The Southern Ocean (SO) connects major ocean basins and hosts large air-sea carbon fluxes due to the resurfacing of deep nutrient and carbon rich waters, driven by strong surface winds. Vertical mixing in the SO, induced by breaking waves excited by strong surface winds and interaction of tides, jets and eddies with rough topography, has been considered of secondary importance for the global meridional overturning circulation. Its importance for biological cycles has largely been assumed to be due to the role of mixing in changing the underlying dynamics on a centennial timescale. Using an eddy-resolving ocean model that assimilates an extensive array of observations, we show that altered mixing can cause up to a 40\% change in SO air-sea fluxes in only a few years through altering the distribution of dissolved inorganic carbon, alkalinity, temperature and salinity. Such enhanced mixing may be induced by the propagation of tidal waves from around the globe to the SO as well as the flux of wave energy from the deep SO to shallow depths. Such processes are unresolved in climate models, yet essential.

The ACT-America Earth Venture mission conducted five airborne campaigns across four seasons from 2016-2019, to study the transport and fluxes of Greenhouse gases across the eastern United States (US). Unprecedented spatial sampling of atmospheric tracers (CO2, CO, and COS) related to biospheric processes offers opportunities to improve our qualitative and quantitative understanding of seasonal and spatial patterns of biospheric carbon uptake. Here, we examine co-variation of boundary layer enhancements of CO2, CO, and COS across three diverse regions: the crop-dominated Midwest, evergreen-dominated South, and deciduous broadleaf-dominated Northeast. To understand the biogeochemical processes controlling these tracers, we compare the observed co-variation to simulated co-variation resulting from model- and satellite- constrained surface carbon fluxes. We found indication of a common terrestrial biogenic sink of CO2 and COS and secondary production of CO from biogenic sources in summer throughout the eastern US. Stomatal conductance likely drives fluxes through diffusion of CO2 and COS into leaves and emission of biogenic volatile organic compounds into the atmosphere. ACT-America airborne campaigns filled a critical sampling gap in the southern US, providing information about seasonal carbon uptake in southern temperate forests, and demanding a deeper investigation of underlying biological processes and climate sensitivities. Satellite- constrained carbon fluxes capture much of the observed seasonal and spatial variability, but underestimate the magnitude of net CO2 and COS depletion in the Southeast, indicating a stronger than expected net sink in late summer.

The air pollutant NO is derived largely from transportation sources, and is known to cause various respiratory diseases. Substantial reduction in transport and industrial processes around the globe stemming from the novel SARS-CoV-2 coronavirus and subsequent pandemic resulted in sharp declines in emissions, including for NO. Additionally, the COVID-19 disease that results from the coronavirus may present in its most severe form in those who have been exposed to high levels of air pollution and thus have various co-morbidities. To explore these links, we compared ground-based NOsensor data from 15 US cities from a one month window in 2019 versus the same window during shutdown in 2020. Levels of NO declined roughly 20-60% in 13 of the 15 cities in 2020, linked to similar declines in traffic volume in those cities. To broaden the spatial analysis beyond the individual ground-based monitors, satellite data for tropospheric NO was also analyzed, and was largely consistent with the ground measurements. Many of the cities studied had a substantial percentage of the population with various pre-existing conditions, and a relationship was found between NO levels, respiratory disease, and COVID-19 case counts. This finding indicates that substantial improvements in air pollution and health outcomes can be achieved quickly with local and state policy directives, perhaps leading to more population-level health resilience in the face of future pandemics.

