Drought has severe impacts on the structure and functionality of terrestrial and riverine ecosystems. The mechanism and duration of drought recovery are critical subjects that can have crucial ramifications for ecology, crop yield, carbon uptake, and ecosystem services, and it has not been thoroughly investigated. This study assesses drought recovery of terrestrial and riverine ecosystems for agricultural and hydrological droughts, respectively. Soil moisture simulations from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) are employed to characterize agricultural drought, and streamflow data from the United States Geological Survey (USGS) are utilized for assessing hydrological droughts. Drought recovery for riverine ecosystems is studied considering both quantity and quality of streamflow. Water temperature, dissolved oxygen, and turbidity are the water quality variables considered in this study. Riverine drought recovery is assessed using a multi-stage framework that is applied to 400 streamflow stations across the CONUS for the study period of 1950-2016. On the other hand, terrestrial drought recovery is investigated utilizing ecosystem Gross Primary Productivity (GPP), a metric of photosynthetic activity, for the regions impacted by agricultural drought. GPP data is acquired from the Moderate resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra satellite at 1km spatial resolution and 8-day temporal resolution across the CONUS during 2000 to 2015. The drought affected regions are assumed to be recovered when the post-drought GPP reverts to its regional average value. Results show that in general, riverine drought recovery takes about two months when considering water quality variables, whereas terrestrial drought recovery duration varies between 1 to 4 months depending on drought severity. Additionally, results indicate that drought recovery duration is positively correlated with drought severity.

Climate change is forcing the ski industry to modify snow-making strategies and facility operations. Over-summer snow storage is an adaptation successfully employed by high-elevation and/or high-latitude ski centers in Europe, Canada, and Asia. The process involves stockpiling winter snow and storing it beneath insulation (e.g., wood chips) through summer. Current methods are empirically-based with few studies quantifying snowmelt through summer or comparing insulation strategies. In this project, we evaluate the feasibility of over-summer snow storage in Vermont, northeastern North America. Soil temperatures were recorded since June 2017 with sensors 5, 20, 50 cm and 1 m below the ground surface. In March 2018, two, 200 m3 snow piles were covered in plastic and wood chips; we monitored their volume bi-weekly through the melt season using terrestrial LiDAR. We also measured air to snow temperature gradients under various insulation materials: rigid foam, open cell foam, and wet wood chips, all with and without reflective coverings. Away from snow piles, ground temperatures at 1 m depth were ~7C in spring 2017, rising to 12C in summer, and falling to just above 0C in winter. As depth decreased, ground temperature became more responsive to air temperature; ground temperature lagged air temperature at all depths. Below summer snow piles, soil temperature at all depths remained near freezing through the summer as cold meltwater percolated into the ground. Snow was lost from each pile at a similar rate (~1.3 m3 day-1) from late March to mid-June; melt then accelerated slightly in response to increased air temperature, solar radiation, and humidity. Large crevasses formed in both piles along the edge of the plastic sheeting which exposed snow to direct sunlight. Temperature was at or above 10C over the snow below both rigid foam and open-cell foam with a strong diurnal variation, regardless of the addition of a reflective blanket. Beneath wet wood chips covered with a reflective blanket, temperature remained close to freezing even though air temperature was > 30C. There was no diurnal variation, indicating that wood chips effectively buffered thermal swings. It appears that a reflective surface over >20cm of wet wood chips is most effective at minimizing summer snow melt in humid, northeastern North America.

Recent developments in space-based surveying methods of Earth’s topography, including the differential synthetic aperture radar interferometry (DInSAR), increased the availability of options for monitoring of land subsidence. However, DInSAR methods require expert knowledge, specialized software, and are time-consuming. Here, we demonstrate that a land subsidence signal in the difference of freely available global digital elevation models (DEMs), e.g., SRTM and TanDEM-X, is identifiable using a simple statistical method. This finding opens up a venue to develop a dedicated computer application to identify land subsidence or uplift of the order > 20 mm yr. Such an application would allow for the monitoring of the impacts of underground mining, earthquakes, landslides, volcanic activities, and similar effects on the Earth’s topography. This software will provide a useful and cost-effective approach to scan the global DEMs for the benefit of many land planning and management agencies around the world.

Marine carbon cycle processes are important for taking up atmospheric CO2 thereby reducing climate change. Biological production is an important pathway of carbon from the surface to the deep ocean where it is stored for thousands of years. Climate change can interact with marine ecosystems via changes in the ocean stratification and ocean circulation. In this study we use the Community Earth System Model version 2 (CESM2) results to assess the effect of a changing climate on biological production and plankton composition in the high latitude North Atlantic Ocean. We find a shift in plankton type dominance from diatoms to small phytoplankton which reduces net primary and export productivity. Using a conceptual carbon-cycle model forced with the CESM2 results, we give a rough estimate of a positive plankton composition-atmospheric CO2 feedback of approximately 60 GtCO2/K warming in the North Atlantic which affects the 1.5K and 2.0K warming safe carbon budgets.

