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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A parameterization of sub-grid topographical effects on solar radiation in the E3SM Land Model (version 1.0): implementation and evaluation over the Tibetan Plateau

Abstract. Topography exerts significant influences on the incoming solar radiation at the land surface. A few stand-alone regional and global atmospheric models have included parameterizations for sub-grid topographic effects on solar radiation. However, nearly all Earth system models (ESMs) that participated in the Coupled Model Intercomparison Project (CMIP6) use a plane-parallel (PP) radiative transfer scheme that assumes that the terrain is flat. In this study, we incorporated a well-validated sub-grid topographic (TOP) parameterization in the Energy Exascale Earth System Model (E3SM) Land Model (ELM) version 1.0 to quantify the effects of sub-grid topography on solar radiation flux, including the shadow effects and multi-scattering between adjacent terrain. We studied the role of sub-grid topography by performing ELM simulations with the PP and TOP schemes over the Tibetan Plateau (TP). Additional ELM simulations were performed at multiple spatial resolutions to investigate the role of spatial scale on sub-grid topographic effects on solar radiation. The Moderate Resolution Imaging Spectroradiometer (MODIS) data was used to compare with the ELM simulations. The results show that topography has non-negligible effects on surface energy budget, snow cover, snow depth, and surface temperature over the TP. The absolute differences in surface energy fluxes for net solar radiation, latent heat flux, and sensible heat flux between TOP and PP exceed 20, 10, and 5 W m−2, respectively. The differences in land surface albedo, snow cover fraction, snow depth, and surface temperature between TOP and PP exceed 0.1, 0.1, 10 cm, and 1 K, respectively. The magnitude of the sub-grid topographic effects is dependent on seasons and elevations and is also sensitive to the spatial scales. Although the sub-grid topographic effects on solar radiation are larger with more spatial details at finer spatial scales, they cannot be simply neglected at coarse spatial scales. When compared to MODIS data, incorporating the sub-grid topographic effects overall reduces the biases of ELM in simulating surface energy balance, snow cover, and surface temperature, especially in the high-elevation and snow-covered regions over the TP. The inclusion of sub-grid topographic effects on solar radiation parameterization in ELM will contribute to advancing our understanding of the role of the surface topography on terrestrial processes over complex terrain.

Hao, Dalei (ORCID:0000000334979774)↗
NASA NTRS1991

Nonlinear influence of mesoscale land use on weather and climate

It is shown that the influence of mesoscale landscape spatial variability on the atmosphere must be parameterized or explicitly modeled in larger-scale atmospheric model simulations including general circulation models. The mesoscale fluxes of heat that result from this variability are shown to be of the same order of magnitude but with a different vertical structure than found for the turbulent fluxes. These conclusions are based on experiments in which no phase changes of water were permitted. To parameterize surface thermal inhomogeneities, the influence of landscape must be evaluated using spectral analysis or an equivalent procedure. To include the nonlinear contribution of each scale, numerical model simulations for the range of observed surface and overlying atmospheric conditions must be performed.

Pielke, R. A.↗
NASA NTRSDate not supplied

Evaluating Subgrid-Scale Properties of Low Clouds over the Beaufort Sea in Arctic System Reanalysis using ARISE Airborne In Situ Observations

Arctic low clouds influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Unfortunately, atmospheric models and retrospective analysis (reanalysis) products struggle to accurately simulate the occurrence and properties of low clouds in the Arctic. To better understand the magnitude and possible causes of this problem, we analyze the disagreements between the Arctic System Reanalysis version 2 (ASR) and data taken during the September 2014 Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) airborne campaign conducted over the Beaufort Sea. Previous analysis of grid scale-averaged meteorological variables revealed a lack of cloud water produced in ASR, related to warm/dry biases, a failure to produce sufficient cloud water in conditions that are observed to be favorable for large cloud water values, and sampling issues with the ARISE flight paths. However, ARISE collected meteorological observations at one second intervals, offering spatial data resolution comparable to the subgrid scale of ASR. Subgrid scale properties and processes must be parameterized in conventional atmospheric models and reanalyses such as ASR, and often rely on assumed distributions of meteorological variables about the grid box mean state. To enable an examination of the realism of ASR’s subgrid scale properties, we use high resolution data from ARISE determine the “subgrid scale” distributions of cloud water and thermodynamic variables in the real atmosphere. Preliminary results show that the subgrid scale distribution of thermodynamic variables about the grid scale mean resembles the triangular distribution assumed in many bulk microphysical parameterization schemes, but also with tails resembling Gaussian distributions. The main goal is to understand the partitioning of the total available atmospheric water into water vapor and cloud water. Models typically covert some percentage of total water in a grid box to cloud water based on the estimated amount of supersaturation from the assumed vapor distribution. The ARISE measurements can reveal the relationship between subgrid scale supersaturation and the partition between cloud water and water vapor.

