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At least 631 records · Page 35

The future of the El Niño–Southern Oscillation: using large ensembles to illuminate time-varying responses and inter-model differences

Future changes in the El Niño–Southern Oscillation (ENSO) are uncertain, both because future projections differ between climate models and because the large internal variability of ENSO clouds the diagnosis of forced changes in observations and individual climate model simulations. By leveraging 14 single model initial-condition large ensembles (SMILEs), we robustly isolate the time-evolving response of ENSO sea surface temperature (SST) variability to anthropogenic forcing from internal variability in each SMILE. We find nonlinear changes in time in many models and considerable inter-model differences in projected changes in ENSO and the mean-state tropical Pacific zonal SST gradient. We demonstrate a linear relationship between the change in ENSO SST variability and the tropical Pacific zonal SST gradient, although forced changes in the tropical Pacific SST gradient often occur later in the 21st century than changes in ENSO SST variability, which can lead to departures from the linear relationship. Single-forcing SMILEs show a potential contribution of anthropogenic forcing (aerosols and greenhouse gases) to historical changes in ENSO SST variability, while the observed historical strengthening of the tropical Pacific SST gradient sits on the edge of the model spread for those models for which single-forcing SMILEs are available. Our results highlight the value of SMILEs for investigating time-dependent forced responses and inter-model differences in ENSO projections. The nonlinear changes in ENSO SST variability found in many models demonstrate the importance of characterizing this time-dependent behavior, as it implies that ENSO impacts may vary dramatically throughout the 21st century.

54 ENVIRONMENTAL SCIENCES↗

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗

Final Technical Report for Department of Energy Award DE-SC0006625, “Predictability of the carbon-climate system on seasonal to decadal time scales.”

The project aims to investigate the feasibility of advancing our understanding of the carbon cycle, using a carbon-weather data assimilation system that updates the modeled carbon dioxide concentration and atmospheric circulation every six hours using CO 2 data (from the OCO 2 satellite) and weather data. At the core of the system is the DOE-NCAR-CAM5fv global circulation model coupled to the National Center for Atmospheric Research's Data Assimilation Testbed, running an ensemble of 30 models. This combination provides realistic vertical carbon dioxide gradients and conservation of dry air mass. A global four-dimensional distribution of atmospheric CO 2 concentration is produced. Our results show (1) that OCO 2 total precipitable water data are reliable and provide valuable uncertainty information for the OCO 2 data assimilation; and (2) that our approach is a promising method for monitoring national carbon dioxide emissions.

54 ENVIRONMENTAL SCIENCES↗

Intermediate-scale horizontal isoprene concentrations in the near-canopy forest atmosphere and implications for emission heterogeneity

The emissions, deposition, and chemistry of volatile organic compounds (VOCs) are thought to be influenced by underlying landscape heterogeneity at intermediate horizontal scales of several hundred meters across different forest subtypes within a tropical forest. Quantitative observations and scientific understanding at these scales, however, remain lacking, in large part due to a historical absence of canopy access and suitable observational approaches. Herein, horizontal heterogeneity in VOC concentrations in the near-canopy atmosphere was examined by sampling from an unmanned aerial vehicle (UAV) flown horizontally several hundred meters over the plateau and slope forests in central Amazonia during the morning and early afternoon periods of the wet season of 2018. Unlike terpene concentrations, the isoprene concentrations in the near-canopy atmosphere over the plateau forest were 60% greater than those over the slope forest. A gradient transport model constrained by the data suggests that isoprene emissions differed by 220 to 330% from these forest subtypes, which is in contrast to a 0% difference implemented in most present-day biosphere emissions models (i.e., homogeneous emissions). Finally, quantifying VOC concentrations, emissions, and other processes at intermediate horizontal scales is essential for understanding the ecological and Earth system roles of VOCs and representing them in climate and air quality models.