We used a spatially distributed and physically based energy and mass balance model to derive the Østrem curve, that is the supraglacial debris-related relative melt alteration versus the debris thickness, for the Djankuat Glacier, Caucasus, Russian Federation. The model is driven by meteorological input data from two on-glacier automatic weather stations and ERA-5 reanalysis data. A direct pixel-by-pixel comparison of the melt rates obtained from both a clean ice and debris-covered ice mass balance model results in the quantification of debris-related relative melt-modification ratios, capturing the degree of melt enhancement or suppression as a function of the debris thickness. In doing so, our model is the first attempt to derive the glacier-specific Østrem curve through spatially distributed energy and mass balance modelling. The main results show that a maximum relative melt enhancement occurs on the Djankuat Glacier for thin and patchy debris with a thickness of 3 cm. However, insulating effects suppress sub-debris melt under debris layers thicker than a critical debris thickness of 9 cm. Sensitivity experiments show that especially within-debris properties, such as the thermal conductivity, the vertical porosity gradient and the moisture content of the debris pack, highly impact the magnitude of the sub-debris melt rates. The Østrem curve is also shaped by the local climate. Our results highlight the need to account for site-specific debris properties and their variation with depth, as well as for the effects of changing local climatic conditions in order to accurately assess (partly) debris-covered glacier behavior and its climate change response.

The geomechanical characterization of volcanic material has important implications 16 for geothermal and mineral exploration, engineering design, geophysical signals of volcano 17 unrest, and models of instability and mass flows. Chemical weathering and hydrothermal 18 systems can alter the host rock, leading to changes in mechanical behavior and failure mode. 19 Here, we compare the physical and mechanical properties of lava, autoclastic breccia, and 20 pyroclastic (scoria) samples from Mt. Ruapehu volcano in New Zealand to mineralogical 21 composition determined via infrared spectroscopy and scanning electron microscopy (SEM) with 22 energy-dispersive X-ray spectroscopy (EDS). Laboratory-based spectroscopy shows that the 23 samples contain absorption features indicative of Al-rich hydrous phyllosilicates, Fe-and Mg-24 rich varieties, and sulfates attributed to surface weathering, supergene, and steam-heated 25 alteration. We find that porosity and primary lithology (i.e. sample origin) is the predominant 26 control on physical and mechanical properties, followed by the pervasiveness of 27 weathering/alteration, and then mineralogical composition. Several properties, such as porosity, 28 uniaxial compressive strength, P-wave seismic velocity, density, and Young’s modulus, show 29 strong linear and exponential correlations to other properties, indicating the potential for transfer 30 functions between these properties. Samples near the active hydrothermal system with high 31 intensity hydrothermal alteration do not follow typical physical and mechanical property trends 32 due to high clay content, low permeability, and low strength. The presence of these rocks within 33 the edifice at Mt. Ruapehu implies local barriers to fluid flow and subsequent pore pressure 34 variation, and producing anomalously shallow brittle-ductile transition zones. Additionally, 35 material in the upper conduit area of Mt. Ruapehu could be over three times weaker than typical 36 porosity-strength trends observed in surface rocks, increasing the likelihood of structural 37 collapse. Trends in the pervasiveness of weathering with physical and mechanical properties 38 suggest that it may be possible to extrapolate these properties from imaging spectroscopy, which 39 could be used to create spatially distributed geotechnical maps in volcanic environments. 40 41 Keywords: uniaxial compressive strength, permeability, porosity, triaxial compressive strength, 42 intact rock mi, andesite, failure mode, hydrothermal alteration, weathering, argillic alteration 43 44 45 46 Confidential manuscript submitted to Engineering Geology

The canonical picture of the magnetotail of unmagnetized planets consists of draped interplanetary magnetic fields (IMF) forming opposite-directed lobes, separated by the current sheet. \citet{DiBraccio2018twisted} showed that Mars’ magnetotail has a twist departing from this picture. Magnetohydrodynamic (MHD) results suggest that open field lines connected to the planet that populate portions of the tail cause the apparent twist. To validate this interpretation, we compare the tail topology determined from MHD simulations to that inferred from data collected by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft, in particular how each topology responds to the upstream IMF orientation. The occurrence rates for open topology from both data and MHD varies with IMF polarities in a similar fashion as the tail twisting. This suggests that Mars’ crustal fields have a global effect on the magnetosphere configuration, supporting the picture of a “hybrid” magnetotail that is partly induced/draped and partly intrinsic/planetary in origin.

