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DOE OSTI2022

Riverine Plastic Pollution: Sampling and Analysis Methods

Riverine plastic pollution has been found in all major U.S. rivers, but the exact amount of plastic being released to the oceans has not been quantified. Field studies conducted in U.S. rivers have used a range of sampling and analysis techniques and rarely measured the mass of the plastic collected. Measurements of riverine plastic pollution are needed to calibrate and validate models used to estimate the U.S. riverine plastic emissions to the oceans. This report surveys measurement methods used to quantify riverine pollution and current estimates of U.S. riverine plastic pollution from measurements and models. Measurement methods include field sampling and laboratory analysis. Field sampling methods are described for large (macro) and small (micro) plastic particles. Laboratory analysis methods are described for macro and microplastic with an emphasis on the detailed characterization processes of microplastics. Waterborne leachate analysis is also briefly described. Three models are described that estimate plastic pollution based on mismanaged plastic waste in the river catchment basins. The models were validated and calibrated with global data sources. The data sources were predominantly outside of the U.S., where the magnitude and composition of plastic pollution is different than what is found in U.S. rivers. Comprehensive measurements of riverine plastics are needed not only to characterize the riverine plastic pollution, but also parameterize and validate models of plastic fate and transport. This report also describes five key U.S. rivers that span a range of sizes and environmental conditions that could be sampled to obtain data to support characterization and model development of plastic pollution from rivers to oceans. Sampling and analysis protocol recommendations are made to ensure the highest quality of data are collected in the five rivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Aerosol-deep convection interaction based on joint cell-thermal tracking in Large Eddy Simulations during the TRACER campaign

In cumulus clouds, aerosol concentrations control cloud droplet concentrations, modifying cloud radiative properties, precipitation processes, and cloud electrification. However, mechanisms of aerosol-deep convection interactions are not well understood due to complex cloud dynamics and microphysics. We investigate the interaction of aerosols with isolated deep convection using Large Eddy Simulations of two cases during the TRacking Aerosol Convection interactions ExpeRiment (TRACER) near Houston, Texas, using a joint cell-thermal tracking algorithm. Cumulus thermals are droplet generators, since supersaturation and droplet nucleation coincide with thermal centers, where the strongest updrafts occur. Primary ice crystal formation does not take place inside thermals, but at layers where previous thermals detrained moisture. As subsequent thermals containing supercooled droplets penetrate these layers, hail and graupel form at or near these thermals. Higher aerosol concentrations result in higher droplet concentrations that suppress drizzle, delay warm rain processes, and transport more moisture aloft. This increases snow and ice amount, as well as graupel and hail, leading to more lightning. Polluted thermals initiate at slightly higher altitudes, and are slightly larger and faster, suggesting a weak invigoration. We also find more thermals per cell, but fewer isolated cells, since convection is more aggregated and intense, especially near the end of the 24 h simulation. Non-linear mesoscale feedback likely triggered by temperature and moisture responses to aerosol-thermal interactions causes the aggregation. Time-lagged aerosol-reinitialization experiments show that the mesoscale response is the predominant forcing for the invigoration. These changes happen within one day, on a smaller scale than previously suggested.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The Arctic

The Arctic environment in 2024 continued on a trajectory that has put it in a state far different from that of the twentieth century. Ongoing accumulation of greenhouse gases in the atmosphere continues to quickly warm the Arctic, resulting in rapid changes in the cryosphere that are driving cascading impacts to climate, ecological, and societal systems. Many weather- and climate-related impacts in the Arctic are the result of compounding change, such as increased riverbank erosion, which is proximately due to increased river discharge from higher seasonal precipitation, yet is also exacerbated by thawing permafrost. However, even individual storms occur within very different ocean and ice conditions than were typically present in the late twentieth century. As a result, the impacts, including high winds, excessive precipitation, and coastal inundation, may be quite different nowadays, as exemplified by the October 2024 storm in northwest Alaska that produced severe coastal flooding in several communities. To share some of these impacts with a wider audience, select extreme weather impacts around the greater Arctic have been highlighted through the inclusion of sidebars in recent State of the Climate Arctic chapters (e.g., Benestad et al. 2023; Thoman et al. 2024).

