Ocean System Research Articles

Reduced Southern Ocean warming enhances global skill and signal-to-noise in an eddy-resolving decadal prediction system

The impact of increased model horizontal resolution on climate prediction performance is examined by comparing results from low-resolution (LR) and high-resolution (HR) decadal prediction simulations conducted with the Community Earth System Model (CESM). There is general improvement in global skill and signal-to-noise characteristics, with particularly noteworthy improvements in the eastern tropical Pacific, when resolution is increased from order 1° in all components to order 0.1°/0.25° in the ocean/atmosphere. A key advance in the ocean eddy-resolving HR system is the reduction of unrealistic warming in the Southern Ocean (SO) which we hypothesize has global ramifications through its impacts on tropical Pacific multidecadal variability. The results suggest that accurate representation of SO processes is critical for improving decadal climate predictions globally and for addressing longstanding issues with coupled climate model simulations of recent Earth system change.

Computational Oil-Slick Hub for Offshore Petroleum Studies

The paper introduces the Oil-Slick Hub (OSH), a computational platform to facilitate the data visualization of a large database of petroleum signatures observed on the surface of the ocean with synthetic aperture radar (SAR) measurements. This Internet platform offers an information search and retrieval system of a database resulting from >20 years of scientific projects that interpreted ~15 thousand offshore mineral oil “slicks”: natural oil “seeps” versus operational oil “spills”. Such a Digital Mega-Collection Database consists of satellite images and oil-slick polygons identified in the Gulf of Mexico (GMex) and the Brazilian Continental Margin (BCM). A series of attributes describing the interpreted slicks are also included, along with technical reports and scientific papers. Two experiments illustrate the use of the OSH to facilitate the selection of data subsets from the mega collection (GMex variables and BCM samples), in which artificial intelligence techniques—machine learning (ML)—classify slicks into seeps or spills. The GMex variable dataset was analyzed with simple linear discriminant analyses (LDAs), and a three-fold accuracy performance pattern was observed: (i) the least accurate subset (~65%) solely used acquisition aspects (e.g., acquisition beam mode, date, and time, satellite name, etc.); (ii) the best results (>90%) were achieved with the inclusion of location attributes (i.e., latitude, longitude, and bathymetry); and (iii) moderate performances (~70%) were reached using only morphological information (e.g., area, perimeter, perimeter to area ratio, etc.). The BCM sample dataset was analyzed with six traditional ML methods, namely naive Bayes (NB), K-nearest neighbors (KNN), decision trees (DT), random forests (RF), support vector machines (SVM), and artificial neural networks (ANN), and the most effective algorithms per sample subsets were: (i) RF (86.8%) for Campos, Santos, and Ceará Basins; (ii) NB (87.2%) for Campos with Santos Basins; (iii) SVM (86.9%) for Campos with Ceará Basins; and (iv) SVM (87.8%) for only Campos Basin. The OSH can assist in different concerns (general public, social, economic, political, ecological, and scientific) related to petroleum exploration and production activities, serving as an important aid in discovering new offshore exploratory frontiers, avoiding legal penalties on oil-seep events, supporting oceanic monitoring systems, and providing valuable information to environmental studies.

Modelling the effect of submarine volcanic eruption on equatorial oceanic flows

In this paper, a three-dimensional, nonlinear model is proposed to incorporate the effect of submarine volcanic eruption on equatorial oceanic flows. The model inspired by the Constantin and Johnson model, considers an appropriate density function to model the density of the oceanic system with a volcano erupting at a point on the sea-bed, synchronizing with the temperature variations. The formulated model contains term related to Coriolis effect and is consistent with β-plane approximation. Exact results for the model have been obtained using the asymptotic system of equations.

