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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Multi-resolution Arctic Shrub Cover Dataset Derived from UAS and Airborne SfM and LiDAR (2013-2025)

We synthesized 177 unoccupied aerial system flights and 77 airborne flights across the Arctic and created a multi-resolution benchmark data of low-to-tall shrub fractional cover leveraging Structure-from-Motion and Light Detection and Ranging. The resulting dataset covered a total of 1899 km2 across Alaska, Western Canada, Sweden, and Siberian Arctic, including key sites from the Oro Arctic to the High Arctic. The dataset is organized into 6 primary data collection directories (“Abisko,” “AWI,” “ERE,” “Fairbanks,” “NGEE,” “Toolik”), each containing site and flight subdirectories. Flight directories include shrub cover rasters (*.tifs) at 1 m, 5 m, and 30 m resolution, the canopy height model at 1 m resolution (*.tifs), and a bounding box *.kml file. For the AWI, Abisko, NGEE, and Fairbanks collections, we also include the GCC raster at 1 m resolution (*.tif). Files are organized by Collection > Site > Flight Name > Data Files. Flight rasters are in the local UTM zone and the .kml files are in the geographic coordinate system EPSG 4326. We also include a .csv file that details the source datasets for every flight. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

canopy height model↗
DOE OSTI2023

A full year of aerosol size distribution data from the central Arctic under an extreme positive Arctic Oscillation: insights from the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition

Abstract. The Arctic environment is rapidly changing due to accelerated warming in the region. The warming trend is driving a decline in sea ice extent, which thereby enhances feedback loops in the surface energy budget in the Arctic. Arctic aerosols play an important role in the radiative balance and hence the climate response in the region, yet direct observations of aerosols over the Arctic Ocean are limited. In this study, we investigate the annual cycle in the aerosol particle number size distribution (PNSD), particle number concentration (PNC), and black carbon (BC) mass concentration in the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. This is the first continuous, year-long data set of aerosol PNSD ever collected over the sea ice in the central Arctic Ocean. We use a k-means cluster analysis, FLEXPART simulations, and inverse modeling to evaluate seasonal patterns and the influence of different source regions on the Arctic aerosol population. Furthermore, we compare the aerosol observations to land-based sites across the Arctic, using both long-term measurements and observations during the year of the MOSAiC expedition (2019–2020), to investigate interannual variability and to give context to the aerosol characteristics from within the central Arctic. Our analysis identifies that, overall, the central Arctic exhibits typical seasonal patterns of aerosols, including anthropogenic influence from Arctic haze in winter and secondary aerosol processes in summer. The seasonal pattern corresponds to the global radiation, surface air temperature, and timing of sea ice melting/freezing, which drive changes in transport patterns and secondary aerosol processes. In winter, the Norilsk region in Russia/Siberia was the dominant source of Arctic haze signals in the PNSD and BC observations, which contributed to higher accumulation-mode PNC and BC mass concentrations in the central Arctic than at land-based observatories. We also show that the wintertime Arctic Oscillation (AO) phenomenon, which was reported to achieve a record-breaking positive phase during January–March 2020, explains the unusual timing and magnitude of Arctic haze across the Arctic region compared to longer-term observations. In summer, the aerosol PNCs of the nucleation and Aitken modes are enhanced; however, concentrations were notably lower in the central Arctic over the ice pack than at land-based sites further south. The analysis presented herein provides a current snapshot of Arctic aerosol processes in an environment that is characterized by rapid changes, which will be crucial for improving climate model predictions, understanding linkages between different environmental processes, and investigating the impacts of climate change in future Arctic aerosol studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Seasonal Clear-Sky Flux and Cloud Radiative Effect Anomalies in the Arctic Atmospheric Column Associated with the Arctic Oscillation and Arctic Dipole

