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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗
DOE OSTI2020

Impacts of Wildfire Aerosols on Global Energy Budget and Climate: The Role of Climate Feedbacks

Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, the Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols’ impacts on global climate with emphasis on the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be -0.78 ± 0.29 W m -2 , which is mostly from shortwave RE due to aerosol–cloud interactions (REaci; -0.70 ± 0.20 W m -2 ). The associated global annual-mean surface air temperature (SAT) change ΔT is -0.64 ± 0.16 K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to reamplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ΔT) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ΔT) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N) but increases in the Southern Hemisphere tropical ocean, which is associated with the southward shift of the intertropical convergence zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal forest fire aerosol indirect effects, through intensifying the cross-equator atmospheric heat transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Mesoscale Organization in Cumulus-Coupled Stratocumulus

Marine cloud systems cover a substantial portion of the world’s oceans. Most of these clouds form relatively close to the ocean surface, typically within one to two kilometers, a region referred to by meteorologists as the marine boundary layer. They are composed predominantly of liquid water, although ice particles can occur in mid- and high-latitude marine clouds during winter. In satellite imagery, these clouds appear bright against the darker ocean surface below, reflecting a large fraction of incoming sunlight back into space that would otherwise warm the ocean. Because marine boundary layer clouds cover such an extensive area of the ocean, they exert a significant influence on Earth’s overall transfer of solar energy absorbed by the surface and thermal energy emitted to space, a balance known as the planetary radiation budget. Marine boundary layer clouds are typically thin, and their formation and dissipation depend on a delicate balance between processes acting at the ocean surface below and the warm, dry air above. They are notoriously difficult to simulate accurately in weather forecast models, which often produce too few marine low clouds in midlatitudes and clouds in tropical regions that are excessively bright, meaning they reflect too much solar radiation. The marine boundary layer is frequently characterized by widespread overcast cloud cover that often transitions from a continuous, single-layer deck to more broken cloud fields toward the tropics. These transitions typically proceed through an intermediate stage in which shallow, broken clouds form beneath the overlying stratiform cloud deck. Once broken clouds develop below the overcast, they frequently self-organize into cloud clusters known as marine boundary layer convective complexes (MBLCCs), although the mechanisms governing the formation and organization of MBLCCs remain poorly understood. Accurately representing these transitions in long-range weather forecast models is essential because they influence the properties of air masses advected over the continental United States and Europe, and they become increasingly important for forecasts on seasonal and longer timescales. We employed two complementary approaches to investigate the processes controlling MBLCCs and their impact on marine cloud cover. Long-term observations from the U.S. Department of Energy’s Eastern North Atlantic (ENA) Observatory provided a unique dataset that allowed us to characterize fundamental properties of MBLCCs, including their typical size and frequency of occurrence. These observations were combined with high-resolution numerical simulations performed on supercomputers to examine the evolution of MBLCCs during cold-air outbreaks over the ENA region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Estimation of the radiation budget during MOSAiC based on ground-based and satellite remote sensing observations

An accurate representation of the radiation budget is essential for investigating the impact of clouds on the climate system, especially in the Arctic, an environment highly sensitive to complex and rapid environmental changes. In this study, we analyse a unique dataset of observations from the central Arctic made during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in conjunction with state-of-the-art satellite products from CERES (Clouds and the Earth's Radiant Energy System) to investigate the radiative effect of clouds and radiative closure at the surface and the top of the atmosphere (TOA). We perform a series of radiative transfer simulations using derived cloud macro- and microphysical properties as inputs to the simulations for the entire MOSAiC period, comparing our results to collocated satellite products and ice-floe observations. The radiative closure biases were generally within the instrumental uncertainty, indicating that the simulations are sufficiently accurate to reproduce the radiation budget during MOSAiC. Comparisons of the simulated radiation budget relative to CERES show similar values in the terrestrial flux but relatively large differences in the solar flux, which are attributed to a lower surface albedo and a possible underestimation of atmospheric opacity by CERES. While the simulation results were consistent with the observations, more detailed analyses reveal an overestimation of simulated cloud opacity for cases involving geometrically thick ice clouds. In the annual mean, we found that, during the MOSAiC expedition, the presence of clouds leads to a loss of 5.2 W m −2 of the atmosphere–surface system to space, while the surface gains 25.0 W m −2 and the atmosphere is cooled by 30.2 W m −2 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Effects of marine organic aerosols as sources of immersion-mode ice-nucleating particles on high-latitude mixed-phase clouds

