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At least 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Underestimated marine stratocumulus cloud feedback associated with overly active deep convection in models

Cloud feedback remains the largest source of uncertainty in equilibrium climate sensitivity (ECS). Many studies have attempted to narrow uncertainties in cloud feedback and ECS by proposing observable metrics with high skill at predicting future climate, referred to as emergent constraints. These constraints are often associated with clouds, convection, and circulation, and are interrelated. However, physical explanations for these connections remain unclear. Here, we propose a new mechanism relating convection and clouds across multiple climate models. Some models show overly active deep convection on daily timescales in the subtropical low cloud regions, which contributes to weaker subsidence inversion and smaller amounts of low-level clouds. Such models predict smaller shortwave (SW) cloud feedback. Using precipitation frequency in these regions as an emergent constraint, encapsulating this mechanism, models with lower SW cloud feedback (<0.50 W m -2 °C - 1) are found to exhibit erroneously frequent convection. Our results suggest that further improvements in understanding and better modeling of cloud and convective systems are necessary for accurate climate predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Atmospheric System Research Marine Low Clouds Workshop Report, January 27-29,2016

Marine low clouds are a major determinant of the Earth?s albedo and are a major source of uncertainty in how the climate responds to changing greenhouse gas levels and anthropogenic aerosol. Marine low clouds are particularly difficult to simulate accurately in climate models, and their remote locations present a significant observational challenge. A complex set of interacting controlling processes determine the coverage, condensate loading, and microphysical and radiative properties of marine low clouds. Marine low clouds are sensitive to atmospheric aerosol in several ways. Interactions at microphysical scales involve changes in the concentration of cloud droplets and precipitation, which induce cloud dynamical impacts including changes in entrainment and mesoscale organization. Marine low clouds are also impacted by atmospheric heating changes due to absorbing aerosols. The response of marine low clouds to aerosol perturbations depends strongly upon the unperturbed aerosol-cloud state, which necessitates greater understanding of processes controlling the budget of aerosol in the marine boundary layer. Entrainment and precipitation mediate the response of low clouds to aerosols but these processes also play leading roles in controlling the aerosol budget. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility and Atmospheric System Research (ASR) program are making major recent investments in observational data sets from fixed and mobile sites dominated by marine low clouds. This report provides specific action items for how these measurements can be used together with process modeling to make progress on understanding and quantifying the key cloud and aerosol controlling processes in the next 5-10 years. Measurements of aerosol composition and its variation with particle size are needed to advance a quantitative, process-level understanding of marine boundary-layer aerosol budget. Quantitative precipitation estimates that combine radar and lidar measurements are becoming available, and these could be used to test process models, quantify precipitation responses to aerosol, and constrain climate models. Models and observations can be used to constrain how clouds respond dynamically to changing precipitation. New measurements of turbulence from ground-based remote sensing could be used to attempt to relate entrainment to the vertical and horizontal structure of turbulence in the boundary layer. Cloud-top entrainment plays a major role in modulating how low clouds respond to both aerosols and to greenhouse gases, so investment in promising new observational estimates would be beneficial. Precipitation formation and radiative cooling both help marine low clouds to organize on the mesoscale. More work is needed to develop metrics to characterize mesoscale organization, to elucidate mechanisms that determine the type and spatial scale of mesoscale cellular convection, and to understand the role of mesoscale structures in the stratocumulus-to-cumulus transition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Internal variability of a dynamically downscaled climate over North America

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Local and Remote Mean and Extreme Temperature Response to Regional Aerosol Emissions Reductions