The impact of the Arctic Oscillation (AO) and Arctic Dipole (AD) on the radiative flux into the Arctic mean atmospheric column is quantified. 3-month-averaged AO and AD indices are regressed with corresponding surface and top-of-atmosphere (TOA) fluxes from the CERES-SFC and CERES-TOA EBAF datasets over the period 2000-2014. An increase in clear-sky fluxes into the Arctic mean atmospheric column during fall is the largest net flux anomaly associated with AO, primarily driven by a positive net longwave flux anomaly (i.e. increase of net flux into the atmospheric column) at the surface. A decrease in the Arctic mean atmospheric column cloud radiative effect during winter and spring is the largest flux anomaly associated with AD, primarily driven by a change in the longwave cloud radiative effect at the surface. These prominent responses to AO and AD are widely distributed across the ice-covered Arctic, suggesting that the physical process or processes that bring about the flux change associated with AO and AD are distributed throughout the Arctic.

Hegyi, Bradley M.↗
NASA NTRS2017

The Regional Influence of the Arctic Oscillation and Arctic Dipole on the Wintertime Arctic Surface Radiation Budget and Sea Ice Growth

An analysis of 2000-2015 monthly Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled (CERES-EBAF) and Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) data reveals statistically significant fall and wintertime relationships between Arctic surface longwave (LW) radiative flux anomalies and the Arctic Oscillation (AO) and Arctic Dipole (AD). Signifying a substantial regional imprint, a negative AD index corresponds with positive downwelling clear-sky LW flux anomalies (greater than10W m(exp -2)) north of western Eurasia (0 deg E-120 deg E) and reduced sea ice growth in the Barents and Kara Seas in November-February. Conversely, a positive AO index coincides with negative clear-sky LW flux anomalies and minimal sea ice growth change in October-November across the Arctic. Increased (decreased) atmospheric temperature and water vapor coincide with the largest positive (negative) clear-sky flux anomalies. Positive surface LW cloud radiative effect anomalies also accompany the negative AD index in December-February. The results highlight a potential pathway by which Arctic atmospheric variability influences the regional surface radiation budget over areas of Arctic sea ice growth.

Hegyi, Bradley M.↗
DOE OSTI2017

Emergent Behavior of Arctic Precipitation in Response to Enhanced Arctic Warming: Enhanced Arctic Precipitation

Amplified warming of the high latitudes in response to human-induced emissions of greenhouse gases has already been observed in the historical record and is a robust feature evident across a hierarchy of model systems, including the models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). The main aims of this analysis are to quantify intermodel differences in the Arctic amplification (AA) of the global warming signal in CMIP5 RCP8.5 (Representative Concentration Pathway 8.5) simulations and to diagnose these differences in the context of the energy and water cycles of the region. This diagnosis reveals an emergent behavior between the energetic and hydrometeorological responses of the Arctic to warming: in particular, enhanced AA and its associated reduction in dry static energy convergence is balanced to first order by latent heating via enhanced precipitation. This balance necessitates increasing Arctic precipitation with increasing AA while at the same time constraining the magnitude of that precipitation increase. The sensitivity of the increase, ~1.25 (W/m 2 )/K (~240 (km 3 /yr)/K), is evident across a broad range of historical and projected AA values. Accounting for the energetic constraint on Arctic precipitation, as a function of AA, in turn informs understanding of both the sign and magnitude of hydrologic cycle changes that the Arctic may experience.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Role of Arctic Low Clouds in the Arctic Climate System: Isolating the Surface Type Influence on Arctic Low-Clouds

