The alignment of intrinsically anisotropic olivine crystals under convection is typically invoked as the cause of the bulk of seismic anisotropy inferred from shear-wave splitting (SWS). This provides a means of constraining the interplay between continental dynamics and the deep mantle, in particular for densely instrumented regions such as North America after USArray. There, a comparison of “fast orientations” from SWS with absolute plate motions (APM) suggests that anisotropy is mainly controlled by plate motions. However, large regional misfits and the limited realism of the APM model motivate us to further explore SWS based anisotropy. If SWS is estimated from olivine alignment in mantle circulation instead, plate-driven flow alone produces anisotropy that has large misfits with SWS. The addition of large-scale mantle density anomalies and lateral viscosity variations significantly improves models. Although a strong continental craton is essential, varying its geometry does, however, not improve the plate-scale misfit. Moreover, models based on higher resolution tomography degrade the fit, indicating issues with the flow model assumptions and/or a missing contributions to anisotropy. We thus compute a “lithospheric complement” to achieve a best-fit, joint representation of asthenospheric and frozen-in lithospheric anisotropy. The complement shows coherent structure and regional correlation with independently imaged crustal and upper mantle anisotropy. Dense SWS measurements therefore provide information on depth-dependent anisotropy with implications for tectonics, but much remains to be understood about continental anisotropy and its origin.

The factors driving variability in rainfall stable water isotopes (specifically δ¹⁸O and deuterium excess, d = δ²H - 8 δ¹⁸O) were studied in a 13-year dataset of daily rainfall samples from coastal southwestern Western Australia (SWWA). Backwards dispersion modelling, automatic synoptic type classification, and a statistical model were used to establish causes of variability on a daily scale; and predictions from the model were aggregated to longer temporal scales to discover the cause of variability on multiple timescales. Factors differ between δ¹⁸O and d and differ according to temporal scale. Rainfall intensity, both at the observation site and upwind, was most important for determining δ¹⁸O and this relationship was robust across all time scales (daily, seasonal, and interannual) as well as generalizing to a second observation site. The sensitivity of δ¹⁸O to rainfall intensity makes annual mean values particularly sensitive to the year’s largest events. Projecting the rainfall intensity relationship back through ∼ 100 years of precipitation observations can explain ∼ 0.2-0.4‰ shifts in rainfall δ¹⁸O. Twentieth century speleothem records from the region exhibit signals of a similar magnitude, indicating that rainfall intensity should be taken into account during the interpretation of regional climate archives. For d, humidity during evaporation from the ocean was the most important driver of variability at the daily scale, as well as explaining the seasonal cycle, but source humidity failed to explain the longer-term interannual variability.

Biogeochemical cycles in the Arctic Ocean are sensitive to the transport of materials from continental shelves into central basins by sea ice. However, it is difficult to assess the net effect of this supply mechanism due to the spatial heterogeneity of sea ice content. Manganese (Mn) is a micronutrient and tracer which integrates source fluctuations in space and time. The Arctic Ocean surface Mn maximum is attributed to freshwater, but studies struggle to distinguish sea ice and river contributions. Informed by observations from 2009 IPY and 2015 Canadian GEOTRACES cruises, we developed a three-dimensional dissolved Mn model within a 1/12 degree coupled ocean-ice model centered on the Canada Basin and the Canadian Arctic Archipelago (CAA). Simulations from 2002-2019 indicate that annually, 87-93% of Mn contributed to the Canada Basin upper ocean is released by sea ice, while rivers, although locally significant, contribute only 2.2-8.5%. Downstream, sea ice provides 34% of Mn transported from Parry Channel into Baffin Bay. While rivers are often considered the main source of Mn, our findings suggest that in the Canada Basin they are less important than sea ice. However, within the shelf-dominated CAA, both rivers and sediment resuspension are important. Climate induced disruption of the transpolar drift may reduce the Canada Basin Mn maximum and supply downstream. Other micronutrients found in sediments, such as Fe, may be similarly affected. These results highlight the vulnerability of the biogeochemical supply mechanisms in the Arctic Ocean and the subpolar seas to climatic changes.