Jason Brant Dodson↗
DOE OSTI2021

Quantifying physical parameterization uncertainties associated with land-atmosphere interactions in the WRF model over Amazon

The Weather Research and Forecasting (WRF) model can be used to diagnose regional land-atmosphere (L-A) coupling strength in the absence of sufficient observations but subjected to uncertainties associated with model physical parameterizations. In this study, we propose a framework to quantify and reduce model physical parameterization uncertainties associated with surface fluxes and L-A coupling. An ensemble of WRF simulations with different physical schemes is used to simulate surface fluxes and land-atmosphere coupling strength over the Amazon region. The physical parameterizations investigated include cloud microphysics (MP), land surface processes (LSM), planetary boundary layer (PBL), surface layer (SL), and cumulus (CU). We perform 120 ensemble simulations using the WRF model and different combinations of six MPs, three LSMs, six PBLs and SLs and three CUs. The measurements from the GoAMAZON field campaign and satellite data are used to evaluate model performance. A Multi-way analysis of variance (ANOVA) approach is applied to quantify the relative importance of different physics processes on L-A coupling. The Tukey’s test is used to sort schemes that have no significant differences into one group. The suite of physics that result in the best simulations of the corresponding variables are selected based on the Taylor skill score. Results show that the relative importance of processes and their interaction vary with the variables of interest. For example, CU was the most important process in modulating soil moisture, 2 m-humidity, latent heat, and net radiation. LSM showed dominant effects on 2 m-temperature and also has the largest impact on sensible heat and the lifting condensation level. The best physical parameterization ensembles show much narrower ranges of the variables of interest than the priori ensemble. Results of this study show the roles of different physical processes in modulating L-A interactions, quantify model uncertainties from physical processes, and provide insights for improving the model physics parameterizations.

Wang, Chen↗
DOE OSTI2021

Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Multiscale Simulation of Precipitation Over East Asia by Variable Resolution CAM-MPAS

This study evaluates the precipitation over East Asia simulated by the variable resolution CAM-MPAS featuring the Model for Prediction Across Scales (MPAS) atmospheric dynamical core coupled with the physics parameterizations of the Community Atmosphere Model (CAM) version 5.4. Two CAM-MPAS experiments, one with a global quasi-uniform resolution mesh of 120 km (MPAS-UR) and the other with a variable resolution mesh of 30 to 120 km refined over East Asia (MPAS-VR), are conducted from 1989 to 2005 following the Atmospheric Model Intercomparison Project protocol. Two regional climate model simulations at ~25 km resolution from the Coordinated Regional Downscaling Experiment East Asia second plan are also analyzed for comparison. Results show that CAM-MPAS performs better than the selected regional models in simulating the precipitation climatology over East Asia. Compared with MPAS-UR, MPAS-VR with refinement over East Asia better simulates the precipitation over and around the Tibetan Plateau (TP), the frequency distribution of light, moderate, and heavy precipitation in various regions of China, and the interannual precipitation pattern associated with the East Asian summer monsoon. The improvements in MPAS-VR relative to MPAS-UR largely come from the decreased grid spacing rather than the use of finer-scale terrain information. Particularly, decreased grid spacing is more essential for simulating the precipitation magnitude over TP and the location of peak precipitation south of TP, likely due to the better resolved physical and dynamical processes associated with orographic precipitation. The 30-120 km CAM-MPAS model is shown to be a promising tool for precipitation simulation over East Asia.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1982

A simple atmospheric model of relevance to El Nino

A linear, equatorial, beta-plane atmosphere model with heating parameterized in terms of SST anomalies is developed and used to simulate surface wind anomalies in the equatorial Pacific during El Nino. The model results show some similarity to observations with respect to movement of the major convergence zones, and equatorial wind anomaly patterns in the central and western Pacific. There is considerable discrepancy between the model results and observations in much of the eastern Pacific, especially in the South Pacific high and southeast trades regions. The results suggest that some additional mechanisms may be responsible for these apparently sizeable and spatially coherent fluctuations, but that a direct link between wind anomalies and SST anomalies may indeed exist in much of the equatorial Pacific.