Interactions between sea ice and clouds represent a mechanism through which sea ice influences climate. Understanding the cloud response to the rapidly changing Arctic surface properties is necessary for improving climate simulations and projection of future change inside and outside the Arctic. Towards the goal of understanding the cloud response to sea ice, we composite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to analyze the cloud property differences between surface types. Restricting the analysis to MIZ crossing events enables the isolation of the sea ice effect on clouds from meteorological factors. We find larger cloud fraction and total water concentration below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months. During summer, the results suggest larger cloud fraction and total water concentration over ice-free surfaces, however differences do not exceed observational uncertainty. Cloud property differences are linked to atmospheric thermodynamic profile differences, namely ice-free surfaces are warmer, moister, less stable, and have more positive surface turbulent fluxes than ice-covered surfaces. Ice-free minus ice-covered cloud property differences scale with surface temperature differences and are only found in the presence of a surface temperature difference. Our results suggest a 0.02 cloud fraction and 0.005 g m 3 total water concentration increase (~5%) at the level of maximum cloud fraction between 2000-2021 due to the observed Arctic sea ice decline in fall, corresponding to ~2 Wm 2 increase in the net surface radiative flux supporting a positive sea ice-cloud radiative feedback in fall and winter and a negative sea ice-cloud radiative feedback in spring. We propose an updated conceptual model where the average surface type influence on cloud properties is mediated by surface temperature differences between ice-free and ice-covered surfaces.

Arctic climate↗
DOE OSTI2026

NGEE Arctic Authorship Guidelines

Authorship Guidelines were developed to help facilitate trust among team members as we span multiple institutions, scientific disciplines, and career stages. NGEE Arctic was built on a foundation of open science, data sharing, and collaboration. In Phase 4 of the project, it was particularly important to keep this foundation in mind as we develop new collaborations across the Arctic. Included in this package is one *.pdf. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.

Iversen, Colleen [ORNL] (ORCID:0000000182933450)↗
DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM3): Improved snow-vegetation interaction

This data product represents the integration of new code capability for arctic tundra snow-vegetation-terrain interactions into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The NGEE Arctic project developed a total of six Integrated Modeling (IM) modules informed by observations and experiments. New ELM capability represented by this data product (IM3) falls into three categories: 1) Downscaling from gridcell to topographic unit level when working through the existing coupler bypass code. 2) Four new parameters (taper, stocking, bendresist, and vegshape) have been added to ELM to allow for flexible definition of snow-vegetation interactions. 3) Vegshape and bendresist parameters are used to calculate the fraction of leaf area and/or stem area buried by snow for a given snow depth. This data record consists of a single document (pdf format) that describes the theoretical basis for the snow-vegetation-terrain interactions added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2026

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗
DOE OSTI2020

Source attribution of Arctic black carbon and sulfate aerosols and associated Arctic surface warming during 1980–2018

Observations show that the concentrations of Arctic sulfate and black carbon (BC) aerosols have declined since the early 1980s. Previous studies have reported that reducing sulfate aerosols potentially contributed to the recent rapid Arctic warming. In this study, a global aerosol–climate model (Community Atmosphere Model, version 5) equipped with Explicit Aerosol Source Tagging (CAM5-EAST) is applied to quantify the source apportionment of aerosols in the Arctic from 16 source regions and the role of aerosol variations in affecting changes in the Arctic surface temperature from 1980 to 2018. The CAM5-EAST simulated surface concentrations of sulfate and BC in the Arctic had a decrease of 43% and 23%, respectively, in 2014–2018 relative to 1980–1984 mainly due to the reduction of emissions from Europe, Russia and local Arctic sources. Increases in emissions from South and East Asia led to positive trends in Arctic sulfate and BC in the upper troposphere. All aerosol radiative impacts are considered including aerosol–radiation and aerosol–cloud interactions, as well as black carbon deposition on snow- and ice-covered surfaces. Within the Arctic, sulfate reductions caused a top-of-atmosphere (TOA) warming of 0.11 and 0.25 W m -2 through aerosol–radiation and aerosol–cloud interactions, respectively. While the changes in Arctic atmospheric BC has little impact on local radiative forcing, the decrease in BC in snow and ice led to a net cooling of 0.05 W m -2 . By applying climate sensitivity factors for different latitudinal bands, global changes in sulfate and BC during 2014–2018 (with respect to 1980–1984) exerted a +0.088 and 0.057 K Arctic surface warming, respectively, through aerosol–radiation interactions. Through aerosol–cloud interactions, the sulfate reduction caused an Arctic warming of +0.193 K between the two time periods. The weakened BC effect on snow–ice albedo led to an Arctic surface cooling of -0.041 K. The changes in atmospheric sulfate and BC outside the Arctic produced a total Arctic warming of +0.25 K, the majority of which is due to the midlatitude changes in radiative forcing. Our results suggest that changes in aerosols over the midlatitudes of the Northern Hemisphere have a larger impact on Arctic temperature than other regions through enhanced poleward heat transport. The combined total effects of sulfate and BC produced an Arctic surface warming of +0.297 K, explaining approximately 20% of the observed Arctic warming since the early 1980s.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Modeling CO 2 emissions from A rctic lakes: Model development and site‐level study

