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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 163 records · Page 9
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DOE OSTI2022

Plankton energy flows using a global size-structured and trait-based model

Plankton community models are critical tools for understanding the processes that shape marine plankton communities, how plankton communities impact biogeochemical cycles, and the feedbacks between community structure and function. Here, using the flexible Marine Biogeochemistry Library (MARBL), we present the Size-based Plankton ECological TRAits (MARBL-SPECTRA) model, which is designed to represent a diverse plankton community while remaining computationally tractable. MARBL-SPECTRA is composed of nine phytoplankton and six zooplankton size classes represented using allometric scaling relationships for physiological traits and interactions within multiple functional types. MARBL-SPECTRA is embedded within the global ocean component of the Community Earth System Model (CESM) and simulates large-scale, emergent patterns in phytoplankton growth limitation, plankton phenology, plankton generation time, and trophic transfer efficiency. The model qualitatively reproduces observed global patterns of surface nutrients, chlorophyll biomass, net primary production, and the biogeographies of a range of plankton size classes. In addition, the model simulates how predator:prey dynamics and trophic efficiency vary across gradients in total ecosystem productivity. Shorter food chains that export proportionally more carbon from the surface to the ocean interior occur in productive, eutrophic regions, whereas in oligotrophic regions, the food chains are relatively long and export less organic matter from the surface. The union of functional type modeling with size-resolved, trait-based modeling approaches allows MARBL-SPECTRA to capture both large-scale elemental cycles and the structure of planktonic food webs affecting trophic transfer efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

A modular biogeochemical modeling suite for next-generation ocean models (Final Report)

The Marine Biogeochemistry Library (MARBL) is a self-contained implementation of ocean biogeochemistry suitable for incorporation in Earth system models. The default configuration of MARBL represents multiple nutrient co-limitation (N, P, Si, and Fe), includes three explicit phytoplankton functional groups (diatoms, diazotrophs, and pico/nano phytoplankton), and one implicit group (calcifiers); there is one zooplankton group. MARBL includes fully prognostic carbonate chemistry and simulates sinking particulate organic matter implicitly, subject to ballasting by mineral dust, biogenic mineral carbonate and opal. MARBL represents subgrid-scale variations in light, variable C:P stoichiometry, semi-labile and refractory dissolved organic material pools, prognostic oceanic emission of ammonia, and an explicit ligand tracer that complexes iron. MARBL is fully runtime-configurable, and is flexible enough to accommodate a variable number of plankton functional types and ecosystem configurations. Critically, MARBL is implemented to be independent of any particular ocean general circulation model (OGCM); it is a standalone library that interfaces with an OGCM's via an explicit "driver" layer. MARBL can thus be coupled to multiple OGCM's, enabling efficient maintenance, development, and cross-model inter-comparison. MARBL is the ocean biogeochemistry component for the Community Earth System Model and the DOE’s Energy Exascale Earth System Model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

LDRD 20190608ER: Diagnosing Near-Future Changes in Arctic Sea Ice and Ocean Conditions

Environmental changes in the Arctic present opportunities and increased hazards as potential shipping corridors open. We apply novel statistical techniques to simultaneously characterize multiple physical properties and uncertainties relevant for Arctic shipping, analyzing existing model projections to understand the likelihood of encountering high wind and low ice conditions along potential transportation routes through the Arctic Ocean. We assess the quality of Department of Energy (DOE) simulations against observed data, for these purposes. We find that the Arctic system is highly variable, but its large-scale patterns are captured by the models, allowing us to consider the two major shipping routes along Arctic coasts: the Northern Sea Route on the Russian side of the Arctic Ocean, and the Northwest Passage through the Canadian Arctic Archipelago. Our work highlights the usefulness and promise of DOE’s new modeling system (E3SM) as well as limitations of the models and observed data, such as resolution, differing types of information available from models and measurements, and challenges for quantifying uncertainty and bias. A procedure developed to increase predictability in Community Earth System Model simulations could be beneficial for E3SM. This research provides insight into Arctic trends and a baseline to articulate future model development needs.