HiGRN: A Hierarchical Graph Recurrent Network for Global Sea Surface Temperature Prediction

Sea surface temperature (SST) is one critical parameter of global climate change, and accurate SST prediction is important to various applications, e.g., weather forecasting, fishing directions, and disaster warnings. The global ocean system is unified and complex, and the SST patterns in different oceanic regions are highly diverse and correlated. However, existing data-driven SST prediction methods mainly consider the local patterns within a certain oceanic region, e.g., El Nino region and the Black sea. It is challenging but necessary to model the global SST correlations rather than that in a specific region to enhance the prediction accuracy of SST. In this work, we proposed a new method called Hierarchical Graph Recurrent Network (HiGRN) to address the issue. First, to learn the dynamic and diverse local SST patterns of specific locations, we design an adaptive node embedding with self-learned parameters to learn various SST patterns. Then we develop a hierarchical cluster generator to aggregate the locations with similar patterns into regional clusters and utilize a graph convolution network to learn the spatial correlations among these clusters. Finally, we introduce a multi-level attention mechanism to fuse the local patterns and regional correlations, and the output is fed into a recurrent network to achieve SST predictions. Extensive experiments on two real-world datasets show that our method largely outperforms the state-of-the-art SST prediction methods. The source code is available at https://github.com/Neoyanghc/HiGRN .

Dynamics of the subpolar gyre and transition zone of the North Atlantic during the last glacial cycle

Past studies of marine sediments of the North Atlantic documented millennial-scale sea-surface cooling related to the Dansgaard-Oeschger events that influenced the oceanic fronts and surface hydrology during the last glacial cycle. Most studies have focused on using ice-rafting, single or multiple species of planktonic foraminifers' abundances, and geochemistry to assess environmental changes. However, detailed planktonic foraminiferal assemblage data in the North Atlantic Transition Zone (NATZ) and subpolar gyre (SPG) for the full last glacial cycle are scarce. Here we report planktonic foraminiferal abundances, oxygen isotopes, and ice-rafted detritus (IRD) counts from two sediment cores, Hu9007-08 and Hu71022-377, collected from the Milne seamount of southwestern SPG (SW SPG) and NATZ, respectively. Further, we have used the published planktonic foraminiferal assemblage, IRD, and isotopic data from the eastern and western SPG to provide an integrated reconstruction of changes in the surface water masses and dynamics of the Polar, Arctic, and subarctic fronts (PF, AF, and SAF, respectively). Despite the overall warmth of the SW SPG (near the Newfoundland Basin) compared to the eastern SPG during marine isotope stage (MIS) 5, the North Atlantic-wide cooling events C24 and C21 were still identified in the SW SPG. Further, the planktonic foraminiferal abundances in cores EW9303-37JPC (i.e., scarce Neogloboquadrina pachyderma and abundant Globigerinoides inflata) and Hu9007-08 reveal a relatively warm MIS 5e compared to the Holocene. However, the decrease in the abundance of G. inflata suggests that the SW SPG was influenced by the seasonal presence of subpolar waters and possibly a southward shift in the oceanic frontal systems between ∼126 and ∼120 ka. During the Heinrich ice-rafting events, when meltwater flooded the surface North Atlantic, the PF, AF, and SAF shifted southward, and the polar/subpolar water masses briefly invaded the western and eastern SPG and NATZ. In the early part of MIS 3 (60–40 ka), the oceanic frontal system shifted northward from its position during MIS 4. The SPG and NATZ gradually warmed, and the subpolar species Globigerina bulloides in cores Hu9007-08, Hu71022-377, and CH69-K09 increased in the middle of MIS 3 (i.e., 38–30 ka), suggesting continuous sea surface warming while the oceanic frontal systems continued to move northward. This hydrological environment rapidly cooled in the late MIS 3-MIS 2 (30–19 ka), with the PF shifted southward to the mid-latitude (∼45°N) during the Last Glacial Maximum. During the last deglaciation-Holocene, the regions of cores Hu9007-08 and Hu71022-377 were mainly influenced by the warm North Atlantic Current, and the SAF was located north of both cores. This study presents the first large-scale water mass movements and frontal changes in the SPG and NATZ to better understand the dynamics of the surface circulation in the North Atlantic during the last glacial cycle.

