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At least 1,045 records · Page 58

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↗

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↗

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↗

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↗

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↗

Middle to Late Holocene Sea Surface Temperature and Productivity Changes in the Northeast Pacific

Variations of the sea surface temperature (SST) and primary productivity in the northeast Pacific have far‐reaching implications. In addition to influencing the regional and global temperature and hydroclimate, these conditions also control marine ecosystems and their services, which subsequently impact regional economies. Yet, our understanding of the variability and controls of northeast Pacific SST and productivity on timescales exceeding observational records remains limited. Here, we use marine sediment records from seven locations, spanning 25.2°N–59.6°N, in the northeast Pacific to characterize the millennial‐scale variability of SST and productivity from 9,000 to 1,000 years BP. We explore the dynamics of their spatiotemporal evolution and compare these data with transient climate model outputs to identify potential drivers. Through a heat budget analysis and optimal fingerprinting analysis, we characterize the spatial pattern of forcings. We find that SST varied spatially in the northeast Pacific, with higher latitudes exhibiting greater magnitude changes than lower latitudes, which differs from previous work suggesting regional synchronicity and coherence during the Holocene. Our analysis did not find evidence for coherent variability of primary producer community nor carbon export, highlighting the difficulty of identifying the complex interactions between environmental conditions, producers, and carbon export. Model‐proxy disagreement demonstrates the need for higher resolution model frameworks, but shows nonetheless that observed variability in the proxy records can be explained by a combination of greenhouse gas and orbital forcing. Here we suggest that the complex SST variations and marine ecosystem responses to forced changes are important factors that can drive disagreements in model projections.

54 ENVIRONMENTAL SCIENCES↗

Simulations of ENSO Phase-locking in CMIP5 and CMIP6

The characteristics of El-Niño-Southern Oscillation (ENSO) phase-locking in observations and CMIP5 and CMIP6 models are examined in this study. Two metrics based on the peaking month histogram for all El Niño and La Niña events are adopted to delineate the basic features of ENSO phase-locking in terms of the preferred calendar month and strength of this preference. It turns out that most models are poor at simulating the ENSO phase-locking, either showing little peak strengths or peaking at the wrong seasons. By deriving ENSO’s linear dynamics based on the conceptual recharge oscillator (RO) framework through the seasonal linear inverse model (sLIM) approach, various simulated phase-locking behaviors of CMIP models are systematically investigated in comparison with observations. In observations, phase-locking is mainly attributed to the seasonal modulation of ENSO’s SST growth rate. In contrast, in a significant portion of CMIP models, phase-locking is co-determined by the seasonal modulations of both SST growth and phase-transition rates. Further study of the joint effects of SST growth and phase-transition rates suggests that for simulating realistic winter peak ENSO phase-locking with the right dynamics, climate models need to have four key factors in the right combination: (1) correct phase of SST growth rate modulation peaking at the fall; (2) large enough amplitude for the annual cycle in growth rate; (3) amplitude of semi-annual cycle in growth rate needs to be small; and (4) amplitude of seasonal modulation in SST phase-transition rate needs to be small.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ocean acidification over the next three centuries using a simple global climate carbon-cycle model: projections and sensitivities

Continued oceanic uptake of anthropogenic CO 2 is projected to significantly alter the chemistry of the upper oceans over the next three centuries, with potentially serious consequences for marine ecosystems. Relatively few models have the capability to make projections of ocean acidification, limiting our ability to assess the impacts and probabilities of ocean changes. In this study we examine the ability of Hector v1.1, a reduced-form global model, to project changes in the upper ocean carbonate system over the next three centuries, and quantify the model's sensitivity to parametric inputs. Hector is run under prescribed emission pathways from the Representative Concentration Pathways (RCPs) and compared to both observations and a suite of Coupled Model Intercomparison (CMIP5) model outputs. Current observations confirm that ocean acidification is already taking place, and CMIP5 models project significant changes occurring to 2300. Hector is consistent with the observational record within both the high- (> 55°) and low-latitude oceans (< 55°). The model projects low-latitude surface ocean pH to decrease from preindustrial levels of 8.17 to 7.77 in 2100, and to 7.50 in 2300; aragonite saturation levels (Ω Ar ) decrease from 4.1 units to 2.2 in 2100 and 1.4 in 2300 under RCP 8.5. These magnitudes and trends of ocean acidification within Hector are largely consistent with the CMIP5 model outputs, although we identify some small biases within Hector's carbonate system. Of the parameters tested, changes in [H + ] are most sensitive to parameters that directly affect atmospheric CO 2 concentrations – Q 10 (terrestrial respiration temperature response) as well as changes in ocean circulation, while changes in Ω Ar saturation levels are sensitive to changes in ocean salinity and Q 10 . We conclude that Hector is a robust tool well suited for rapid ocean acidification projections and sensitivity analyses, and it is capable of emulating both current observations and large-scale climate models under multiple emission pathways.

