This study aims at understanding the impact of low-frequency climate modes on Rossby Wave Packets (RWPs) during the southern hemisphere summer. In particular, we focus on long-lived RWPs (lifespan above 8 days) and determine how El Niño-Southern Oscillation (ENSO) and Southern Annular Mode (SAM) modulate their frequency of occurrence plus the main areas of detection and dissipation. We find that the occurrence of long lived RWPs is maximum during El Niño years and negative SAM events. Years with largest numbers of long-lived RWPs are characterized by a zonally symmetric and narrow upper level jet that is shifted northward from its climatological position. Conversely, when the jet is shifted southward, as during positive SAM phases, particularly in the southwestern Pacific basin, the number of long-lived RWPs detected diminishes. El Niño sets atmospheric conditions that support the formation of long lived RWPs whereas La Niña years presents high interannual variability in the frequency of occurrence. Moreover, during El Niño events the main formation area is between 61-120ºE and its main dissipation area between 300-359ºE. During La Niña events, the main formation area moves to 241-300ºE and no main dissipation area is identified. During positive SAM two main formation areas appear at 61-120ºE and 241-300ºE and two main dissipation areas between 121-180º and 301-359º, whereas in negative SAM only one formation area at 241-300º is detected and no main dissipation area is found.

Atmospheric deposition is an important source of trace metals to surface environments, but knowledge about plant bioavailability of recently deposited metals is limited. We performed a fully factorial soil and atmosphere exposure experiment with three vegetables (radish, lettuce, and soybean), which allowed to effectively distinguish impacts of recently deposited metals (<1 year) from longer-term metal exposures in soils. Results showed that recently deposited Cu, Cd, and Pb accounted for 0.5-15.2% of total soil Cu, Cd, and Pb pools near emission source, while they contributed 15-76% of Cu, Cd, and Pb concentrations in edible parts of vegetables. The soil retention of recently deposited metals (52-73%) presented as higher mobile fractions than these previously present in soils (7-42%). These findings highlight a preferential uptake and high rates of bioaccumulation of deposited metals in vegetables and implicated that quick and potentially stronger reduction can be achieved by reducing current atmospheric source loads.

The uplift of the southern African Plateau is often attributed to mantle processes, but there are conflicting theories for the specific timing and drivers of topographic development. Evidence for most proposed plateau development histories is derived from continental erosion histories, marine stratigraphic architecture, or landscape morphology. Here we use a landscape evolution model to integrate these three types of data for southern Africa, including a large dataset of low temperature thermochronology, sediment flux rates to surrounding marine basins. We explore three main hypotheses for surface uplift: 1) southern Africa was already elevated at the time of Gondwana breakup, 2) uplift and continental tilting occurred in the mid-Cretaceous, or 3) uplift occurred in the mid to late Cenozoic. We test which of these three intervals of plateau development are plausible by using an inversion method to constrain the range in erosional and uplift model parameters that can best reproduce the observed data. Results indicate two families of uplift histories are most compatible with the data. Both have limited initial topography with some topographic uplift and continental tilting starting in the east at ~95 Ma. In one acceptable scenario, nearly all of the topography, ~1400 m, is created at this time with little Cenozoic uplift. In the other acceptable scenario, only ~500 m of uplift occurs in the mid-Cretaceous with another ~850 m of uplift in the mid-Cenozoic. The two model scenarios have different geodynamic implications, which in the future could be evaluated by direct comparison between geodynamic and landscape model predictions.

The observation that individual volcanic centres have their own eruption frequencies has been known for a long time but is as yet poorly understood. The key to a better understanding of the mechanisms controlling the eruption frequency comes from integrating accurate geochronology and geochemical data with numerical models. In many silicic volcanic systems, the eruption frequency is studied for short timescales of <1 Ma. Here, we combine two published numerical models to improve our understanding of the eruption frequency in a long-lived (>3 Ma) felsic magmatic system, the Milos volcanic field. From these two models, we interpret the time intervals between magma pulses into the subvolcanic reservoir (ti), the rates of magma supply (Qav) and chamber growth rates (Gmc) as the key parameters controlling the eruption frequency. During the time intervals of 1.5-1.04 Ma and 0.97-0.63 Ma the ti is longer than 500 years and the volcanic quiescence periods are longer than 350 ka. Furthermore, these periods are characterized by low values for Qav (≤ 0.001 km3·yr-1) and for Gmc (<0.0008 km3·yr-1). In contrast, during the time intervals of 3.3-1.5 Ma and 0.60-0.06 Ma, the ti is shorter (<0.5 ka) and the values for Qav (> 0.001 km3·yr-1) and for Gmc (> 0.001 km3·yr-1) are higher corresponding to frequent eruptions. The parameters ti, Qav, and Gmc appear to determine the eruption frequency of a volcanic system. Changes in one or more of these three parameters of the Milos volcanic field correlate with changes in the tectonic stress field.