Zebiak, S. E.↗
NASA NTRS1991

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

Johnson, Kevin D.↗
NASA NTRS1978

Documentation of a ground hydrology parameterization for use in the GISS atmospheric general circulation model

The moisture transport processes related to the earth's surface relevant to the ground circulation model GCM are presented. The GHM parametrizations considered are: (1) ground wetness and soil parameters; (2) precipitation; (3) evapotranspiration; (4) surface storage of snow and ice; and (5) runout. The computational aspects of the GHM using computer programs and flow charts are described.

Lin, J. D.↗
NASA NTRS2016

Exploring Climatology and Long-Term Variations of Aerosols from NASA Reanalysis MERRA-2 with Giovanni

Dust plays important roles in energy cycle and climate variations. The dust deposition is the major source of iron in the open ocean, which is an essential micronutrient for phytoplankton growth and therefore may influence the ocean uptake of atmospheric CO2. Mineral dust can also act as fertilizer for forests over long time periods. Over 35 years of simulated global aerosol products from NASA atmospheric reanalysis, second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) are available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). The MERRA-2 covers the period 1980-present, continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated by using MERRA-2 aerosol model, which interact directly with the radiation parameterization, and radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Dust deposition data along with other major aerosol compositions (e.g. black carbon, sea salt, and sulfate, etc.) are simulated as dry and wet deposition, respectively. The hourly and monthly data are available at spatial resolution of 0.5ox0.625o (latitude x longitude). Quick data exploration of climatology and interannual variations of MERRA-2 aerosol can be done through the online visualization and analysis tool, Giovanni. This presentation, using dust deposition as an example, demonstrates a number of MERRA-2 data services at GES DISC. Global distributions of dust depositions, and their seasonal and inter-annual variations are investigated from MERRA-2 monthly aerosol products.

data services↗
NASA NTRS2004

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were sigmficantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-china peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and gradient, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation apd associated moisture transport and convection.

Wang, Yansen↗
NASA NTRS2004

Simulation of the Onset of the Southeast Asian Monsoon during 1997 and 1998: The Impact of Surface Processes

The onset of the southeast Asian monsoon during 1997 and 1998 was simulated by coupling a mesoscale atmospheric model (MM5) and a detailed, land surface model, PLACE (the Parameterization for Land-Atmosphere-Cloud Exchange). The rainfall results from the simulations were compared with observed satellite data from the TRMM (Tropical Rainfall Measuring Mission) TMI (TRMM Microwave Imager) and GPCP (Global Precipitation Climatology Project). The control simulation with the PLACE land surface model and variable sea surface temperature captured the basic signatures of the monsoon onset processes and associated rainfall statistics. Sensitivity tests indicated that simulations were significantly improved by including the PLACE land surface model. The mechanism by which the land surface processes affect the moisture transport and the convection during the onset of the southeast Asian monsoon were analyzed. The results indicated that land surface processes played an important role in modifying the low-level wind field over two major branches of the circulation: the southwest low-level flow over the Indo-China peninsula and the northern, cold frontal intrusion from southern China. The surface sensible and latent heat fluxes modified the low-level temperature distribution and merit, and therefore the low-level wind due to the thermal wind effect. The more realistic forcing of the sensible and latent heat fluxes from the detailed, land surface model improved the low-level wind simulation and associated moisture transport and convection.

Wang, Yansen↗
DOE OSTI2022

Aircraft Observations of Turbulence in Cloudy and Cloud-Free Boundary Layers Over the Western North Atlantic Ocean From ACTIVATE and Implications for the Earth System Model Evaluation and Development

This study examines boundary layer turbulence derived from high temporal resolution meteorological measurements from 40 research flights over the western North Atlantic Ocean during the 2020 deployments of ACTIVATE. Frequency distributions of various turbulent quantities reveal stronger turbulence during the winter deployment than in summer and for cloud‐topped than in cloud‐free boundary layers during the summer deployment. Maximum turbulence kinetic energy (TKE) is most often within cloud from observations in winter and summer, whereas it is mostly below cloud in both seasons by a global model turbulence parameterization. Further, bivariate frequency distributions are consistent with the bivariate Gaussian probability distribution functions assumed for the closure of higher‐order turbulence/shallow convection parameterizations used by some global models. Turbulence simulated by the Community Atmosphere Model version 6 and the Energy Exascale Earth System Model Atmosphere Model version 2 using such parameterizations is not as strong as observed, with more TKE going into vertical wind perturbations rather than into zonal wind perturbations as observed, suggesting that the treatment of turbulence in Earth system models still needs to be further improved.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Rationalizing Burned Carbon with Carbon Monoxide Exported from South America