Abstract Recent studies indicated that Arctic lakes play an important role in receiving, processing, and storing organic carbon exported from terrestrial ecosystems. To quantify the contribution of Arctic lakes to the global carbon cycle, we developed a one‐dimensional process‐based Arctic Lake Biogeochemistry Model (ALBM) that explicitly simulates the dynamics of organic and inorganic carbon in Arctic lakes. By realistically modeling water mixing, carbon biogeochemistry, and permafrost carbon loading, the model can reproduce the seasonal variability of CO 2 fluxes from the study Arctic lakes. The simulated area‐weighted CO 2 fluxes from yedoma thermokarst lakes, nonyedoma thermokarst lakes, and glacial lakes are 29.5, 13.0, and 21.4 g C m −2 yr −1 , respectively, close to the observed values (31.2, 17.2, and 16.5 ± 7.7 g C m −2 yr −1 , respectively). The simulations show that the high CO 2 fluxes from yedoma thermokarst lakes are stimulated by the biomineralization of mobilized labile organic carbon from thawing yedoma permafrost. The simulations also imply that the relative contribution of glacial lakes to the global carbon cycle could be the largest because of their much larger surface area and high biomineralization and carbon loading. According to the model, sunlight‐induced organic carbon degradation is more important for shallow nonyedoma thermokarst lakes but its overall contribution to the global carbon cycle could be limited. Overall, the ALBM can simulate the whole‐lake carbon balance of Arctic lakes, a difficult task for field and laboratory experiments and other biogeochemistry models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASM can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes in the freshwater flux between arctic climate system components resulting from decadal changes in land and sea ice, seasonal snow, vegetation, and ocean circulation. - Changing energetics due to decadal changes in ice mass, vegetation, and air-sea interactions. - The role of small-scale atmospheric and oceanic processes that influence decadal variability. This research has been addressing modes of natural climate variability as well as extreme and rapid climate change. RASM can facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts.

58 GEOSCIENCES↗
DOE OSTI2021

Linear Response Function Reveals the Most Effective Remote Forcing in Causing September Arctic Sea Ice Melting in CESM

We apply the linear response function method to investigate the most excitable mode of the September Arctic sea ice and its corresponding remote oceanic forcing in climate models. The method is useful in identifying the fundamental, dynamical and causal relationship between the remote forcing and sea ice response. We find that the most excitable mode of the September Arctic sea ice preferentially takes place over the Pacic side of the Arctic and its remote forcing corresponds to a dipole pattern of precipitation anomaly in the tropics with an increase of precipitation over the western and central tropical and subtropical Pacic ocean while a decrease over the Maritime Continent. The tropical precipitation anomaly likely drives a Rossby wave train propagating toward higher latitudes and leads to a ridge anomaly over the Pacic side of the Arctic, resulting in poleward atmospheric heat transport, enhanced downward longwave radiation and thus melting of the sea ice. In addition, a good agreement is found with the leading tropical Arctic teleconnection mode detected in a pre-industrial control simulation, which supports the usefulness and robustness of the linear response function method and the importance of tropical forcing in shaping the sea ice variability.

