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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resource systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the Himalayan Tila river basin, the annual average energy production is expected to increase under future hydroclimatic conditions (up to 39% in Tila-2 hydropower project, suggested by ensemble mean). Furthermore, this increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is region-specific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Planning the Next Decade of Coordinated Research to Better Understand and Simulate Marine Low Clouds

Marine low clouds have a large impact on the Earth’s energy and hydrologic cycle. They strongly reflect incoming solar radiation, with little compensating impact on outgoing longwave radiation resulting in a net cooling of the climate. The representation of marine low clouds in climate models is one of the largest uncertainties in the estimation of climate sensitivity (e.g. Bony and Dufresne 2005), and marine low clouds are critical mediators of global aerosol radiative forcing (Zelinka et al. 2014). Despite the importance of these cloud systems to the Earth’s climate, their parameterization continues to be challenging, due to an incomplete understanding of key processes that regulate them and insufficient resolution of these processes in models. To help define research pathways to address outstanding issues related to our understanding of marine low clouds, a workshop was held January 27-29, 2016 at Brookhaven National Laboratory. The overarching goal was to identify current gaps in knowledge or simulation capabilities and promising strategies for addressing them, with a particular emphasis on improving the representation of marine low clouds in climate models and contributions that could be made with U.S. Department of Energy Atmospheric System Research support using Atmospheric Radiation Measurement facility measurements.

Wood, Robert↗
DOE OSTI2021

AI Scaling Laws for Extremes (AISLE)

Focal Area(s) Using artificial intelligence to understand the physics of hydrologic events across temporal and spatial scales, to assess their representation in climate models, and to predict their response to climate warming. This covers both the prescribed foci of (2) predictive modeling using a hierarchy of models and (3) insight gleaned from complex data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

On the representation of aerosol activation and its influence on model-derived estimates of the aerosol indirect effect

Abstract. Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNCs). However, different activation schemes can exhibit different sensitivities to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC (two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC) coupled with the National Center for Atmospheric Research's (NCAR) Community Earth System Model (CESM; version 1.2)). Although the model produces a reasonable present-day CDNC climatology when compared with observations regardless of the scheme used, ΔCDNCs between the present and preindustrial era regionally increase by over 100 % in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity may lead to a different evolution of the model meteorology, and ultimately to a spread of over 0.8 W m −2 in global average shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom intercomparison. Model-derived AIE strongly scales with the simulated preindustrial CDNC burden, and those models with the greatest preindustrial CDNC tend to have the smallest AIE, regardless of their ΔCDNC. This suggests that present-day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of the AIE, which will arise from differences in model estimates of the preindustrial aerosol and cloud climatology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

The Benefits of Global High Resolution for Climate Simulation: Process Understanding and the Enabling of Stakeholder Decisions at the Regional Scale

Many think that the time scales of the Paris Climate Agreement indicate urgent action is required on climate policies over the next few decades, in order to avoid the worst risks posed by climate change. On these relatively short time scales the combined effect of climate variability and change are both key drivers of extreme events, with decadal time scales also important for infrastructure planning. Hence, in order to assess climate risk on such time scales, we require climate models to be able to represent key aspects of both internally driven climate variability and the response to changing forcings. In this paper we argue that we now have the modeling capability to address these requirements—specifically with global models having horizontal resolutions considerably enhanced from those typically used in previous Intergovernmental Panel on Climate Change (IPCC) and Coupled Model Intercomparison Project (CMIP) exercises. The improved representation of weather and climate processes in such models underpins our enhanced confidence in predictions and projections, as well as providing improved forcing to regional models, which are better able to represent local-scale extremes (such as convective precipitation). We choose the global water cycle as an illustrative example because it is governed by a chain of processes for which there is growing evidence of the benefits of higher resolution. At the same time it comprises key processes involved in many of the expected future climate extremes (e.g., flooding, drought, tropical and midlatitude storms).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Performance analysis of fully explicit and fully implicit solvers within a spectral element shallow-water atmosphere model

In this study, explicit Runge–Kutta methods and implicit multistep methods utilizing a Newton–Krylov nonlinear solver are evaluated for a range of configurations of the shallow-water dynamical core of the spectral element community atmosphere model to evaluate their computational performance. These configurations are designed to explore the attributes of each method under different but relevant model usage scenarios including varied spectral order within an element, static regional refinement, and scaling to the largest problem sizes. This analysis is performed within the shallow-water dynamical core option of a full climate model code base to enable a wealth of simulations for study, with the aim of informing solver development within the more complete hydrostatic dynamical core used for climate research. The limitations and benefits to using explicit versus implicit methods, with different parameters and settings, are discussed in light of the trade-offs with Message Passing Interface (MPI) communication and memory and their inherent efficiency bottlenecks. Given the performance behavior across the configurations analyzed here, the recommendation for future work using the implicit solvers is conditional based on scale separation and the stiffness of the problem. For the regionally refined configurations, the implicit method has about the same efficiency as the explicit method, without considering efficiency gains from a preconditioner. The potential for improvement using a preconditioner is greatest for higher spectral order configurations, where more work is shifted to the linear solver. Finally, initial simulations with OpenACC directives to utilize a Graphics Processing Unit (GPU) when performing function evaluations show improvements locally, and that overall gains are possible with adjustments to data exchanges.