54 ENVIRONMENTAL SCIENCES↗

The effect of ground hydrology on climate sensitivity to solar constant variations

A zonally averaged climate model is used to investigate the effects of different evaporation parameterizations on climate sensitivity to solar constant variations. The model is based on the annual mean zonally averaged hemispheric climate model of Ohring and Adler (1978), with some modifications on the heating parameterizations. The dynamic model utilizes the two-level quasi-geostrophic potential vorticity equations. The heating processes are related to solar radiation, long-wave radiation, convection, evaporation, latent heat release, and ocean transport. Evaporation parameterization has been improved by using a nonlinear formulation in which the Bowen ratio is determined by the vertical gradients of water vapor and temperature near the earth's surface.

Chow, S.-H.↗

Nutrient Inputs Stimulate Mercury Methylation by Syntrophs in a Subarctic Peatland

Climate change dramatically impacts Arctic and subarctic regions, inducing shifts in wetland nutrient regimes as a consequence of thawing permafrost. Altered hydrological regimes may drive changes in the dynamics of microbial mercury (Hg) methylation and bioavailability. Important knowledge gaps remain on the contribution of specific microbial groups to methylmercury (MeHg) production in wetlands of various trophic status. Here, we measured aqueous chemistry, potential methylation rates (k meth ), volatile fatty acid (VFA) dynamics in peat-soil incubations, and genetic potential for Hg methylation across a groundwater-driven nutrient gradient in an interior Alaskan fen. We tested the hypotheses that (1) nutrient inputs will result in increased methylation potentials, and (2) syntrophic interactions contribute to methylation in subarctic wetlands. We observed that concentrations of nutrients, total Hg, and MeHg, abundance of hgcA genes, and rates of methylation in peat incubations (k meth ) were highest near the groundwater input and declined downgradient. hgcA sequences near the input were closely related to those from sulfate-reducing bacteria (SRB), methanogens, and syntrophs. Hg methylation in peat incubations collected near the input source (FPF2) were impacted by the addition of sulfate and some metabolic inhibitors while those down-gradient (FPF5) were not. Sulfate amendment to FPF2 incubations had higher k meth relative to unamended controls despite no effect on k meth from addition of the sulfate reduction inhibitor molybdate. The addition of the methanogenic inhibitor BES (25 mM) led to the accumulation of VFAs, but unlike molybdate, it did not affect Hg methylation rates. Rather, the concurrent additions of BES and molybdate significantly decreased k meth , suggesting a role for interactions between SRB and methanogens in Hg methylation. The reduction in k meth with combined addition of BES and molybdate, and accumulation of VFA in peat incubations containing BES, and a high abundance of syntroph-related hgcAsequences in peat metagenomes provide evidence for MeHg production by microorganisms growing in syntrophy. Collectively the results suggest that wetland nutrient regimes influence the activity of Hg methylating microorganisms and, consequently, Hg methylation rates. Our results provide key information about microbial Hg methylation and methylating communities under nutrient conditions that are expected to become more common as permafrost soils thaw.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding the Biases in Global Monsoon Simulations from the Perspective of Atmospheric Energy Transport

Understanding global monsoon (GM) variability and projecting its future changes rely heavily on climate models. However, climate models generally show pronounced biases in GM simulations, and the reasons for this remain unclear. Here, in this study, we evaluate the performance of 20 pairs of climate models that participated in both phase 5 of the Coupled Model Intercomparison Project (CMIP5) and phase 6 of CMIP (CMIP6) and identify the sources of their GM simulation biases from an energy transport perspective. The multimodel mean improvement in CMIP6 compared to CMIP5 is demonstrated by the increasing skill scores for various GM metrics from 0.20–0.79 to 0.48–0.83. More specifically, the dry biases in the Northern Hemisphere Summer Monsoon (NHSM) precipitation in CMIP5 [root-mean-square error (RMSE): 1.85 mm day −1 ] are reduced in CMIP6 (RMSE: 1.66 mm day −1 ). This higher simulation skill is associated with higher skill in simulating the precipitation-solstitial mode, monsoon intensity, and monsoon domains. The improvement in the NHSM precipitation simulation results from that in the meridional transport of atmospheric energy. Atmospheric energy budget analysis shows that the negative biases in downward surface longwave radiation and northward energy transport are smaller in CMIP6 than in CMIP5 in the boreal summer, resulting in a more realistic interhemispheric thermal contrast and meridional gradient of moist static energy. However, a major weakness of the CMIP6 models is found in the Southern Hemisphere Summer Monsoon precipitation simulation due to the positive bias in the top-of-the-atmosphere downward longwave radiation. This study shows that reasonably reproducing the meridional global atmospheric energy transportation is necessary for skillful GM simulation.