Mixed-phase clouds are frequently observed in high-latitude regions and have important impacts on the surface energy budget and regional climate. Marine organic aerosol (MOA), a natural source of aerosol emitted over ~70 % of Earth's surface, may significantly modify the properties and radiative forcing of mixed-phase clouds. However, the relative importance of MOA as a source of ice-nucleating particles (INPs) in comparison to mineral dust, and MOA's effects as cloud condensation nuclei (CCN) and INPs on mixed-phase clouds are still open questions. In this study, we implement MOA as a new aerosol species into the Community Atmosphere Model version 6 (CAM6), the atmosphere component of the Community Earth System Model version 2 (CESM2), and allow the treatment of aerosol–cloud interactions of MOA via droplet activation and ice nucleation. CAM6 reproduces observed seasonal cycles of marine organic matter at Mace Head and Amsterdam Island when the MOA fraction of sea spray aerosol in the model is assumed to depend on sea spray biology but fails when this fraction is assumed to be constant. Model results indicate that marine INPs dominate primary ice nucleation below 400 hPa over the Southern Ocean and Arctic boundary layer, while dust INPs are more abundant elsewhere. By acting as CCN, MOA exerts a shortwave cloud forcing change of -2.78 W m-2 over the Southern Ocean in the austral summer. By acting as INPs, MOA enhances the longwave cloud forcing by 0.35 W m-2 over the Southern Ocean in the austral winter. The annual global mean net cloud forcing changes due to CCN and INPs of MOA are -0.35 and 0.016 W m-2, respectively. These findings highlight the vital importance for Earth system models to consider MOA as an important aerosol species for the interactions of biogeochemistry, hydrological cycle, and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Distinct roles of land cover in regulating spatial variabilities of temperature responses to radiative effects of aerosols and clouds

Surface temperature responses to radiative perturbations due to aerosols and clouds are complicated by the land surface properties. To disentangle these complexities, this study, from a terrestrial surface energy budget perspective, isolates the underlying biophysical processes from the instantaneous radiative effects of aerosols and clouds on surface temperature using the National Center for Atmospheric Research Community Earth System Model version 1.2.1. It is found that in comparison with the global heterogeneous distributions of instantaneous radiative perturbations at the surface induced by aerosols and clouds, the spatial variations of the corresponding surface temperature responses to aerosol direct radiative effects (DRE) during the daytime and cloud radiative effects (CRE) during the nighttime are amplified. It is because of the consistent global distribution of the local surface climate sensitivity (a function of land cover properties such as surface roughness and Bowen ratio) with those of daytime DRE and nighttime CRE. By applying identical anthropogenic aerosol and precursor emissions over eight major past, present and projected future anthropogenic aerosol emitting regions (i.e. Brazil, China, East Africa, India, Indonesia, South Africa, United States and Western Europe), surface temperature responses to aerosol radiative cooling in the daytime and cloud radiative warming in the nighttime over these regions positively regulated by local surface climate sensitivities are prominent.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Dependence of Cloud Macrophysical Properties and Phase Distributions on Environmental Conditions Over the North Atlantic and Southern Ocean: Results From COMBLE and MARCUS

