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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Azimuthally averaged wind and thermodynamic structures of tropical cyclones in global climate models and their sensitivity to horizontal resolution

Characteristics of tropical cyclones (TCs) in global climate models (GCMs) are known to be influenced by details of the model configurations, including horizontal resolution and parameterization schemes. Understanding model-to-model differences in TC characteristics is a prerequisite for reducing uncertainty in future TC activity projections by GCMs. This study performs a process-level examination of TC structures in eight GCM simulations that span a range of horizontal resolutions from 1° to 0.25°. A recently developed set of process-oriented diagnostics is used to examine the azimuthally averaged wind and thermodynamic structures of the GCM-simulated TCs. Results indicate that the inner-core wind structures of simulated TCs are more strongly constrained by the horizontal resolutions of the models than are the thermodynamic structures of those TCs. As expected, the structures of TC circulations become more realistic with smaller horizontal grid spacing, such that the radii of maximum wind (RMW) become smaller, and the maximum vertical velocities occur off the center. However, the RMWs are still too large, especially at higher intensities, and there are rising motions occurring at the storm centers, inconsistently with observations. The distributions of precipitation, moisture, radiative and surface turbulent heat fluxes around TCs are diverse, even across models with similar horizontal resolutions. At the same horizontal resolution, models that produce greater rainfall in the inner-core regions tend to simulate stronger TCs. Further, when TCs are weak, the radial gradient of net column radiative flux convergence is comparable to that of surface turbulent heat fluxes, emphasizing the importance of cloud-radiative feedbacks during the early developmental phases of TCs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Evidence for Limited Indirect Aerosol Forcing in Stratocumulus

Increases in cloud cover and condensed water contribute more than half of the indirect aerosol effect in an ensemble of general circulation model (GCM) simulations estimating the global radiative forcing of anthropogenic aerosols. We use detailed simulations of marine stratocumulus clouds and airborne observations of ship tracks to show that increases in cloud cover and condensed water in reality are far less than represented by the GCM ensemble. Our results offer an explanation for recent simplified inverse climate calculations indicating that indirect aerosol effects are greatly exaggerated in GCMs.

Ackerman, Andrew S.↗
NASA NTRS2008

Global Radiative Forcing of Coupled Tropospheric Ozone and Aerosols in a Unified General Circulation Model

Global simulations of sea salt and mineral dust aerosols are integrated into a previously developed unified general circulation model (GCM), the Goddard Institute for Space Studies (GISS) GCM II', that simulates coupled tropospheric ozone-NOx-hydrocarbon chemistry and sulfate, nitrate, ammonium, black carbon, primary organic carbon, and secondary organic carbon aerosols. The fully coupled gas-aerosol unified GCM allows one to evaluate the extent to which global burdens, radiative forcing, and eventually climate feedbacks of ozone and aerosols are influenced by gas-aerosol chemical interactions. Estimated present-day global burdens of sea salt and mineral dust are 6.93 and 18.1 Tg with lifetimes of 0.4 and 3.9 days, respectively. The GCM is applied to estimate current top of atmosphere (TOA) and surface radiative forcing by tropospheric ozone and all natural and anthropogenic aerosol components. The global annual mean value of the radiative forcing by tropospheric ozone is estimated to be +0.53 W m(sup -2) at TOA and +0.07 W m(sup -2) at the Earth's surface. Global, annual average TOA and surface radiative forcing by all aerosols are estimated as -0.72 and -4.04 W m(sup -2), respectively. While the predicted highest aerosol cooling and heating at TOA are -10 and +12 W m(sup -2) respectively, surface forcing can reach values as high as -30 W m(sup -2), mainly caused by the absorption by black carbon, mineral dust, and OC. We also estimate the effects of chemistry-aerosol coupling on forcing estimates based on currently available understanding of heterogeneous reactions on aerosols. Through altering the burdens of sulfate, nitrate, and ozone, heterogeneous reactions are predicted to change the global mean TOA forcing of aerosols by 17% and influence global mean TOA forcing of tropospheric ozone by 15%.

