Interplanetary shocks have been long known sources of suprathermal and energetic ions, and their origin will contribute in unveiling the origin of cosmic rays. Sudden ion intensity enhancements in the form of spikes that last anywhere between minutes to tens of seconds are observed during the passage of such shocks. Identification of spikes with peak intensities lasting ~1 min surveyed in over 304 shocks from January 2007 – December 2014 observed by the SEPT (Solar Electron and Proton Telescope) onboard STEREO (Solar Terrestrial Relations Observatory) A/B Spacecraft was performed using a new Python Code, followed by visual inspection. We also inspected the database of EPAM (Electron, Proton, and Alpha Monitor) onboard ACE (Advanced Composition Explorer) from 2003 to 2014. We present and discuss the statistical analysis of the shock spikes as a function of parameters such as shock normal angle and Mach number. The Python code can be used to analyse other databases such as WIND and this further paves the way for the employment of ML techniques to replace visual inspection. Such studies are vital in performing exhaustive and in-depth assessment of shock associated particle events.

The Plankton, Aerosol, Cloud, and Ocean Ecosystem (PACE) mission is NASA’s next great investment in Earth Science, continuing NASA’s legacy of over forty years of satellite ocean color measurements. PACE, expected to launch in 2023, will advance our Earth-observing and monitoring capabilities through hyperspectral imaging and multi-angle polarimetric observations of ocean, atmosphere, and land ecosystems. PACE will give us an unprecedented view of our home planet and will support user-driven environmental applications through research and applied science to address societal challenges and inform decision-making. The PACE Applications program seeks to strengthen the ties between science and decision-making through programming such as the Early Adopter initiative, workshops and focus sessions, and information-sharing and co-production activities. Practical applications of PACE data include waterborne pathogen monitoring and prediction, harmful algal bloom species discrimination and early-detection, support for best-management practices for estuary and watershed health, as well as sustainable fishery and aquaculture practices. Hyperspectral and polarimetric PACE data will provide water resource managers and decision-makers with highly accurate ocean color and atmospheric observations that will directly improve their operational products and applied technologies, ultimately fulfilling real-world needs. This presentation will highlight PACE’s novel hyperspectral and polarimetric capabilities, introduce PACE’s standard and exploratory data products, outline the PACE Applications Program, share real-world coastal applications of PACE data, and summarize the results of the 2021 PACE Applications Water Quality Focus Session and the 2021 PACE Applications Workshop as they relate to community engagement and capacity development. Finally, we will share the revamped PACE Applications Outreach Strategy and how it will be used to promote partnerships within the existing user communities of practice and new user communities of potential for greater societal benefit.

There exist two large (~1000 km) dome-like structures rising from the base of the mantle in global tomographic models that exhibit low seismic wave-speeds, known as “Large Low Velocity Provinces” (LLVPs). The LLVP beneath Africa is also known as Tuzo, while the LLVP beneath the Pacific Ocean is known as Jason – two early pioneers of plate tectonics and plume theory (Wilson and Morgan, respectively). The source of these anomalously low wave-speeds is debated as both thermal and chemical heterogeneities can lower wave-speeds. These heterogeneities, however, lead to dynamically different modes of convection, where the former results in buoyant LLVPs and the latter relatively dense LLVPs. Recent studies that include dynamical modeling, Stoneley modes, and body tide constraints, are beginning to converge towards a picture where dense, chemical heterogeneities may be stored in the deepest part of the LLVPs. Many of these analyses, however, have not treated each LLVP distinctly. Considering the interdisciplinary focus of this session, we combine the unique geodetic observation of Earth’s solid body tide with methods that combine Backus-Gilbert estimation with theoretical advances in adjoint methodology, to constrain the density of each LLVP separately. This process results in the enhancement of the combined data sensitivity to a chosen region (e.g., one LLVP) while diminishing the combined data sensitivity elsewhere. We discuss the results in the context of geochemical observations unique to Tuzo and Jason and implications for the dynamics of mantle evolution.

