We develop an algorithm to measure densely-spaced vertical offsets along a scarp-like feature, and apply it to end-glacial fault-scarps (EGFs) in Fennoscandia, a stable-continental region (SCR). We find significant variability in apparent vertical offsets, and develop an equation to estimate the uncertainty (1σ) for a given average offset and number of measurements. We calculate the slip-to-length ratios for the faults, assuming their fault-scarps were formed in a single earthquake, and find that these ratios are up to ten times higher than found in rapidly deforming regions, which have been more studied. We find potential magnitudes of the earthquakes that formed these scarps were M7-8.2. We suggest that slip-variability along ruptures could be higher than often assumed, which means paleoseismological results should have larger uncertainty, but reduces in a predictable way with increase in number of measurements, and at least 5 measurements should be taken. We also suggest that the slip-to-length ratio used to simulate earthquakes in SCRs should be 7.5±2x10^-5, in comparison with the Wells and Coppersmith value of roughly 2±0.5x10^-5.

The 2018 eruption of Kīlauea Volcano included caldera collapse at the summit of the volcano that was well recorded by a network of both permanent and temporary seismometers and infrasound microphones. Volcanic activity prior to the start of the eruption was elevated, including high lava lake levels and increased seismicity. Deflation of the summit began shortly after the eruption in the lower East Rift Zone commenced and was accompanied by a drop in the summit lava lake, which eventually disappeared from view after lowering by several hundred meters. Continued volume loss from beneath the summit eventually led to caldera collapse, which was accompanied by increases in earthquake rates and tremor amplitudes. Infrasonic tremor that originally rose from spattering at the surface of the lava lake was replaced by discrete infrasonic events arising from rockfalls and slumps. On May 16, the first of tens of collapse events occurred, beginning a cycle of increasing earthquake rates and energy release in the presence of deflation. After an initial increase in rate, seismicity rates remained constant for several hours prior to the next collapse event. Earthquakes during these events were typically part of repeating earthquake families and occurred on one of several circumferential cracks that marked active collapsing blocks. Through time, earthquake activity has mirrored the morphology of the collapse, migrating primarily north and east as caldera down drop extended in those directions. Collapse-related infrasound arrivals were initially down, suggesting downdropping of the surface, followed several seconds later by higher frequency infrasound, which we interpret to reflect the explosive or expulsion phase reaching the surface. Infrasound signals were 2-3 times more energetic below 0.5 Hz than above. Especially after May 29, when caldera collapse became much larger in surface area, infrasound signals were highly repetitive with a strong downward first motion. The collapse events were also deficient at seismic frequencies > 0.5 Hz, compared to typical tectonic earthquake sources. Despite similarities in waveforms at low frequencies (<0.1 Hz) and in infrasound, the seismic waveforms at high frequencies were not similar, reflecting either a unique source in each collapse event or a change in location.

Despite much field and laboratory research, the origin of calcification in coccolithophores remains indeterminate. While most experiments on living species are not applicable to extinct taxa, long-term morphologic changes in lineages under well constrained oceanographic conditions may help elucidate the primary forcing on coccolithophore evolution if examined in the context of fundamental requirements (e.g., nutrient availability) of the living cell. The Order Discoasterales (66–1.92 Ma) was among the most prolific (>600 species, 16 genera) with greatest abundance and diversity in warm oligotrophic waters. Their coccoliths tell a story of morphologic changes that affected also their constituent elements resulting in lightweight constructions that became increasingly cavernous as oligotrophy increased in the Paleocene ocean, leading to increase in surface/volume ratio in keeping with increase in cell size. This likely constitutes direct evidence that coccoliths were involved in regulating cell physiology, both by maintaining a sufficient surface for nutrient absorption when cell volume increases or when nutrient content in seawater decreases, and by determining sinking rates. The cavernous nature of coccoliths further suggest mixotrophic physiology. Calcification may thus have been the innovation permitting the migration of the ancestral coccolithophore from nutrient-rich coastal waters to the blue ocean.