58 GEOSCIENCES↗
DOE OSTI2023

Rainbows and Climate Change: A tutorial on climate model diagnostics and parameterization

Earth System Models (ESMs) must represent processes below the grid scale of a model using representations (parameterizations) of physical and chemical processes. As a tutorial exercise to understand diagnostics and parameterization, this work presents a representation of rainbows for an ESM: the Community Earth System Model version 2 (CESM2). Using the 'state' of the model, basic physical laws, and some assumptions, we generate a representation of this unique optical phenomena as a diagnostic output. Rainbow occurrence and it's possible changes are related to cloud occurrence and rain formation which are critical uncertainties for climate change prediction. The work highlights issues which are typical of many diagnostics parameterizations such as assumptions, uncertain parameters and the difficulty of evaluation against uncertain observations. Results agree qualitatively with limited available global 'observations' of Rainbows. Rainbows are seen in expected locations in the sub-tropics over the ocean where broken clouds and frequent precipitation occurs. The diurnal peak is in the morning over ocean and in the evening over land. The representation of rainbows is found to be quantitatively sensitive to the assumed amount of cloudiness and the amount of stratiform rain. Rainbows are projected to have decreased, mostly in the Northern Hemisphere, due to aerosol pollution effects increasing cloud coverage since 1850. In the future, continued climate change is projected to decrease cloud cover, associated with a positive cloud feedback. As a result the rainbow diagnostic projects that rainbows will increase in the future, with the largest changes at mid-latitudes. The diagnostic may be useful for assessing cloud parameterizations, and is an exercise in how to build and test parameterizations of atmospheric phenomena.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Hierarchy of Global Ocean Models Coupled to CESM1

Abstract We develop a hierarchy of simplified ocean models for coupled ocean, atmosphere, and sea ice climate simulations using the Community Earth System Model version 1 (CESM1). The hierarchy has four members: a slab ocean model, a mixed‐layer model (MLM) with entrainment and detrainment, an Ekman MLM, and an ocean general circulation model (OGCM). Flux corrections of heat and salt are applied to the simplified models ensuring that all hierarchy members have the same climatology. We diagnose the needed flux corrections from auxiliary simulations in which we restore the temperature and salinity to the daily climatology obtained from a target CESM1 simulation. The resulting three‐dimensional corrections contain the interannual variability fluxes that maintain the correct vertical gradients of temperature and salinity in the tropics. We find that the inclusion of mixed‐layer entrainment and Ekman flow produces sea surface temperature and surface air temperature fields whose means and variances are progressively more similar to those produced by the target CESM1 simulation. We illustrate the application of the hierarchy to the problem of understanding the response of the climate system to the loss of Arctic sea ice. We find that the shifts in the positions of the mid‐latitude westerly jet and of the Inter‐tropical Convergence Zone (ITCZ) in response to sea‐ice loss depend critically on upper ocean processes. Specifically, heat uptake associated with the mixed‐layer entrainment influences the shift in the westerly jet and ITCZ. Moreover, the shift of ITCZ is sensitive to the form of Ekman flow parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Positive Low Cloud–Sea Surface Temperature Feedback in the East Asian Marginal Seas during El Niño Mature Winters and Their Following Spring

During the winter and subsequent spring of an El Niño year, the East Asian marginal sea (EAMS) exhibits positive sea surface temperature anomalies (SSTAs) and fewer low clouds, while the western North Pacific experiences negative SSTAs. In this study, we suggest that the positive SSTAs in EAMS are maintained by a positive low cloud–SST feedback. In neutral winters and springs, the EAMS is covered by low clouds, which have a cooling effect on surface temperatures. During an El Niño year, a western North Pacific anomalous anticyclone is established, and along its northwestern flank, there are favorable conditions for convergence of moisture and weaker surface latent heat flux over the EAMS. Once a positive SSTA has been established, a further reduction of turbulent mixing results in less low cloud and enhanced solar heating of the ocean mixed layer; this reinforces and maintains both the positive SSTA and the lack of low cloud via a positive feedback mechanism. Further, the concurrent increase of low cloud–SST feedback and anticyclone circulation strengths is evident in the coupled-model simulations from phase 6 of the Coupled Model Intercomparison Project. Furthermore, sensitivity experiments, performed with the atmospheric components of Community Earth System Model (CESM2), reveal that a positive SSTA helps to maintain the western North Pacific anomalous anticyclone. Four pacemaker-coupled experiments by CESM2, with sea surface temperature in the equatorial Pacific restored to the observational anomalies plus the model climatology and altered low cloud feedback over EAMS, suggest that the low cloud–SST feedback results in more than the maintenance of a positive SSTA over the EAMS: the positive feedback is also a previously overlooked mechanism for the maintenance of the western North Pacific anomalous anticyclone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A hierarchy of global ocean models coupled to CESM1