Deploying seismic or infrasound arrays on the ground to probe a planet’s interior structure remains challenging in remote regions facing harsh surface conditions such as Venus with a surface temperature of 464°C. Fortunately, a fraction of the seismic energy transmits in the upper atmosphere as infrasound waves, i.e. low-frequency pressure perturbations (< 20Hz). On July 22, 2019, a heliotrope balloon, equipped with pressure sensors, was launched from the Johnson Valley, CA with the objective of capturing infrasound signals from the aftershock sequence of the 2019 Ridgecrest earthquake. At 16:27:36 UTC, the sound of a natural earthquake of Mw 4.2 was detected for the first time by a balloon platform. This observation offered the opportunity to attempt the first inversion of seismic velocities from the atmosphere. Shear velocities extracted by our analytical inversion method fell within a reasonable range from the values provided by regional tomographic models. While our analysis was limited by the observation’s low signal-to-noise ratio, future observations of seismic events from a network of balloons carrying multiple pressure sensors could provide excellent constraints on crustal properties. However, to build robust estimates of seismic properties, inversion procedures will have to account for uncertainties in terms of velocity models, source locations, and instrumental errors. In this contribution, we will discuss the current state of balloon-based observations, the sensitivity of the acoustic wavefield on subsurface properties, and perspectives on future inversions of seismically-induced acoustic data.

A multi-stage fuzzy inference system (FIS), a symbolic knowledge-based artificial intelligence technique, is used to delineate exploration targets for rare earth elements (REEs) associated with carbonatite-alkaline complexes in NE India. A conceptual REE mineral systems model was used to identify the following targeting criteria for REE deposits. The multi-stage FIS was structured based on the mineral systems model. The first stage of the multi-stage FIS comprised of three individual FIS to represent (1) plume-metasomatised SCLM in an extensional regime that make up fertile source regions for REE-bearing fluids and favourable geodynamic settings; (2) trans-lithospheric structures that provide favourable lithospheric architecture for the transportation of REE-enriched alkaline-carbonatite magma and (3) near-surface higher-order structures that make up a shallow crustal architecture facilitating emplacement of alkaline-carbonatite complexes. The targeting criteria were represented by their spatial proxies in the form of GIS layers derived using spatial analyses and geoprocessing tools for inputting to the FIS. The outputs of the FIS were mapped to generate prospectivity maps that were analysed to identify exploration targets for REE in the study area. The uncertainties in the outputs of the FIS were quantified using Monte-Carlo-based simulations. Exploration targets at low uncertainty levels were delineated around Sung valley and Jasra carbonatite-alkaline-complexes. Areas around the carbonatite-alkaline complex around Swangkre and to the south of the Nongstoin town were identified as high-uncertainty targets. It is recommended that ground follow-up exploration should be carried out in the former targets, and more data should be collected to increase confidence in the latter targets.

The compound extremes of hydrometeorological variables might not only affect as an extreme from a single variable, but might also result due to their interaction in time and space. This occurrence is called compound unusual events. A statistical approach based on the data depth function is being used to identify these occurrences in the multivariate dataset. To illustrate the methodology, the daily historical series of precipitation and mean temperature series from several selected observation stations in Germany will be used. The zero values of precipitation and the anomalies of mean temperature are used in this study. This study will help in answering the occurrence of unusual events for both variables on temporal and spatial scales.