Most marine plastic pollution originates on land. However, once plastic is at sea, it is difficult to determine its origin. Here we present a Bayesian inference framework to compute the probability that a piece of plastic found at sea came from a particular source. This framework combines information about plastic emitted by rivers with a Lagrangian simulation, and yields maps indicating the probability that a particle sampled somewhere in the ocean originates from a particular source. We applied the framework to the South Atlantic Ocean, focusing on floating river-sourced plastic. We computed the probability as a function of the particle age, at three locations, showing how probabilities vary according to the location and age. We computed the source probability of beached particles, showing that plastic found at a given latitude is most likely to come from the closest source. This framework lays the basis for source attribution of marine plastic.

Covid- 19 dominantly impacted the Indian agricultural sector. During the period of COVID-19 the southwest monsoon covered a major part of the country, thus resulting in an increase of 9 percent coverage in rainfall than the usual average period. Due to the good amount of rainfall the area under cultivation during the kharif season stood above 4.8% than the previous year. During, the initial lockdown period the agriculture has not been much affected and an increase in migration resulted an increase in people employed in agriculture. Through regression analysis the relationship between the yield and rainfall has been determined. The R2 values have been calculated and the spatial relationship between them has been established. Regions with higher R2 values have been found to be more dominantly affected by Covid-19, though in certain areas strong R2 has shown a weaker spatial relationship owing to certain other factors and policies taken by the Government. Therefore, regression analysis can be used as a suitable method to study the relationship of rainfall and agricultural yield during Covid-19. Keywords: Agriculture, Regression Analysis, Spatial relationship, Rainfall, Covid-19.

We present space and ground-based multi-instrument observations demonstrating the impact of the 2022 Tonga volcanic eruption on dayside equatorial electrodynamics. A strong counter electrojet (CEJ) was observed by Swarm and ground-based magnetometers on 15 January after the Tonga eruption and during the recovery phase of a moderate geomagnetic storm. Swarm also observed an enhanced equatorial electrojet (EEJ) preceding the CEJ in the previous orbit. The observed EEJ and CEJ exhibited complex spatiotemporal variations. We combine them with the Ionospheric Connection Explorer (ICON) neutral wind measurements to disentangle the potential mechanisms. Our analysis indicates that the geomagnetic storm had minimal impact; instead, a large-scale atmospheric disturbance propagating eastward from the Tonga eruption site was the most likely driver for the observed intensification and directional reversal of the equatorial electrojet. The CEJ was associated with strong eastward zonal winds in the E-region ionosphere, as a direct response to the lower atmosphere forcing.

Understanding lowermost stratosphere (LMS) ozone variability is an important topic in the trends and climate assessment communities because of feedbacks among changing temperature, dynamics and ozone. LMS evaluations are usually based on satellite observations. Free tropospheric (FT) ozone assessments typically rely on profiles from commercial aircraft. Ozonesonde measurements constitute an independent dataset encompassing both LMS and FT. We used Southern Hemisphere Additional Ozonesondes (SHADOZ) data (5.8°N to 14°S) from 1998-2019 in the Goddard Multiple Linear Regression model to analyze monthly mean FT and LMS ozone changes across five well-distributed tropical sites. Our findings: (1) both FT (5-15 km) and LMS (15-20 km) ozone trends show marked seasonal variability. (2) All stations exhibit FT ozone increases in February-May (up to 15%/decade) when the frequency of convectively-driven waves have changed. (3) After May, monthly ozone changes are both positive and negative, leading to mean trends of +(1-4)%/decade, depending on station. (4) LMS ozone losses reach (4-9)%/decade mid-year, correlating with an increase in TH as derived from SHADOZ radiosonde data. (5) When the upper FT and LMS are defined by tropopause-relative coordinates, the LMS ozone trends all become insignificant. Thus, the 20-year decline in tropical LMS ozone reported in recent satellite-based studies likely signifies a perturbed tropopause rather than chemical depletion. The SHADOZ-derived ozone changes highlight regional and seasonal variability across the tropics and define a new reference for evaluating changes derived from models and satellite products over the 1998 to 2019 period.