Constraining the properties of continental margin where dynamic interplay between the lithosphere and convective upper mantle actively occurs can provide implications to understand the evolution and modification process of cratonic lithosphere. Cratonic lithosphere in the eastern Eurasian plate has experienced multiple episodes of tectonic events at the continental margin during the Phanerozoic, which are characterized by collision and subduction of continental and oceanic plates with extensive magmatic intrusion, extension, and rifting. To better understand the complex tectonic processes and their influences on the continental lithosphere, we imaged upper mantle structure beneath the Archean-Proterozoic basement in the Korean Peninsula (KP) by seismic tomography. Our dataset is entirely based on relative arrival time of teleseismic body wave recorded by dense seismic array across the southern KP in order to extract velocity variations from the local area and reduce the effects from deeper upper mantle structures. The images show a sharp and large lateral velocity variation within a short distance (< 200 km) in KP, which indicates highly variable lithospheric structure. An anomalously thick high-velocity structure beneath the southwestern part suggests a fragment of a long-lasting cratonic lithosphere (~150 km) at the continental margin. The absence of deep lithosphere and mostly occupied by hot, buoyant, low-velocity upper mantle beneath the Gyeonggi massif, Gyeongsang continental arc-backarc system, and eastern continental margin of KP shows highly modified regions. In addition, there are clear spatial correlations of low-velocity upper mantle with partial melting zones and the localities of Cenozoic basalts, high surface heat flux, and high topography with recent uplift along the eastern mountain ranges. A strong variation in the upper mantle velocity structure without clear distinctions in surface geology across different massifs suggests heterogeneous modification of continental lithosphere by recent and transient processes, such as the opening of the East Sea (Sea of Japan) or a subduction of Philippine Sea Plate. Dynamic interaction of the prominent lithospheric structure and convective upper mantle has controlled reactivation and destabilization at the cratonic margin of KP.

We present a seismo-acoustic analysis of the debris-flow activity between 2017 and 2019 at the Illgraben catchment (Switzerland). To understand fluid dynamic processes involved in the seismo-acoustic energy generation by debris-flows, seismic and acoustic amplitudes (maximum root mean square amplitude, RMSA) and peak frequencies are compared with flow measurements (front velocity, maximum flow depth and density). Front velocity, maximum depth, peak discharge and peak mass flux show a positive correlation with both infrasonic and seismic maximum RMSA, suggesting that seismo-acoustic radiation is controlled by these flow parameters. Comparison between seismo-acoustic peak frequencies and flow parameters reveal that, unlike seismic signals, characterized by a constant peak frequency regardless of the magnitude of the flow, infrasound peak frequency decreases with increasing flow velocity, depth and discharge. Based on all collected evidence, we suggest that infrasound signals of debris-flows are generated by flow waves and water splashes that develop at the free-surface of the flow, whose dimension scales with flow magnitude. According to fluid dynamics, such surface oscillations are mostly generated wherever the flow encounters significant channel irregularities, such as topographic steps and planform steep bends, that therefore likely constitute preferential sources of infrasound. As for seismic waves, results are consistent with previous theoretical models and field observations, which attribute debris-flow seismicity to solid particle collisions, friction and fluid dynamic structures. Finally, the observed positive correlations between seismo-acoustic signal features and flow parameters highlight the potential to use infrasound and seismic measurements for debris-flow monitoring and risk management.

Absorption muon imaging is a technique that can measure density variations underground down to a few hundred meters. Then, it can prove to be useful in a mining environment: to help assess the ore bodies volumes and/or to monitor the underground for natural hazards that can happen at the surface because of the mining exploitation. Here we report the result of an experiment designed to test the capabilities and resolution power of a cosmic muon measurement in a mining environment compared to other standard geophysics tools: gravimetry and seismic studies. It consists of three independent measurement of a subset of the decommissioned iron mine of May-sur-Orne (France). The first one was made using a 50x50cm² micromegas based muon telescope installed at the deepest non-submerged level (50m underground) during 3 months. The second one is a gravimetry survey of the surface area inside the muon telescope acceptance cone. And the third one is a study of refracted and reflected seismic waves along a single line above the muon telescope location. The investigation volume was chosen because of the presence of surface risks (neighborhood), the unknown of some uncharted volume and the presence of an ore storage volume of several meter cubed that was used during the mine exploitation and which filling state is unknown. The data analysis showed that while muon tomography is able to detect the negative density anomaly of the storage volume, the gravimetry measurement is not sensible to it. However, the seismic study was able to detect the volume as well and its location and extension is compatible with the muon measurement.