Due to the coupled nature of the earth system, precipitation forecast errors at S2S lead times are caused by a combination of errors/biases from the atmosphere, ocean, ice and land across a range of spatial and temporal scales. We show that UFS precipitation errors over the U.S. at Weeks 3-4 can be directly related to biases in simulating tropical dynamics. In particular, the inability of the UFS to realistically simulate the Madden-Julian oscillation (MJO) leads to biases in the teleconnection to North America that produces these errors. When the tropics are nudged to produce an accurate representation of the MJO and other tropical disturbances, U.S. West Coast precipitation biases are substantially reduced. A clustering analysis is used to show that the greatest forecast improvements with nudging occur during warm ENSO events when MJO convection is in the Indian Ocean and about to move into the Maritime Continent. Physical mechanisms that explain the improvement in tropical-extratropical teleconnections during certain MJO and ENSO states will be discussed. We will also present future plans to combine state-of-the-art developments in machine learning with process-based diagnostics of the tropical moisture and moist static energy (MSE) budgets to understand and correct precipitation biases in coupled UFS hindcasts. In particular, we will discuss how model biases and errors in tropical variability (e.g. MJO) and associated teleconnections to midlatitudes lead to errors in U.S. precipitation on S2S timescales, and present methods to reduce these errors via post-processing on a forecast-by-forecast basis.

For the past 5 years, NASA’s Oceans Melting Greenland (OMG) mission has been motivated by the question: “to what extent are the oceans melting Greenland’s ice from below?” Three out of the mission’s four observational components employed aircraft to collect data on and around the ice sheet: (i) airborne gravity above the continental shelf to infer seafloor geometry, (ii) airborne radar (GLISTIN-A) to measure year-to-year glacier elevation changes, and (iii) airborne-deployed oceanographic instruments (AXCTDs, ALAMO and APEX floats, XBTs, and drifters) to measure year-to-year ocean temperature and salinity changes. After highlighting the mission’s operational parameters and key scientific findings, we will detail our rationale for designing the mission to include extensive aircraft-based measurements. Now that OMG has completed its final observational campaign, we will summarize our experience with using aircraft in polar environments and suggest ways in which aircraft could be used to efficiently extend the ocean climate data record started by OMG and the potential for using aircraft in future missions to make similar oceanographic measurements around Antarctica.

In this study we investigate how landscapes are inherited from continental rifting on long timescales. Areas that are currently undergoing extension typically have topographical features and drainage patterns that are easy to recognize. How these topographical rift features evolve on long timescales, however, is poorly understood. Recent work from onshore parts of the northeast Atlantic margin suggests that some present-day landforms are inherited from late Paleozoic, Mesozoic and Early Cenozoic rifting and opening of the North Atlantic Ocean. These relict landscapes are difficult to recognize, as the topography is reworked by post-rift Cenozoic uplift and erosion, as well as repeated Quaternary glaciations. For that reason, interpretations of these landscapes vary considerably. However, some of these relict rift features are demonstrably preserved in half-grabens, as sedimentary basins with well-established ages. Our research studies the topography around three half-grabens in Norway and on Svalbard, and aims to quantify landscape inheritance from rifting and margin formation. To do so, we use structural and geomorphological field observations, and remote sensing such as digital elevation model analyses and seismic images. We classify landscapes in detail, systematically reviewing present-day landscape distributions in order to distinguish extensional tectonic landforms from other geomorphological features. Preliminary results find that certain present-day landforms along the northeast Atlantic Ocean are relics from rifting from as far back as the late Paleozoic. This is expressed by, among other things, major topographic contrasts between footwall and hanging wall in all three half-grabens. This means higher topographical elevations and deeper incision in the footwalls compared to the hanging walls. Additionally, the three study areas have very different landscapes, suggesting that their individual post-rift landscape evolutions were very different from each other. These differences seem to be influenced by the degree of glacial incision, the degree of erosional exploitation of pre-rift structures, and possible Late-Cretaceous or younger reactivation of basin-bounding normal faults.