The accurate representation of Cold Air Outbreaks (CAOs) and affiliated mixed-phase boundary layer (BL) clouds in models is challenging. How BL cloud properties evolve during CAOs and their dependence on meteorological conditions is not well understood but is important for the simulation of Earth's energy budgets. Here the properties of polar BL clouds over the North Atlantic (NA) and Southern Ocean (SO) are compared using observations from the Measurements of Aerosol Radiation and CloUds over the SO (MARCUS) and CAOs in the Marine BL Experiment (COMBLE) conducted over the NA. MARCUS observations show a stronger BL inversion than COMBLE, with a higher mean EIS (estimated inversion strength)/LTS (lower tropospheric stability) of -0.03 K/13 K compared to COMBLE’s -3.2 K/9.3 K. 39% of CAOs observed during COMBLE were intense with M > 5 K, while MARCUS only had 1.3%. 78%/72% of clouds sampled in CAOs during COMBLE/MARCUS had cloud top heights <4 km. The mean BL cloud top height was over 400 m higher, and the BL was over 500 m deeper for M of 10 K compared to 0 K for both regions. MARCUS observed a 27% moister BL structure than COMBLE when M > 5 K due to stronger BL inversion trapping more moisture within the BL. Under the same LTS, EIS, and M conditions, MARCUS observed a 12% drier BL structure, and clouds were 46% more turbulent than COMBLE. During CAOs, 54% of single-layer BL clouds sampled during MARCUS had liquid-dominated bases compared to 39% during COMBLE.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Subtropical Eastern North Pacific SST bias in earth system models

Karthik Balaguru (PNNL), Luke Van Roekel (LLNL), L. Ruby Leung (PNNL) and Milena Veneziani (LLNL) Abstract: This study systematically evaluates the warm SST bias in the Subtropical Eastern North Pacific (SENP), a problem plaguing most CMIP6 models, using the Energy Exascale Earth System Model version 1 (E3SM). Compared to the model at its standard resolution (1o atmosphere, 30-60 km ocean), the SST bias improves in several regions at high resolution (0.25o atmosphere, 18-6 km ocean) except in subtropical eastern boundary regions, such as the SENP. A mixed layer heat budget analysis reveals that errors in the surface radiative fluxes and horizontal heat advection are primarily responsible for the bias. Analysis of HighResMIP models indicates that the lack of improvement in the SENP SST bias with resolution is not native to E3SM alone. A larger CMIP6 inter-model correlation of SST bias with biases in surface winds than radiation highlights the important role of large-scale circulation biases in the SENP SST bias in coupled models.

Balaguru, Karthik↗
DOE OSTI2021

Greater committed warming after accounting for the pattern effect

Our planet’s energy balance is sensitive to spatial inhomogeneities in sea surface temperature and sea ice changes, but this is typically ignored in climate projections. Here, we show the energy budget during recent decades can be closed by combining changes in effective radiative forcing, linear radiative damping and this pattern effect. The pattern effect is of comparable magnitude but opposite sign to Earth’s net energy imbalance in the 2000s, indicating its importance when predicting the future climate on the basis of observations. Additionally, after the pattern effect is accounted for, the best-estimate value of committed global warming at present-day forcing rises from 1.31 K (0.99–2.33 K, 5th–95th percentile) to over 2 K, and committed warming in 2100 with constant long-lived forcing increases from 1.32 K (0.94–2.03 K) to over 1.5 K, although the magnitude is sensitive to sea surface temperature dataset. Further constraints on the pattern effect are needed to reduce climate projection uncertainty.

