Analysis of the time-dependent behavior of the buoyant plume rising above Grotto Vent (Main Endeavour Field, Juan de Fuca Ridge) as imaged by the Cabled Observatory Vent Imaging Sonar (COVIS) between September 2010 and October of 2015 captures long-term time-dependent changes in the direction of background bottom currents independent of broader oceanographic processes, indicating a systematic evolution in vent output along the Endeavour Segment of the Juan de Fuca Ridge. The behavior of buoyant plumes is a convolved expression of hydrothermal flux from the seafloor and ocean bottom currents in the vicinity of the hydrothermal vent. Plume behavior can be quantified by describing the volume, velocity and orientation of the effluent relative to the seafloor. Using three-dimensional acoustic images by the COVIS system, we looked at the azimuth and inclination of the Grotto plume in 3 hour intervals and identified a bimodal shift in their bending from NW and SW to SE in 2010, 2011, and 2012 to single mode NW in 2013 and 2014. Modeling of the distribution of azimuths for each year with a bimodal Guassian indicates that the prominence of southward bottom currents decreased systematically between 2010 and 2014. Spectral analysis of the azimuthal data showed a strong semi-diurnal peak, a weak or missing diurnal peak, and some energy in the sub-inertial and weather bands. This suggests the dominant current generating processes are either not periodic (such as the entrainment fields generated by the hydrothermal plumes themselves) or are related to tidal processes. The surface wind patterns in buoy data at 2 sites in the Northeast Pacific and the incidence of sea-surface height changes related to mesoscale eddies show little systematic change over this time period. Given the limited bottom current data for the Main Endeavour Field and other parts of the Endeavour segment, we hypothesize that changes in venting either within the Main Endeavour Field or along the Endeavour Segment have resulted in the changes in background currents. Previous numerical simulations (Thomsen et al 2009) showed that background bottom currents were more likely to be controlled by the local (segment-scale) venting than by outside ocean circulation or atmospheric patterns.

PM10 has natural and anthropogenic sources, it is an urban air pollutant from desertic areas or emitted by industry and traffic activities, it reduces visibility and threatens human wellbeing mainly in big cities. Casablanca concentrates many industrial units and a large vehicle fleet. The rate of urbanization in the metropolis and the population density are the highest in Morocco. Marrakech is one of the most populated cities in the country where the motorization rate has increased during recent years. The present work is based on PM10 daily measurements between 2013 and 2016. The main objective is to assess the concentrations of PM10 in Casablanca and Marrakech and study their relationship with the atmospheric circulation. First, we assessed PM10 correlations with climate indexes (NAO and MO), then we characterized the contribution of large-scale atmospheric patterns related to PM10 extreme events. The novelty of this research is the creation of a new climate index to characterize the oscillation, in the country’s southern desert, between the Saharan depression and the Azores high. The time series of the new Saharan Oscillation Index (SaOI) were calculated. This study has demonstrated the relationship between MO and PM10 averages and has shown that particulate pollution in the study area is partly induced by continental northeasterly to southwesterly flow. This flow is triggered by the Saharan trough and managed by the high-pressure area in the north. The assessed correlations related to the SaOI confirm the relationship between this index, PM10 averages, and MO and NAO indexes mainly in winter. The Saharan Oscillation is the new relevant key to understand worldwide pollution by fine particles.

Watersheds serve as natural spatial boundaries whose characteristics are often indicators of the hydrologic processes within them. Watershed characteristics are frequently used as predictors, parameters, or proxies in models of hydrologic and ecologic dynamics. Developments in DEMs over the past decade have resulted in elevation data spanning the globe that allows watershed delineation at arbitrary locations. In tandem, satellite-based observations and large-scale modeling efforts provide many sources of near-global watershed characteristics, e.g. topography, soil types, vegetation, climate, permafrost extent, and many more. However, with growing data availability comes a growing need for tools that can rapidly query and summarize them. We developed River and Basin Profiler (RaBPro), a Python module providing a pipeline to delineate drainage basins for any point on Earth and calculate watershed statistics for practically any geospatial raster dataset. RaBPro makes use of the MERIT-Hydro or HydroBASINS datasets to define watershed polygons, which can be exported in GeoJSON or ESRI shapefile format for further use in GIS software. RaBPro will also generate streamlines and river elevation profiles. Finally, RaBPro calculates statistics over delineated basins using Google Earth Engine (GEE). By taking advantage of GEE’s vast dataset archive and distributed computing system, RaBPro can quickly compute many statistics over even very large basins efficiently and without the need for storing large geo-rasters locally. Additionally, users may upload their own datasets to GEE and create custom statistic functions.