Previous studies have shown that Strong Thermal Emission Velocity Enhancement (STEVE) events occur at the end of a prolonged substorm expansion phase. However, the connection between STEVE occurrence and substorms and the global high-latitude ionospheric electrodynamics associated with the development of STEVE and non-STEVE substorms are not yet well understood. The focus of this paper is to identify electrodynamics features that are unique to STEVE events through a comprehensive analysis of ionospheric convection patterns estimated from SuperDARN plasma drift and ground-based magnetometer data using the Assimilative Mapping of Geospace Observations (AMGeO) procedure. Results from AMGeO are further analyzed using principal component analysis and superposed epoch analysis for 32 STEVE and 32 non-STEVE substorm events. The analysis shows that the magnitude of cross-polar cap potential drop is generally greater for STEVE events. In contrast to non-STEVE substorms, the majority of STEVE events investigated accompany with a pronounced extension of the dawn cell into the pre-midnight subauroral latitudes, reminiscent of the Harang reversal convection feature where the eastward electrojet overlaps with the westward electrojet, which tends to prolong over substorm expansion and recovery phases. This is consistent with the presence of an enhanced subauroral electric field confirmed by previous STEVE studies. The global and localized features of high-latitude ionospheric convection associated with optical STEVE events characterized in this paper provide important insights into cross-scale magnetosphere-ionosphere coupling mechanisms that differentiate STEVE events from non-STEVE substorm events.

Anthropogenic aerosol emissions from North America and Europe have strong effects on the decadal variability of the West African monsoon. Anthropogenic aerosol effective radiative forcing is model dependent, but the impact of such uncertainty on the simulation of long-term West African monsoon variability is unknown. We use an ensemble of simulations with HadGEM3-GC3.1 that span the most recent estimates in simulated anthropogenic aerosol effective radiative forcing. We show that uncertainty in anthropogenic aerosol radiative forcing leads to significant uncertainty at simulating multi-decadal trends in West African precipitation. At the large scale, larger forcing leads to a larger decrease in the interhemispheric temperature gradients, in temperature over both the North Atlantic Ocean and northern Sahara. There are also differences in dynamic changes specific to the West African monsoon (locations of the Saharan heat low and African Easterly Jet, of the strength of the west African westerly jet, and of African Easterly Waves activity). We also assess effects on monsoon precipitation characteristics and temperature. We show that larger aerosol forcing results in a decrease of the number of rainy days and of heavy and extreme precipitation events and warm spells. However, simulated changes in onset and demise dates does not appear to be sensitive to the magnitude of aerosol forcing. Our results demonstrate the importance of reducing the uncertainty in anthropogenic aerosol forcing for understanding and predicting multi-decadal variability in the West African monsoon.

Juno’s arrival at Jupiter in 2016 revealed unprecedented details about Jupiter’s ultraviolet aurorae thanks to its unique suite of remote sensing and in situ instruments. Here we present results from in situ observations during Juno flybys above specific bright auroral spots in Jupiter’s polar aurora. We compare data observed by Juno-UVS, JEDI, JADE, Waves, and MAG instruments when Juno was magnetically connected to bright polar auroral spots during perijove 3 (PJ3), PJ15, and PJ33. The highly energetic particles observed by JEDI show enhancements dominated by upward electrons, which suggests that the particle acceleration region takes place below the spacecraft. Moreover, both brightness and upward particle flux were higher for the northern bright spot in PJ3 compared to the southern spots found in PJ15 and PJ33. In addition, we notice the intensification of whistler-mode waves at the time of the particle enhancements, suggesting that wave-particle interactions contribute to the acceleration of particles which cause the UV aurorae. The MAG data reveal magnetic perturbations during the PJ3 spot detection by Juno, which suggests the presence of significant field-aligned electric currents. While the stable position of the bright spots in System III suggests that the phenomenon is fixed with respect to the rotation of the planet, the presence of field-aligned currents leaves open the possibility of an origin rooted much farther in the magnetosphere.