Sensing the profile of particulate beam attenuation coefficient through a single-photon oceanic Raman lidar.

A lidar technique has been proposed and demonstrated for remotely sensing particulate beam attenuation coefficient (cp) profiles using the Raman backscattered signal from water. In Raman lidar, the backscatter coefficient at 180° can be considered constant, allowing for the determination of the lidar attenuation coefficient (Klidar) from the Raman backscattered signal. This scheme has these features. 1) The bandwidth of the filter that used to extract the Raman component from the backscattered signal of the lidar was optimized to ensure sufficient lidar signal strength while minimizing the influence of chlorophyll fluorescence on inversion. 2) A receiving telescope with narrow field of view (FOV) and small aperture was utilized to suppress multi-scattering components in the backscattered signal. 3) A relationship between the beam attenuation coefficient (c) and Klidar was established after simulations via a semi-analytic Monto Carlo. 4) The value of cp was obtained by subtracting the attenuation coefficient of pure seawater (cw) from c. According to the theoretical analysis, the maximum relative error of cp is less than 15% for chlorophyll concentrations up to 10 mg/m3. Due to the water Raman backscattered signal being several orders of magnitude lower than the elastic backscattered signal, a single-photon detector is required to significantly improve the detection sensitivity to the single-photon level. To validate this approach, a field experiment was conducted aboard the R/V Tan Kah Kee in the South China Sea from September 4th to September 5th, 2022, and continuous subsurface profiles of cp were obtained. These measurements confirm the robustness and reliability of the oceanic single-photon Raman lidar system and the inversion method.

A Space-Time Partial Differential Equation Based Physics-Guided Neural Network for Sea Surface Temperature Prediction

Sea surface temperature (SST) prediction has attracted increasing attention, due to its crucial role in understanding the Earth’s climate and ocean system. Existing SST prediction methods are typically based on either physics-based numerical methods or data-driven methods. Physics-based numerical methods rely on marine physics equations and have stable and explicable outputs, while data-driven methods are flexible in adapting to data and are capable of detecting unexpected patterns. We believe that these two types of method are complementary to each other, and their combination can potentially achieve better performances. In this paper, a space-time partial differential equation (PDE) is employed to form a novel physics-based deep learning framework, named the space-time PDE-guided neural network (STPDE-Net), to predict daily SST. Comprehensive experiments for SST prediction were conducted, and the results proved that our method could outperform the traditional finite-difference forecast method and several state-of-the-art deep learning and physics-guided deep learning methods.

A self-powered wide-range ocean-wave sensor enabled by triboelectric nanogenerators embedded with overrunning clutches

Accurate and effective observation of ocean waves is critical for many applications including weather forecasting, marine resources development, etc. In marine environments where electrical power supply is limited, the self-powered ocean-wave sensors are highly demanded. Herein, we propose an innovative solution to achieve self-powered ocean-wave sensing using triboelectric nanogenerators (TENGs) embedded with overrunning clutches. The ocean wave spectrum is obtained through the pulsed electrical output of two TENGs converting the up-and-down wave motion into rotary frictions, where the rise and fall of waves is distinguished by the combination of a rectifier bridge and a developed intelligent mechanical structure, one-way overrunning clutch embedded with a brake. The ocean wave observation capability of the developed sensor was demonstrated, where the wave height and period were revealed with the accuracy of 90.20 % and 99.16 %. The proposed sensor can easily achieve centimeter to meter level monitoring, which is 10 times higher than that of previous work. This significant advantage makes the proposed sensor highly suitable for practical applications in ocean wave height observations, where the wave height is usually larger than 100 cm. This work paves a new way to solve the energy-harvesting and information sensing issues for the ocean observation system in the meantime.