With the increasing volume of data generated in agriculture, developing guidelines for appropriate data sharing and management is essential. Founded in 2015, the AgBioData Consortium aims to identify the current major issues in data curation and management and ensure more Findable, Accessible, Interoperable, and Reusable (FAIR) data. In 2021 we received funding from the National Science Foundation for a Research Coordination Network grant, whose main goals are: (1) make recommendations and implementation plans for FAIR data in agriculture; (2) expand the AgBioData network by recruiting key stakeholders in agricultural research; (3) provide educational material to train researchers on FAIR data sharing; and (4) develop a roadmap for a sustainable genomic, genetic and breeding (GGB) Database Ecosystem. We have started by launching nine working groups covering different aspects of data management in agriculture and recruitment. We also plan new groups focused on sharing and archiving new types of data, such as those generated with high-throughput phenotyping platforms. As plant phenomics becomes a major part of agriculture, we foresee opportunities to collectively identify best data management practices in current and future phenomics repositories to ensure that phenomics data is FAIR from the start. We are welcoming new members with expertise in the field. If you are interested in joining, please visit our website (https://www.agbiodata.org).

Impactites generally consist of target rocks subjected to a shock wave during an impact event, but theoretically can be composed of surficial materials such as soil or other unconsolidated surface materials. Frothy samples found in the impact melt-bearing breccia circum Lonar crater, India have a significantly lower density than shocked bedrock basalts. Analyses of petrographic and back-scattered electron images, along with mineralogical and geochemical comparisons between the target basalts and local Deccan soils suggest that these are shocked soils that were compressed and lithified during the impact event. Hyperspectral images reveal both unshocked and shocked silicates and glasses along with organics on a scale of millimeters. Shocked soils/regolith could hold tremendous value as recorders of ancient lithosphere-hydrosphere-atmosphere reactions on this planet as well as Mars.

Links between hydrology and sliding of the Greenland Ice Sheet (GrIS) are poorly understood. Here, we monitored meltwater’s propagation through the entire glacial hydrologic system for catchments at different elevations by quantifying the lag cascade as daily meltwater pulses traveled through the supraglacial, englacial, and subglacial drainage systems. We found that meltwater’s residence time within supraglacial catchments-depending upon area, snow cover, and degree of channelization-controls the timing of peak moulin head, resulting in the two hour later peak observed at higher-elevations. Unlike at lower elevations where peak moulin head and sliding coincided, at higher elevations peak sliding lagged moulin head by ~2.8 hours. This delay was likely caused by the area’s lower moulin density, which required diurnal pressure oscillations to migrate further away from subglacial conduits to elicit the observed velocity response. These observations highlight the supraglacial drainage system’s control on coupling GrIS hydrology and sliding.

Geothermal heat flux (GHF) is an important basal boundary condition for models of ice sheet dynamics, but is poorly constrained by conventional borehole-based estimates. The accuracy and uncertainties associated with geophysical proxy-based GHF models are contingent upon reliable models of heat production and thermal conductivity that are difficult to constrain. In this study, we examine (1) the statistical distribution of these thermal properties to gain insight into the Antarctic crust, (2) revaluate GHF estimates using these new constraints, and (3) identify areas where a lack of knowledge still hampers our ability to produce accurate models of GHF. Our approach centers on developing statistical models for the thermal properties based on global and regional distributions from global geochemical datasets. We then calibrate our heat production models of Antarctica using a combination of exposed Antarctic terranes, conjugate terranes and crustal tomography models of Antarctica. Regions where exposures and conjugate terranes are not accessible, we use a terrane model of Antarctica to reduce uncertainty. We then estimate GHF for different proxy-based temperature models using our thermal property calibrations. We find more diversity in GHF models derived from geophysical-based proxies when using a standardized crustal property model than predicted by the original. We suggest that there is still much to learn about the thermal state of Antarctica, which requires further improvements in predictors of thermal properties, especially their variation with depth.

