasses representational errors, sampling, geophysical local bias, random error, and sensor filtering.

Hoffman, Ross↗

NASA NTRS1989

Calibrating the simple biosphere model for Amazonian tropical forest using field and remote sensing data. I - Average calibration with field data

Using meteorological and hydrological measurements taken in and above the central-Amazon-basin tropical forest, calibration of the Sellers et al. (1986) simple biosphere (SiB) model are described. The SiB model is a one-dimensional soil-vegetation-atmosphere model designed for use within GCMs models, representing the vegetation cover by analogy with processes operating within a single representative plant. The experimental systems and the procedures used to obtain field data are described, together with the specification of the physiological parameterization required to provide an average description of data. It was found that some of the existing literature on stomatal behavior for tropical species is inconsistent with the observed behavior of the complete canopy in Amazonia, and that the rainfall interception store of the canopy is considerably smaller than originally specified in the SiB model.

Sellers, Piers J.↗

NASA NTRS1989

Variational objective analysis for cyclone studies

Significant accomplishments during 1987 to 1988 are summarized with regard to each of the major project components. Model 1 requires satisfaction of two nonlinear horizontal momentum equations, the integrated continuity equation, and the hydrostatic equation. Model 2 requires satisfaction of model 1 plus the thermodynamic equation for a dry atmosphere. Model 3 requires satisfaction of model 2 plus the radiative transfer equation. Model 4 requires satisfaction of model 3 plus a moisture conservation equation and a parameterization for moist processes.

Achtemeier, Gary L.↗

NASA NTRS1990

Wolf-Rayet nebulae - Chemical enrichment and effective temperatures of the exciting stars

Extensive new spectrophotometric observations of five Wolf-Rayet nebulas are analyzed by means of models photoionized by plane-parallel and also WR atmosphere models. Abundance ratios O/H and Ne, S, Cl, and Ar relative to O are close to solar. N/H is enriched relative to solar and variable over the faces of the nebulas. He/H varies from one to three times solar. The O(+)/O - S(+)/S(2+) diagram is used in estimating T(eff) for the exciting stars. It indicates that S 308, NGC 3199, NGC 6888, and NGC 2359 are ionized by hot stars. RCW 58, RCW 104, MR 26, and MR 100 have such low-excitation spectra that their stellar T(eff) and nebular He/H cannot be reliably determined.

Rosa, Michael R.↗

NASA NTRS1997

Diagnostic Studies With GLA Fields

Assessments of the NASA Goddard Earth Observing System-1 Data Assimilation System (GEOS-1 DAS) regarding heating rates, energetics and angular momentum quantities were made. These diagnostics can be viewed as measures of climate variability. Comparisons with the NOAA/NCEP reanalysis system of momentum and energetics diagnostics are included. Water vapor and angular momentum are diagnosed in many models, including those of NASA, as part of the Atmospheric Model Intercomparison Project. Relevant preprints are included herein.

Salstein, David A.↗

NASA NTRS2013

Reducing Spread in Climate Model Projections of a September Ice-Free Arctic

This paper addresses the specter of a September ice-free Arctic in the 21st century using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that large spread in the projected timing of the September ice-free Arctic in 30 CMIP5 models is associated at least as much with different atmospheric model components as with initial conditions. Here we reduce the spread in the timing of an ice-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea ice climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea ice conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September ice extent will drop to approx. 1.7 million sq km in the mid 2040s and reach the ice-free state (defined as 1 million sq km) in 2054-2058. Under a medium-mitigation scenario, both approaches project a decrease to approx.1.7 million sq km in the early 2060s, followed by a leveling off in the ice extent.

simulation↗

DOE OSTI2013

A BIOMASS-BASED MODEL TO ESTIMATE THE PLAUSIBILITY OF EXOPLANET BIOSIGNATURE GASES

Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H{sub 2}S, CH{sub 4}, CH{sub 3}Cl, and DMS. We have applied the models to propose NH{sub 3} as a biosignature gas on a 'cold Haber World', a planet with a N{sub 2}-H{sub 2} atmosphere, and to demonstrate why gases such as CH{sub 3}Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such as CH{sub 4}, H{sub 2}S, and N{sub 2}O) produced from life that extracts energy from chemical potential energy gradients will always have false positives because geochemistry has the same gases to work with as life does, and gases (such as DMS and CH{sub 3}Cl) produced for secondary metabolic reasons are far less likely to have false positives but because of their highly specialized origin are more likely to be produced in small quantities. The biomass model estimates are valid to one or two orders of magnitude; the goal is an independent approach to testing whether a biosignature gas is plausible rather than a precise quantification of atmospheric biosignature gases and their corresponding biomasses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Numerical Representations of Marine Ice-Nucleating Particles in Remote Marine Environments Evaluated Against Observations

The clouds over remote oceans are often comprised of supercooled liquid droplets, but global models struggle to represent the complex processes that control ice formation in these clouds. One poorly understood, but critical, aspect controlling the liquid-ice partitioning in these clouds is the abundance of particles that catalyze ice crystal formation, or ice-nucleating particles (INPs). Observations show that INPs are extremely rare in remote marine environments and are dominated by an oceanic source. However, current global models do not account for these uniquely low INP concentrations and their marine source. In this work, we used observations of INPs from two previous field campaigns to evaluate INP concentrations estimated from a global climate model that incorporates particles from sea salt, marine organic matter, and mineral dust. Our results constitute an early evaluation of the potential of present-day global atmospheric models to successfully predict INP concentrations in the lowest atmospheric level that feeds clouds over the ocean. Extrapolating our approach to higher altitudes, the model suggests mineral/soil dust particles from long-range transport may also be a critical INP source for marine clouds.

2017 Office of Science Graduate Student Research (↗

NASA NTRS1975

Consideration of probability of bacterial growth for Jovian planets and their satellites

Environmental parameters affecting growth of bacteria (e.g., moisture, temperature, pH, and chemical composition) were compared with current atmospheric models for Jupiter and Saturn, and with the available physical data for their satellites. Different zones of relative probability of growth were identified for Jupiter and Saturn, with the highest in pressure regions of 1-10 million N/sq m (10 to 100 atmospheres) and 3-30 million N/sq m (30 to 300 atmospheres), respectively. Of the more than two dozen satellites, only the largest (Io, Europa, Ganymede, Callisto, and Titan) were found to be interesting biologically. Titan's atmosphere may produce a substantial greenhouse effect providing increased surface temperatures. Models predicting a dense atmosphere are compatible with microbial growth for a range of pressures at Titan's surface. For Titan's surface the probability of growth would be enhanced if (1) the surface is entirely or partially liquid (water), (2) volcanism (in an ice-water-steam system) is present, or (3) access to internal heat sources is significant.

Taylor, D. M.↗

NASA NTRS1983

LANDSAT 4 band 6 data evaluation

Computer modelled atmospheric transmittance and path radiance values were compared with empirical values derived from aircraft underflight data. Aircraft thermal infrared imagery and calibration data were available on two dates as were corresponding atmospheric radiosonde data. The radiosonde data were used as input to the LOWTRAN 5A code. The aircraft data were calibrated and utilized to generate analogous measurements. The results of the analysis indicate that there is a tendancy for the LOWTRAN model to underestimate atmospheric path radiance and overestimate atmospheric transmittance.

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