Thoman, Richard L. [Univ. of Alaska, Fairbanks, AK↗
DOE OSTI2022

Trace metal contents of autotrophic flagellates from contrasting open‐ocean ecosystems

Abstract Nano‐ and picophytoplankton are a major component of open‐ocean ecosystems and one of the main plankton functional types in biogeochemical models, yet little is known about their trace metal contents. In cultures of the picoeukaryote Ostreococcus lucimarinus , iron limitation reduced iron quotas by 68%, a fraction of the plasticity known in diatoms. In contrast, a commonly co‐occurring cyanobacterium, Prochlorococcus , showed variable iron contents with iron availability in culture. Synchrotron X‐ray fluorescence was used to measure single‐cell metal (Mn, Fe, Co, Ni, Zn) quotas of autotrophic flagellates (1.4–16.8‐ μ m diameter) collected from four ocean regions. Iron quotas were tightly constrained and showed little response to iron availability, similar to cultured Ostreococcus . Zinc quotas also did not vary with zinc availability but appeared to vary with phosphorus availability. These results suggest that macronutrient and metal availability may be equally important for controlling metal contents of small eukaryotic open‐ocean phytoplankton.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Manganese Limitation of Phytoplankton Physiology and Productivity in the Southern Ocean

Although iron and light are understood to regulate the Southern Ocean biological carbon pump, observations have also indicated a possible role for manganese. Low concentrations in Southern Ocean surface waters suggest manganese limitation is possible, but its spatial extent remains poorly constrained and direct manganese limitation of the marine carbon cycle has been neglected by ocean models. Here, using available observations, we develop a new global biogeochemical model and find that phytoplankton in over half of the Southern Ocean cannot attain maximal growth rates because of manganese deficiency. Manganese limitation is most extensive in austral spring and depends on phytoplankton traits related to the size of photosynthetic antennae and the inhibition of manganese uptake by high zinc concentrations in Antarctic waters. Importantly, manganese limitation expands under the increased iron supply of past glacial periods, reducing the response of the biological carbon pump. Overall, these model experiments describe a mosaic of controls on Southern Ocean productivity that emerge from the interplay of light, iron, manganese and zinc, shaping the evolution of Antarctic phytoplankton since the opening of the Drake Passage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Increased exposure of coastal cities to sea-level rise due to internal climate variability

Adaptation to future sea-level rise is based on projections of continuously improving climate models. These projections are accompanied by inherent uncertainties, including those due to internal climate variability (ICV). The ICV arises from complex and unpredictable interactions within and between climate-system components, rendering its impact irreducible. Although neglecting this uncertainty can lead to an underestimation of future sea-level rise, its estimation and impacts have not been fully explored. Combining the Community Earth System Model version 1 Large Ensemble experiments with power-law statistics, we show that, by 2100, if the ICV uncertainty reaches its upper limit, new sea-level-rise hotspots would appear in Southeast Asian megacities (Chennai, Kolkata, Yangon, Bangkok, Ho Chi Minh City and Manila), in western tropical Pacific Islands and the Western Indian Ocean. Here, the better the ICV uncertainty is taken into account and correctly estimated, the more effective adaptation strategies can be elaborated with confidence and actions to follow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Wildfire aerosol deposition likely amplified a summertime Arctic phytoplankton bloom

Summertime wildfire activity is increasing in boreal forest and tundra ecosystems in the Northern Hemisphere. However, the impact of long range transport and deposition of wildfire aerosols on biogeochemical cycles in the Arctic Ocean is unknown. Here, we use satellite-based ocean color data, atmospheric modeling and back trajectory analysis to investigate the transport and fate of aerosols emitted from Siberian wildfires in summer 2014 and their potential impact on phytoplankton dynamics in the Arctic Ocean. We detect large phytoplankton blooms near the North Pole (up to 82°N in the eastern Eurasian Basin). Our analysis indicates that these blooms were induced by the northward plume transport and deposition of nutrient-bearing wildfire aerosols. We estimate that these highly stratified surface waters received large amounts of wildfire-derived nitrogen, which alleviated nutrient stress in the phytoplankton community and triggered an unusually large bloom event. Our findings suggest that changes in wildfire activity may strongly influence summertime productivity in the Arctic Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Analysis of an Arctic cold air outbreak during autumn and related air mass transformations forced by surface changes and advection in higher altitudes

During marine cold air outbreaks (MCAOs), cold and dry Arctic air masses are transported from the central Arctic southward across the closed sea ice and much warmer open oceans. They experience significant transformations including a rapid heating and moistening, often leading to cloud formation. While intense wintertime MCAOs have been analyzed widely, the air mass transformations during other seasons have been studied sparsely. We address this gap by investigating an MCAO case observed in September 2020. To study the transformation processes, we combine the fifth generation of atmospheric reanalyses of the global climate (ERA5), trajectory calculations, as well as shipborne and airborne measurements. In the central Arctic, observations acquired from aboard the research vessel (RV) Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition characterized the initial state of the air mass over closed sea ice. Trajectories indicated the pathway the air mass took from RV Polarstern southward to the Fram Strait. For the first 24 h of the southbound drift, the air masses remained quasi-stationary. Then, still 15 h ahead of the marginal sea ice zone, differential advection across the boundary layer flow introduced humidity and clouds at higher altitudes between 1.5 and 2.5 km. ERA5-derived temperature and humidity tendencies indicated complex vertical interactions. Radiative cloud-top cooling, entrainment, and turbulence were significantly reduced in the lower and enhanced in the upper advected cloud layer. Eventually, the lower cloud deck dissipated. After this confluence of 2 different air masses, observations gathered by Polar 5 in Fram Strait as part of the MOSAiC Airborne observations in the Central Arctic campaign revealed cloudy, moist layers throughout the lowest 3.5 km and an increasing boundary layer height. Comparing the initial with the final state 48 h later, the largest net heating of +8 K was found close to the surface, yet the largest net moistening of +2.5 g kg -1 at an altitude of 1 km, as the initial profile was exceptionally dry here. We conclude that the observed air mass transformations were driven by the surface changes from sea ice to open ocean but additionally strongly impacted by the differential advection of clouds and moisture across the near-surface MCAO flow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrating CVMix into GOTM (v6.0): a consistent framework for testing, comparing, and applying ocean mixing schemes