We present several estimates cross-checking the fluxes of carbon to the atmosphere from burning, comparing models that are based on simple land-surface parameterizations and atmospheric transport dynamics. Both estimates made by NASA Ames and USP modeling techniques are quite high compared to some detailed satellite/land-use studies of emissions. The flux of carbon liberated to the atmosphere via biomass burning is important for several reasons. This flux is a fundamental statistic for the parameterization of the large-scale flux of gases controlling the reactive greenhouse gases methane and ozone. Similarly, it is central to the estimation of the translocation of nitrogen and pyrodenitrification in the tropics. Thirdly, CO2 emitted from rainforest clearing contributes directly to carbon lost from the rainforest system as it contributes to greenhouse gas forcing. While CO2 from pasturage, agriculture, etc, is considered to be reabsorbed seasonally, and so "off budget" for the carbon cycle, it must also be accounted. CO2 anomalies related to daily weather and interannual climatic variation are strong enough to perturb our scientific perception of long-term carbon storage trends. We compare fluxes deduced from land-use statistics (originally, W.M. Hao) and from satellite hot pixels (A. Setzer) with atmospheric fluxes determined by the mesoscale/continental scale models RAMS and MM5, and point to some new work with highly resolved global models (the NASA Data Assimilation Office's GEOS4). Our simulations are tied to events, so that measured tracers like CO tie the models directly to the burning and meteorology of a specific period. We point out a particular sensitivity in estimates based on CO, and indicate how analysis of CO2 along with other biomass-burning tracers may lead to an improved multi-species estimator of carbon burned.

Chatfield, R.↗
DOE OSTI2022

Mesoscale Convective Systems Simulated by a High–Resolution Global Nonhydrostatic Model Over the United States and China

Mesoscale convective systems (MCSs) contribute a large fraction of warm-season precipitation and generate hazardous weather with substantial socio-economic impacts. Uncertainties in convection parameterizations in climate models limit our understanding of MCS characteristics and reliability of future projection. We examine the MCS simulation from the global 14-km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) without cumulus parameterization against satellite observation from Global Precipitation Measurement (GPM) during 2001-2008. We focus on MCSs over the central U.S. and eastern China where MCSs prevail from March to August. A process-oriented tracking method incorporating both cloud and precipitation criteria is used to identify and track MCSs. About 140/100 MCSs initiate in the central U.S./eastern China per warm season and most of them initiate east of high mountains and in coastal regions. The frequency distribution of MCS lifetime is well captured in NICAM. But the simulated MCSs have stronger precipitation, smaller precipitation area, and larger cold cloud system than observed in both regions, which may be caused by weak entrainment as it is not well resolved at 14 km resolution. Here, the simulated MCS number is also underestimated in summer. By examining the climatological and MCS large-scale environments, the significant underestimation of MCS number in summer over the central U.S. may be attributed to the large climatological dry bias in the atmosphere. For China, mean moisture in summer is well simulated but deficiency in capturing the dynamic condition related to the coastal topography for triggering convection may have contributed to underestimation of MCS even in a sufficiently moist environment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Studies in the parameterization of cloudiness in climate models and the analysis of radiation fields in general circulation models

Broad-band parameterizations for atmospheric radiative transfer were developed for clear and cloudy skies. These were in the shortwave and longwave regions of the spectrum. These models were compared with other models in an international effort called ICRCCM (Intercomparison of Radiation Codes for Climate Models). The radiation package developed was used for simulations of a General Circulation Model (GCM). A synopsis is provided of the research accomplishments in the two areas separately. Details are available in the published literature.

HARSHVARDHAN↗
NASA NTRS1992

Adaptation of a matrix parameterization of the middle atmospheric radiative cooling for an arbitrary vertical coordinate grid

Matrices corresponding to a revised vertical grid are shown to be derived from the original grid by integrating the radiative cooling rate over model layers. The method is applied to temperature profiles that represent average or extreme atmospheric conditions and a range of vertical resolutions. The example makes use of the 15-micron CO2 band parameterization proposed by Akmaev and Shved (1982) for the LTE region of the middle atmosphere. Cooling rate errors provided by the present method are not more than 0.11 K/day for a vertical grid spacing of less than 5 km. The matrix transformation method is shown to be valuable for adapting effective matrix parameterizations of middle atmosphere cooling to atmospheric models with arbitrary vertical resolutions.

Akmaev, R. A.↗