We develop a hierarchy of simplified ocean models for coupled ocean, atmosphere, and sea ice climate simulations using the Community Earth System Model version 1 (CESM1). The hierarchy has four members: a slab ocean model, a mixed-layer model (MLM) with entrainment and detrainment, an Ekman MLM, and an ocean general circulation model (OGCM). Flux corrections of heat and salt are applied to the simplified models ensuring that all hierarchy members have the same climatology. We diagnose the needed flux corrections from auxiliary simulations in which we restore the temperature and salinity to the daily climatology obtained from a target CESM1 simulation. The resulting three-dimensional corrections contain the interannual variability fluxes that maintain the correct vertical gradients of temperature and salinity in the tropics. We find that the inclusion of mixed-layer entrainment and Ekman flow produces sea surface temperature and surface air temperature fields whose means and variances are progressively more similar to those produced by the target CESM1 simulation. We illustrate the application of the hierarchy to the problem of understanding the response of the climate system to the loss of Arctic sea ice. We find that the shifts in the positions of the mid-latitude westerly jet and of the Inter-tropical Convergence Zone (ITCZ) in response to sea-ice loss depend critically on upper ocean processes. Specifically, heat uptake associated with the mixed-layer entrainment influences the shift in the westerly jet and ITCZ. Moreover, the shift of ITCZ is sensitive to the form of Ekman flow parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Source attribution of black carbon and its direct radiative forcing in China

Abstract. The source attributions for mass concentration, haze formation, transport and direct radiative forcing of black carbon (BC) in various regions of China are quantified in this study using the Community Earth System Model (CESM) with a source-tagging technique. Anthropogenic emissions are from the Community Emissions Data System that is newly developed for the Coupled Model Intercomparison Project Phase 6 (CMIP6). Over north China where the air quality is often poor, about 90 % of near-surface BC concentration is contributed by local emissions. Overall, 35 % of BC concentration over south China in winter can be attributed to emissions from north China, and 19 % comes from sources outside China in spring. For other regions in China, BC is largely contributed from nonlocal sources. We further investigated potential factors that contribute to the poor air quality in China. During polluted days, a net inflow of BC transported from nonlocal source regions associated with anomalous winds plays an important role in increasing local BC concentrations. BC-containing particles emitted from East Asia can also be transported across the Pacific. Our model results show that emissions from inside and outside China are equally important for the BC outflow from East Asia, while emissions from China account for 8 % of BC concentration and 29 % in column burden in the western United States in spring. Radiative forcing estimates show that 65 % of the annual mean BC direct radiative forcing (2.2 W m−2) in China results from local emissions, and the remaining 35 % is contributed by emissions outside of China. Efficiency analysis shows that a reduction in BC emissions over eastern China could have a greater benefit for the regional air quality in China, especially in the winter haze season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Future climate emulations using quantile regressions on large ensembles

The study of climate change and its impacts depends on generating projections of future temperature and other climate variables. For detailed studies, these projections usually require some combination of numerical simulation and observations, given that simulations of even the current climate do not perfectly reproduce local conditions. We present a methodology for generating future climate projections that takes advantage of the emergence of climate model ensembles, whose large amounts of data allow for detailed modeling of the probability distribution of temperature or other climate variables. The procedure gives us estimated changes in model distributions that are then applied to observations to yield projections that preserve the spatiotemporal dependence in the observations. We use quantile regression to estimate a discrete set of quantiles of daily temperature as a function of seasonality and long-term change, with smooth spline functions of season, long-term trends, and their interactions used as basis functions for the quantile regression. A particular innovation is that more extreme quantiles are modeled as exceedances above less extreme quantiles in a nested fashion, so that the complexity of the model for exceedances decreases the further out into the tail of the distribution one goes. We apply this method to two large ensembles of model runs using the same forcing scenario, both based on versions of the Community Earth System Model (CESM), run at different resolutions. The approach generates observation-based future simulations with no processing or modeling of the observed climate needed other than a simple linear rescaling. The resulting quantile maps illuminate substantial differences between the climate model ensembles, including differences in warming in the Pacific Northwest that are particularly large in the lower quantiles during winter. We show how the availability of two ensembles allows the efficacy of the method to be tested with a “perfect model” approach, in which we estimate transformations using the lower-resolution ensemble and then apply the estimated transformations to single runs from the high-resolution ensemble. Finally, we describe and implement a simple method for adjusting a transformation estimated from a large ensemble of one climate model using only a single run of a second, but hopefully more realistic, climate model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Multi-scale processes driving tropical convection and influence of the aerosol (Final Technical Report)