New prediction method for reliability analysis of ocean sustainable energy systems

With the aim of overcoming the shortcomings of traditional approaches, in this paper, an exponential Weibull distribution for fitting the significant wave height data is proposed in order to calculate more accurately the sea-state parameter distribution tails and to extrapolate well. This proposal is applied in predicting the probability distribution tails of a measured ocean wave dataset, and its accuracy is clearly demonstrated. The proposal is subsequently utilised in combination with Monte Carlo sampling to form a new environmental contour method for deriving a 50 year contour line based on the aforementioned measured ocean wave dataset. The derived environmental contour line is compared with that predicted by using a traditional contour line approach. Additionally, the engineering significance of using a more reliable environmental contour line, such as the one derived using the proposed new method for predicting the long-term design force values for an ocean sustainable energy system is highlighted. In conclusion, the newly proposed environmental contour method is recommended to be used when predicting the extreme dynamic response values for the safe and successful design of ocean sustainable energy systems.

Fluid-assisted grain size reduction leads to strain localization in oceanic transform faults

Oceanic Transform Faults are major plate boundaries representing the most seismogenic part of the mid ocean ridge system. Nonetheless, their structure and deformation mechanisms at depth are largely unknown due to rare exposures of deep sections. Here we study the mineral fabric of deformed mantle peridotites - ultramafic mylonites - collected from the transpressive Atobá ridge, along the northern fault of the St. Paul transform system in the Equatorial Atlantic Ocean. We show that, at pressure and temperature conditions of the lower oceanic lithosphere, the dominant deformation mechanism is fluid-assisted dissolution-precipitation creep. Grain size reduction during deformation is enhanced by dissolution of coarser pyroxene grains in presence of fluid and contextual precipitation of small interstitial ones, leading to strain localization at lower stresses than dislocation creep. This mechanism potentially represents the dominant weakening factor in the oceanic lithosphere and a main driver for the onset and maintenance of oceanic transform faults.

Paleozoic and Mesozoic magmatism in the Gaodi porphyry Mo-Cu deposit: Implications for the evolution of the Mongol-Okhotsk Ocean in the northern Great Xing'an Range, NE China

The newly discovered "460 Gaodi porphyry Mo–Cu deposit" (with Re-Os age of 179.6 ± 3.6 Ma) is located 30 km west of Hanjiayuanzi town in the northern Great Xing’an Range (GXR), NE China. The intrusive rocks in the deposit area can be classified into four periods: (1) Early Ordovician, which includes a high-K calc-alkaline monzodiorite (480 Ma) indicating significant crustal contamination, and a “syntectic” I-type granodiorite (479 Ma) with low Mg# values (34–38) and εHf(t) values (−4.4 to +0.9) show mixing of mantle-crust derived materials, which is related to post-orogenic event between the Ergun and Xing’an blocks; (2) Late Triassic, which includes an adakitic granodiorite porphyry (220 Ma) related to partial melting of the lower part of a thickened crust (C-type adakitic) with low Na2O/K2O ratio (1.27–1.49), Cr and Ni contents, with εHf(t) values of −0.7 to +3.3; (3) early Early Jurassic, which includes a differentiated I-type monzogranite (198 Ma) and syenogranite (196 Ma) with negative Eu anomaly (0.06–0.74), low Mg# (9–37) and high Rb/Sr (0.84–5.07). The εHf(t) values of them are −3.3 to 1.8 and −3.0 to +2.3, respectively, indicating the same source areas originated from partial melting of juvenile lower crust; (4) late Early Jurassic, which includes an ore-related C-type adakitic granite porphyry (182 Ma) with relative low Mg# (36–38), and low Na2O/K2O (0.65–0.81), strongly peraluminous quartz porphyry (181 Ma) with highly differentiated characteristics, and post-collisional gabbroic diorite (180 Ma). The ore-related granite porphyry yields εHf(t) values ranging from −4.1 to −0.4, suggesting partial melting of juvenile lower crust. The 460 Gaodi deposit formed in a late-collisional setting related to the Mongol-Okhotsk Ocean system. A post-collisional stage about 182 to 163 Ma immediately following the main collision is proposed.