A combination of magmatic and tectonic processes occur on the western branch of the East African Rift System (EARS) driven by active volcanoes adjacent to active rift faults. Mt. Nyiragongo and Mt. Nyamuragira have the most recent eruptive histories of the 8 volcanoes in the Virunga Volcanic Zone (VVZ) located in a region between Rwanda, Uganda and Democratic Republic of Congo (DRC). On May 22nd 2021, Mt.Nyiragongo erupted the first major eruption following its 2002 eruption. This eruption didn’t have the common precursory seismic activity expected before an eruption as was observed in the 2002 eruption seismic record. Rather, there were numerous post-eruption earthquake events with the largest of those events being a magnitude ML 5.1. Around the region of the earthquake swarm, there was observable ground deformation in the city of Goma and Rubavu where surface fissures destroyed houses and split roads apart. This deformation appears to be related to a N-S striking dike intrusion from the volcano trending south towards and under Lake Kivu, according to observed seismicity. In collaboration with the Government of Rwanda, following the May Mt. Nyiragongo eruption, we established a network of 6 seismometers (2 Meridian Compact PH and 4 Trillium Compact PH) operating at 100 sps and two complimentary raspberry Shake and Booms (SBS) around Lake Kivu. This study will focus on characterizing deformation associated with the eruption and the subsequent seismic swarm. Here we present model results based on deformation during the May 2021 eruption as recorded through ALOS InSAR scenes to understand slip concentration during the dike intrusion. Using GTDef, a set of algorithms developed in MATLAB that can incorporate a wide range of geodetic data types to model deformation observed on the Earth’s surface, we model the slip distribution in this region based on the current hypothesis that the observed seismicity was a result of a dike intrusion defined by the southward propagation of the seismic swarm from Mt. Nyiragongo. Given an approximate source, we determine a preferred GNSS/GPS network design based on resolution-cost of additional stations at given locations and discuss first order characterization of the observed deformation.

Even though in Earth System Sciences (ESS) the importance of good research data management has been widely discussed, the easy discoverability of quality-checked data has not yet been addressed in detail. This is the aim of the Earth System Data Branding (EASYDAB). EASYDAB is a branding to highlight FAIR and open data from Earth System Sciences that are published with DataCite DOIs. The EASYDAB guideline defines principles on how to achieve high metadata quality of ESS datasets by demanding specific metadata information. The EASYDAB logo is protected and may only be used by repositories that agree to follow the EASYDAB terms. The logo indicates that published data have an open licence, open file formats and rich metadata information. Quality controls by the responsible repository ensure that these conditions are met. For the control, the repository can choose between different approved quality guidelines such as e.g. the ATMODAT Standard, ISO 19115 or the OGC Geopackage Encoding Standard. Ideally, a quality guideline provides detailed mandatory and recommended specifications for rich metadata in the data files, the DataCite DOI and the landing page. One example of such a quality guideline is the ATMODAT standard, which has been developed specifically for atmospheric model data (AtMoDat project). In addition to the metadata specifications, it also demands controlled vocabularies, structured landing pages and specific file formats (netCDF). The ATMODAT standard includes checklists for data producers and data curators so that compliance with the requirements can easily be obtained by both sides. To facilitate an automated compliance check of the netCDF files metadata, a Python tool has also been developed and published. The automated checking of the quality principles enables a simplified control of the data by the repository. Nevertheless, repositories can also use checklists for the curation of the data. The overall aim of the curation of EASYDAB datasets shall always be the enhancement of the reuse of reviewed, high-quality data. Therefore, EASYDAB shows scientists the way to open and FAIR data while it enables repositories to indicate their efforts in publishing data with high maturity.