This DOE GoAmazon collaborative project between scientists in the US and Brazil addresses fundamental processes that drive tropical deep convection including aerosol effects. The results provide guidance for improving the parameterizations of cloud and aerosol effects by increasing the knowledge of processes at work in tropical convection, especially over tropical land. Highlights include: • GoAmazon2014/5 observations permitted, for the first time, a comprehensive evaluation of the strong relationship between lower free tropospheric moisture and deep convective onset over the Amazon (Schiro et al. 2016, JAS; Schiro et al. 2018b, PNAS; Chakraborty et al. 2018, ACP; Schiro and Neelin 2018c). A set of diagnostics for deep convective onset has been established using data from the GoAmazon2014/5 campaign (Schiro et al. 2016, JAS), highlighting similarities and differences between the convective transition statistics over tropical land versus corresponding statistics from ARM campaigns in the tropical Western Pacific. The initial set of diagnostics has been provided as a module to be incorporated into the ARM Diagnostics Package of Shaocheng Xie and coworkers, which is being integrated into the PCMDI and E3SM diagnostics packages. Additionally, a set of downdraft diagnostics to inform model parameterizations has been developed (Schiro and Neelin 2018a, ACP). • These diagnostics have been used in constraining the behavior of modeled convective parameterizations. This includes using them with parameter perturbation experiments in the Community Earth System Model to show which parameter ranges are consistent with observed onset statistics, and to show that the primary causal direction of the water vapor-precipitation relationship is via the impact of mixing processes and free tropospheric moisture on convection (Kuo et al. 2017, JAS). Lintner et al. (2017, GRL) used this impact of free tropospheric moisture to systematically analyze issues in the simulation of Amazon rainfall in the CMIP5 model ensemble. • Leveraging the multi-instrument GoAmazon observations, Schiro et al. (2018, PNAS) are able to provide for the first time an empirical mixing using radar wind profiler data that provides a good predictor of precipitation for both mesoscale convective systems and smaller-scale convection. In addition, buoyancy estimated from these results is a good predictor of precipitation across the seasonal and diurnal cycles (Schiro and Neelin 2018c, JAS) and permits the effects of aerosols to be distinguished from those of the thermodynamic environment in the transition to deep convection (Chakraborty et al. 2018, ACP). • Placing the GoAmazon campaign in a larger context, in collaboration with U. São Paulo investigators, Rehbein et al. (2018) analyzed the characteristics of the mesoscale convective systems (MCS) that affect Amazon rainfall, including origins, lifetimes, propagation speed and displacement. de Barros Soares et al. (2017) establish statistically significant observed warming trends over much of South America and are able to attribute the origin of this to anthropogenic forcing based on the agreement of climate model simulations with and without anthropogenic forcings. This analysis left open the attribution of precipitation trends due to large natural variability. Barkhardorian et al. (2018) provide evidence indicating that the observed regional precipitation decrease and drying during recent over northern South America during recent austral springs will continue and intensify in the course of unfolding anthropogenic climate change.