Fast Prediction of Solute Concentration Field in Rotationally Influenced Fluids Using a Parameter-Based Field Reconstruction Convolutional Neural Network

Many high-performance fluid dynamic models do not consider fluids in a rotating environment and often require a significant amount of computational time. The current study proposes a novel parameter-based field reconstruction convolutional neural network (PFR-CNN) approach to model the solute concentration field in rotationally influenced fluids. A new three-dimensional (3D) numerical solver, TwoLiquidMixingCoriolisFoam, was implemented within the framework of OpenFOAM to simulate effluents subjected to the influence of rotation. Subsequently, the developed numerical solver was employed to conduct numerical experiments to generate numerical data. A PFR-CNN was designed to predict the concentration fields of neutrally buoyant effluents in rotating water bodies based on the Froude number (Fr) and Rossby number (Ro). The proposed PFR-CNN was trained and validated with a train-validation dataset. The predicted concentration fields for two additional tests demonstrated the good performance of the proposed approach, and the algorithm performed better than traditional approaches. This study offers a new 3D numerical solver, and a novel PFR-CNN approach can predict solute transport subjected to the effects of rotation in few seconds, and the PFR-CNN can significantly reduce the computational costs. The study can significantly advance the ability to model flow and solute transport processes, and the proposed CNN-based approach can potentially be employed to predict the spatial distribution of any physical variable in the lentic, ocean, and earth system.

Design Study of an HTS Linear Power Generator Suitable for Wave Energy Converter

In this paper, we show a conceptual structure of a direct drive linear power generator with REBaCuO high-temperature superconducting (HTS) bulk field poles for wave energy conversion. The proposed linear power generator structure is comprised of a moving armature coil and HTS bulks concept, which we call it a dual translator power generation system. Its performance has been analyzed using a finite-element electromagnetic field analysis method. A determination of the main machine parameters for the dual translator HTS linear power generator was conducted. Simulation results were compared between our dual translator HTS linear generator structure and the use of permanent magnets (PMs) for the field poles of that structure. It was found that the electromotive forces, electromagnetic forces and output power of the dual translator HTS linear power generator structure are 1.67, 2.63 and 2.60 times superior to that of dual translator PM linear generator structure, respectively. A combination of the dual translator power generation system and HTS bulks has the potential to help us to achieve higher torque and higher output power despite low ocean wave speed, which is important to achieve practical application of ocean power generation systems.

180 years of marine animal diversity as perceived by public media in southern Brazil.

Commoditization of marine resources has dramatically increased anthropogenic footprints on coastal and ocean systems, but the scale of these impacts remain unclear due to a pervasive lack of historical baselines. Through the analysis of historical newspapers, this paper explores changes in marine animals (vertebrates and invertebrates) targeted by historical fisheries in southern Brazil since the late 19th century. The investigation of historical newspaper archives revealed unprecedented information on catch composition, and perceived social and economic importance of key species over decades, predating official national-level landing records. We show that several economically and culturally important species have been under persistent fishing pressure at least since the first national-scale subsidies were introduced for commercial fisheries in Brazil in the late 19th and early 20th centuries. Our work expands the current knowledge on historical fish catch compositions in the southwestern Atlantic Ocean, while advocating for the integration of historical data in ocean sustainability initiatives.

Remote sensing oil in water with an all-fiber underwater single-photon Raman lidar.

The detection of oil in water is of great importance for maintaining subsurface infrastructures such as oil pipelines. As a potential technology for oceanic application, an oceanic lidar has proved its advantages for remote sensing of optical properties and subsea materials. However, current oceanic lidar systems are highly power-consuming and bulky, making them difficult to deploy underwater to monitor oil in water. To address this issue, we have developed a compact single-photon Raman lidar by using a single-photon detector with high quantum efficiency and low dark noise. Due to the single-photon sensitivity, the detection of the relatively weak Raman backscattered signal from underwater oil was realized with a laser with a pulse energy of 1µJ and a telescope with a diameter of 22.4mm. An experimental demonstration was conducted to obtain the distance-resolved Raman backscatter of underwater oil of different thicknesses up to a distance of 12m. The results indicate the single-photon Raman lidar's potential for inspecting underwater oil pipelines.