Extension and rifting of the lithosphere is fundamental to the evolution of the continents, but the mechanism by which the lithosphere thins remains enigmatic. Using new dense magnetotelluric array data collected within the rifted margin and adjacent areas of Southeast China, we resolve the three-dimensional electrical structure of the lithosphere to constrain the process of rifting and thinning. Our measurements discover a brittle-ductile transition zone featuring low electrical resistivity and low seismic velocity in the Cathaysia Block. A southeast-directed dip is resolved for the Jiangshan-Shaoxing Fault that documents the Neoproterozoic suturing of the Yangtze and Cathaysia Blocks, and has been reactivated by the Early Paleozoic and Early Mesozoic intracontinental orogenies. It acted as a low-angle detachment fault during the Mesozoic-Cenozoic extension and rifting. Given the asymmetries of topography, electrical resistivity, Bouguer gravity anomaly and Mesozoic volcanism across the Gan-Hang Rift, an asymmetric simple shear extension model is proposed for the South China Mesozoic-Cenozoic rift system. Water content of up to 0.1 wt% and melt fraction of up to 1% are estimated at 70 km depth beneath the central Wuyi Mountains, suggesting hydration of the mantle lithosphere. The hydration weakening of the mantle lithosphere promoted both the gravitational instability and convective removal of the lowermost lithosphere in South China.

The conditions in Venus’ upper mesosphere at around 120 km have some similarities to the upper mesosphere of Earth and Mars where ice clouds form. Here we show, using published satellite products and numerical modelling, that the upper mesosphere of Venus is sufficiently cold that both H2O and CO2 can condense to form particles. In fact, we show that there is likely to be a competition between the direct nucleation of particles from the gas phase (homogeneous nucleation) and the nucleation on meteoric smoke particles (MSPs, heterogeneous nucleation). Amorphous solid water particles (ASW) are likely to nucleate first, resulting in clouds of nano-scaled particles at around 120 km globally. The temperatures can then become sufficiently low that CO2 particles can nucleate either on MSPs or on ASW particles (>30% of the time poleward of 60°). Since the main component of the atmosphere is CO2 these particles will grow and sediment on a timescale of 10-20 minutes. Mie calculations show that these Venusian mesospheric clouds (VMCs) should be observable by contemporary satellite instruments, although their short lifetime means that the probability of detection is small. We suggest that VMCs are important for the redistribution of meteoric smoke and may serve as a cold-trap, removing some water vapour from the very upper mesosphere of Venus, through the growth and sedimentation of cloud particles, and possibly reducing the loss of water to space.

Plate reconstructions show that the plume feeding today’s Icelandic volcanism passed beneath the continental lithosphere of Greenland between 50 and 100 million years ago. While there has been ample volcanism on the margins of Greenland, both on the west and the east coasts, the thickness of the Greenland craton prevented surface eruptions within Greenland, leaving details of the plume track unclear. However, the passage of the plume is expected to leave a scar in the lower continental lithosphere of Greenland, where the hot plume material interacts with and erodes the stiff cratonic root. This interaction should cause increased surface heat flux and reduced lithosphere thickness along the plume track, and can potentially be constrained by observations that constrain heat flux (e.g., magnetic data and ice flow rates) and lithospheric structure (e.g., seismic tomography and magnetotelluric modeling). While most seismic tomography models indicate that there might be an east-west trending corridor of reduced lithosphere thickness, recent heat flux maps inferred from magnetic data show a northwest-southeast trending anomaly of high heat flux, suggesting an alternative direction of the passage of the Iceland plume. In order to resolve the discrepancy between the suggested hotspot tracks, we use numerical models to investigate how the surface heat flux would evolve in response to the passage of a plume beneath thick cratonic lithosphere. Our work focuses both on the temporal evolution (e.g. the onset and duration), and the shape of the heat flux anomaly, as well as lithospheric thinning related to convective erosion of the cratonic root by hot plume material. We show that both the onset and the duration of the heat flux anomaly, as well as the degree of lithosphere thinning, depend on various parameters, especially the viscosity structure of lithosphere and asthenosphere and the plume strength. A comparison between observations from Greenland and our model predictions should provide new and better constraints on the subsurface structure of Greenland, and how it was modified by its interaction with the Iceland plume.