Abstract. The General Ocean Turbulence Model (GOTM) is a one-dimensional water column model, including a set of state-of-the-art turbulence closure models, and has widely been used in various applications in the ocean modeling community. Here, we extend GOTM to include a set of newly developed ocean surface vertical mixing parameterizations of Langmuir turbulence via coupling with the Community Vertical Mixing Project (CVMix). A Stokes drift module is also implemented in GOTM to provide the necessary ocean surface waves information to the Langmuir turbulence parameterizations, as well as to facilitate future development and evaluation of new Langmuir turbulence parameterizations. In addition, a streamlined workflow with Python and Jupyter notebooks is also described, enabled by the newly developed and more flexible configuration capability of GOTM. The newly implemented Langmuir turbulence parameterizations are evaluated against theoretical scalings and available observations in four test cases, including an idealized wind-driven entrainment case and three realistic cases at Ocean Station Papa, the northern North Sea, and the central Baltic Sea, and compared with the existing general length scale scheme in GOTM. The results are consistent with previous studies. This development extends the capability of GOTM towards including the effects of ocean surface waves and provides useful toolsets for the ocean modeling community to further study the effects of Langmuir turbulence in a broader scope.

58 GEOSCIENCES↗
DOE OSTI2022

Complete Genome Sequences of Two Phylogenetically Distinct Nitrospina Strains Isolated from the Atlantic and Pacific Oceans

The complete genome sequences of two chemoautotrophic nitrite-oxidizing bacteria of the genus Nitrospina are reported. Nitrospina gracilis strain Nb-211 was isolated from the Atlantic Ocean, and Nitrospina sp. strain Nb-3 was isolated from the Pacific Ocean. We report two highly similar ~3.07-Mbp genome sequences that differ by the presence of ferric iron chelator (siderophore) biosynthesis genes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Investigation of Surface and Marine-Cloud Coupling and its Impact on Cloud Droplet Number Concentrations and Cloud Cover Over the Southern Ocean

The proposed work involves characterizing and quantifying both the thermodynamic and dynamical coupling of marine low clouds (MLC) with the sea surface using Atmospheric Radiation Measurement (ARM) observations during MARCUS field campaign and an LES model. ARM data from multiple sensors will be used (e.g., Doppler cloud radar, ceilometer, and microwave radiometer) to characterize the MLC-surface coupling by virtue of the vertical structure and integrated quantities of boundary-layer clouds, aerosols, as well as atmospheric profiles and surface meteorology. We have used a combination of case studies and statistics-based composite analyses to find any linkages between large-scale dynamics, MLC-surface coupling, and cloud and boundary layer properties, the sequence of which reflects the chain of causality. An LES model with explicit aerosol physics, which includes the cycle of aerosols by being consumed as CCN and be regenerated following cloud droplet evaporation, has been run to determine the sources and sinks of Nd and their dependence on the degree of MLC-surface coupling. We have examined the systematic differences in both Nd and cloud occurrence between the two clusters under different meteorological conditions and further examine their respective roles, as well as causal relationships by means of LES modeling. This study helped improve our understanding of the ACI by differentiating the dynamic role of the coupling and cloud physics denoted by Nd, bridging the linkage in the chain toward understanding mechanisms governing the persistence of MLC over the Southern Ocean, solving the long-lasting problem of the cloud cover underestimation over the SO by GCMs. Ample ARM data and LES model have been employed to achieve the objectives of the study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Modeling assessment of storm surge in the Salish Sea