54 ENVIRONMENTAL SCIENCES↗

Moist Energy Constraints on Surface Temperature Variance Under Climate Warming

Understanding the factors controlling surface temperature variance is crucial for predicting temperature extremes. Previous investigations have examined individual impacts of temperature advection and surface turbulent fluxes on temperature fluctuations. Here, we explore the constraints on temperature variance from the moist static energy (MSE) balance and introduce a new scaling relation that connects the generation of temperature variance through moist energy transport with its dissipation due to the net energetic forcing of the atmosphere. This theory is evaluated in an idealized aquaplanet model. We find that surface temperature variance is influenced by eddy (sensible) heat flux, MSE gradient, and the Clausius‐Clapeyron relation for evaporative cooling. Under global warming, the reduced temperature variance in the aquaplanet model is dominated by the weakening in eddy heat flux, but it is also affected by changes in evaporative cooling and MSE gradient, which may be more important in realistic, moisture‐limited regions over land.

Eddy heat flux↗

West African Monsoon System’s Responses to Global Ocean–Regional Atmosphere Coupling

This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere-only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean–atmosphere coupling’s influence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ~25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fluxes. Contrastingly, as intended, coupling improves SSTs and monsoon fluxes’ relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara–Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

54 ENVIRONMENTAL SCIENCES↗

Microbial functional diversity covaries with permafrost thaw-induced environmental heterogeneity in tundra soil

Permafrost soil in high latitude tundra is one of the largest terrestrial carbon (C) stocks and is highly sensitive to climate warming. Understanding microbial responses to warming-induced environmental changes is critical to evaluating their influences on soil biogeochemical cycles. In this study, a functional gene array (i.e., geochip 4.2) was used to analyze the functional capacities of soil microbial communities collected from a naturally degrading permafrost region in Central Alaska. Varied thaw history was reported to be the main driver of soil and plant differences across a gradient of minimally, moderately, and extensively thawed sites. Compared with the minimally thawed site, the number of detected functional gene probes across the 15-65 cm depth profile at the moderately and extensively thawed sites decreased by 25% and 5%, while the community functional gene β-diversity increased by 34% and 45%, respectively, revealing decreased functional gene richness but increased community heterogeneity along the thaw progression. Particularly, the moderately thawed site contained microbial communities with the highest abundances of many genes involved in prokaryotic C degradation, ammonification, and nitrification processes, but lower abundances of fungal C decomposition and anaerobic-related genes. Significant correlations were observed between functional gene abundance and vascular plant primary productivity, suggesting that plant growth and species composition could be co-evolving traits together with microbial community composition. Finally, altogether, this study reveals the complex responses of microbial functional potentials to thaw-related soil and plant changes and provides information on potential microbially mediated biogeochemical cycles in tundra ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Chemistry, Dynamics, and Radiation of Ozone Loss: Airborne Measurements of OH, HO2, NO2, ClO, BrO, IO, ClONO2, BrONO2, ClOOCl, and H2O

This grant continued the research initially funded under NAG1-01095. This research addresses, through a combination of in situ and remote aircraft-borne instruments, the following scientific questions: Which mechanisms are responsible for the continuing erosion of ozone over midlatitudes of the Northern Hemisphere? Will the rapid loss of ozone over the Arctic in late winter continue to worsen over the next two decades? Are these large losses dynamically coupled to midlatitudes? Which mechanisms dictate the rate of exchange of material between the troposphere and stratosphere? How will these processes change in response to changes in climate? Will regional scale pollution episodes, that are emerging as predictable seasonal events, significantly affect the middle-to-upper troposphere chemical composition. If so, how will these changes alter the chemical composition of the middle world? What changes are predicted for the overworld? Why has the arctic stratosphere become colder in the late winter phase in recent years? Have increases in tropical upper troposphere temperatures increased the temperature gradient such as to change the trajectories of vertically propagating waves, thus reducing the effectiveness of the meridional circulation for transport of heat, momentum and ozone from the tropics to high latitudes?