The climatic implications of regional aerosol and precursor emissions reductions implemented to protect human health are poorly understood. We investigate the mean and extreme temperature response to regional changes in aerosol emissions using three coupled chemistry–climate models: NOAA GFDL CM3, NCAR CESM1, and NASA GISS-E2. Our approach contrasts a long present-day control simulation from each model (up to 400 years with perpetual year 2000 or 2005 emissions) with 14 individual aerosol emissions perturbation simulations (160–240 years each). We perturb emissions of sulfur dioxide (SO2) and/or carbonaceous aerosol within six world regions and assess the statistical significance of mean and extreme temperature responses relative to internal variability determined by the control simulation and across the models. In all models, the global mean surface temperature response (perturbation minus control) to SO2 and/or carbonaceous aerosol is mostly positive (warming) and statistically significant and ranges from +0.17 K (Europe SO2) to -0.06 K (US BC). The warming response to SO2 reductions is strongest in the US and Europe perturbation simulations, both globally and regionally, with Arctic warming up to 1 K due to a removal of European anthropogenic SO2 emissions alone; however, even emissions from regions remote to the Arctic, such as SO2 from India, significantly warm the Arctic by up to 0.5 K. Arctic warming is the most robust response across each model and several aerosol emissions perturbations. The temperature response in the Northern Hemisphere midlatitudes is most sensitive to emissions perturbations within that region. In the tropics, however, the temperature response to emissions perturbations is roughly the same in magnitude as emissions perturbations either within or outside of the tropics. We find that climate sensitivity to regional aerosol perturbations ranges from 0.5 to 1.0 K (W m(exp -2))(exp -1) depending on the region and aerosol composition and is larger than the climate sensitivity to a doubling of CO2 in two of three models. We update previous estimates of regional temperature potential (RTP), a metric for estimating the regional temperature responses to a regional emissions perturbation that can facilitate assessment of climate impacts with integrated assessment models without requiring computationally demanding coupled climate model simulations. These calculations indicate a robust regional response to aerosol forcing within the Northern Hemisphere midlatitudes, regardless of where the aerosol forcing is located longitudinally. We show that regional aerosol perturbations can significantly increase extreme temperatures on the regional scale. Except in the Arctic in the summer, extreme temperature responses largely mirror mean temperature responses to regional aerosol perturbations through a shift of the temperature distributions and are mostly dominated by local rather than remote aerosol forcing.

Westervelt, Daniel M.↗
NASA NTRS2023

On the Remote Impacts of Mid-Holocene Saharan Vegetation on South American Hydroclimate: A Modeling Intercomparison

Proxy reconstructions from the mid-Holocene (MH: 6,000 years ago) indicate an intensification of the West African Monsoon and a weakening of the South American Monsoon, primarily resulting from orbitally-driven insolation changes. However, model studies that account for MH orbital configurations and greenhouse gas concentrations can only partially reproduce these changes. Most model studies do not account for the remarkable vegetation changes that occurred during the MH, in particular over the Sahara, precluding realistic simulations of the period. Here, we study precipitation changes over northern Africa and South America using four fully coupled global climate models by accounting for the Saharan greening. Incorporating the Green Sahara amplifies orbitally-driven changes over both regions, and leads to an improvement in proxy-model agreement. Our work highlights the local and remote impacts of vegetation and the importance of considering vegetation changes in the Sahara when studying and modeling global climate.

Paleoclimate modeling↗
DOE OSTI2024

Aerosol-Cloud Interactions From Aviation Soot Emissions

Current models estimate global aviation contributes approximately 5% to the total anthropogenic climate forcing, with aerosol-cloud interactions having the greatest effect. However, radiative forcing estimates from aviation aerosol-cloud interactions remain undetermined. There is an expected significant increase in aircraft emissions with aviation demand expected to rise by over 4% per year. Soot may play an important role in the ice nucleation of aircraft-induced cirrus formation due to a high emission rate, but the ice nucleating properties are poorly constrained. Understanding the microphysical processes leading to atmospheric ice crystal formation is crucial for the reliable parameterization of aerosol-cloud interactions in climate models due to their impact on precipitation and cloud radiative properties. Ice nucleation of aircraft-emitted soot is potentially affected by particle morphology with condensation of supercooled water occurring in pores followed by ice nucleation. However, soot has heterogeneous properties and undergoes atmospheric aging and oxidation that could change surface properties and contribute to complex ice nucleation processes. Further, this review synthesizes current knowledge of ice nucleation catalyzed by aviation in the cirrus regime and its effects on global radiative forcing. Further research is required to determine the ice nucleation and microphysical processes of cirrus cloud formation from aviation emissions in both controlled laboratory and field investigations to inform models for more accurate climate predictions and to provide efficient mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The relationship between interannual and long-term cloud feedbacks

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual and long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Statistical Treatment of Convolutional Neural Network Superresolution of Inland Surface Wind for Subgrid-Scale Variability Quantification

Abstract Machine learning models have been employed to perform either physics-free data-driven or hybrid dynamical downscaling of climate data. Most of these implementations operate over relatively small downscaling factors because of the challenge of recovering fine-scale information from coarse data. This limits their compatibility with many global climate model outputs, often available between ∼50- and 100-km resolution, to scales of interest such as cloud resolving or urban scales. This study systematically examines the capability of a type of superresolving convolutional neural network (SR-CNNs) to downscale surface wind speed data over land from different coarse resolutions (25-, 48-, and 100-km resolution) to 3 km. For each downscaling factor, we consider three convolutional neural network (CNN) configurations that generate superresolved predictions of fine-scale wind speed, which take between one and three input fields: coarse wind speed, fine-scale topography, and diurnal cycle. In addition to fine-scale wind speeds, probability density function parameters are generated through which sample wind speeds can be generated, accounting for the intrinsic stochasticity of wind speed. For assessing generalization to new data, CNN models are tested on regions with different topography and climate that are unseen during training. The evaluation of superresolved predictions focuses on subgrid-scale variability and the recovery of extremes. Models with coarse wind and fine topography as inputs exhibit the best performance when compared with other model configurations, operating across the same downscaling factor. Our diurnal cycle encoding results in lower out-of-sample generalizability when compared with other input configurations.