Wu, Yutian↗
DOE OSTI2022

Relative importance of high-latitude local and long-range-transported dust for Arctic ice-nucleating particles and impacts on Arctic mixed-phase clouds

Dust particles, serving as ice-nucleating particles (INPs), may impact the Arctic surface energy budget and regional climate by modulating the mixed-phase cloud properties and lifetime. In addition to long-range transport from low-latitude deserts, dust particles in the Arctic can originate from local sources. However, the importance of high-latitude dust (HLD) as a source of Arctic INPs (compared to low-latitude dust, LLD) and its effects on Arctic mixed-phase clouds are overlooked. In this study, we evaluate the contribution to Arctic dust loading and INP population from HLD and six LLD source regions by implementing a source-tagging technique for dust aerosols in version 1 of the US Department of Energy's Energy Exascale Earth System Model (E3SMv1). Our results show that HLD is responsible for 30.7 % of the total dust burden in the Arctic, whereas LLD from Asia and North Africa contributes 44.2 % and 24.2 %, respectively. Due to its limited vertical transport as a result of stable boundary layers, HLD contributes more in the lower troposphere, especially in boreal summer and autumn when the HLD emissions are stronger. LLD from North Africa and East Asia dominates the dust loading in the upper troposphere with peak contributions in boreal spring and winter. The modeled INP concentrations show better agreement with both ground and aircraft INP measurements in the Arctic when including HLD INPs. The HLD INPs are found to induce a net cooling effect (-0.24 W m -2 above 60 °N) on the Arctic surface downwelling radiative flux by changing the cloud phase of the Arctic mixed-phase clouds. The magnitude of this cooling is larger than that induced by North African and East Asian dust (0.08 and -0.06 W m -2 , respectively), mainly due to different seasonalities of HLD and LLD. Uncertainties of this study are discussed, which highlights the importance of further constraining the HLD emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Local radiative feedbacks over the Arctic based on observed short-term climate variations

We compare various radiative feedbacks in response to short-term climate variations estimated from reanalysis, satellite, and global climate model datasets using the combined Kernel-Gregory approach over the Arctic (60-90°N). Except for the shortwave cloud feedback, all feedbacks are positive over the Arctic. Lapse rate feedback is comparable with surface albedo feedback. Relative to the tropics (30°S-30°N), the temperature feedback (lapse rate feedback plus Planck feedback deviation from its global mean) is the largest contributor to Arctic amplification among all feedbacks, followed by surface albedo feedback. The choice of meteorological fields has a small impact on the cloud feedback estimate, but different top-of-the-atmosphere clear-sky fluxes datasets can result in a wide spread of estimated cloud feedbacks. The net cloud feedback over the Arctic is positive due to a larger positive in longwave than the negative shortwave feedback, but has the largest uncertainty. Relative to the tropics, the longwave cloud feedback largely contributes to the Arctic amplification.

Zhang, Rudong↗
NASA NTRSDate not supplied

On the Nature of the Arctic’s Positive Lapse-rate Feedback: Cause or Symptom of Arctic Amplification

Radiative energy fluxes exiting the atmosphere towards the surface and to space are sensitive to the vertical structure of temperature. Under anthropogenic forcing, this sensitivity gives rise to the lapse-rate feedback. Shown to be negative in the tropics and positive in the Arctic, studies argue that the lapse-rate feedback is the primary cause of Arctic Amplification. While mechanistically the negative tropical lapse-rate feedback is understood, the mechanics of the positive Arctic lapse-rate feedback are less clear. Previous arguments state that the Arctic’s stable stratification is the origin of its positive lapse-rate feedback. We present results using CMIP5 and CMIP6 model output that arguing that the magnitude, spatial variability, seasonality, and inter-model spread in the Arctic lapse-rate feedback is controlled by surface properties and atmosphere-ocean-sea ice energy exchanges, not the degree of stable stratification. We argue that the Arctic’s positive lapse-rate feedback is a seasonal and regional phenomenon that manifests from local surface characteristics and surface albedo, ice insulation, and thermal inertia feedbacks that cause surface warming to outpace atmospheric warming in sea ice-retreat regions. We view the Arctic’s positive lapse-rate feedback as a symptom rather than the primary cause of Arctic Amplification.

Patrick Charles Taylor↗