Anderson, James G.↗

Chemistry, Dynamics, and Radiation of Ozone Loss: Airborne Measurements of OH, HO2, N02, Cl0, BrO, IO, ClON02, BrON02, CIOOCl, and H2O

This research addresses, through a combination of in situ and remote aircraft-borne Which mechanisms are responsible for the continuing erosion of ozone over midlatitudes of the Northern Hemisphere? Will the rapid loss of ozone over the Arctic in late winter continue to worsen over the next two decades? Are these large losses dynamically coupled to midlatitudes? Which mechanisms dictate the rate of exchange of material between the troposphere and stratosphere? How will these processes change in response to changes in climate? Will regional scale pollution episodes, that are emerging as predictable seasonal events, significantly affect the middle-to-upper troposphere chemical composition. If so, how will these changes alter the chemical composition of the middle world? What changes are predicted for the overworld? Why has the arctic stratosphere become colder in the late winter phase in recent years? Have increases in tropical upper troposphere temperatures increased the temperature gradient such as to change the trajectories of vertically propagating waves, thus reducing the effectiveness of the meridional circulation for transport of heat, momentum and ozone from the tropics to high latitudes?

Anderson, James G.↗

Recent increases in annual, seasonal, and extreme methane fluxes driven by changes in climate and vegetation in boreal and temperate wetland ecosystems

Climate warming is expected to increase global methane (CH 4 ) emissions from wetland ecosystems. Although in situ eddy covariance (EC) measurements at ecosystem scales can potentially detect CH 4 flux changes, most EC systems have only a few years of data collected, so temporal trends in CH 4 remain uncertain. Here, we use established drivers to hindcast changes in CH 4 fluxes (FCH 4 ) since the early 1980s. We trained a machine learning (ML) model on CH 4 flux measurements from 22 [methane-producing sites] in wetland, upland, and lake sites of the FLUXNET-CH 4 database with at least two full years of measurements across temperate and boreal biomes. The gradient boosting decision tree ML model then hindcasted daily FCH 4 over 1981-2018 using meteorological reanalysis data. We found that, mainly driven by rising temperature, half of the sites (n = 11) showed significant increases in annual, seasonal, and extreme FCH 4 , with increases in FCH 4 of ca. 10% or higher found in the fall from 1981–1989 to 2010–2018. The annual trends were driven by increases during summer and fall, particularly at high-CH 4 -emitting fen sites dominated by aerenchymatous plants. We also found that the distribution of days of extremely high FCH 4 (defined according to the 95th percentile of the daily FCH 4 values over a reference period) have become more frequent during the last four decades and currently account for 10–40% of the total seasonal fluxes. The share of extreme FCH 4 days in the total seasonal fluxes was greatest in winter for boreal/taiga sites and in spring for temperate sites, which highlights the increasing importance of the non-growing seasons in annual budgets. Our results shed light on the effects of climate warming on wetlands, which appears to be extending the CH 4 emission seasons and boosting extreme emissions.

54 ENVIRONMENTAL SCIENCES↗

A New Research Approach for Observing and Characterizing Land–Atmosphere Feedback