Geostationary satellites observe the earth surface and atmosphere with a short repeat time which can thus provide aerosol parameters with high temporal resolution. Due to the limited information content in satellite data, and the coupling between the signals received from the surface and the atmosphere, the accurate retrieval of multiple aerosol parameters over land is difficult. Here we propose a Neural Network AEROsol retrieval framework for Geostationary satellite (NNAeroG) which can potentially be applied to different instruments to retrieve various aerosol parameters. NNAeroG was applied for aerosol retrieval using data from the Advanced Himawari Imager on Himawari-8 and the results were evaluated versus independent ground-based sun photometer reference data. The retrieved Aerosol Optical Depth, Ångström Exponent and Fine Mode Fraction are significantly better than the official JAXA aerosol products. The use of thermal infrared bands is meaningful for aerosol retrieval.

Vast areas of boreal peatlands are impacted by linear disturbances known as seismic lines. Tree removal and ground disturbance alter vegetation communities and are expected to change ecosystem functioning. We investigate seismic line disturbances on peatland plant community composition and phenological patterns using readily available digital photography at a bog and a fen in Alberta, Canada. Our objectives were to: 1) compare the understory vegetation on seismic lines with those in adjacent undisturbed peatlands using two phenological metrics (green and red chromatic coordinates); 2) evaluate if vegetation greenness is directly related to vegetation community composition, and 3) determine whether plot-scale greenness predicts plant productivity. We found that disturbed peatlands have an earlier seasonal peak (maximum greenness) compared to undisturbed areas, and vegetation communities had a stronger relationship to greenness and gross primary production (GPP) at disturbed sites relative to undisturbed sites. This change in understory vegetation results in greater CO2; uptake in disturbed sites. We demonstrate an easy-to-use application of digital photography that successfully quantifies phenological changes in boreal peatland vegetation. This non-destructive method for understanding vegetation phenology eliminated the need for fixed infrastructure and allowed us to sample more plots and study sites while allowing for repeated measures in the future. As boreal landscapes continue to be disturbed by linear disturbances, understanding the magnitude and mechanisms of vegetation and phenology changes is the first step toward predicting carbon cycling changes across broad spatial scales.

Southeast Asia’s extensive tropical peatlands account for a significant proportion of the global riverine dissolved organic carbon (DOC) flux to the ocean. Peat-derived DOC is rich in polyphenolic compounds, the microbial degradation of which is thought to rely on extracellular phenol oxidases. Despite substantial interest in the biogeochemical fate of terrigenous DOC (tDOC), few studies have quantified phenol oxidase activity in aquatic environments, and microbial remineralization rates of tDOC have never been measured in Southeast Asia. Here, we assess the potential for using phenol oxidase assays as a proxy of tDOC biodegradation across peat-draining rivers and coastal waters of Sarawak, Borneo, and report experimental measurements of microbial tDOC remineralization rates from this region. We show first that phenol oxidase assays in aquatic samples are problematic because of the rapid, pH-dependent auto-oxidation of the assay substrate. Our field measurements of phenol oxidase activity detected only substrate auto-oxidation, suggesting that real phenol oxidase activity was low or absent. Second, we report that peatland tDOC, collected from one of the few remaining intact peatlands on Borneo, showed at most very limited biodegradation (0–6% loss of DOC, and 0–12% loss of coloured dissolved organic matter) during several 56-day incubation experiments at in-situ temperature of ~30°C, even when diluted with seawater or amended with nutrients. Our results suggest that direct microbial respiration is perhaps not a major pathway for peatland tDOC remineralization in Southeast Asia, and that photo-oxidation is more likely to control the fate of this carbon.