58 GEOSCIENCES↗
DOE OSTI2020

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Water sources and land capacitor effects stimulate observed summer Arctic moistening and warming

The primary sources of recent summer Arctic moistening trends in reanalysis are uncertain, hindering attribution of observed Arctic warming due to radiative effects from water vapor changes. Here, we use a combined online numerical water tracer and circulation nudging approach in the Community Earth System Model to track the sources of water vapor beyond its initial sources. Trends in boreal summer large-scale circulation have driven moistening of the Arctic over recent decades, having a large impact on the Arctic radiative budget, accounting for 94% of the strengthening water vapor radiative feedback. We identify two key regions supplying the Arctic water vapor feedback: Northeast North America and western/central Eurasia. In both regions, anticyclonic circulations over the southwest Atlantic and eastern Europe move moisture from the tropical oceans poleward to high latitude land through precipitation in winter and spring. During summer, evapotranspiration over land releases this water vapor, and it is transported by winds into the Arctic. We refer to this sequence of terrestrial moisture storage and release as the land capacitor effect. Thus, the impacts of circulation changes on poleward moisture transport and land-atmosphere interactions over high latitudes represent the underlying mechanisms of the recent moistening and warming in the Arctic.

Arctic amplification↗
DOE OSTI2026

Indirect climate impacts of the Hunga eruption

Injection of sulfur and water vapour by the Hunga volcanic eruption significantly altered chemical composition and radiative budget of the stratosphere. Yet, whether the eruption could also affect surface climate, especially via indirect pathways, remains poorly understood. Here we investigate these effects using large ensembles of simulations with the CESM2(WACCM6) Earth system model, incorporating interactive chemistry and aerosols in both coupled ocean and atmosphere-only configurations. We find some statistically significant extratropical regional climate responses to the eruption driven by circulation changes; these are partially linked to the modulation of El Niño–Southern Oscillation, and its associated teleconnections, and to perturbations of the stratospheric polar vortex in both hemispheres. The stratospheric anomalies affect surface climate through modulating the North Atlantic Oscillation in the Northern Hemisphere (up to three boreal winters following the eruption) and the Southern Annular Mode in the Southern Hemisphere in late 2023. The latter is partly related to a concurrent reduction in Antarctic ozone, as increased stratospheric aerosols and water vapor reach the polar vortex. Our study suggests that the eruption could have had a non-negligible influence on regional surface climate, and discusses the mechanisms via which such an influence could occur. However, the results also highlight that this forcing is relatively weak compared to interannual variability, and is subject to model uncertainties in the representation of key processes. More research is thus needed before definitive statements on the role of the eruption in contributing to surface climate and weather events in the following years are made.

Geosciences↗
DOE OSTI2020

Aerosol-Ice Formation Closure Pilot Study (AEROICSTUDY) Field Campaign Report

The aerosol-ice formation closure pilot study (AEROICESTUDY) was a field campaign conducted at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility at the Southern Great Plains (SGP) observatory from October 7 to 28, 2019. The purpose of this campaign was to test a field observational approach for conducting an aerosol-ice formation closure study. In other words, the goal was to predict the number of ice nucleating particles (INPs) from the measurements of physical and chemical aerosol properties and compare those to measured INP number concentrations. This project was motivated by the fact that the aerosol community has widely conducted aerosol radiative closure, aerosol-cloud condensation nuclei (CCN), and CCN-droplet closure studies to test the physical models and parameterizations that cloud-resolving and climate models rely on to perform reliable simulations of the Earth system and energy budget. However, very few closure studies related to INPs have been conducted, and to our knowledge, none using robust, size-resolved, ambient aerosol composition measurements as model inputs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Diffuse Radiation Forcing Constraints on Gross Primary Productivity and Global Terrestrial Evapotranspiration