54 ENVIRONMENTAL SCIENCES↗

Comparing different generations of idealized solar geoengineering simulations in the Geoengineering Model Intercomparison Project (GeoMIP)

Abstract. Solar geoengineering has been receiving increased attention in recent years as a potential temporary solution to offset global warming. One method of approximating global-scale solar geoengineering in climate models is via solar reduction experiments. Two generations of models in the Geoengineering Model Intercomparison Project (GeoMIP) have now simulated offsetting a quadrupling of the CO2 concentration with solar reduction. This simulation is idealized and designed to elicit large responses in the models. Here, we show that energetics, temperature, and hydrological cycle changes in this experiment are statistically indistinguishable between the two ensembles. Of the variables analyzed here, the only major differences involve highly parameterized and uncertain processes, such as cloud forcing or terrestrial net primary productivity. We conclude that despite numerous structural differences and uncertainties in models over the past two generations of models, including an increase in climate sensitivity in the latest generation of models, the models are consistent in their aggregate climate response to global solar dimming.

54 ENVIRONMENTAL SCIENCES↗

Land Surface Cooling Induced by Sulfate Geoengineering Constrained by Major Volcanic Eruptions

Based on observations of large volcanic eruptions1 and dedicated model simulations2, solar radiation management by stratospheric sulfate aerosol injection (SRM-SAI) is thought to be one of the most promising methods to counteract anthropogenic global warming3. However, coordinated simulations of SRM-SAI using Earth System Models (ESMs) reveal fundamental uncertainties in the climate response to geoengineering, including global cooling and any resulting risks to natural and human ecosystems. Here we identify an emergent relationship4,5,6,7 linking the long-term global land surface cooling due to SRM-SAI and the short-term cooling following the 20th century major volcanic eruptions across an ESM ensemble. This emergent relationship, combined with observations and reanalysis, is used to constrain the global land surface temperature (GLST) response to reduced downward solar radiation. Based on these constraints, we find that GLST decreases by approximately 0.43 K per W.m-2 ([0.18,0.67]), which is 22% smaller in magnitude than the model mean of an unconstrained ensemble of ESMs simulating SRM-SAI and 46% smaller in magnitude than some past estimates8. These new estimates may affect how trade-offs between cost, risk and effectiveness of SRM-SAI might be considered.

Plazzotta, Maxime↗

Final Report – Study of Shortwave Spectra in Fully 3D Environment. Synergy Between Scanning Radars and Spectral Radiation Measurements

ARM set out 20 years ago to “close” the radiation problem, that is, to improve radiation models to the point where they could routinely predict the observed spectral radiation fluxes knowing the optical properties of the surface and of gases, clouds and aerosols in the atmosphere. Only then could such radiation models form a proper springboard for global climate model (GCM) parameterizations of spectral radiation. Sustained efforts have more or less achieved that goal with regard to longwave radiation; ASR models now routinely predict ARM spectral longwave radiances to 1–2%. Similar efforts in the shortwave have achieved far less; the successes are mainly for carefully selected 1D stratiform cloud cases. Such cases amount, even with the most optimistic interpretation, to no more than 30% of all cases at SGP. The problem has not been lack of effort but lack of appropriate instruments.The new ARM stimulus-funded instruments, with their new capabilities, will dramatically improve this situation and once again make progress possible on the shortwave problem. The new shortwave spectrometers will provide a reliable, calibrated record including the near infrared – and for other climatic regimes than SGP. The new scanning radars will provide the 3D cloud view, making it possible to tackle fully 3D situations. Thus, our main theme for the project is the understanding and closure of the surface spectral shortwave radiation problem in fully 3D cloud situations by combining the new ARM scanning radars and shortwave spectrometers with the arsenal of radiative transfer tools.