The interface between rivers and groundwater is a key driver for the turnover of reactive nitrogen compounds, that cause eutrophication of rivers and endanger drinking-water production from groundwater. Molecular-biological data and omics tools have been used to characterize microorganisms responsible for the turnover of nitrogen compounds. While transcripts of functional genes and enzymes are used as measures of microbial activity it is not yet clear how they quantitatively relate to actual turnover rates under variable environmental conditions. We developed a reactive-transport model for denitrification that simultaneously predicts the distributions of functional-gene transcripts, enzymes and reaction rates. Applying the model, we evaluate the response of transcripts and enzymes at the river–groundwater interface to stable and dynamic hydrogeochemical regimes. While functional-gene transcripts respond to short-term (diurnal) fluctuations of substrate availability and oxygen concentrations, enzyme concentrations are stable over such time scales. The presence of functional-gene transcripts and enzymes globally coincides with the zones of active denitrification. However, transcript and enzyme concentrations do not directly translate into denitrification rates in a quantitative way because of non-linear effects and hysteresis caused by variable substrate availability and oxygen inhibition. Based on our simulations, we suggest that molecular-biological data should be combined with aqueous chemical data, which can typically be obtained at higher spatial and temporal resolution, to parameterize and calibrate reactive-transport models.

The ionospheric scale height is a key parameter that defines the shape of the electron density profile. Its main characteristic, including the diurnal variation and its altitudinal dependence are still under investigation. This paper analyses the characteristics of the effective scale height at middle latitudes based on coincident Digisonde and Swarm A satellite data. Based on the assumption that the topside electron density function with altitude is approximated with the α-Chapman model, the effective scale height at the Swarm A altitude is calculated and it is compared with the effective scale height at hmF2. A general conclusion is that the effective scale height in the topside at ~450 km exhibits a diurnal variation with highest values in the early morning and evening sectors, while at hmF2 it gets its maximum values at noon. At night, the effective scale height tends to increase with altitude, however in the daytime, its behavior is more complex. At local scale, evidence for connection between spread F irregularities and high variability in the topside effective scale height is reported. Although the analysis is in progress to include data from the whole Swarm mission, these preliminary results indicate the potential to further exploit Swarm and Digisonde data for effective scale height modeling and for setting up a nowcasting system for the probability of occurrence of ionospheric instabilities in the topside ionosphere based on the bottomside stratification.

Thermal demagnetization furnaces are routine facilities that underpin countless paleomagnetic studies by allowing the progressive removal of naturally acquired magnetic remanence or the imparting of well controlled laboratory magnetization. The ideal thermal demagnetizer should maintain “zero” magnetic field during thermal treatments. However, magnetic field noise, including residual magnetic fields of material used to construct the furnace and induced fields caused by the heating current in the furnace are always present. As technology advances allowing the measurement of ever weaker magnetic remanences, it is essential that high-performance demagnetization furnaces are developed to reduce these sources of magnetic field noise. By combining efficient demagnetization of shielding and a new structure of heating wire, we have developed a new demagnetization furnace with low magnetic field noise. Repeated progressive thermal demagnetization experiments using specimens that were previously completely thermally demagnetized above their Curie temperature were carried out to explore the effects of fields within various types of furnace during demagnetization. These experiments confirm that magnetic field noise in various furnaces can have an observable and detrimental impact on demagnetization behavior and that this is reduced with our new design. The new heating element design and procedure for reducing magnetic field noises represent a significant improvement in the design of thermal demagnetizers and allows for extremely weak specimens to be successfully measured.

Two adjacent segments of the Chile margin exhibit significant differences in earthquake magnitude and rupture extents during the 1960 Valdivia and 2010 Maule earthquakes. We use the Discrete Element Method to simulate the upper plate as having an inner and outer wedge defined by different frictional domains along the decollement. We find that outer wedge width strongly influences coseismic slip distributions. We use the published peak slip magnitudes to pick best fit slip distributions and compare our models to geophysical constraints on outer wedge widths for the margins. We obtain reasonable fits to published slip distributions for the 2010 Maule rupture. Our best-fit slip distribution for the 1960 Valdivia earthquake suggests that peak slip occurred close to the trench, differing from published models but being supported by new seismic interpretations along this margin. Finally, we also demonstrate that frictional conditions beneath the outer wedge can affect the coseismic slip distributions.