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 OSTI2025

Extratropical Cloud Feedback Constrained by Cloud Sources and Sinks in Cyclones

Constraining cloud feedback in global climate models (GCMs) using observations is important for establishing accurate predictions of future climate. Uncertainty in shortwave cloud feedback (SW FB ) dominates uncertainty in total cloud feedback. Recent studies show a shift toward more positive extratropical SW FB in the latest generations of GCMs leading to the emergence of very high equilibrium climate sensitivity (ECS). In this study, we use precipitation efficiency and albedo susceptibility to constrain liquid water path (LWP) response to warming and SW FB in the Southern Ocean (SO; 50°–80°S). We analyze precipitation in extratropical cyclones (ECs) to learn about extratropical condensed water sink processes, combined with observations of clouds and moisture convergence, and use the analysis to better understand and constrain SW FB . We utilize a perturbed parameter ensemble (PPE) hosted in the Community Atmosphere Model, version 6 (CAM6), to provide a constraint on SW FB based on observations from Clouds and the Earth’s Radiant Energy System (CERES) and Multisensor Advanced Climatology of LWP (MAC-LWP). We apply Gaussian process regression to emulate the model response to all parameters perturbed in the PPE. Confronting the emulator output with observations provides a new estimated response of Earth to global warming. Furthermore, our new estimates of SO LWP reduce the PPE range by 66%–72%, which results in a shortwave cloud radiative effect estimated range that is 27%–34% less than the PPE range. Observations suggest a more positive SO SW FB than the Community Earth System Model, version 2 (CESM2), and consequently do not reject the high climate sensitivity GCMs emerging from the Coupled Model Intercomparison Project phase 6 (CMIP6).

Atmosphere↗
DOE OSTI2018

Improved Representation of Surface Spectral Emissivity in a Global Climate Model and Its Impact on Simulated Climate

Surface longwave emissivity can be less than unity and vary significantly with frequency. However, most climate models still assume a blackbody surface in the longwave (LW) radiation scheme of their atmosphere models. This study incorporates realistic surface spectral emissivity into the atmospheric component of the Community Earth System Model (CESM), version 1.1.1, and evaluates its impact on simulated climate. By ensuring consistency of the broadband surface longwave flux across different components of the CESM, the top-of-the-atmosphere (TOA) energy balance in the modified model can be attained without retuning the model. Inclusion of surface spectral emissivity, however, leads to a decrease of net upward longwave flux at the surface and a comparable increase of latent heat flux. Global-mean surface temperature difference between the modified and standard CESM simulation is 0.20 K for the fully coupled run and 0.45 K for the slab-ocean run. Noticeable surface temperature differences between the modified and standard CESM simulations are seen over the Sahara Desert and polar regions. Accordingly, the climatological mean sea ice fraction in the modified CESM simulation can be less than that in the standard CESM simulation by as much as 0.1 in some regions. When spectral emissivities of sea ice and open ocean surfaces are considered, the broadband LW sea ice emissivity feedback is estimated to be −0.003 W m −2 K −1 , assuming flat ice emissivity as sea ice emissivity, and 0.002 W m −2 K −1 , assuming coarse snow emissivity as sea ice emissivity, which are two orders of magnitude smaller than the surface albedo feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Effects of Surface Longwave Spectral Emissivity on Atmospheric Circulation and Convection over the Sahara and Sahel

This study quantifies the impact of the inclusion of realistic surface spectral emissivity in the Sahara and Sahel on the simulated local climate and beyond. The surface emissivity in these regions can be as low as 0.6–0.7 over the infrared window band while close to unity in other spectral bands, but such spectral dependence has been ignored in current climate models. Realistic surface spectral emissivities over the Sahara and Sahel are incorporated into the Community Earth System Model (CESM) version 1.1.1, while treatments of surface emissivity for the rest of the globe remain unchanged. Both the modified and standard CESM are then forced with prescribed climatological SSTs and fixed present-day forcings for 35-yr simulations. The outputs from the last 30 years are analyzed. Compared to the standard CESM, the modified CESM has warmer surface air temperature, as well as a warmer and wetter planetary boundary layer over the Sahara and Sahel. The modified CESM thus favors more convection in these regions and has more convective rainfall, especially in the Sahara. The moisture convergence induced by such inclusion of surface spectral emissivity also contributes to the differences in simulated precipitation in the Sahel and the region south to it. Compared to observations, inclusion of surface spectral emissivity reduces surface temperature biases in the Sahara and precipitation biases in the Gulf of Guinea but exacerbates the wet biases in the Sahara. Such realistic representation of surface spectral emissivity can help unmask other factors contributing to regional biases in the original CESM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Implementation and Evaluation of Physics-Driven Dynamic Entrainment-Mixing Parameterization in a Climate Model and Its Impact on Low-Cloud Simulation