High-Precision In Situ Total Alkalinity Analyzer Capable of Month-Long Observations in Seawaters.

Total alkalinity (TA) is an essential variable for the study of physical and biogeochemical processes in coastal and oceanic systems, and TA data obtained at high spatiotemporal resolutions are highly desired. The performance of the current in situ TA analyzers/sensors, including precision, accuracy, and deployment duration, cannot fully meet most research requirements. Here, we report on a novel high-precision in situ analyzer for surface seawater TA (ISA-TA), based on an automated single-point titration with spectrophotometric pH detection, and capable of long-term field observations. The titration was carried out in a circulating loop, where the titrant (a mixture of HCl and bromocresol green) and seawater sample were mixed in a constant volume ratio. The effect of ambient temperature on the TA measurement was corrected with an empirical formula. The weight, height, diameter, and power consumption of ISA-TA were 8.6 kg (in air), 33 cm, 20 cm, and 7.3 W, respectively. A single measurement required ∼7 min of running time, ∼32 mL of seawater, and ∼0.6 mL of titrant. ISA-TA was able to operate continuously in the field for up to 30 days, and its accuracies in the laboratory and field were 0.5 ± 1.7 μmol kg-1 (n = 13) and 10.3 ± 2.8 μmol kg-1 (n = 29) with precisions of 0.6-0.8 μmol kg-1 (n = 51) and 0.2-0.7 μmol kg-1 (n = 8), respectively. This study provides the research community with a new tool to obtain seawater TA data of high temporal resolution.

Consequence of Climate Change on Biodiversity and Biome of Antarctica - A Short Review

In specific areas of the Arctic and Antarctic regions, air temperatures are expanding at rates more than two times the international average; additionally, there are other direct human impacts on polar regions. A quick change in climate impacting the polar regions will similarly have huge physical and biological consequences for the last existing parts of the planet since the ice-engulfed Arctic Ocean, the Antarctic landform, and the worldwide eminent Antarctic Circumpolar Current (ACC) serve a basic job in managing the Earth’s current circumstance and ocean systems. Polar biodiversity is presently responding to this rapid climate change and more massive impacts will happen in this era. Intensifying the danger to polar biodiversity is the certainty that numerous polar environments have restricted functional redundancy; in case of the disappearance of a solitary keystone species, they may possibly be exposed to descending impacts and complete biological system rebuilding. This study focussed on the contributing factors of ecological change, the effects of natural change on the Antarctic environment, next to the effects of environmental change on the types of Antarctic biodiversity. The most rapidly changing biological agenda on our planet are arranged in the polar regions. This issue is picked to research the effects of natural change on a particular region’s biodiversity.

Spatial and temporal variations in sea surface pCO2 and air-sea flux of CO2 in the Bering Sea revealed by satellite-based data during 2003–2019

The understanding of long-time-series variations in air-sea CO2 flux in the Bering Sea is critical, as it is the passage area from the North Pacific Ocean water to the Arctic. Here, a data-driven remote sensing retrieval method is constructed based on a large amount of underway partial pressure of CO2 (pCO2) data in the Bering Sea. After several experiments, a Gaussian process regression model with input parameters of sea surface temperature, sea surface height, mixed-layer depth, chlorophyll a concentration, dry air mole fractions of CO2, and bathymetry was selected. After validation with independent data, the root mean square error of pCO2 was< 24 μatm (R2 = 0.94) with satisfactory performance. Then, we reconstructed the sea surface pCO2 in the Bering Sea from 2003 to 2019 and estimated the corresponding air-sea CO2 fluxes. Significant seasonal variations were identified, with higher sea surface pCO2 in winter/spring than in summer/autumn in both the basin and shelf area. Semiquantitative analysis reveals that the Bering Sea is a non-temperature-dominated area with a mean temperature effect on pCO2 of 12.7 μatm and a mean non-temperature effect of −51.8 μatm. From 2003 to 2019, atmospheric pCO2 increased at a rate of 2.1 μatm yr−1, while sea surface pCO2 in the basin increased rapidly (2.8 μatm yr−1); thus, the CO2 emissions from the basin increased. However, the carbon sink in the continental shelf still continuously increased. The whole Bering Sea exhibited an increasing carbon sink with the area integral of air-sea CO2 fluxes increasing from 6 to 19 TgC over 17 years. Meanwhile, the seasonal amplitudes in pCO2 in the shelf area also increased, approaching 14 μatm per decade. The reaction of the continuously added CO2 in continental seawater reduced the ocean CO2 system capacity. This is the first study to present long-time-series satellite data with high resolution in the Bering Sea, which is beneficial for studying the changes in ocean ecosystems and carbon sink capacity.