An international effort to improve ozonesonde data quality and to reevaluate historical records has made significant improvements in the accuracy of global network data. However, between 2014 and 2016, ozonesonde total column ozone (TCO; O3) at 14 of 37 regularly reporting stations exhibited a sudden drop-off relative to satellite measurements. The ozonesonde TCO drop is 3-7 % compared to satellite and ground-based TCO, and 5-10 % or more compared to satellite stratospheric O3 profiles, compromising the use of recent data for trends, although they remain reliable for other uses. Hardware changes in the ozonesonde instrument are likely a major factor in the O3 drop-off, but no single property of the ozonesonde explains the findings. The bias remains in recent data. Research to understand the drop-off is in progress; this letter is intended as a caution to users of the data. Our findings underscore the importance of regular ozonesonde data evaluation.

The Alfred Wegener Institute Climate Model (AWI-CM) participates for the first time in the Coupled Model Intercomparison Project (CMIP), CMIP6. The sea ice-ocean component, FESOM, runs on an unstructured mesh with horizontal resolutions ranging from 8 to 80 km. FESOM is coupled to the Max-Planck-Institute atmospheric model ECHAM 6.3 at a horizontal resolution of about 100 km. Using objective performance indices, it is shown that AWI-CM performs better than the average of CMIP5 models. AWI-CM shows an equilibrium climate sensitivity of 3.2°C, which is similar to the CMIP5 average, and a transient climate response of 2.1°C which is slightly higher than the CMIP5 average. The negative trend of Arctic sea ice extent in September over the past 30 years is 20-30% weaker in our simulations compared to observations. With the strongest emission scenario, the AMOC decreases by 25% until the end of the century which is less than the CMIP5 average of 40%. Patterns and even magnitude of simulated temperature and precipitation changes at the end of this century compared to present-day climate under the strong emission scenario SSP585 are similar to the multi-model CMIP5 mean. The simulations show a 11°C warming north of the Barents Sea and around 2 to 3°C over most parts of the ocean as well as a wetting of the Arctic, subpolar, tropical and Southern Ocean. Furthermore, in the northern mid-latitudes in boreal summer and autumn as well as in the southern mid-latitudes a more zonal atmospheric flow is projected throughout the year.

The Antarctic stratospheric sudden warming (SSW) occurred on August 30, 2019, and was a vortex displacement minor warming event. We investigated variations in gravity waves (GWs) before and after this rare Antarctic SSW event using two satellite measurements (AIRS and CIPS) and reanalysis data (GEOS-5 FP). The observations showed that the GW activities decreased after the SSW onset, with a weakening of zonal wind. The decrease in GW activity coincided with a reversal of the zonal wind around September 8 in GEOS-5 FP. The temporal variation of GWs was similar to that of Arctic GWs during vertex displacement minor SSWs. The decline in GW activities was probably caused by wind filtering and polar night jet breaking. However, the GW activities over the Andes and the Antarctic peninsula decreased at the onset, although the westly wind was 40–60 ms-1. This decrease could have been caused by wave saturation.

Source time functions are essential observable quantities in seismology; they have been investigated via kinematic inversion analyses and compiled into databases. Given the numerous available results, some empirical laws on source time functions have been established, even though they are complicated and fluctuate along time series. Theoretically, stochastic differential equations, which include a random variable and white noise, are suitable for modeling such complicated phenomena. In this study, we model source time functions as the convolution of two stochastic processes (known as Bessel processes). We mathematically and numerically demonstrate that this convolution satisfies some of the empirical laws of source time functions, including non-negativity, finite duration, unimodality, a growth rate proportional to t³, ω⁻²-type spectra, and frequency distribution. We interpret this convolution and speculate that the stress drop rate and fault impedance follow the same Bessel process.