Forecast errors with respect to wind, temperature, moisture, clouds, and precipitation largely correspond to the limited capability of current earth system models to capture and simulate and-atmosphere feedback. To facilitate its realistic simulation in next generation models, an improved process understanding of the related complex interactions is essential. To this end, accurate 3D observations of key variables in the land-atmosphere (L-A) system with high vertical and temporal resolution from the surface to the free troposphere are indispensable. Recently, we developed a synergy of innovative ground-based, scanning active remote sensing systems for 2D to 3D measurements of wind, temperature, and water vapor from the surface to the lower troposphere that is able to provide comprehensive data sets for characterizing L-A feedback independently of any model input. Several new applications are introduced such as the mapping of surface momentum, sensible heat, and latent heat fluxes in heterogeneous terrain, the testing of Monin-Obukhov similarity theory and turbulence parameterizations, the direct measurement of entrainment fluxes, and the development of new flux-gradient relationships. An experimental design taking advantage of the sensors’ synergy and advanced capabilities was realized for the first time during the Land Atmosphere Feedback Experiment (LAFE), conducted at the Atmospheric Radiation Measurement Program Southern Great Plains site in August 2017. The scientific goals and the strategy of achieving them with the LAFE data set are introduced. We envision the initiation of innovative L-A feedback studies in different climate regions to improve weather forecast, climate, and earth system models worldwide.

54 ENVIRONMENTAL SCIENCES↗

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗

Liquid Containing Clouds at the North Slope of Alaska Demonstrate Sensitivity to Local Industrial Aerosol Emissions

Abstract Cloud condensation nucleus control alter cloud solar albedo through cloud droplet size. Here, we leverage anthropogenic emissions at the North Slope of Alaska as a natural laboratory to study relationships between aerosols and Arctic liquid‐containing clouds. Averaging 14 years of MODIS observations, we found a reduction in temporally averaged cloud effective radius ( ) of up to 1.0 μm related to localized pollution. Pronounced regional gradients in cloud frequency of occurrence and liquid water path prohibit the detection of potential changes of these variables. Observed changes of alter radiative fluxes and increase cloud‐reflected shortwave radiation by up to 0.8 W m − 2 in the Prudhoe Bay area for the period covered by observations (April–September). Due to the frequent occurrence of liquid‐containing clouds, this implies that enhanced local emissions in Arctic regions can impact climate processes.

54 ENVIRONMENTAL SCIENCES↗

The Atacama Desert: A Window into Late Mars Surface Habitability?

Decades of robotic exploration have revealed that Mars was capable of sustaining life in the Noachian and Hesperian periods (> 3 billion years ago). But habitability conditions progressively deteriorated thereafter, and a lasting trend of climate change has made the surface of the planet likely uninhabitable at present times. One of the outstanding enigmas in Mars exploration is when was the last time that the surface of the planet could have sustained life. In this chapter we address this question through comparisons with one of the oldest and driest deserts on Earth, the Atacama Desert in northern Chile. We base our analysis on a latitudinal rainfall gradient that allows to investigate how microbial communities respond to increasing dryness. We posit that the ecological successions observed along the Atacama rainfall gradient represent a possible model for the adaptation of an early martian biosphere to increasing dryness throughout the planet’s geologic history, offering clues to the last surface environments that could have sustained life, and the timing of the last surface habitable period. These might in turn be the best locations to search for evidence of life.

Atacama Desert↗

Evaluating the effect of meso/submesoscale current–wave interactions on wave energy resource characterization at northeast U.S. coast

Wave energy is a promising renewable resource, but accurate assessment is difficult in regions with strong currents due to wave–current interactions (WCI). Here, this study develops a two-way coupled WCI model within the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) framework at 2 km resolution to improve wave energy characterization along the northeastern U.S. coast, including the Mid-Atlantic Bight and Gulf of Maine. The model integrates WaveWatchIII (WWIII) and the Regional Ocean Modeling System (ROMS) to enhance wave hindcasting by accounting for Doppler-shift, refraction, and nonlinear energy exchanges. Validation against buoy and satellite observations confirms model accuracy. Analysis shows that Doppler-shifting can alter wave power density by over 20%, while strong current gradients and shear distort wave crests via focusing/defocusing and stretching/squeezing, modifying wave direction and frequency. These processes together can induce wave power fluctuations of up to 40% on synoptic scales. Applying a 2.5 MW Ocean Energy Converter power matrix shows that WCI may change harvested energy by up to 100% in shallow-waters and 60% in deep-waters. These results underscore the importance of incorporating nonlinear WCI for reliable wave climate predictions and resource assessments in energetic coastal regions.

doppler-shift↗