58 GEOSCIENCES↗
DOE OSTI2016

Barotropic and Baroclinic Eddy Feedbacks in the Midlatitude Jet Variability and Responses to Climate Change–Like Thermal Forcings

Abstract Studies have suggested that the persistence in the meridional vacillation of the midlatitude jet (i.e., annular mode time scale) in comprehensive climate models is related to the model biases in climatological jet latitude, with important implications for projections of future climates and midlatitude weather events. Through the use of the recently developed finite-amplitude wave activity formalism and feedback quantifying techniques, this paper has quantified the role of barotropic and baroclinic eddy feedbacks in annular mode time scales using an idealized dry atmospheric model. The eddy–mean flow interaction that characterizes the persistent anomalous state of the midlatitude jet depends on processes associated with the lower-tropospheric source of vertically propagating Rossby waves, baroclinic mechanisms, and processes associated with upper-tropospheric wave propagation and breaking, barotropic mechanisms. A variety of climate change–like thermal forcings are used to generate a range of meridional shifts in the midlatitude eddy-driven jet. The idealized model shows a reduction in annular mode time scale associated with an increase in jet latitude, similar to comprehensive climate models. This decrease in time scale can be attributed to a similar decrease in the strength of the barotropic eddy feedback, which, in the positive phase of the annular mode, is characterized by anomalous potential vorticity (PV) mixing on the equatorward flank of the climatological jet. The decrease in subtropical PV mixing is, in turn, associated with a stronger subtropical jet as the eddy-driven jet is more distant from the subtropics. These results highlight the importance of subtropical eddy–mean flow interactions for the persistence of an eddy-driven jet.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bias Correction and Statistical Downscaling of Future Solar Irradiance Projections Using the NSRDB

Assessing renewable energy resources under future climate scenarios has been highlighted to understand potential impacts of future climate change in renewable generation on the power sector. Climate model projection has been recognized by the renewable energy community as a useful data set to analyze the impacts of future climate change on renewable resources. However, future climate projections generated from general circulation models (GCMs) contain inherent biases that need to be corrected for accurate analysis of future projections of climate variables. In addition, the coarse spatiotemporal resolution of GCMs needs to be improved for regional climate studies. In this work, we develop statistical methods to downscale future projections of global horizontal irradiance (GHI) in a computationally efficient way. Our approach builds statistical downscaling models that correct bias of climate projection of GHI and downscale the future GHI projection from daily-scale to hourly-scale. The National Solar Radiation Database (NSRDB) is used to calibrate the statistical models and validate the downscaled GHI projections across the contiguous United State (CONUS). Preliminary results show that the statistical approach efficiently downscales climate projections of GHI with a nBIAS of 3%, nMAE of 34 % and nRMSE of 46% calculated against NSRDB for CONUS. This study describes the implemented methodology and initial results as well as future research to create high-resolution climate data sets for solar energy applications.

analytical models↗
DOE OSTI2017

Global long-range transport and lung cancer risk from polycyclic aromatic hydrocarbons shielded by coatings of organic aerosol

Polycyclic aromatic hydrocarbons (PAHs) have toxic impacts on ecosystems and human health. Laboratory measurements show that one of the most carcinogenic PAHs, benzo(a)pyrene, which is adsorbed on surfaces of soot particles, reacts very quickly with atmospheric oxidants like ozone within ~2 hours. Yet, field observations indicate that it actually persists for much longer periods in the atmosphere, and this large discrepancy is not well understood. Driven by novel experimental understanding, we develop a new modelling approach, whereby particle-bound BaP is shielded from oxidation by a coating of viscous organic aerosol (OA). We show that application of this new approach in a global climate model leads to higher atmospheric BaP concentrations that agree much better with measurements, compared to the default model, as well as stronger long-range transport and greater deposition fluxes. Here, this new approach also predicts elevated lung-cancer risk from PAHs. Predicted oxidation of BaP is highest over a tropical belt where OA is liquid-like.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