A three-dimensional physical-biogeochemical ocean numerical model with eddy-permitting horizontal resolution was applied to simulate upper-ocean carbon cycle variabilities in the Tropical Maritime Continent (TMC) over the last decade (2010–2019). Forced by atmospheric and oceanic reanalysis products with high temporal resolution, the model showed robust consistency with the observed seasonality of pCO2 and atmospheric CO2 sink/source characteristics across the modeling domain. Within the TMC, the model results indicated strong CO2 degassing along the west of Sumatra-south of Java associated with the seasonal cycle of the upwelling system in the area. While acting as a full-year atmospheric CO2 source, the TMC exhibited pronounced interannual modulation in both pCO2 and sea-air CO2 flux over the last decade. Large-scale anomalous strong CO2 degassing from 2015 to 2016 in response to the evolution of the 2015/2016 El Niño was observed from the simulation results. Modulations related to the Indian Ocean Dipole (IOD), on the other hand, were confined along the west of Sumatra-south of Java with a higher magnitude compared with anomalies related to El Niño/La Niña. Simulation results also captured the asymmetric response of the upper-ocean carbon cycle to the IOD over the last decade, where anomalies during negative IOD (nIOD) were notably strong despite being indicated as weak nIOD events by the Dipole Mode Index.

Climate change has been a common interest and the forefront of crucial political discussion and decision-making for many years. Shallow clouds play a significant role in understanding the Earth’s climate but they are challenging to interpret and represent in a climate model. By classifying these cloud structures there is a better possibility of understanding the physical structures of the clouds which would improve the climate model generation resulting in a better prediction of climate change or forecasting weather update. Clouds organise in many forms which makes it challenging to build traditional rule-based algorithms to separate cloud features. In this paper classification of cloud organization patterns was performed using a new scaled-up version of Convolutional Neural Network (CNN) named as EfficientNet as the encoder and UNet as decoder where they worked as feature extractor and reconstructor of fine grained feature map and was used as a classifier which will help experts to understand how clouds will shape the future climate. By using a segmentation model in a classification task it was shown that with a good encoder alongside UNet it is possible to obtain good performance from this dataset. Dice coefficient has been used for the final evaluation metric which gave the score of 66.26% and 66.02% for public and private (test set) leaderboard on Kaggle competition respectively.

The spatio-temporal variation of stomatal conductance directly regulates photosynthesis, water partitioning, and biosphere-atmosphere interactions. While many studies have focused on stomatal response to stresses, the spatial variation of unstressed stomatal conductance remains poorly determined, and is usually characterized in land surface models (LSMs) simply based on plant functional type (PFT). Here, we derived unstressed stomatal conductance at the ecosystem-scale using observations from 115 global FLUXNET sites. When aggregated by PFTs, the across-PFT pattern was highly consistent with the parameterizations of LSMs. However, PFTs alone captured only 17\% of the variation in unstressed stomatal conductance across sites. Within the same PFT, unstressed stomatal conductance was negatively related to climate dryness and canopy height, which explained 45\% of the total spatial variation. Our results highlight the importance of plant-environment interactions in shaping stomatal traits. The trait-environment relationship established here provides an empirical approach for improved parameterizations of stomatal conductance in LSMs.