Afforestation has been suggested as an effective ecological engineering approach for carbon sequestration and environmental benefits. However, the impact of afforestation on soil inorganic carbon (SIC) is less clear and sometimes controversial. Here, we conducted a field campaign, with 2346 soil profiles from 619 afforested plots and 163 control plots, to investigate the relative and absolute changes of SIC between afforested and corresponding control plots in northern China. We found positive responses of SIC to afforestation in acidic soils, where afforestation increased soil pH. In contrast, in alkaline soil, afforestation caused soil acidification and thus negative SIC responses. Fitting a structure equation model (SEM) confirmed that afforestation-induced soil pH change (ΔpH) was the most significant factor regulated SIC responses to afforestation. In particular, we observed stronger SIC sensitivity to pH change in arid areas, where both soil pH and SIC stocks were high. Other factors indirectly affected SIC responses to afforestation through modulating soil pH and soil organic carbon (SOC) dynamics. Afforestation-induced SIC changes also varied considerably among different planted tree species and across different soil depths. Specifically, in Pinus sylvestris var. mongholica, Pinus tabuliformis and Populus spp. plantations, changes of SIC were large enough to be comparable to that of SOC. Our finding provides a data-based comprehensive understanding on the impact of afforestation on SIC and its underlying mechanisms. With increased uses of afforestation and reforestation as potential nature-based climate solutions, decisions need to consider potential associated SIC changes, especially in SIC-rich areas.

To characterize the subsurface geomechanical response to hydraulic fracturing activities, we study the spatiotemporal changes of seismic velocity during the completion of four injection wells in the Fox Creek area, Alberta, Canada. We estimate temporal velocity changes (dv/v) from ambient seismic noise recorded during the Tony Creek Dual Microseismic Experiment (ToC2ME) by comparing a 5-day stacked noise correlation function with a reference noise correlation function stacked over the deployment period. In the frequency band (0.1 - 0.4 Hz) most sensitive to the injection depths (~3.4 km), we observe daily dv/v that revealed alternating gradual velocity decreases and increases with magnitudes in the range of ±0.9%. We found a strong temporal correlation between the onset of velocity decreases and periods of intense seismicity, suggesting that the observed dv/v reductions are likely caused by stress-induced subsurface deformation due to elevated pore pressures, increased crack density, and ground shaking. A period of dv/v increase observed between the beginning and end of different well stimulation is attributed to crustal healing. Comparing the dv/v time series with injection parameters, we observed a 272.66% increase in induced seismicity and 50% more reduction in dv/v during the second injection phase that are correlated with 90.53%, 169.64%, and 4.34% increase in the injection volume, rate, and pressure, respectively. Our study provides valuable new information on the changes in reservoir elastic properties within the Western Canadian Sedimentary Basin. It also demonstrates that coda wave interferometry using data from dense seismic arrays near injection sites can be an additional tool for monitoring hydraulic fracturing operations.

The annual area burned due to wildfires in the western United States (WUS) increased by more than 300% between 1984 and 2020. However, accounting for the nonlinear, spatially heterogeneous interactions between climate, vegetation, and human predictors driving the trends in fire frequency and sizes at different spatial scales remains a challenging problem for statistical fire models. Here we introduce a novel stochastic machine learning (ML) framework to model observed fire frequencies and sizes in 12 km x 12 km grid cells across the WUS. This framework is implemented using Mixture Density Networks trained on a wide suite of input predictors. The modeled WUS fire frequency corresponds well with observations at both monthly (r= 0.94) and annual (r= 0.85) timescales, as do the monthly (r= 0.90) and annual (r= 0.88) area burned. Moreover, the annual time series of both fire variables exhibit strong correlations (r >= 0.6) in 16 out of 18 ecoregions. Our ML model captures the interannual variability and the distinct multidecade increases in annual area burned for both forested and non-forested ecoregions. Evaluating predictor importance with Shapley additive explanations, we find that fire month vapor pressure deficit (VPD) is the dominant driver of fire frequencies and sizes across the WUS, followed by 1000-hour dead fuel moisture (FM1000), total monthly precipitation (Prec), mean daily maximum temperature (Tmax), and fraction of grassland cover in a grid cell. Our findings serve as a promising use case of ML techniques for wildfire prediction in particular and extreme event modeling more broadly.