Micron to sub-micron sized ferromagnetic inclusions in rock forming silicate minerals may give rise to particularly stable remanent magnetizations. When a population of inclusions have a preferred crystallographic or shape orientation in a rock, the recorded paleomagnetic direction and intensity may be biased by magnetic anisotropy. To better understand this effect, we investigated plagioclase grains from oceanic gabbro dredged from the Mid-Atlantic Ridge at 11-17N. The plagioclase grains contain abundant needle and lath shaped magnetite inclusions aligned along specific directions of the plagioclase lattice. Electron back scatter diffraction and anisotropy of magnetic remanence measurements are used to correlate the orientation distribution of the magnetite inclusions in the host plagioclase that contains multiple twin types (Manebach, Carlsbad, Albite and Pericline) with the bulk magnetic anisotropy of the inclusion-host assembly. In unaltered plagioclase, the anisotropy ellipsoid of magnetic remanence has oblate shapes that parallels the plagioclase (010) plane. It is suggested that recrystallization of magnetite inclusions from hydrothermal alteration shifts the relative abundance of the inclusions pertaining to the different orientation classes. We show that the maximum axis of the anisotropy ellipsoid of magnetic remanence parallels the plagioclase [001] direction, which in turn controls the recorded remanent magnetization direction. Our results are relevant for paleointensity and paleodirection determinations and for the interpretation of magnetic fabrics.

In September 2019, a minor but strong sudden stratospheric warming (SSW) event occurred in the Southern Hemisphere. We examine the dynamical characteristics of the gravity waves (GWs) and Rossby waves (RWs), especially quasi-6-day waves (Q6DWs), during this event based on Program of the Antarctic Syowa (PANSY) radar observations and high-resolution Japanese Atmospheric General circulation model for Upper Atmosphere Research (JAGUAR) simulations. For the GWs, strongly negative vertical fluxes of zonal momentum in the stratosphere were observed around the edge of the polar vortex during the SSW event. In the mesosphere, strongly positive momentum fluxes were observed in the Eastern Hemisphere, where westward winds were dominant associated with the SSW event. For the RWs, two types of Q6DWs appeared during the SSW event: one with eastward phase velocity (Q6DW-E) and one with westward phase velocity (Q6DW-W). These waves had a baroclinic structure in vertical, differing from normal-mode 5-day Rossby waves. It is shown that Q6DW-E, which was observed prior to the SSW onset, was an unstable wave owing to the baroclinic instability in the high-latitude mesosphere. Conversely, Q6DW-W was observed after the onset and had characteristics of an upward-propagating internal RW. It is considered to be generated by barotropic/baroclinic instability in the upper stratosphere. This instability was likely caused by forcings resulting from the in situ generated Q6DW-E and RWs originating from the mid- and high-latitude troposphere, as well as the GW forcings, which were positive in the mesosphere and negative in the stratosphere associated with the SSW event.

Increasing agricultural demand for freshwater in the face of a changing climate requires improved irrigation management to maximize resource efficiency. Soil water deficits can significantly reduce plant growth and development, directly impacting crop quantity and quality. Dendrometers are a plant-based tool that have shown potential to improve irrigation management in high-value woody perennial crops (e.g. trees and vines). A dendrometer continuously measures small fluctuations in stem diameter; this has been directly correlated to water stress. While plant-based measures of water deficits are the best indication of water stress, current dendrometers are imprecise due to mechanical hysteresis and thermal expansion. The high-precision dendrometer created at the OPEnS Lab alleviates these key failure points using zero-thermal expansion carbon fiber, zero friction via a spring tensioning approach, and a linear magnetic encoder. The device achieves 0.5-micron resolution, and thermal fluctuations are less than 1 micron over diurnal swings of 25°C. The cost of the device varies with build quantity; parts are $200 - $450 each and assembly requires 6 to 12 hours per system. Dendrometers are currently being deployed with telemetry based on LoRa, which is under evaluation. Without solar charging and telemetry, the battery is sufficient for over two years of operation. Mass deployment of these automated dendrometers has the potential to provide a continuous record of water stress driven changes in stems, providing valuable decision support for irrigation management.

The Heliophysics Application Programmer’s Interface (HAPI) is a standard mechanism for accessing time series data. Because of its adoption at multiple Heliophysics (HP) and Space Weather (SW) data centers, it is now a useful way to reach many different resources within the community. It is also a COSPAR standard. The use of HAPI so far has been as a standard layer on top of a traditional mission or instrument archive, where HAPI lives alongside an existing, custom web-based computer interface. We will give highlights of recent additions to the specification which is now at version 3.0, with 3.1 around the corner. We also will present explorations into two new ways in which HAPI can be utilized. 1) HAPI as a way to access output from model runs, which can generate large volumes of data at various time cadences and spatial distributions. 2) HAPI as an interface over cloud-based data resources. In the cloud, HAPI can connect large volumes of data to scientist-friendly front-end analysis capabilities, such as a JupyterHub or potentially a Pangeo-like environment. The evolution of HAPI and its uses is expected to keep enhancing interoperability among Heliophysics and Space Weather resources.