In this study, we examine the ability of the data assimilation of global satellite-based carbon monoxide (CO) observations to constrain high-latitude boreal wildfire emissions. We compare the optimized emissions from inversions using CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) and Infrared Atmospheric Sounding Interferometer (IASI). We found that both inversions yield generally consistent posterior CO emissions globally; however, distinct differences are observed for the episodic 2017 Canadian wildfires. The 3-day global coverage of MOPITT limits its ability to accurately optimize emissions, while the daily global coverage of IASI provides a moderate improvement despite its lower surface sensitivity. Through a series of observing system simulation experiments (OSSEs), we show that the temporal coverage of IASI most strongly influenced the posterior estimates, while the differences in vertical sensitivities of MOPITT and IASI have a minor contribution.

A document by Aodhan John Sweeney. Click on the document to view its contents.

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise, a task typically completed by human analysts. This process has usually been done by experts labeling each waveform visually, which is time-consuming and tedious for large datasets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, k-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show the two trained models agree with labels from human analysts but required only 0.4% time. Although the quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our analyses demonstrate the capability of the automated processing using these two machine learning models to reduce outliers in surface-wave-related measurements without human quality control screening.

Paleoclimate studies on speleothems commonly use oxygen isotopes as a record of precipitation variability and carbon isotopes to document soil, vegetation, and atmospheric processes. Magnetic minerals in speleothems record complementary paleoclimate information but need to be interpreted within the context of the particular geographic and geologic setting in which a karst environment occurs. This study surveys 23 caves in South America (7°N to 25°S latitude). The present-day climate is dominated by a monsoon regime, with variable precipitation between 50 to 800 mm/month covering different biomes, therefore making South America a good candidate to explore the properties of magnetic minerals at the tropical/subtropical climate. We share a database of magnetic properties from 23 stalagmites samples (90 specimens), 4 soil samples (34 specimens) and 2 limestone samples (15 specimens). Measured rock magnetic parameters include magnetic susceptibility, natural, anhysteretic, and isothermal remanent magnetization (NRM, ARM, IRM), as well as low-temperature magnetometry and first-order reversal curves. These data help constrain the types and granulometry of the magnetic mineralogy that commonly occur in South American speleothems, their host carbonates, and their overlying soils. We show that concentration-dependent parameters in soils overlying the caves are two to three orders of magnitude higher than those in stalagmite and limestones. Despite these differences, unmixed coercivities between soil (median value of 19 mT) and stalagmites (median value 20 mT) and substantially different from those of host limestones (median 39 mT). Our results suggest that much of the magnetite in South American speleothems is pedogenic in origin, and may allow magnetic measurements to capture changing soil and vegetation dynamics in the epikarst through time.

There have been numerous calls to promote reproducible research. This growing awareness coincides with major advances in data/code sharing technologies. Yet authors, journals, institutions, and funders still need to act to advance more reproducible research. Here, we suggest to view reproducibility as a continuum that includes the 1) availability of data, models, code, and directions to use the digital artifacts, 2) replication of results, and 3) reproducibility of findings. We present a simple survey tool to assess where a peer-reviewed journal article lies on the continuum. We use the tool to assess 360 random sampled articles of the 1,989 articles published in 2017 in six well-regarded hydrology and water resources journals. 49% of sampled articles had some materials available online, but just 5.6% made available all the data, models, code, and directions. For 1.6% of articles, we generated results that replicated some or all of the published results. Assessments took 5 to 14 minutes per article to determine the availability of digital artifacts and 25 to 86 minutes to replicate results (25-75% range). The availability of data, models, code, and directions differed by journal and journal policy towards data availability. From the 360 article sample, we estimate that 0.6% to 6.8% of all articles published in the six journals in 2017 can be replicated using their published artifacts (95% confidence interval). These results suggest several practices to improve the reproducibility of published research. First, authors should provide directions to use their data, models, and code in addition to the digital artifacts. Second, on author submission, journals should use a tool like ours to assess the submission’s position on the reproducibility continuum. Third, journals should formulate policies that require authors to state the intended reproducibility of their work and place relevant information in an easy-to-find article location. Fourth, journals, institutions, and funders should highlight work whose digital artifacts, results, and findings are available, replicable, and reproducible.