The motion of the Pacific plate relative to Pacific hotspots produces age-progressive chains of volcanoes. New methods of analysis of volcano locations and age dates using a small number of adjustable parameters (10 per chain) are presented. Simple fits to age progressions along Pacific hotspot chains indicate $1\sigma$ age uncertainties of $\approx\pm$1.0 to $\pm$3.0 Ma. Motion between the Hawaii and Louisville hotspots differs insignificantly from zero with rates of 2$\pm$4 mm/a (=$\pm$2$\sigma$) for 0–48 Ma and 26$\pm$34 mm/a (=$\pm$2$\sigma$) for 48–80 Ma. Relative to a mean Pacific hotspot reference frame, motions of the Hawaii, Louisville, and Rurutu hotspots are also insignificant. Therefore plumes underlying these Pacific hotspots may be more stable in a convecting mantle than previously inferred. We find no significant difference in age between the Eocene bends of the Pacific hotspot chains. The best-fitting assumed-coeval age for the bends is 47.4$\pm$1.0 Ma (=$\pm$2$\sigma$), coincident with the initiation of the doubling of the spreading rate of the Pacific plate relative to the Farallon and Vancouver plates. The initiation of the Eocene slowdown of India preceded the bends and was completed after the bends. Any causal relation of this slowdown to the Hawaiian-Emperor bend remains obscure. On the other hand, initiation of subduction of the Pacific plate in the west and southwest Pacific Ocean Basin likely preceded the formation of the bends, consistent with subduction initiation changing the torque on the Pacific plate such that it started moving in a more westward direction thus creating the Hawaiian-Emperor Bend.

Seismic reflection data (normal incidence and wide-angle) are unique assets for Solid Earth Science. They provide critical information about the physical properties and structure of the lithosphere, and are useful to understand the geometry and evolution of the tectonic plates, and for exploration of natural resources, civil engineering, characterization of seismogenic zones and hazard assessment. The resolution of seismic reflection data is highly appreciated for basic and applied Earth Sciences. However, these datasets are logistically complex and expensive to acquire, and their geographical coverage is limited. In addition, legacy seismic reflection data also have an added value as new information can be retrieved by applying new processing approaches. The preservation and dissemination of seismic open access data is an asset to promote accurate and innovative research. Here, we present the Seismic DAta REpository (SeisDARE), which is, to our knowledge, one of the first comprehensive open access online databases that stores seismic data registered with a permanent digital object identifier (DOI). The datasets included here are accessible online and guarantee the FAIR (Findable, Accessible, Interoperable, Reusable) principles of data management, so that each dataset enters into a statistic referencing database and its impact can be measured. This database has been built thanks to a network of several institutions, promoting a multidisciplinary research, and is open for international data exchange and collaborations. SeisDARE includes deep seismic sounding and high-resolution data acquired in the last three decades in the Iberian Peninsula and Morocco. In addition, as result of fruitful collaborations, we are starting to host data acquired worldwide. Our first incorporation of this kind are seismic profiles recorded in Hardeman County, Texas, within the COCORP project. SeisDARE aims to make easily accessible legacy and recently acquired seismic data and establish a framework for future seismic data management plans. The datasets are available at https://digital.csic.es/handle/10261/101879, bringing endless opportunities to the scientific, industrial and educational communities. This research has been funded by EPOS IP 676564, EPOS SP 871121, EIT Raw Materials 17024-SIT4ME and SERA 730900.

Carbonyl sulfide (COS) is the major long-lived sulfur bearing gas in the atmosphere, and is used to estimate the rates of regional and global (both past and current) photosynthesis. Sulfur isotope measurements (34S/32S ratio, δ34S) of COS may offer a way for improved determinations of atmospheric COS sources. However, measuring the COS δ34S at the atmospheric concentrations of ~0.5 ppb is challenging. Here we present high-accuracy δ34S measurements of atmospheric COS done by gas chromatograph (GC) connected to a multicollector inductively coupled plasma mass spectrometer (MC-ICPMS), after pre-concentrating from 2-liters of air. We showed that the precision of COS δ34S measurement for gas standards is ≤0.2‰, and that N2 and CO2 in the gas standard mixture had no effect on the measured δ34S. Natural air samples were collected in Israel and in the Canary Islands. The COS δ34S values in both locations were found to be 13.2±0.6‰, and are believed to represent the background tropospheric value. This δ34S value is markedly different from the previously reported value of 4.9‰. We estimate the expected isotopic signature of COS sources and sinks, and use the δ34S value of atmospheric COS we measured to estimate that ~48% of it originates from the ocean.