Prior investigations have attempted to characterize the longitudinal variability of the column number density ratio of atomic oxygen to molecular nitrogen (ΣO/N2) in the context of non-migrating tides. The retrieval of thermospheric ΣO/N2 from far ultra-violet (FUV) emissions assumes production is due to photoelectron impact excitation on O and N2. Consequently, efforts to characterize the tidal variability in O/N2 have been limited by ionospheric contamination from O+ radiative recombination at afternoon local times (LT) around the equatorial ionization anomaly. The retrieval of ΣO/N2 from FUV observations by the Ionospheric Connection Explorer (ICON) provides an opportunity to address this limitation. In this work, we derive modified ΣO/N2 datasets to delineate the response of thermospheric composition to non-migrating tides as a function of LT in the absence of ionospheric contamination. We assess estimates of the ionospheric contribution to 135.6 nm emission intensities based on either Global Ionospheric Specification (GIS) electron density, International Reference Ionosphere (IRI) model output, or observations from the Extreme Ultra-Violet imager (EUV) onboard ICON during March and September equinox conditions in 2020. Our approach accounts for any biases between the ionospheric and airglow datasets. We found that the ICON-FUV dataset, corrected for ionospheric contamination based on GIS, uncovered a previously obscured diurnal eastward wavenumber 2 tide in a longitudinal wavenumber 3 pattern at March equinox in 2020. This finding demonstrates not only the necessity of correcting for ionospheric contamination of the FUV signals but also the utility of using GIS for the correction.

We propose a machine learning-based approach to estimate the flood defense standard (FDS) for ungauged sites. We adopted random forest regression (RFR) to characterize the relationship between the observed FDS and ten explanatory factors contained in publicly available datasets. We compared RFR with multiple linear regression (MLR) and demonstrated the proposed approach in the conterminous United States (CONUS) and England, respectively. The results showed the following: (1) RFR performed better than MLR, with a Nash–Sutcliffe efficiency (NSE) of 0.82 in the CONUS and 0.73 in England. A negative NSE when using MLR indicated that the relationship between the FDS and each explanatory factor did not obey an explicit linear function. (2) River flood factors had higher importance than physical and socio-economic factors in the FDS estimation. The proposed approach achieved the highest performance using all factors for prediction and could not provide satisfactory predictions (NSE < 0.6) using physical or socio-economic factors individually. (3) We estimated the FDS for all ungauged sites in the CONUS and England. Approximately 80% and 29% of sites were identified as high or highest standard (> 100-year return period) in the CONUS and England, respectively. (4) We incorporated the estimated FDS in large-scale flood modeling and compared the model results with official flood hazard maps in three case studies. We identified obvious overestimations in protected areas when flood defenses were not taken into account; and flood defenses were successfully represented using the proposed approach.

Quantification of heterogeneous multiscale permeability in geologic porous media is key for understanding and predicting flow and transport processes in the subsurface. Recent utilization of in situ imaging, specifically positron emission tomography (PET), enables the measurement of three-dimensional (3-D) time-lapse radiotracer solute transport in geologic media. However, accurate and computationally efficient characterization of the permeability distribution that controls the solute transport process remains challenging. Leveraging the relationship between local permeability variation and solute advection rates, an encoder-decoder based convolutional neural network (CNN) is implemented as a permeability inversion scheme using a single PET scan of a radiotracer pulse injection experiment as input. The CNN consists of Densely Connected Neural Networks that can accurately capture the 3-D spatial correlation between the permeability and the radiotracer solute arrival time difference maps in geologic cores. We first test the inversion accuracy using 500 synthetic test datasets. We then use a suite of experimental PET imaging datasets acquired on four different geologic cores. The network-inverted permeability maps from the geologic cores are used to parameterize forward numerical models that are directly compared with the experimental PET imaging datasets. The results indicate that a single trained network can generate robust, denoised 3-D permeability inversion maps in seconds. Numerical models parameterized with these permeability maps closely capture the experimental solute arrival time behavior. This approach presents an unprecedented improvement for efficiently characterizing multiscale permeability heterogeneity in complex geologic materials.