The ROTI index based on the variation of the TEC is used to detect and characterize the ionospheric irregularities. In the present work, we present a comparative study of five different methodologies to ROTI calculation in order to evaluate the most suitable for the Brazilian region. This was performed over three GNSS stations at different latitudes: São Luís (SALU, 2°31′ S, 44°16′ W; dip: -6.60°) that is located near the dip equator; Cachoeira Paulista (CHPI, 22°40’ S, 44°59’ W; dip: -35.99°) which set close to the southern crest of the EIA at low latitude); and Santa Maria (SMAR, 29° 41′ S, 53° 48′ W, dip: -43.51°) a low-to-mid latitude station close to center of the SAMA region. The period of analysis covered January and December 2015. Our results show that only one out of the five techniques proposed seems to be appropriated for ROTI construction in the Brazilian sector. Our results are supported by comparison of the ROTI with TEC maps obtained over Brazil, ionograms acquired at Fortaleza (FZA0M), SALU, and CHPI ionosonde stations, and All-Sky imagers collected at the São João do Cariri, and CHPI. In addition, we were able to observe the typical irregularities of the Brazilian ionosphere by using the ROTI which we have classified as EPB.

Unplanned urban growth exerts significant stresses on the underlying aquifers in terms of increasing the groundwater extraction and reducing the surface area for aquifer recharge. This situation has led to a more difficult process in the search for new locations of productive tubular wells, particularly in the Federal District of Brazil. In this region, the groundwater extraction is challenged by fractured aquifers with difficult identification of hydraulic tarps and significant uncertainty in the estimation of recharge potential. The aim of the present study is to optimize the demarcation of new locations of tubular wells by conducting geophysical investigations. In the first stage, based on the information of the physical environment and data from the existing wells, the total exploitable amount of groundwater was calculated. Then Electrical Resistivity Tomography (ERT) was carried out along specific sites, which were selected based on the surficial characteristics. The resistivity values obtained from the dipole-dipole array were inverted and the resultant conducting zones (weathered rocks and fractures) were delineated, which represent possible hydraulic traps where groundwater may exist. Based on the results, the suitability of the selected sites for deep tubular wells installation was prioritized on a linear scale varying from 1 to 5, where 1 is the highest and 5 is the least suitable. Based on this approach, eight new deep tubular well sites were proposed and classified. The study provides a promising framework for investigating groundwater in fractured aquifers.

Natural variability of fault friction and slip uncertainty exist in the Earth's crust. To what extent it influences crustal stress and its evolution is intriguing. We established a quasi-static, 2D model to simulate the stress evolution due to Coulomb frictional slips in the brittle crust. The model simply features randomly-oriented fractures with heterogeneous frictional coefficients. We emphasized the global stress response by summing the contribution of cascades of local frictional slip under specific boundary conditions. We illustrated that the decrease in stress difference manifests as a self-organized process that ultimately leads to frictional equilibrium. The model informs that the frictional equilibrium of a stochastic system can depart substantially from a deterministic estimation. Although the model quantitatively corroborates the notion of frictional equilibrium in places where fracture slip is the dominant mechanism for stress release, it reveals far more profound influence of system heterogeneity on the local and global stress evolution.

The Nile river basin is one of the global hotspots vulnerable to climate change impacts due to fast growing population and geopolitical tensions. Previous studies demonstrated that general circulation models (GCMs) frequently show disagreement in the sign of change in annual precipitation projections. Here, we first evaluate the performance of 20 GCMs from the 6 Coupled Model Intercomparison Project (CMIP6) benchmarked against a high spatial resolution precipitation dataset dating back to 1983 from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR). Next, a Bayesian Model Averaging (BMA) approach is adopted to derive probability distributions of precipitation projections in the Nile basin. Retrospective analysis reveals that most GCMs exhibit considerable (up to 64% of mean annual precipitation) and spatially heterogenous bias in simulating annual precipitation. Moreover, it is shown that all GCMs underestimate interannual variability; thus, the ensemble range is under-dispersive and a poor indicator of uncertainty. The projected changes from the BMA model show that the value and sign of change varies considerably across the Nile basin. Specifically, it is found that projected change in the two headwaters basins, namely Blue Nile and upper White Nile is 0.03% and -1.65% respectively; both statistically insignificant at 0.05. The uncertainty range estimated from the BMA model shows that the probability of a precipitation decrease is much higher in the upper White Nile basin whereas projected change in the Blue Nile is highly uncertain both in magnitude and sign of change.