Temporary seismic network deployments are quite common both in land and offshore. The acquired data have significantly helped improve our understanding of earthquake processes and internal structure of the Earth. However, some temporary stations, especially these all-in-one units without external GPS timing system, suffer from incorrect timing record and thus pose a challenge to fully utilize the valuable data. To inspect and fix such time problems, ambient noise cross-correlation function (NCCF) is widely adopted by using daily waveforms. However, it is difficult to identify short-term time drift after stacking the NCCF output for several days to months. To detect such clock errors, travel times of local and distant earthquakes are utilized along with NCCF. We apply such a strategy on an Ocean Bottom Seismograph (OBS) dataset from southern Mariana subduction zone and a dataset from a temporary dense network from Weiyuan shale gas field, Sichuan, China. By inspecting travel times from local and distant events, we identify a very short-term clock drift (~25 sec) on the OBS data that was not detectable using NCCF only. To overcome the problem, short segments (3, 6, 12 hours) of daily wavefrom data is inspected as clock errors become stable within the selected segments. In addition, the data quality is carefully inspected with impact of different interstation distance and period band on NCCF. In particular, we find that the 6-hour segment with a period band of 2-5 sec is able to detect and correct short term changes, including linear drift. For the dense array data, we observe that NCCF symmetry is well-preserved for short interstation distance (within 1 km) but becomes distorted for larger interstation distances. Therefore, we split our dense array (79 stations) into 16 groups with a maximum interstation distance of 500 meters and 1-2 sec period band was selected after testing. Short data segments improve the time-drift detection efficiency in NCCF results, which is consistent for both local and distant events. In a nutshell, the carefull selection of data length and NCCF parameters can be helpful to identify and correct the time drift errors of temporary seismic stations.

Energy balance regimes (e.g., Radiative Convective Equilibrium or RCE) qualitatively characterize the low, mid, and high latitudes of Earth’s modern climate. Currently we do not have a complete quantitative understanding of the spatio-temporal structure of energy balance regimes. Here we use the vertically-integrated moist static energy budget to define a nondimensional number that quantifies when and where RCE is approximately satisfied in Earth’s modern climate. We find RCE exists yearround in the tropics and also in the Northern midlatitudes during summertime. Decomposing the seasonal RCE regime transition in the midlatitudes over land and ocean shows that RCE occurs predominantly over land. We use idealized models (energy balance and aquaplanet models) to test the hypothesis that the RCE regime occurs during midlatitude summer for land-like (small heat capacity) surface conditions. Consistent with the hypothesis, an aquaplanet model configured with a shallow mixed layer depth transitions to RCE in the midlatitudes during summertime whereas it does not for a deep mixed layer depth.

Leveraging aerosol data from multiple airborne and surface-based field campaigns encompassing diverse environmental conditions, we calculate statistics of the oxalate-sulfate mass ratio (median: 0.0217; 95% confidence interval: 0.0154 – 0.0296; R = 0.76; N = 2948). Ground-based measurements of the oxalate-sulfate ratio fall within our 95% confidence interval, suggesting the range is robust within the mixed layer for the submicrometer particle size range. We demonstrate that dust and biomass burning emissions can separately bias this ratio towards higher values by at least one order of magnitude. In the absence of these confounding factors, the 95% confidence interval of the ratio may be used to estimate the relative extent of aqueous processing by comparing inferred oxalate concentrations between air masses, with the assumption that sulfate primarily originates from aqueous processing.

The Underground Gas Storage (UGS) project of Castor, Spain, was strategically conceived to guarantee the Spanish gas demand during 50 days. Yet, the project did not enter into operation because it was cancelled as a result of a sequence of felt earthquakes induced after cushion gas injection. The project cancellation implied an investment compensation to the operating company that may cost up to 4.73 billion euros to Spanish citizens. The sequence contained the three largest earthquakes (M4.08, M4.01 and M3.97) ever induced by any of the more than 640 UGS facilities around the world. The largest earthquakes were induced some 20 days after stopping injection, which lasted for 15 days. The focal depth of these earthquakes was between 4 to 10 km, far deeper than the 1.7 km injection depth. To understand the causes of this induced seismicity, we have performed coupled two-phase flow and geomechanical numerical simulations and we have employed Okada’s solution to analyze the shear slip stress transfer. We analyzed four seismicity-inducing mechanisms (pore pressure build-up, stress transfer, destabilizing buoyancy, and recovery of pressure drops that ensure transient stability in regions that are mechanically destabilized after a microseism). We found that the onset of seismicity was induced by gas injection, which reactivated the critically stressed Amposta fault through pore pressure buildup and buoyancy. The Amposta fault, a mature fault bounding the storage formation, crept, accumulating aseismic slip. Destabilization of the fault continued even after the stop of injection because of the permanent effect of buoyancy caused by the low density of the injected gas. The progressive accumulation of slip perturbed the stress around the rupture area of the Amposta fault and eventually reactivated a critically stressed unmapped fault located in the crystalline basement. Once this deep fault was reactivated, the sequence of earthquakes was induced by shear slip stress transfer, with transient slip-driven pore pressure changes likely controlling the delay between earthquakes. We contend that an analysis of fault stability prior to gas injection would have identified the high risk of inducing seismicity at Castor.