The Baltic Sea is a shallow, stratified, brackish water sea with several subbasins. In this work, we analyzed CTD casts from HELCOM monitoring data of the Baltic Sea, data from FMI's glider missions in 2016 and 2017 and profiles from FMI's Argo floats. We used clustering and machine learning algorithms developed for time series analysis to classify vertical profiles. We endeavored to classify profiles into classes with similar shapes. Then, we defined whether it was possible to define the depth of the upper mixed layer and possible halocline depth in each of these classes. Our results show that time series classification algorithm can cluster vertical profiles of CTD temperature and salinity and classify them according to sea area and season.

In many streams, discharge is often anticipated to be the residual between the inputs to watersheds (precipitation, groundwater inputs), outputs (evapotranspiration, groundwater outflow), and changes to water storage. This basic water balance approach fails to capture many of the aspects that drive streamflow, namely the sequence between fluxes and storages that must occur prior to streamflow generation. This is further complicated by the limitations of ever estimating total water storage, namely due to subsurface heterogeneity, poorly defined boundary conditions, and difficulties of associated with measuring certain fluxes (GW in and outflows) and storage reservoirs (soil water). From a hillslope perspective, the relationship between watershed storage and discharge is not so linear. There are sequences of storage thresholds which must be breached prior to other storage units being activated. As storage units fill (i.e., fill and spill storage + surficial soil storage) they activate other hydrologic processes (percolation) that spurs the filling of other storage components (groundwater storage). These thresholds are complex, time varying, with non-linear and hysteretic activations, and result in much more complex transit times than a simple water balance would suggest. We use records from ~13 years of intensive hydrologic monitoring at 3 adjacent low-relief, groundwater driven headwater streams that drain the Savannah River Site in the Upper Atlantic Coastal of Plain to explore the sequential storage thresholds that govern stream discharge at the site. Coupled with a spatially discrete water table model and remotely sensed estimates of surface water storage, we provide a more robust estimate of total water storage and help elucidate how much water is going unmeasured via deep groundwater flow pathways

The regional to global responses of the Standardized Precipitation-Evapotranspiration Index, Palmer Drought Severity Index, and Aridity Index to future global warming tend to be much more pervasively and strongly negative than the responses of comprehensive land model runoff and bulk soil-moisture outputs to the same warming. We term these systematic differences “index-impact gaps.” Some studies have assumed that these gaps arise because land-surface models include water-saving CO2-plant effects that the dryness indices do not, but recently published work makes clear that the gaps largely persist even in model simulations in which these effects are switched off. Thus, the main reason(s) for the index-impact gaps are still unclear, making it difficult to trust either the common dryness indices or the comprehensive land-surface models under climate change. In this study, we are investigating several postulated causes of these index-impact gaps using sensitivity experiments with the state-of-the-art Community Land Model version 5.0. In addition to CO2-plant effects, we are testing the roles of stomatal closure driven by high vapor-pressure deficits, short-term runoff enhancement due to sharper concentration of rain in time with warming, and annual-scale runoff enhancement due to changes in the seasonality of precipitation and/or infiltration with warming. If CLM5.0’s runoff and bulk soil-moisture responses start to agree with the dryness-index responses much more after eliminating these pathways, it will imply that the dryness indices are in fact a useful theoretical baseline for understanding the comprehensive model responses. However, if the index-impact gaps still remain wide, it will imply either that dryness-index responses are fundamentally different from runoff and soil-moisture responses to climate change, or else that CLM5.0’s evapotranspiration is not sensitive enough to rising temperatures. Further experiments will be required in that case.

We introduce a computer program for time series tuning and analysis. The well known in paleo-climatic community program AnalySeries after Paillard et al. is restricted to the Mac OS (32-bit) and, according to Apple plans to move entirely onto the 64-bit system, it will not be supported in the future upgrades of Macintosh OS. QAnalySeries is an attempt to re-implement the major functionality of AnalySeries thus providing the community with a useful tool. QAnalySeries is written using Qt SDK as a free software and can be run on Macintosh, Windows and Linux systems. Paillard, D., L. Labeyrie and P. Yiou (1996), Macintosh program performs time-series analysis, Eos Trans. AGU, 77: 379.