54 ENVIRONMENTAL SCIENCES↗

Mid-century climate change impacts on tornado-producing tropical cyclones

Tornadoes are a co-occurring extreme that can be produced by landfalling tropical cyclones (TCs). These tornadoes can exacerbate the loss of life and property damage caused by the TC from which they were spawned. It is uncertain how the severe weather environments of landfalling TCs may change in a future climate and how this could impact tornado activity from TCs. In this study, we investigated four TCs that made landfall in the U.S. and produced large tornado outbreaks. We performed four-member ensembles of convective-allowing (4-km resolution) regional climate model simulations representing each TC in the historical climate and a mid-twenty-first century future climate. To identify potentially tornadic storms, or TC-tornado (TCT) surrogates, we used thresholds for three-hourly maximum updraft helicity and radar reflectivity, as tornadoes are not resolved in the model. We found that the ensemble-mean number of TCT-surrogates increased substantially (56–299%) in the future, supported by increases in most-unstable convective available potential energy, surface-to-700-hPa bulk wind shear, and 0–1-km storm-relative helicity in the tornado-producing region of the TCs. On the other hand, future changes in most-unstable convective inhibition had minimal influence on future TCT-surrogates. This provides robust evidence that tornado activity from TCs may increase in the future. Furthermore, TCT-surrogate frequency between 00Z and 09Z increased for three of the four cases, suggesting enhanced tornado activity at night, when people are asleep and more likely to miss warnings. All of these factors indicate that TC-tornadoes may become more frequent and a greater hazard in the future, compounding impacts from future increases in TC winds and precipitation.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Tropical Precipitation Relations in CMIP6 Models with ARM Data

Abstract A set of diagnostics based on simple, statistical relationships between precipitation and the thermodynamic environment in observations is implemented to assess phase 6 of the Coupled Model Intercomparison Project (CMIP6) model behavior with respect to precipitation. Observational data from the Atmospheric Radiation Measurement (ARM) permanent field observational sites are augmented with satellite observations of precipitation and temperature as an observational baseline. A robust relationship across observational datasets between column water vapor (CWV) and precipitation, in which conditionally averaged precipitation exhibits a sharp pickup at some critical CWV value, provides a useful convective onset diagnostic for climate model comparison. While a few models reproduce an appropriate precipitation pickup, most models begin their pickup at too low CWV and the increase in precipitation with increasing CWV is too weak. Convective transition statistics compiled in column relative humidity (CRH) partially compensate for model temperature biases—although imperfectly since the temperature dependence is more complex than that of column saturation. Significant errors remain in individual models and weak pickups are generally not improved. The conditional-average precipitation as a function of CRH can be decomposed into the product of the probability of raining and mean precipitation during raining times (conditional intensity). The pickup behavior is primarily dependent on the probability of raining near the transition and on the conditional intensity at higher CRH. Most models roughly capture the CRH dependence of these two factors. However, compensating biases often occur: model conditional intensity that is too low at a given CRH is compensated in part by excessive probability of precipitation.

54 ENVIRONMENTAL SCIENCES↗

Model Hierarchies for Understanding Atmospheric Circulation

In this review, we highlight the complementary relationship between simple and comprehensive models in addressing key scientific questions to describe Earth's atmospheric circulation. The systematic representation of models in steps, or hierarchies, connects our understanding from idealized systems to comprehensive models and ultimately the observed atmosphere. First, we define three interconnected principles that can be used to characterize the model hierarchies of the atmosphere. We explore the rich diversity within the governing equations in the dynamical hierarchy, the ability to isolate and understand atmospheric processes in the process hierarchy, and the importance of the physical domain and resolution in the hierarchy of scale. We center our discussion on the large-scale circulation of the atmosphere and its interaction with clouds and convection, focusing on areas where simple models have had a significant impact. Our confidence in climate model projections of the future is based on our efforts to ground the climate predictions in fundamental physical understanding. This understanding is, in part, possible due to the hierarchies of idealized models that afford the simplicity required for understanding complex systems.

58 GEOSCIENCES↗

The First Habitable-zone Earth-sized Planet from TESS. III. Climate States and Characterization Prospects for TOI-700 d

We present self-consistent three-dimensional climate simulations of possible habitable states for the newly discovered habitable-zone Earth-sized planet TOI-700 d. We explore a variety of atmospheric compositions, pressures, and rotation states for both ocean-covered and completely desiccated planets in order to assess the planet’s potential for habitability. For all 20 of our simulated cases, we use our climate model outputs to synthesize transmission spectra, combined-light spectra, and integrated broadband phase curves. These climatologically informed observables will help the community assess the technological capabilities necessary for future characterization of this planet—as well as similar transiting planets discovered in the future—and will provide a guide for distinguishing possible climate states if one day we do obtain sensitive spectral observations of a habitable planet around an M star. We find that TOI-700 d is a strong candidate for a habitable world and can potentially maintain temperate surface conditions under a wide variety of atmospheric compositions. Unfortunately, the spectral feature depths from the resulting transmission spectra and the peak flux and variations from our synthesized phase curves for TOI-700 d do not exceed 10 ppm. This will likely prohibit the James Webb Space Telescope from characterizing its atmosphere; however, this motivates the community to invest in future instrumentation that perhaps can one day reveal the true nature of TOI-700 d and to continue to search for similar planets around less distant stars.