Episodic volcanic eruptions are often either not considered in future climate projections, or represented in terms of a constant volcanic forcing. This conventional representation of volcanic eruptions in climate models does not account for how climate change might affect the dynamics of volcanic plumes and the stratospheric sulfate aerosol lifecycle and, ultimately, volcanic radiative forcing. The height of eruptive plumes is indeed sensitive to atmospheric conditions such as stratification and the strength of wind. In addition, climate change will affect tropopause height, the Brewer Dobson circulation and stratospheric temperatures which all govern volcanic sulfate aerosol cycle. A recent study showed that for tropical eruptions, these changes would either lead to a dampening or an amplification of volcanic forcing depending on the eruption intensity. In this study, to account for volcano-climate interactions in future climate projections, we present a new modelling approach through coupling a 1-D plume-rise model (Plumeria) with an Earth System model (UKESM). In this approach, each time a volcanic eruption of prescribed intensity (i.e., mass eruption rate) and SO2 mass occur, atmospheric conditions simulated by UKESM are passed interactively to Plumeria which then computes the corresponding height of eruptive plumes. Volcanic SO2 is then injected at the same height in UKESM stratospheric aerosol module. With this new methodology, plume heights are consistent with the climate conditions simulated by UKESM. Our study thus represents a first attempt to consider the impacts of climate change on volcanic eruptions in an Earth System model, which allows us to better evaluate the climate impacts of volcanoes under global warming.

It is recapitulated that the gravitational potential energy that is conserved along the neutral surfaces needs two terms, one from buoyancy and the other from gravity. I also show a mathematical identity for the time change of this gravitational potential energy which can be interpreted as exchange of energy amongst kinetic, internal, and gravitational potential forms. Movements along the neutral surface conserve the gravitational potential energy and it is shown that not only conversions into and out of the gravitational potential energy balance, but that each of the conversion terms is zero.

Para- and ferro-magnetic fabrics are known to provide essential clues for understanding impact cratering processes. However, research on the effects of shock waves on diamagnetic fabrics is lacking. We, therefore, conducted a hypervelocity impact experiment on a block of diamagnetic Taunus quartzite and studied the changes in diamagnetic fabrics. In the crater subsurface, the reorientation of the diamagnetic fabrics is concentrated in a zone of ~4 projectile diameters (25 mm) width directly below the point of impact. Higher reorientation in this zone indicates the concentration of damage. We argue that although the shockwaves traversed through the target with a hemi spherical wavefront, the damage was concentrated directly below the point of impact. Another important observation is that the weak shock waves have changed the diamagnetic parameters. The bulk susceptibility has increased overall, while the corrected degree of anisotropy (P’) and the shape parameter (T) have increased in the crater subsurface but have decreased at the target surface. We propose that the variable response of P’ and T could be due to the difference in incident angle subtended by the shock wave on the diamagnetic foliation at the target surface (c. 34°) and in the subsurface (c. 54°). These results, thus, show that the changes in diamagnetic fabrics can be used as a proxy for plastic deformation caused by shock waves at low peak pressures.