We analyze changes in vegetation greenness across the coastal, Andean, and Amazonian regions of continental Ecuador, 1982-2010. Using Normalized Difference Vegetation Index (NDVI) anomalies derived from the Advanced Very High-Resolution Radiometer (AVHRR) on monthly and annual bases, we identify: i) long-term changes in annual NDVI, ii) seasonal shifts in greenness patterns, and iii) spatial patterns of change in vegetation greenness. Results indicate overall significant greening, or NDVI increase, after the mid-1990s, with distinct seasonal and regional variations. In the Amazon changes occur between September and February, resulting in a prolonged growing season during the later period. Significant increases are witnessed in coastal regions between February and May, but with no change in growing season. Fluctuations in NDVI in the Andes mimic the coast in the western slopes and the Amazon in the eastern slopes but exclude major changes in NDVI. The research investigates the possible effects of precipitation and CO2, and contributes to the understanding of tropical vegetation change in a rapidly changing environment.

The Vector Electric Field Instrument (VEFI) aboard the CNOFS satellite recorded over 20 thousand 12-s-duration, 3-axis continuous VLF waveforms syncronously on 3 crossed antenna booms. Tbis provides an important data archive on Poynting flux and wave intensity, of relevance to wave-particle interactions in tbe low-latitude inner plasmasphere. We will provide a summary of all the observations, not limited to discrete whistlers associable with known lightning events (our focus in previous reports).

Over-pumping and extended drought events have raised awareness on groundwater resources management within the Mediterranean Basin. As groundwater often has an important role in sustaining certain types of aquatic, terrestrial and coastal ecosystems, water policy makers should pay special concern to maintain groundwater contribution to the environmental flow. To this aim, the present study focuses on the assessment of a newly introduced groundwater management tool, the Groundwater Footprint (GWF) (Gleeson et al., 2012). GWF represents a water balance between aquifer inflows and outflows, focusing on environmental flow requirements and expresses the area required to sustain groundwater use and groundwater dependent ecosystem services. GWF is applied to a pilot aquifer in the Mediterranean Basin, crossed by an intermittent river. Total abstraction, natural and artificial recharge, groundwater contribution to environmental stream flow are the critical parameters related to GWF estimation. In order to estimate groundwater contribution to the environmental stream flow, the assumption that groundwater contributes to the environmental flow to the same percentage as baseflow contributes to the natural flow has been made. However, the main constraint met in GWF estimation has been the estimation of the environmental flow in non-perennial river, as the quantification of the environmental flow requirements has been mainly studied for perennial rivers. For this reason, the available to the literature studies referring to environmental flow requirements have been assessed and the most appropriate method for the specific pilot area has been applied. The ratio GWF to the actual area of the aquifer (A) can be used to assess groundwater management, as GWF/A>1 indicates unsustainable groundwater consumption. Consequently, GWF/A may consist a comprehensible to the general public groundwater stress indicator and can be used to raise awareness.

Differential Interferometric Synthetic Aperture Radar (DInSAR) based mapping of surface deformation has proven valuable in a variety of geoscience applications. Conventional approaches to DInSAR analysis require significant expertise and are not suited to addressing the opportunities and challenges presented by the large multi-temporal SAR datasets generated by future radar constellations. As a result, the Canada Centre for Mapping and Earth Observation (CCMEO) developed, in support of Natural Resources Canada and Government of Canada priorities, a system for automatic generation of standard and advanced deformation products based on DInSAR technology from RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) data. Existing RADARSAT-2 processing algorithms were adapted to RCM specifications and novel advanced processing algorithms were developed to address the large data sets resulting from the constellation’s four-day rapid revisit cycle. This permitted expanding the DInSAR functionality across a wide-range of spatial and temporal scales. The system architecture is scalable and can be expanded to serve a large number of clients; it can simultaneously address multiple application areas including natural and anthropogenic hazards, natural resource development, permafrost and glacier monitoring, coastal and environmental change and wetlands mapping.