Previous approaches to modify the surface albedo of Arctic ice have been proposed to slow the rate of ice melt or to increase ice thickness. (Seitz 2011, Desch 2018, Field 2018) Sea ice, glacial ice, and ice-covered thermokarst lakes are all known to melt aided by surface albedo feedback loops. In this process, melting of snow and/or the formation of melt ponds on the surface of the ice causes a lowering of surface albedo, which causes more absorption of sunlight, further warming the ice and increasing the rate of melt. In this study on a freshwater pond, we demonstrate the real-time dynamics of melting and a reduction of ice melt rate by 26% via surface albedo modification.

Exploration of SST-Streamflow connection unravels the large scale climate influences that have a potential role in modulating local hydrological components. Most studies exploring this relationship only focus on seasonal or annual scales however, various atmospheric and oceanic phenomena occur at different timescales, which need to be considered. This study investigates the influence of sea surface temperature (SST) on German streamflow, divided into Alpine, Atlantic and Continental streamflow regions, at timescales ranging from sub-seasonal to decadal by integrating wavelet transform and complex network techniques. Wavelet transform is used to decompose the time series into multiple frequency signals, and the spatial connections are identified based on these decomposed signals for the 99 percentile correlation coefficient value by applying network theory. The degree centrality metric is used to evaluate the characteristics of the spatially embedded networks. Our results re-establish known SST regions that have a potential connection with the various streamflow regions of Germany. Spatial patterns that resemble the North Atlantic SST tripole-like pattern is predominant for Alpine streamflow regions at lower timescale. Equatorial Atlantic Mode regions observed for Atlantic streamflow at inter-annual timescale and Vb weather system connected regions in the Mediterranean Sea have appeared for all the streamflow regions of Germany. Besides, continental streamflow regions exhibited combined characteristics of the Alpine and Atlantic streamflow spatial patterns. In addition to the above regions, we also identify the scale specific patterns in the Pacific, Indian and Southern Ocean regions at different timescales ranging from seasonal to decadal scale.

Symmetries and topology have been actively introduced currently to characterize the mode structure of waves in various systems physics, giving rise to the concepts of topological insulators, topological superconductors and topological photonics, to name a few. Very recently, the equatorial wave systems have been described from a topological point of view by Delplace et. al. (Science 358, 1075-1077 (2017)). It was shown that the emergence of unidirectional edge waves (Yanai and Kelvin waves) can be attributed to the topological bound states. An f-plane model is used to connect the topological invariants, the Chern numbers, to the existence of these modes. We have extended this analysis by incorporating a beta plane model thereby including the Earth’s sphericity from beginning. Equatorial beta plane model renders the Poincare and Rossby waves also equatorially trapped. Further, the effect of moisture balance on the topology of the equatorial waveguide is examined. It is shown that the presence of a new eastward propagating mode within a low-frequency regime is similar to the observed MJO mode. We explained how moisture localizes these low-frequency unidirectional oscillations. The topological origin of moist waves is emphasized by relating their topological invariants, or Chern numbers. From this perspective, equatorial moist waves also show the strong similarities with bulk-edge correspondence encountered in quantum valley Hall effect and its classical analogues. Our study shows that the topological origin of MJO-like mode and its localization due to low-level moisture encode essential information of the tropical climatic systems.