Liao, Hong↗
NASA NTRS1983

Numerical experiments with a stochastic zonal climate model

A zonally averaged energy balance climate model is developed to generate zonal temperature variability through fluctuating meridional energy transports. Stochastic transport fluctuations are included in the model by multiplying the eddy diffusion coefficients by Gaussian random deviates. For a variability of eddy coefficients of 50 percent, the model is found to generate an interannual temperature variability of 0.03 K for the global temperature, and 0.04 and 0.05 K for the Northern and Southern Hemispheres, respectively. It is shown that the temperature variability level generated is linearly related to the transport variability level introduced. An increase in the level of model-generated temperature variability and a change in the shape of variance spectra of temperature anomaly time series are obtained by switching from the multiplicative noise model to an additive noise model. The results of these model studies are compared with a time series of central England temperatures as well as GCM generated climate variability.

Schneider, S. H.↗
NASA NTRS2016

A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

Boundary conditions↗
NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering significant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

cloud↗
NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗
DOE OSTI2025

Uncertainty of 21st Century western U.S. snowfall loss derived from regional climate model large ensemble

Abstract The western United States is dependent on winter snowfall over its major mountain ranges, which gradually melts each year, serving as a natural reservoir for water resources. In a future warmer climate, much of this snowfall could be replaced by rain, making it more challenging to capture and store water. In this study, we utilize an ensemble of dynamically downscaled simulations forced by 14 global climate models (GCMs). These GCMs project wildly different futures, in terms of both temperature and precipitation change, producing significant uncertainty in snowfall projections. Here we exploit the robust statistics of the downscaled ensemble, and diagose the sensitivity of end-of-century snowfall loss across the region to both warming and regional wetting/drying in the driving GCM. The windward slopes of the Sierra Nevada and Cascades are particularly sensitive to warming (losing ~ 15% annual snowfall per degree warming), with little influence of precipitation. By contrast, snowfall loss in the inter-mountain west is less sensitive to warming (~ 5% K −1 ), but is significantly offset/exacerbated by precipitation changes (~ 0.5% snow per 1% precipitation). Combining such sensitivities with the warming and regional precipitation signals in the full CMIP6 ensemble, we can fully quantify likely snowfall loss and its uncertainty at any location, for any emissions scenario. We find that the western U.S. as a whole will lose 34 ± 8% of its total volumetric snowfall by end-of-century under the high-emissions SSP3-7.0 scenario, but 25 ± 6% and 17 ± 6% under the lower-emissions SSP2-4.5 and SSP1-2.6 scenarios.

Norris, Jesse (ORCID:0000000289883326)↗
NASA NTRS1988

Temperature dependence of cirrus extinction - Implications for climate feedback

The sensitivities of changes in cirrus optical properties to the changes in global temperature were investigated using data obtained in previous extensive lidar and radiometer observations of cirrus clouds. It is demonstrated how the temperature dependence of cirrus optical properties can be used in climate sensitivity calculations to yield predictions of feedback effects at various cirrus temperatures and how these properties can be parameterized simply for use in the GCM or climate models.

Platt, C. Martin R.↗
DOE OSTI2024

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗
DOE OSTI2025

Examining future changes in coastal low-level jet properties offshore California through dynamical downscaling

The coastal low-level jet, or coastal low-level jet (CLLJ), is a synoptically-forced meteorological feature frequently present offshore the western United States (U.S.). Characterized by a wind speed maximum that resides at the top of the marine boundary layer, the CLLJ is largely controlled by the location and strength of the North Pacific High (NPH) as well as the coastal geometry. Considering the rich wind resource available in this offshore region, the Bureau of Ocean Energy Management identified wind energy lease areas offshore California and supported the deployment of two U.S. Department of Energy wind lidar buoys near Morro Bay and Humboldt. Despite our relatively good understanding of the fundamental mechanisms responsible for large-scale CLLJ properties offshore the western U.S., future changes in CLLJ characteristics are less clear. To address this research challenge, and ultimately to better inform future wind turbine deployments, we use simulations driven by three global climate models (GCMs). We apply self-organizing maps to the model outputs for a historical and two future climate periods to show the range of NPH regimes that support CLLJ conditions during the warm seasons, as well as the subtle contribution from land-falling cyclones approaching the mainland during the cold seasons. Compared to the historical period, the three GCM-driven simulations agree that CLLJ conditions will become more (less) prevalent from central California northward (southward). They agree less with respect to future changes in maximum CLLJ wind speeds and CLLJ heights. However, after considering model biases present during the historical period, wind speeds between the models are actually more similar during the 2070–2095 period than during the historical period. The potential combination of more frequent CLLJ conditions characterized by relatively consistent wind speeds occurring at lower heights across northern California suggests that the Humboldt lease area may be ideal for a long-term wind turbine deployment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