The gap between governmental policy and actions taken by local officials often exists and this gap could be even more severe when it is climate adaptation policy. On the other hand, most of existing studies tend to pay more attention to the structure and the performance of the model rather than the practical operation procedure. To minimize the gap and to evaluate the effectiveness of the adaptation policy, a cross-scale and cross-sector adaptation assessment model, Agriculture and Hydrology assessment model (AgriHydro), is proposed in this study. AgriHydro is established physically to embed top down policies and bottom up local actions and combine with the standard assessment framework, Climate Adaptation 6-Steps and Climate Risk Template, to support decision-making. For sub-models of the AgriHydro, the Aquacrop crop model and the system dynamic water distribution model were calibrated and integrated to form the feedback mechanism. The weather generator (WthGen) modular including climate change scenarios is also established and coupled into the AgriHydro to form a fully functional adaptation assessment tool. An actual application for analyzing the adaptation policy for water supply and crop yield in Taoyuan City of Taiwan is implemented due to the diversity and the complexity of Taoyuan City in land use and water system. The results reflect the possible trade-off of future risks between water resource and agriculture fields under different climate and social scenarios. Moreover, this study shows that the proposed model can provide the linkage to the standard assessment framework, which allows a consist understanding among users on risk and model output. This enables AgriHydro to become a practical and operational tool for decision making and ready for further application.

Radio science experiments for planetary geodesy or tests or relativistic gravity involve precise measurements of the spacecraft range rate enabled by two-way microwave links. Since the uncertainty on the estimated parameters depend almost linearly on the noise in the radio link, finding ways to reduce disturbances is essential for best scientific results. Tropospheric and antenna mechanical noises, among the leading noise sources in two-way Ka-band radio links, could be reduced using a suitable combination of Doppler data collected at the two-way antenna and at an additional, smaller and stiffer, three-way antenna [1]. The Time-Delay Noise Cancellation technique (TDMC) can provide significant reduction of the measurement noise if the listen-only antenna is located in a site with particularly favorable tropospheric conditions. This noise-reducing technique has only been tested by artificially producing a large mechanical noise event at the two-way antenna and using a similar three-way antenna to cancel the disturbance. We report on a practical demonstration of the capabilities of the TDMC technique applied to Doppler data from Cassini spanning 2004 through the last Titan gravity flyby in 2016. The tracking configuration in those passes was not tailored for the use of the TDMC, therefore the technique proves to be effective only with favorable noise conditions. Nonetheless, for those passes where tropospheric or antenna mechanical noises were relevant, we find substantial noise reduction. For example, Doppler data from the Titan-122 gravity flyby processed with the TDMC show about a factor-of-three noise reduction (at 60-s integration time) with respect to the two-way link. These results suggest that the choice of the three-way antenna and the scheduling of the tracking passes are crucial parameters that should be considered to fully exploit the improvement in accuracy provided by the TDMC technique. [1] Armstrong, J. W. et al., Radio Science 43 RS3010 (2008)

The use of geophysical methods to characterize subsurface properties has significantly grown in the last decade. Although geophysics can bring relevant spatial and temporal information on subsurface processes, the quantitative interpretation and integration in models remain difficult. Indeed, standard deterministic solutions suffer from (excessive) smoothing and spatially variable resolution, whereas joint or coupled inversions remain difficult to apply in complex cases. Hermans et al. (2016) proved using cross-borehole ERT that physical properties distribution could be directly retrieved from data using Bayesian Evidential Learning (BEL). BEL uses a series of prior models to derive a direct relationship between data and forecast in a reduced dimension space. This can be challenging when the prediction becomes more complex with higher dimensions. In this contribution, we extend the work of Hermans et al. (2016) to a full 4D experiment (3D + time). We demonstrate that the shape and amplitude of the temperature plume can be retrieved, with uncertainty quantification, during a push-pull experiment using surface ERT. We analyze the robustness of the solution using a synthetic benchmark. The results indicate that the median of the posterior is very close to the true temperature distribution. The relative error increases at the edge of the temperature plume where the change of temperature is limited. This is related to the limited resolution of geophysics and the process of dimension reduction. We also investigate how discrete cosine transform can improve the dimension reduction process without altering the final prediction. Finally, we show that BEL is able to retrieve the spatio-temporal variability of the plume, while the smoothness constraint inversion fails to accurately image the corresponding contrast, largely underestimating the amplitude of the temperature change. BEL is therefore a well-suited framework for the interpretation of 4D geophysical data avoiding the drawbacks of standard deterministic solutions. Hermans, T., Oware, E., & Caers, J. (2016). Direct prediction of spatially and temporally varying physical properties from time-lapse electrical resistance data. Water Resources Research, 52, 7262-7283.