STRATOSPHERIC TEMPERATURES AND WATER LOSS FROM MOIST GREENHOUSE ATMOSPHERES OF EARTH-LIKE PLANETS

A radiative-convective climate model is used to calculate stratospheric temperatures and water vapor concentrations for ozone-free atmospheres warmer than that of modern Earth. Cold, dry stratospheres are predicted at low surface temperatures, in agreement with recent 3D calculations. However, at surface temperatures above 350 K, the stratosphere warms and water vapor becomes a major upper atmospheric constituent, allowing water to be lost by photodissociation and hydrogen escape. Hence, a moist greenhouse explanation for loss of water from Venus, or some exoplanet receiving a comparable amount of stellar radiation, remains a viable hypothesis. Temperatures in the upper parts of such atmospheres are well below those estimated for a gray atmosphere, and this factor should be taken into account when performing inverse climate calculations to determine habitable zone boundaries using 1D models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Collaborative Research: Centralized Activities in Support of the Radiative Forcing Model Intercomparison Project (Final Technical Report)

This final technical report summarizes the work accomplished by Atmospheric and Environmental Research in support of the Radiative Forcing Model Intercomparison Project, an international effort to assess sources of error and spread in the radiative forcing calculated by state-of-the-art climate models for historical and future climate studies. Our efforts on this project focused on the performing the line-by-line reference calculations for the gas forcing component of RFMIP. This included enhancing AER's line-by-line radiation model with the latest spectroscopic updates, completing the longwave and shortwave clear-sky high-resolution reference calculations using the line-by-line model, and an initial analysis of the reference calculations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Seasonal Dependent Impact of Ice Cloud Longwave Scattering on the Polar Climate

Most climate models neglect cloud longwave (LW) scattering because scattering is considered negligible compared to strong LW absorption by clouds and greenhouse gases. While this rationale is valid for simulating extrapolar regions, it is questionable for the polar regions, where the atmosphere is dry and hence has weak absorption, and ice clouds that have strong scattering capability frequently occur. Using the slab-ocean Community Earth System Model, we show that ice cloud LW scattering can warm winter surface air temperature by 0.8–1.8 K in the Arctic and 1.3–1.9 K in the Antarctic, while this warming becomes much weaker in polar summer. Such scattering effect cannot be correctly assessed when sea surface temperature and sea ice are prescribed as this effect is manifested through a surface-atmosphere coupling. Furthermore, cloud LW scattering is a necessity for the correct simulation of polar climate and surface radiation budget, especially in the winter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Future Community Efforts in Understanding and Modeling Atmospheric Processes

Atmospheric processes are important for weather, climate, and water prediction, as well as climate change projection, but their representation through subgrid parameterizations remains challenging. Understanding and representing these processes are therefore major goals of international research programs. The Global Atmospheric System Studies (GASS) Panel (Zeng and Klocke 2017), as part of the Global Energy and Water Exchanges Project (GEWEX), is dedicated to developing and improving the representation of the atmosphere in weather and climate models by facilitating and supporting the international community to carry out and use observations, process studies, and numerical model experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A protocol for model intercomparison of impacts of marine cloud brightening climate intervention

A modeling protocol (defined by a series of climate model simulations with specified model output) is introduced. Studies using these simulations are designed to improve the understanding of climate impacts using a strategy for climate intervention (CI) known as marine cloud brightening (MCB) in specific regions; therefore, the protocol is called MCB-REG (where REG stands for region). The model simulations are not intended to assess consequences of a realistic MCB deployment intended to achieve specific climate targets but instead to expose responses to interventions in six regions with pervasive cloud systems that are often considered candidates for such a deployment. A calibration step involving simulations with fixed sea surface temperatures (SSTs) is first used to identify a common forcing, and then coupled simulations with forcing in individual regions and combinations of regions are used to examine climate impacts. Synthetic estimates constructed by superposing responses from simulations with forcing in individual regions are considered a means of approximating the climate impacts produced when MCB interventions are introduced in multiple regions. A few results comparing simulations from three modern climate models (CESM2, E3SMv2, and UKESM1) are used to illustrate the similarities and differences between model behavior and the utility of estimates of MCB climate responses that were synthesized by summing responses introduced in individual regions. Cloud responses to aerosol injections differ substantially between models (CESM2 clouds appear much more susceptible to aerosol emissions than the other models), but patterns in precipitation and surface temperature responses were similar when forcing is imposed with similar amplitudes in the same regions. A previously identified La Niña-like response to forcing introduced in the Southeast Pacific is evident in this study, but the amplitude of the response was shown to markedly differ across the three models. Other common response patterns were also found and are discussed. Forcing in the Southeast Atlantic consistently (across all three models) produces weaker global cooling than that in other regions, and the Southeast Pacific and South Pacific show the strongest cooling. This indicates that the efficiency of a given intervention depends on not only the susceptibility of the clouds to aerosol perturbations, but also the strength of the underlying radiative feedbacks and ocean responses operating within each region. These responses were generally robust across models, but more studies and an examination of responses with ensembles would be beneficial.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity

Abstract It has been widely recognized that tropical cyclone (TC) genesis requires favorable large‐scale environmental conditions. Based on these linkages, numerous efforts have been made to establish an empirical relationship between seasonal TC activities and large‐scale environmental favorability in a quantitative way, which lead to conceptual functions such as the TC genesis index. However, due to the limited amount of reliable TC observations and complexity of the climate system, a simple analytic function may not be an accurate portrait of the empirical relationship between TCs and their ambiences. In this research, we use convolution neural networks (CNNs) to disentangle this complex relationship. To circumvent the limited amount of seasonal TC observation records, we implement transfer‐learning technique to train ensemble of CNNs first on suites of high‐resolution climate model simulations with realistic seasonal TC activities and large‐scale environmental conditions, and then on a state‐of‐the‐art reanalysis from 1950 to 2019. The trained CNNs can well reproduce the historical TC records and yields significant seasonal prediction skills when the large‐scale environmental inputs are provided by operational climate forecasts. Furthermore, by inputting the ensemble CNNs with 20th century reanalysis products and Phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we investigated TC variability and its changes in the past and future climates. Specifically, our ensemble CNNs project a decreasing trend of global mean TC activity in the future warming scenario, which is consistent with our future projections using high‐resolution climate model.

Meteorology & Atmospheric Sciences↗
DOE OSTI2021

“Scrutinizing entrainment and mass flux closures in shallow cumulus parameterizations using cloud-radar observations and large-eddy simulation” (Final report for DOE grant)

Warm, shallow clouds are responsible for a substantial portion of Earth System Model (ESM) uncertainty and divergence among model climate projections. A substantial amount of this uncertainty is tied to the representation of convection in ESMs, in particular assumptions underlying the convective parameterizations. This study focuses on entrainment and entrainment closures in ESM parameterizations. The completed project was a joint observational and modeling study to observationally derive estimates of entrainment and to use high-resolution modeling to scrutinize entrainment and mass flux closures in shallow convection parameterizations.

58 GEOSCIENCES↗
DOE OSTI2017

Overlooked possibility of a collapsed Atlantic Meridional Overturning Circulation in warming climate

Changes in the Atlantic Meridional Overturning Circulation (AMOC) are moderate in most climate model projections under increasing greenhouse gas forcing. This intermodel consensus may be an artifact of common model biases that favor a stable AMOC. Observationally based freshwater budget analyses suggest that the AMOC is in an unstable regime susceptible for large changes in response to perturbations. By correcting the model biases, we show that the AMOC collapses 300 years after the atmospheric CO2 concentration is abruptly doubled from the 1990 level. Compared to an uncorrected model, the AMOC collapse brings about large, markedly different climate responses: a prominent cooling over the northern North Atlantic and neighboring areas, sea ice increases over the Greenland-Iceland-Norwegian seas and to the south of Greenland, and a significant southward rain-belt migration over the tropical Atlantic. Our results highlight the need to develop dynamical metrics to constrain models and the importance of reducing model biases in long-term climate projection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Role of Microphysical Parameterizations with Droplet Relative Dispersion in IAP AGCM 4.1

In previous studies we see that accurate descriptions of the cloud droplet effective radius (Re) and the autoconversion process of cloud droplets to raindrops (Au) can effectively improve simulated clouds and surface precipitation, and reduce the uncertainty of aerosol indirect effects in global climate models (GCMs). In this paper, we implement cloud microphysical schemes including two-moment Au and R e considering relative dispersion of the cloud droplet size distribution into version 4.1 of the Institute of Atmospheric Physics atmospheric GCM (IAP AGCM 4.1), which is the atmospheric component of the Chinese Academy of Sciences-Earth System model (CAS-ESM 1.0). An analysis of the effects of different schemes shows that the newly implemented schemes can improve both the simulated shortwave (SWCF) and longwave cloud radiative forcings (LWCF) as compared to the standard scheme in IAP AGCM 4.1. The new schemes also effectively enhance the large-scale precipitation, especially over low latitudes, although the influences of total precipitation are insignificant for different schemes. Further studies show that similar results can be found with the Community Atmosphere Model 5.1 (CAM5.1).

54 ENVIRONMENTAL SCIENCES↗