17 WIND ENERGY↗
DOE OSTI2018

Simulation of Hurricane Katrina at 3km resolution

A regional climate model simulation of Hurricane Katrina at 3 km resolution, part of a study published in Nature titled, “Anthropogenic Influences on Major Tropical Cyclone Events,” by Berkeley Lab researchers Christina Patricola and Michael Wehner. The study found that climate change intensified the amount of rainfall in recent hurricanes such as Katrina, Irma, and Maria by 5 to 10 percent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modes of Variability in E3SM and CESM Large Ensembles

An adequate characterization of internal modes of climate variability (MoV) is a prerequisite for both accurate seasonal predictions and climate change detection and attribution. Assessing the fidelity of climate models in simulating MoV is therefore essential; however, doing so is complicated by the large intrinsic variations in MoV and the limited span of the observational record. Large ensembles (LEs) provide a unique opportunity to assess model fidelity in simulating MoV and quantify intermodel contrasts. Here, in this work, these goals are pursued in four recently produced LEs: the Energy Exascale Earth System Model (E3SM) versions 1 and 2 LEs, and the Community Earth System Model (CESM) versions 1 and 2 LEs. In general, the representation of global coupled modes is found to improve across successive E3SM and CESM versions in conjunction with the fidelity of the base state climate while the patterns of extratropical modes are well simulated across the ensembles. Various persistent shortcomings for all MoV are however identified and discussed. The results both demonstrate the successes of these recent model versions and suggest the potential for continued improvement in the representation of MoV with advances in model physics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Dependence of Atmospheric Transport into the Arctic on the Extent of the Hadley Cell

Recent studies have shown a large spread in the transport of atmospheric tracers into the Arctic among a suite of chemistry climate models, and have suggested that this is related to the multi–model spread in the meridional extent of the Hadley Cell (HC). Here we examine the HC–transport relationship using an idealized model, where we can vary the mean circulation and isolate its impact on transport to the Arctic. It is shown that the poleward transport depends on the relative position between the northern edge of the HC and the tracer source, with maximum poleward transport occurring when the HC edge lies near the middle of the source region. Such dependence highlights the critical role of near–surface transport by Eulerian mean circulation rather than eddy mixing in the free troposphere. These results suggest that variations in the HC extent and the tracer source region are both important for modeling Arctic composition.

Atmospheric transport↗
DOE OSTI2023

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world's largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Global Teleconnections: Atmospheric Interactions Across Scales [Slides]

This project aims at an improved understanding of non-hydrostatic dynamics in atmospheric modeling using the DOE’s next generation climate model. One aspect that we have been focusing on is baroclinic instability which is closely related to mid-latitude cyclone genesis. The other aspect that we recently developed is E3SM simulations under Radiative-Convective Equilibrium (RCE), a prototype of tropical climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Laboratory Experiments and Instrument Intercomparison Studies of Carbonaceous Aerosol Particles