The turbulent entrainment-mixing process in the Community Earth System Model version 1.2 (CESM1.2) is assumed to follow the extremely inhomogeneous entrainment-mixing. However, different entrainment-mixing scenarios can occur in real clouds. To address this deficiency, a unifying parameterization that represents different entrainment-mixing processes is implemented and evaluated in CESM1.2. The results indicate that the homogeneous mixing degree values simulated by the new parameterization in CESM1.2 are predominantly greater than 50%, suggesting a tendency toward homogeneous mixing. Compared to the extremely inhomogeneous mixing mechanism, the new parameterization increases the cloud droplet number concentration (Nc). More importantly, the new parameterization improves low-cloud fraction (CLDLOW) simulation in Northwest Pacific (NWP) and Southeast Pacific (SEP) regions, with relative improvements of 2.95% and 4.17%, respectively. Furthermore, the improvements reach up to 44.6% and 16.2% in the NWP and SEP regions, respectively, when considering the relationship between N c and CLDLOW. Further analysis reveals that the new parameterization enhances cloud optical depth, longwave radiative cooling effect, net condensation rate, cloud water mixing ratio, lower-troposphere stability, and CLDLOW by increasing N c . Additionally, these results underscore the importance of improving entrainment-mixing parameterization in climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Change Projection in the Twenty-First Century Simulated by NIMS-KMA CMIP6 Model Based on New GHGs Concentration Pathways

Abstract The National Institute of Meteorological Sciences-Korea Meteorological Administration (NIMS-KMA) has participated in the Coupled Model Inter-comparison Project (CMIP) and provided long-term simulations using the coupled climate model. The NIMS-KMA produces new future projections using the ensemble mean of KMA Advanced Community Earth system model (K-ACE) and UK Earth System Model version1 (UKESM1) simulations to provide scientific information of future climate changes. In this study, we analyze four experiments those conducted following the new shared socioeconomic pathway (SSP) based scenarios to examine projected climate change in the twenty-first century. Present day (PD) simulations show high performance skill in both climate mean and variability, which provide a reliability of the climate models and reduces the uncertainty in response to future forcing. In future projections, global temperature increases from 1.92 °C to 5.20 °C relative to the PD level (1995–2014). Global mean precipitation increases from 5.1% to 10.1% and sea ice extent decreases from 19% to 62% in the Arctic and from 18% to 54% in the Antarctic. In addition, climate changes are accelerating toward the late twenty-first century. Our CMIP6 simulations are released to the public through the Earth System Grid Federation (ESGF) international data sharing portal and are used to support the establishment of the national adaptation plan for climate change in South Korea.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bayesian Approach to Regional Decadal Predictability: Sparse Parameter Estimation in High-Dimensional Linear Inverse Models of High-Latitude Sea Surface Temperature Variability

Stochastic reduced models are an important tool in climate systems whose many spatial and temporal scales cannot be fully discretized or underlying physics may not be fully accounted for. One form of reduced model, the linear inverse model (LIM), has been widely used for regional climate predictability studies—typically focusing more on tropical or midlatitude studies. However, most LIM fitting techniques rely on point estimation techniques deriving from fluctuation–dissipation theory. In this methodological study we explore the use of Bayesian inference techniques for LIM parameter estimation of sea surface temperature (SST), to quantify the skillful decadal predictability of Bayesian LIM models at high latitudes. We show that Bayesian methods, when compared to traditional point estimation methods for LIM-type models, provide better calibrated probabilistic skill, while simultaneously providing better point estimates due to the regularization effect of the prior distribution in high-dimensional problems. We compare the effect of several priors, as well as maximum likelihood estimates, on 1) estimating parameter values on a perfect model experiment and 2) producing calibrated 1-yr SST anomaly forecast distributions using a preindustrial control run of the Community Earth System Model (CESM). Finally, we employ a host of probabilistic skill metrics to determine the extent to which an LIM can forecast SST anomalies at high latitudes. We find that the choice of prior distribution has an appreciable impact on estimation outcomes, and priors that emphasize physically relevant properties enhance the model’s ability to capture variability of SST anomalies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Community climate simulations to assess avoided impacts in 1.5 and 2 °C futures

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5 °C above preindustrial levels and well below 2 °C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. Here, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2 °C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 and 2 °C levels and an overshoot 1.5 °C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. We also describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60 % greater frequency in the 2 °C climate than in a 1.5 °C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0 °C climate than a 1.5 °C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0 °C scenario, and 1 in 40 years in the 1.5 °C scenario. Significance of impact differences with respect to multi-model variability is not assessed.

54 ENVIRONMENTAL SCIENCES↗