This study investigates the contributions of incipient vortex circulation and mid-level moisture to tropical cyclone (TC) expansion within an idealized numerical modeling framework. We find that the incipient vortex circulation places the primary constraint on TC expansion. Increasing the mid-level moisture further promotes expansion but mostly expedites the intensification process. The expansion rate for initially large vortices exhibits a stronger response to increasing the mid-level moisture compared to initially small vortices. Previous studies have noted a proclivity for relatively small TCs to stay small and relatively large TCs to stay large; that is, TCs possess a sort of “memory” with respect to their incipient circulation. We reproduce this finding with an independent modeling framework and further demonstrate that an initially large vortex can expand more quickly than its relatively smaller counterpart; therefore, with all other factors contributing to expansion held constant, the contrast in size between the two vortices will increase with time. Varying the incipient vortex circulation is associated with subsequent variations in the amount and scale of outer-core convection. As the incipient vortex circulation decreases, outer-core convection is relatively scarce and characterized by small-scale, isolated convective elements. On the contrary, as the incipient vortex circulation increases, outer-core convection abounds and is characterized by relatively large rainbands and mesoscale convective systems. A combined increase in the amount and scale of outer-core convection permits an initially large vortex to converge a substantially larger amount of absolute angular momentum compared to its relatively smaller counterpart, resulting in distinct expansion rates.

Deliberately blocking out a small portion of the incoming solar radiation would cool the climate. One such approach would be injecting SO$_2$ into the stratosphere, which would produce sulfate aerosols that would remain in the atmosphere for 1–3 years, reflecting part of the incoming shortwave radiation. This would not affect the climate the same way as increased greenhouse gas (GHG) concentrations, leading to residual differences when a GHG increase is offset by stratospheric sulfate geoengineering. Many climate model simulations of geoengineering have used a uniform reduction of the incoming solar radiation as a proxy for stratospheric aerosols, both because many models are not designed to adequately capture relevant stratospheric aerosol processes, and because a solar reduction has often been assumed to capture the most important differences between how stratospheric aerosols and GHG would affect the climate. Here we show that dimming the sun does not produce the same surface climate effects as simulating aerosols in the stratosphere. By more closely matching the spatial pattern of solar reduction to that of the aerosols, some improvements in this idealized representation are possible, with further improvements if the stratospheric heating produced by the aerosols is included. This is relevant both for our understanding of the physical mechanisms driving the changes observed in stratospheric sulfate geoengineering simulations, and in terms of the relevance of impact assessments that use a uniform solar dimming.

While estuarine salt plugs can develop worldwide in estuaries adjacent to buoyant coastal currents, their formation has been scarcely documented. This study aims to generalize a mechanism for salt plug formation that does not invoke evaporation processes but involves a buoyant coastal current modified by wind stresses. A numerical model, Delft3D, is used to simulate two idealized bays, one with a single inlet and another with two inlets. The numerical experiments are inspired by recent observations and simulate nine different scenarios of wind and tidal forcings under the influence of an along-shelf buoyant current. Results show that the salt plug induces an inverse circulation at the inlet with inflow at the surface and outflow underneath. This circulation is modified by wind action. The persistence of the salt plug depends on tidal flushing, as well as wind intensity and direction. A yearlong numerical experiment with non-stationary buoyant currents and non-stationary winds indicate that: (i) onshore winds transport oceanic waters into the bay, while offshore winds export estuarine water to the ocean; (ii) onshore winds enhance the inverse circulation at the inlet, while offshore winds stall it. The ratio between wind-driven and density-induced accelerations, given by the Wedderburn number, determines the dominant contribution to the along-estuary circulation in an along-estuary transect. In general, baroclinicity dominates over wind-stress at the inlet, while wind-stress governs the circulation along the estuary. This study represents the first attempt to identify the role of wind and buoyant coastal currents on the dynamics of salt plug formation.

Here we use a 3-D climate system model to study the habitability of Earth-like planets orbiting in circumbinary systems. A circumbinary system is one where a planet orbits around two stars simultaneously, resulting in large and rapid changes to both the stellar energy distribution and the total stellar energy received by the planet. We find that Earth-like planets, having abundant surface liquid water, are generally effective at buffering against these time-dependent changes in the stellar irradiation due to the high thermal inertia of oceans compared with the relatively short periods of circumbinary-driven variations in the received stellar flux. Ocean surface temperatures exhibit little to no variation in time, however land surfaces can experience modest changes in temperature, thus exhibiting an additional mode of climate variability driven by the circumbinary variations. Still, meaningful oscillations in surface temperatures are only found for circumbinary system architectures featuring the largest physically possible amplitudes in the stellar flux variation. In the most extreme cases, an Earth-like planet could experience circumbinary-driven variations in the global mean land surface temperature of up to ~5 K, and variations of local daytime maximum temperatures of up to ~12 K, on monthly timescales. Still, habitable planets in circumbinary systems are remarkably resilient against circumbinary driven climate variations.