Aerosols containing black carbon (and some specific types of organic particulate matter) directly absorb incoming light, heating the atmosphere. In addition, all aerosol particles backscatter solar light, leading to a net-cooling effect. Indirect effects involve hydrophilic aerosols, which serve as cloud condensation nuclei (CCN) that affect cloud cover and cloud stability, impacting both atmospheric radiation balance and precipitation patterns. At night, all clouds produce local warming, but overall clouds exert a net-cooling effect on the Earth. The effect of aerosol radiative forcing on climate may be as large as that of the greenhouse gases, but predominantly opposite in sign and much more uncertain. The uncertainties in the representation of aerosol interactions in climate models makes it problematic to use model projections to guide energy policy. The objective of our program is to reduce the uncertainties in the aerosol radiative forcing in the two areas highlighted in the ASR Science and Program Plan. That is, (1) addressing the direct effect by correlating particle chemistry and morphology with particle optical properties (i.e. absorption, scattering, extinction), and (2) addressing the indirect effect by correlating particle hygroscopicity and CCN activity with particle size, chemistry, and morphology. In this connection we are systematically studying particle formation, oxidation, and the effects of particle coating. The work is specifically focused on carbonaceous particles where the uncertainties in the climate relevant properties are the highest. The ongoing work consists of laboratory experiments and related instrument inter-comparison studies both coordinated with field and modeling studies, with the aim of providing reliable data to represent aerosol processes in climate models. The work is performed in the aerosol laboratory at Boston College. At the center of our laboratory setup are two main sources for the production of aerosol particles: (a) two well-characterized source of soot particles and (b) a flow reactor for controlled OH and/or O3 oxidation of relevant gas phase species to produce well-characterized SOA particles. After formation, the aerosol particles are subjected to physical and chemical processes that simulate aerosol growth and aging. A suite of instruments in our laboratory is used to characterize the physical and chemical properties of aerosol particles before and after processing. The Time of Flight Aerosol Mass Spectrometer (ToF-AMS) together with a Scanning Mobility Particle Sizer (SMPS) measures particle mass, volume, density, composition (including black carbon content), dynamic shape factor, and fractal dimension. The–ToF-AMS was developed at ARI with Boston College participation. About 120 AMS instruments are now in service (including 5 built for DOE laboratories) performing field and laboratory studies world-wide. Other major instruments include a thermal denuder, two Differential Mobility Analyzers (DMA), a Cloud Condensation Nuclei Counter (CCN), a Thermal desorption Aerosol GC/MS (TAG) and the new Soot Particle Aerosol Mass Spectrometer (SP-AMS). Optical instrumentation required for the studies have been brought to our laboratory as part of ongoing and planned collaborative projects with colleagues from DOE, NOAA and university laboratories. Optical instruments that will be utilized include a Photoacoustic Spectrometer (PAS), a Cavity Ring Down Aerosol Extinction Spectrometer (CRD-AES), a Photo Thermal Interferometer (PTI), a new 7-wavelength Aethalometer and a Cavity Attenuated Phase Shift Extinction Monitor (CAPS). These instruments are providing aerosol absorption, extinction and scattering coefficients at a range of atmospherically relevant wavelengths. During the past two years our work has continued along the lines of our original proposal. We report on 12 completed and/or continuing projects conducted during the period 08/14 to 0814/2015. These projects are described in 17 manuscripts published in refereed journals.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Tropical High Cloud Feedback Relationships to Climate Sensitivity

Clouds constitute a large portion of uncertainty in predictions of equilibrium climate sensitivity (ECS). While low cloud feedbacks have been the focus of intermodel studies due to their high variability among global climate models, tropical high cloud feedbacks also exhibit considerable uncertainty. Here, we apply the cloud radiative kernel technique of Zelinka et al. to 22 models across the CMIP5 and CMIP6 ensembles to survey tropical high cloud feedbacks and analyze their relationship to ECS. We find that the net high cloud feedback and its altitude and optical depth feedback components are significantly positively correlated with ECS in the tropical mean. On the other hand, the tropical mean high cloud amount feedback is not correlated with ECS. These relationships are most pronounced outside of areas of strong climatological ascent, suggesting the importance of thin cirrus feedbacks. Finally, we explore connections between high cloud feedbacks, climate sensitivity, and mean state high cloud properties. In general, high ECS models are cloudier in the upper troposphere but have a thinner high cloud population. Furthermore, we find that having more thin cirrus in the mean state relates to more positive high cloud altitude and optical depth feedbacks, and it either amplifies or dampens the high cloud amount feedback depending on the large-scale dynamical regime (amplifying in descent and dampening in ascent). In summary, our analysis highlights the importance of tropical high cloud feedbacks for driving intermodel spread in ECS and suggests that mean state high cloud characteristics might provide a unique opportunity for observationally constraining high cloud feedbacks.

atmosphere↗
NASA NTRS2006

Recovery of the Antarctic Ozone Hole

The Antarctic ozone hole develops each year and culminates by early Spring. Antarctic ozone values have been monitored since 1979 using satellite observations from the TOMS and OMI instruments. The severity of the hole has been assessed using the minimum total ozone value from the October monthly mean (depth of the hole), the average size during the September-October period, and the ozone mass deficit. Ozone is mainly destroyed by halogen catalytic cycles, and these losses are modulated by temperature variations in the collar of the polar lower stratospheric vortex. In this presentation, we show the relationships of halogens and temperature to both the size and depth of the hole. Because atmospheric halogen levels are responding to international agreements that limit or phase out production, the amount of halogens in the stratosphere should decrease over the next few decades. We use two methods to estimate ozone hole recovery. First, we use projections of halogen levels combined with age-of-air estimates in a parametric model. Second, we use a coupled chemistry climate model to assess recovery. We find that the ozone hole is recovering at an extremely slow rate and that large ozone holes will regularly recur over the next 2 decades. Furthermore, full recovery to 1980 levels will not occur until approximately 2068. We will also show some error estimates of these dates and the impact of climate change on the recovery.

Newman, Paul A.↗