The effect of global warming on lightning frequencies

The first attempt to model global lightning distributions by using the Goddard Institute for Space Studies (GISS) GCM is reported. Three sets of observations showing the relationship between lightning frequency and cloud top height are shown. Zonally averaged lightning frequency observed by satellite are compared with those calculated using the GISS GCM, and fair agreement is found. The change in lightning frequency for a double CO2 climate is calculated and found to be nearly 2.23 x 10 exp 6 extra lightning flashes per day.

Price, Colin↗
NASA NTRS2000

Influence of the Latitudinal Temperature Gradient on Soil Dust Concentration and Deposition in Greenland

To investigate the effects of changes in the latitudinal temperature gradient and the global mean temperature on dust concentration in the Northern Hemisphere, experiments with the Goddard Institute for Space Studies General Circulation Model (GISS GCM) are performed. The dust concentration over Greenland is calculated from sources in central and eastern Asia, which are integrated on-line in the model. The results show that an increase in the latitudinal temperature gradient increases both the Asian dust source strength and the concentration over Greenland. The source increase is the result of increased surface winds, and to a minor extent, the increase in Greenland dust is also associated with increased northward transport. Cooling the climate in addition to this increased gradient leads to a decrease in precipitation scavenging, which helps produce a further (slight) increase in Greenland dust in this experiment. Reducing the latitudinal gradient reduces the surface wind and hence the dust source, with a subsequent reduction in Greenland dust concentrations. Warming the climate in addition to this reduced gradient leads to a further reduction in Greenland dust due to enhanced precipitation scavenging. These results can be used to evaluate the relationship of Greenland ice core temperature changes to changes in the latitudinal and global temperatures.

Tegen, Ina↗
NASA NTRS2000

Influence of the Latitudinal Temperature Gradient on Soil Dust Concentration and Deposition in Greenland

To investigate the effects of changes in the latitudinal temperature gradient and the global mean temperature on dust concentration in the Northern Hemisphere, experiments with the GISS GCM (Goddard Institute for Space Studies General Circulation Model) are performed. The dust concentration over Greenland is calculated from sources in central and eastern Asia, which are integrated on-line in the model. The results show that an increase in the latitudinal temperature gradient increases both the Asian dust source strength and the concentration over Greenland. The source increase is the result of increased surface winds, and to a minor extent, the increase in Greenland dust is also associated with increased northward transport. Cooling the climate in addition to this increased gradient leads to a decrease in precipitation scavenging, which helps produce a further (slight) increase in Greenland dust in this experiment. Reducing the latitudinal gradient reduces the surface wind and hence the dust source, with a subsequent reduction in Greenland dust concentrations. Warming the climate in addition to this reduced gradient leads to a further reduction in Greenland dust due to enhanced precipitation scavenging. These results can be used to evaluate the relationship of Greenland ice core temperature changes to changes in the latitudinal and global temperatures.

Tegen, Ina↗
NASA NTRS1991

A simplified biosphere model for global climate studies

A comprehensive analysis of the simple biosphere model (SIB) of Sellers et al. (1986) is performed in an effort to bridge the gap between the typical hydrological treatment of the land surface biosphere and the conventional general circulation model treatment, which is specified through a single parameter. Approximations are developed that stimulate the effects of reduced soil moisture more simply, maintaining the essence of the biophysical concepts utilized in SIB. Comparing the reduced parameter biosphere with those from the original formulation in a GCM and a zero-dimensional model shows the simplified version to reproduce the original results quite closely.