Abstract The diffuse radiation fertilization effect—the increase in plant productivity in the presence of higher diffuse radiation ( K ↓,d )—is an important yet understudied aspect of atmosphere‐biosphere interactions and can modify the terrestrial carbon, energy, and water budgets. The K ↓,d fertilization effect links the carbon cycle with clouds and aerosols, all of which are large sources of uncertainties for our current understanding of the Earth system and for future climate projections. Here we establish to what extent observational and modeling uncertainty in sunlight's diffuse fraction ( k d ) affects simulated gross primary productivity (GPP) and terrestrial evapotranspiration ( λE ). We find only 48 eddy covariance sites with simultaneous sufficient measurements of K ↓,d with none in the tropical climate zone, making it difficult to constrain this mechanism globally using observations. Using a land modeling framework based on the latest version of the Community Land Model, we find that global GPP ranges from 114 Pg C year −1 when using k d forcing from the Modern‐Era Retrospective analysis for Research and Applications, version 2 reanalysis to a ∼7% higher value of 122 Pg C year −1 when using the Clouds and the Earth's Radiant Energy System satellite product, with especially strong differences apparent over the tropical region (mean increase ∼9%). The differences in λE , although smaller (−0.4%) due to competing changes in shaded and sunlit leaf transpiration, can be greater than regional impacts of individual forcing agents like aerosols. Our results demonstrate the importance of comprehensively and systematically validating the simulated k d by atmosphere modules as well as the response to differences in k d within land modules across Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic Aerosol Sources and Mixing States Field Campaign Report

The Arctic is warming at a faster rate than anywhere else on Earth, with rapidly shrinking sea ice extent transforming the region. Depending on chemical and physical properties, atmospheric aerosols directly scatter and/or absorb radiation, serve as cloud droplet and/or ice crystal nuclei, and/or reduce the reflectiveness of the snow surface, thereby altering the atmospheric energy budget. There is a wide spread in the magnitude of simulated arctic aerosol radiative forcing, and significant differences in aerosol concentration levels and seasonal cycles often exist between models and observations. Increasing local natural and anthropogenic emissions are significant, with uncertain climate impacts due to complex feedbacks. Model evaluations, however, are limited by the dearth of arctic aerosol observations available and an inadequate understanding of arctic aerosol processes. The majority of previous arctic aerosol observations have been made through intensive spring/summer field campaigns, with few intensive measurement studies focused on the fall-winter transition, a period when freeze-up is occurring later and thinning sea ice is resulting in wintertime ice fracturing. Aerosol monitoring at arctic coastal stations has provided knowledge of long-term seasonal trends in aerosol concentrations. The completed ARM field campaign addresses observational and knowledge gaps through detailed aerosol size and chemical composition measurements during the fall-winter transition in the coastal Arctic and through the entire annual cycle in the central Arctic. The observations are improving our understanding of the sources and processes controlling the aerosol population in the rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Remote Influence of Andean Convection on Amazonian Rainfall and Its Mechanisms

Models from Coupled Model Intercomparison Project Phase 6 produce too much precipitation over the Andes but too little over the Amazon or the Wet Andes-Dry Amazon (WADA) bias pattern. Unlike the conventional view that convection parameterization and land model deficiencies can contribute to Amazonian rainfall biases, we approach this long-standing biased model behavior through the lens of Andean convection. Using Community Earth System Model v1.1 and focusing on the wet season, our mechanism-denial experiments demonstrate that Andean convection notably reduces precipitation over the Amazon during austral summer. The Andean forced Amazonian response operates on weather timescale. Furthermore, the reduction of Amazonian rainfall is detectable within a few hours after initial Andean forcing. The precipitation response is primarily driven by variations in the moisture budget and is moderated by changes in convective available potential energy over the Amazon. Changes in the total advection of moisture over the Amazon are dominated by the vertical advection term and can be attributed to discrepancies in the dynamic omega field. In the experiments, the Andean east flank region is scrutinized where the vertical velocity and moisture fields play an intermediary role for the Andean driven WADA connection. The Andean forcing induces descending anomalies on the Andean east flank. The disturbances of wind and geopotential fields over the Andean east flank propagate eastward via Kelvin waves. Over the Amazon, descending anomalies and advective drying lead to reduction of mid-to-high level cloud, increase of shortwave cloud forcing and surface net radiation, and enhancement of themodynamic stability and rainfall reduction.

58 GEOSCIENCES↗
DOE OSTI2021

Significant impact of forcing uncertainty in a large ensemble of climate model simulations

Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.

54 ENVIRONMENTAL SCIENCES↗