This study aims to give a brief overview of an ensemble of regional climate model (RCM) simulations with bias correction for daily precipitation for the Carpathian Region located in Central/Eastern Europe. Within the international initiation called the COordinated Regional Downscaling Experiment (CORDEX) EURO-CORDEX and Med-CORDEX provide RCM simulations targeting Europe as a whole or in a part at the grid resolutions of 0.44o (~50 km) and 0.11o (~12 km). The ensemble of RCMs provides a huge amount of data, which are however prone to biases compared to high resolution observations. Percentile-based bias corrections of the daily precipitation output of EURO-CORDEX and Med-CORDEX RCM ensemble at a common 0.11o × 0.11o horizontal grid resolution are performed based on the high-resolution, high-quality observational dataset: CARPATCLIM. The region covered by the CARPATCLIM dataset can be considered as the Carpathian Region for which the RCM ensemble (consisting of total six members at 0.11o resolution) of a historical period (1976-2005) and under the Representative Concentration Pathway 8.5 over two future time slices (2021-2050 and 2070-2099) are assessed. The present study focuses on precipitation climate indices over the entire Carpathian Region and two subregions representing high- and lowlands within the target region. The analyzed indices are: frequency of rainy days (RR1, days with a total rainfall of at least 1 mm), heavy precipitation days (RR10, days with a total rainfall of at least 10 mm), highest daily precipitation (RX1), maximum consecutive dry days (CDD, the duration of the longest period with < 1 mm total daily precipitation), maximum consecutive wet periods (CWD, the duration of the longest period with > 1 mm total daily precipitation). The key findings are as follows: (1) the influence of orography on seasonal precipitation change is evident throughout the analyzed periods, (2) precipitation change holds an unequivocal seasonality as most models estimate significant winter (DJF) precipitation increase (~30%), while in general drier (~20%) summers (JJA) are projected over most part of the Carpathian Region by the end of the 21st century, (3) over the subregions RR10 shows a clear signal of increase in all seasons (10-50%), except summer (~-15%), while RX1 shows increase in all seasons.

NASA’s future missions will focus on looking for evidence of life under extreme environments, such as cold arid planets (Mars) and icy moons (Eurpoa). There is particular interest in studying localized geo-chemical systems that host gradients with the potential for harboring evidence of past or present life. Such gradient-driven systems include, for example, layering of minerals of varying oxidation states in the Martian subsurface or in Earth’s seafloor sediments; chemical precipitates separating fluids of different pH or Eh such as in a hydrothermal vent; or radiation-induced oxidant production in planetary ices. A challenge is that these simulated precipitates are redox sensitive and evolve over a relatively short lifetime (1-4 hrs) necessitating viable in-situ, non-destructive analytical techniques. Promising techniques for such studies are electrochemical methods, which are particularly suited for characterizing interfaces and chem-ical gradients. Combined with recent advances in electrochemical instrument technologies, new methods have been developed toward integrating portable, electrochemical systems for ex-situ and/or in-situ chemical characterization. JPL has already made significant progress in developing these new technologies, particularly electro-chemical impedance spectroscopies (EIS) for in-situ characterization of geochemical materials (i.e., soils ice mineralogy, and brines) and even life detection sensoring. Currently, we are exploring further appli-cations of electrical spectroscopy techniques in developing an electrochemistry-based framework using planetary analog systems based on MRO/CRISM and Cassini/INMS observations in attempts to distin-guish abiotic vs biotic environments, and with active and inactive containing organics from electrical properties characterization. We will highlight some of our group’s successes and preliminary results of geochemical experimentation using various electrochemical techniques.

Interferometric Synthetic Aperture Radar (InSAR) phase unwrapping error is a major limiting factor on the InSAR-derived tectonic deformation velocity. This is particularly the case when atmospheric turbulence, large deformation gradient and strong phase noise exist. To address limitations of existing phase unwrapping error correction methods which are not supported for multi-looked InSAR data, here we present a new algorithm that integrates decorrelation phase correction, triplet phase closure (TPC) test and integer linear programming (ILP) to overcome this limit. The rationale behind is that we mitigate the phase inconsistence using decorrelation correction and then detect the phase unwrapping error magnitude using TPC. Next we borrow the ILP from Compressed Sensing that converts the phase unwrapping error correction to a sparse signal recovery problem. We demonstrated the validity of our method by using synthetic data and 5-years Sentinel-1 real data covering the Central San Andreas Fault creep section, where exists obvious tectonic deformation, strong atmospheric disturbance and decorrelated scatterers, and the inverted long-term creep model constrained by InSAR velocity after correction shows a lower uncertainty than that constrained by the uncorrected one.