Xue, Y.↗
NASA NTRS2005

Martian Atmospheric Circulation and Climate

This project was submitted with four work tasks. The reviews recommended focusing on the following three, with an appropriately reduced budget: 1. In the first, we proposed to use Thermal Emission Spectrometer (TES) data to examine the general circulation of the atmosphere and to better constrain and validate a Mars General Circulation Model (GCM). 2. In the second, we proposed to examine processes responsible for the injection of dust into the atmosphere. We will conduct a global, seasonal survey of dust lifting events, and specifically of dust devil activity, using MGS MOC, MGS TES, and Odyssey THEMIS data. The results of this survey will be compared with model predictions of dust devil and other dust lifting processes. It is expected that some of the observational results will motivate specific simulations with the GCM and mesoscale models. 3. In the third task, we proposed to extract seasonal and spatial near-surface wind information from aeolian streaks. Detailed analysis will focus on streaks in the polar regions and in regions of large topography (such as Tharsis). The streak information will be used along with the mesoscale model to examine the processes that control local and regional scale flow patterns.

Richardson, Mark I.↗
NASA NTRS2019

Inter-annual variation of tropical cyclones simulated by GEOS-5 AGCM with modified convection scheme

The Goddard Earth Observing System version 5 (GEOS-5) global climate model with a 50-km horizontal resolution is forced by observed sea surface temperature (SST) to examine the fidelity of the seasonal-mean and inter-annual variation of tropical cyclones (TCs) in the western North Pacific (WNP) and the North Atlantic (NATL). The standard Relaxed Arakawa Schubert (RAS) deep convection scheme is modified to improve the representation of TCs, where the scheme implements a stochastic limit of the cumulus entrainment rate. The modification drives mid- and upper-tropospheric cooling and low- to mid-tropospheric drying in the background state, which tends to increase atmospheric instability. This enables the model to increase convective variability on an intra-seasonal timescale and improve the simulation of intense storms. Five-member ensemble runs with the modified RAS scheme for 12 years (1998–2009) exhibit realistic spatial distributions in the climatological-mean TC development area and their pathways over WNP and NATL. The GCM is able to reproduce the inter-annual variation of accumulated cyclone energy (ACE) by prescribing yearly varying observed SST even though the individual TC intensity is still underpredicted. A sensitivity of TC activity to El Niño–Southern Oscillation (ENSO) phase is also reproduced realistically over WNP in terms of the spatial pattern changes in the main development region and TC pathways. However, the model exhibits a notable deficiency in NATL in reproducing the observed inter-annual variation of TC activity and the sensitivity to the ENSO.

accumulated cyclone energy↗
DOE OSTI2022

Evaluation of CMIP6 GCMs Over the CONUS for Downscaling Studies

Despite the necessity of Global Climate Models (GCMs) sub-selection in downscaling studies, an objective approach for their selection is currently lacking. Building on the previously established concepts in GCMs evaluation frameworks, we develop a weighted averaging technique to remove the redundancy in the evaluation criteria and rank 37 GCMs from the sixth phase of the Coupled Models Intercomparison Project over the contiguous United States. GCMs are rated based on their average performance across 66 evaluation measures in the historical period (1981–2014) after each metric is weighted between zero and one, depending on its uniqueness. The robustness of the outcome is tested by repeating the process with the empirical orthogonal function analysis in which each GCM is ranked based on its sum of distances from the reference in the principal component space. The two methodologies work in contrasting ways to remove the metrics redundancy but eventually develop similar GCMs rankings. A disparity in GCMs' behavior related to their sensitivity to the size of the evaluation suite is observed, highlighting the need for comprehensive multi-variable GCMs evaluation at varying timescales for determining their skillfulness over a region. The sub-selection goal is to use a representative set of skillful models over the region of interest without substantial overlap in their future climate responses and modeling errors in representing historical climate. Additional analyses of GCMs' independence and spread in their future projections provide the necessary information to objectively select GCMs while keeping all aspects of necessity in view.

54 ENVIRONMENTAL SCIENCES↗