Here we present a modeling assessment of storm surge in the Salish Sea—a large and complex estuarine system in the Pacific Northwest that is exposed to extratropical cyclones. A method was developed to systematically identify storm surge events in the Salish Sea based on water level records at four representative tidal gauges in the Salish Sea. The maximum storm surge distribution in the Salish Sea was calculated based on model simulations of 34 major historical storm events from 1980 to 2016. The model simulations were validated by field observations of water level and velocity using a suite of model performance metrics. Model results suggest that the maximum storm surge in the Salish Sea is generally in the range of 0.8 m–1.03 m and is heterogeneous in space. The model results also show a strong north-south gradient with larger surge magnitudes occurring in the north that is primarily caused by the southerly wind in winter months. The sensitivity analysis of wind forcing suggested that storm surge in the Salish Sea is dominated by the remote surge from the Pacific Ocean, and the local wind contributes up to approximately 20% of the surge variability. This paper systematically elucidates storm surge characteristics and potential risk in the Salish Sea.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Relative Impact of Sea Ice and Temperature Changes on Arctic Marine Production

We use a modern Earth system model to approximate the relative importance of ice versus temperature on Arctic marine ecosystem dynamics. We show that while the model adequately simulates ice volume, water temperature, air-sea CO 2 flux, and annual primary production in the Arctic, itunderestimates upper water column nitrate across the region. This nitrate bias is likely responsible for the apparent underestimation of ice algae production. Despite this shortcoming, the model appears to be a useful tool for exploring the impacts of environmental change on phytoplankton production and carbon dynamics over the Arctic Ocean. Our experiments indicate that under a warmer climate scenario, the percentage of ocean warming that could be apportioned to a reduction in ice area ranged from 11% to 100%, while decreasing ice area could account for 22–100% of the increase in annual ocean primary production. The change to CO2 air-sea flux in response to ice and temperature changes averaged an Arctic-wide 5.5 Tg C yr –1 (3.5%) increase, into the ocean. This increased carbon sink may be short-lived, as ice cover continues to decrease and the ocean warms. The change in carbon fixation from phytoplankton in response to increased temperatures and reduced ice was generally more than a magnitude larger than the changes to CO 2 flux, highlighting the importance of fully considering changes to the marine ecosystem when assessing Arctic carbon cycle dynamics. Our work demonstrates the importance of ice dynamics in controlling ocean warming and production and thus the need for well-behaved ice and BGC models within Earth system models if we hope to accurately predict Arctic changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Partial Coupling Method to Isolate the Roles of the Atmosphere and Ocean in Coupled Climate Simulations

This study describes the formulation and application of a partial coupling method that disentangles the coupling between the atmosphere and ocean and isolates the atmosphere- and ocean-driven components of the coupled climate interactions. In contrast to strategies using stand-alone simulations with prescribed atmosphere or ocean states, the climate components in the partially coupled method remain coupled, but the impact of ocean circulation changes is removed from the air-sea interaction using temperature-like tracers. The partially coupled simulation thereby suppresses the ocean-driven interaction and isolates an atmosphere-driven interaction only. The ocean-driven component can be inferred by comparing climate response in the partially coupled simulation with that of a standard fully coupled one. The partial coupling approach is applied to decompose the fully coupled climate response to CO 2 quadrupling into atmosphere- and ocean-driven components. The linearity of the decomposition is validated by simulating the ocean-driven response using another complimentary partially coupled simulation forced only with the atmosphere-driven anomalous surface fluxes. A comparison of the two partially coupled simulations with the fully coupled simulation indicates that the sum of the atmosphere- and ocean-driven components accurately describes the fully coupled response. The decomposition identifies several robust atmosphere- and ocean-driven features of the global warming and provides new insights into the impacts of atmospheric feedbacks on the Atlantic overturning circulation and sea ice response to CO 2 increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the Correspondence between Seasonal Forecast Biases and Long-Term Climate Biases in Sea Surface Temperature

In this paper, the correspondence between mean sea surface temperature (SST) biases in retrospective seasonal forecasts (hindcasts) and long-term climate simulations from five global climate models is examined to diagnose the degree to which systematic SST biases develop on seasonal time scales. The hindcasts are from the North American Multi-Model Ensemble and the climate simulations are from the Coupled Model Intercomparison Project. The analysis suggests that most robust climatological SST biases begin to form within 6 months of a realistically initialized integration, although the growth rate varies with location, time, and model. In regions with large biases, interannual variability and ensemble spread is much smaller than the climatological bias. Additional ensemble hindcasts of the Community Earth System Model with a different initialization method suggest that initial conditions do matter for the initial bias growth, but the overall global bias patterns are similar after 6 months. A hindcast approach is more suitable to study biases over the tropics and sub-tropics than over the extra-tropics because of smaller initial biases and faster bias growth. The rapid emergence of SST biases makes it likely that fast processes with times scales shorter than the seasonal time scales in the atmosphere and upper ocean are responsible for a substantial part of the climatological SST biases. Studying the growth of biases may provide important clues to the causes and ultimately the amelioration of these biases. Further, initialized seasonal hindcasts can profitably be used in the development of high-resolution coupled ocean-atmosphere models.

54 ENVIRONMENTAL SCIENCES↗