79 ASTRONOMY AND ASTROPHYSICS↗

Regridding uncertainty for statistical downscaling of solar radiation

Abstract. Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM outputs from their native grids and at differing spatial resolutions to a common grid in order to be comparable to observed data and (2) bias correcting RCM data, for example via quantile mapping, for future modeling and analysis. The uncertainty associated with (1) is not always considered for downstream operations in (2). This work examines this uncertainty, which is not often made available to the user of a regridded data product. This analysis is applied to RCM solar radiation data from the NA-CORDEX (North American Coordinated Regional Climate Downscaling Experiment) data archive and observed data from the National Solar Radiation Database housed at the National Renewable Energy Lab. A case study of the mentioned methods over California is presented.

14 SOLAR ENERGY↗

Weather effects on the lifecycle of U.S. Department of Defense equipment replacement (WELDER)

Extreme weather has a direct and significant impact on buildings and infrastructure, resulting in billions of dollars of damage each year. This problem continues to grow as climate patterns change and buildings are exposed to new and different hazards than what they were designed to withstand. In order to better plan for the long-range sustainment, restoration, modernization, and eventual recapitalization of these buildings, organizations with large building portfolios, such as the U.S. Department of Defense (DoD), must have an awareness of the risks that these extreme weather events present. This research aimed to develop an approach to estimate condition loss and reduction in service life for the components of a building due to extreme weather hazards, to understand the risks that may be present in certain buildings and building systems. To achieve this objective, a damage association matrix was developed that categorizes climate hazards, the damage modes that they produce, and the individual component types impacted. This damage matrix formally links state-of-the-art climate model output, which provides projections of the probability of various climate hazards with a damage effects model that quantifies the consequence on component-level condition and service life. This method is applied to an actual portfolio of buildings in a particular geographic location and with a pre-defined component inventory that comprises the building. This approach can be aggregated to the system-, facility-, and site-level thus helping support billions of dollars in recapitalization decisions related to restoration/modernization of facilities.

54 ENVIRONMENTAL SCIENCES↗

Advances in Cross-Cutting Ideas for Computational Climate Science

This report presents results from the DOE-sponsored workshop titled, ``Advancing X-Cutting Ideas for Computational Climate Science Workshop,'' known as AXICCS, held on September 12--13, 2016 in Rockville, MD. The workshop brought together experts in climate science, computational climate science, computer science, and mathematics to discuss interesting but unsolved science questions regarding climate modeling and simulation, promoted collaboration among the diverse scientists in attendance, and brainstormed about possible tools and capabilities that could be developed to help address them. Emerged from discussions at the workshop were several research opportunities that the group felt could advance climate science significantly. These include (1) process-resolving models to provide insight into important processes and features of interest and inform the development of advanced physical parameterizations, (2) a community effort to develop and provide integrated model credibility, (3) including, organizing, and managing increasingly connected model components that increase model fidelity yet complexity, and (4) treating Earth system models as one interconnected organism without numerical or data based boundaries that limit interactions. The group also identified several cross-cutting advances in mathematics, computer science, and computational science that would be needed to enable one or more of these big ideas. It is critical to address the need for organized, verified, and optimized software, which enables the models to grow and continue to provide solutions in which the community can have confidence. Effectively utilizing the newest computer hardware enables simulation efficiency and the ability to handle output from increasingly complex and detailed models. This will be accomplished through hierarchical multiscale algorithms in tandem with new strategies for data handling, analysis, and storage. These big ideas and cross-cutting technologies for enabling breakthrough climate simulation advancements also need the "glue" of outreach and learning across the scientific domains to be successful. The workshop identified several strategies to allow productive, continuous engagement across those who have a broad knowledge of the various angles of the problem. Specific ideas to foster education and tools to make material progress were discussed. Examples include follow-on cross-cutting meetings that enable unstructured discussions of the types this workshop fostered. A concerted effort to recruit undergraduate and graduate students from all relevant domains and provide them experience, training, and networking across their immediate expertise is needed. This will broaden and expand their exposure to the future needs and solutions, and provide a pipeline of scientists with a diversity of knowledge and know-how. Providing real-world experience with subject matter experts from multiple angles may also motivate the students to attack these problems and even come up with the missing solutions.

54 ENVIRONMENTAL SCIENCES↗