Effect of western Pacific current uncertainties on the forecasting of eddy shedding from the Kuroshio loop into the South China Sea: A case study

The process of eddy shedding from the Kuroshio loop current (LC) into the South China Sea via the Luzon Strait is highly variable and significantly controlled by the uncertainties in the Western Pacific (WP) currents. This study investigates the forecast of a strong eddy shedding event from the Kuroshio LC during the winter 2016–2017 using the regional ocean modeling system and ensemble Kalman filter assimilation method. Experiments are conducted to explore the sensitivity of forecasts to the assimilation of satellite sea surface height anomaly data from different key regions of the WP, such as the subtropical countercurrent (STCC) and Northern Equatorial Current (NEC) regions. The results indicate that the improved forecast performance of the strong Kuroshio LC eddy shedding event is mainly attributed to assimilation in the STCC region and partly owing to assimilation in the NEC region. Specifically, assimilation in the STCC region reproduces a westward-propagating cyclonic eddy that collides with the Kuroshio in the Luzon Strait, blocking the Kuroshio northward flow and causing Kuroshio LC eddy shedding. Furthermore, assimilation in the NEC region enhances the simulation of the weak Kuroshio background current, which further facilitates the formation of a strong Kuroshio background LC and the occurrence of Kuroshio LC eddy shedding.

Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires

Abstract. Tropospheric nitrogen dioxide (NO2) measured from satellites has been widely used to track anthropogenic NOx emissions, but its retrieval and interpretation can be complicated by the free tropospheric NO2 background to which satellite measurements are particularly sensitive. Tropospheric NO2 vertical column densities (VCDs) from the spaceborne Ozone Monitoring Instrument (OMI) averaged over the contiguous US (CONUS) show no trend after 2009, despite sustained decreases in anthropogenic NOx emissions, implying an important and rising contribution from the free tropospheric background. Here, we use the GEOS-Chem chemical transport model applied to the simulation of OMI NO2 to better understand the sources and trends of background NO2 over CONUS. The previous model underestimate of the background is largely corrected by the consideration of aerosol nitrate photolysis, which increases the model NO2 VCDs by 13 % on an annual basis (25 % in spring) and also increases the air mass factor (AMF) to convert the tropospheric slant column densities (SCDs) inferred from the OMI spectra into VCDs by 7 % on an annual basis (11 % in spring). The increase in the AMF decreases the retrieved NO2 VCDs in the satellite observations, contributing to the improved agreement with the model. Accounting for the 2009–2017 increase in aircraft NOx emissions drives only a 1.4 % mean increase in NO2 VCDs over CONUS and a 2 % increase in the AMF, but the combination of decreasing surface NOx emissions and increasing aircraft emissions is expected to drive a 14 % increase in the AMF over the next decade that will be necessary to account for in the interpretation of satellite NO2 trends. Fire smoke identification with the National Oceanic and Atmospheric Administration (NOAA) Hazard Mapping System (HMS) indicates that wildfires contribute 1 %–8 % of OMI NO2 VCDs over the western US in June–September and that this contribution has been increasing since 2009, contributing to the flattening of OMI NO2 trends. Future analyses of NO2 trends from satellite data to infer trends in surface NOx emissions must critically consider the effects of a rising free tropospheric background due to increasing emissions from aircraft, fires, and possibly lightning.