Radiation management (RM) has been proposed as a conceivable climate engineering (CE) intervention to mitigate global warming. In this study, we use a coupled climate model (MPI-ESM) with a very idealized setup to investigate the efficacy and risks of CE at a local scale in space and time (regional radiation management, RRM) assuming that cloud modification is technically possible. RM is implemented in the climate model by the brightening of low-level clouds (solar radiation management, SRM) and thinning of cirrus (terrestrial radiation management, TRM). The region chosen is North America, and we simulate a period of 30 years. The implemented sustained RM resulted in a net local radiative forcing of -9.8 Wm and a local cooling of -0.8 K. Surface temperature (SAT) extremes (90 and 10 percentile) show negative anomalies in the target region. However, substantial climate impacts are also simulated outside the target area, with warming in the Arctic and pronounced precipitation change in the eastern Pacific. As a variant of RRM, a targeted intervention to suppress heat waves (HW) is investigated in further simulations by implementing intermittent cloud modification locally, prior to the simulated HW situations. The intermittent RRM results in most cases in a successful reduction of temperatures locally, with substantially smaller impacts outside the target area, compared to the sustained RRM.

Although there are numerous modeling tools available for managing water resources, they tend to focus on relatively small watersheds (<25,000 km2) and evidence is scarce regarding their applications to large watershed management and planning. The use of hydrological modeling tools in decision making is particularly challenging in large tropical countries such as Brazil. Here we tailored and customized SWAT (Soil and Water Assessment Tool) calibration, validation and sensitivity analysis for large Brazilian watersheds (>25,000 km2). Our results show that customized SWAT calibrations successfully simulated flow behaviors across the Rio das Velhas basin, which contains heterogeneous landforms and land uses. The multisite calibration method was adopted because of the large basin area and the availability of flow monitoring stations. As a result of the multi-site calibration, specific regionalized parameters were obtained for each group of sub-basins. Our results showed a good adjustment of the model. NS (Nash & Sutcliffe coefficient) values were 0.73 - 0.97 (calibration) and 0.51 - 0.98 (validation). PBIAS (% bias) was 11.3 to 19.4 (calibration) and -18.6 to 24.6 (validation) and R² values were >0.6 in all sub-basins. We conclude that hydrological models coupled with GIS facilitates simulating complex hydrological processes and can improve decision making by Brazilian water resource managers.

Explosive volcanic eruptions radiate seismic waves as a consequence of pressure and shear traction changes within the conduit/chamber system. Kinematic source inversions utilize these waves to determine equivalent seismic force and moment tensor sources, but relation to eruptive processes is often ambiguous and nonunique. In this work, we provide an alternative, forward modeling approach to calculate moment tensor and force equivalents of a model of eruptive conduit flow and chamber depressurization. We explain the equivalence of two seismic force descriptions, the first in terms of traction changes on the conduit/chamber walls, and the second in terms of changes in magma momentum, weight, and momentum transfer to the atmosphere. Eruption onset is marked by a downward seismic force, associated with loss of restraining shear tractions from fragmentation. This is followed by a much larger upward seismic force from upward drag of ascending magma and reduction of magma weight remaining in the conduit/chamber system. The static force is upward, arising from weight reduction. We calculate synthetic seismograms to examine the expression of eruptive processes at different receiver distances. Filtering these synthetics to the frequency band typically resolved by broadband seismometers produces waveforms similar to very long period (VLP) seismic events observed in strombolian and vulcanian eruptions. However, filtering heavily distorts waveforms, accentuating processes in early, unsteady parts of eruptions and eliminating information about longer time scale depressurization and weight changes that dominate unfiltered seismograms. The workflow we have introduced can be utilized to directly and quantitatively connect eruption models with seismic observations.

Dissolved iron (dFe) plays an important role in regulating marine biological productivity. In high nutrient, low chlorophyll (HNLC) regions (> 33% of the global ocean) iron is the primary growth limiting nutrient, and elsewhere can regulate nitrogen fixation and growth by diazotrophs. Overall, dFe supply potentially impacts half of global ocean productivity. The link between iron availability and carbon export is strongly dependent on the phytoplankton iron quotas, or cellular Fe:C ratios. This ratio can vary by more than an order of magnitude in the open ocean and is positively correlated with ambient dFe concentration in sparse field observations. The Community Earth System Model (CESM) ocean component has been modified to simulate dynamic, group-specific, phytoplankton iron quotas (Fe:C) that vary as a function of ambient iron concentration. The simulated Fe:C ratios match the spatial trends in the observations and improve the correlation with global-scale, observed nutrient distributions. Acclimation of phytoplankton Fe:C ratios dampens the biogeochemical response to varying atmospheric deposition fluxes of soluble iron, compared to a model with fixed Fe:C. However, varying atmospheric soluble iron supply still has first order impacts on global carbon and nitrogen fluxes, and on the spatial patterns of nutrient limitation; both of which are strongly sensitive to changes in pyrogenic sources of iron. Accounting for dynamic, phytoplankton iron quotas is critical for capturing the ocean biogeochemical responses to varying atmospheric soluble iron inputs, including expected changes in both the mineral dust and pyrogenic sources with climate warming and anthropogenic activity.

A set of LSE observations from field experiments were conducted on 16-18 Oct 2013 along a south/north desert road in the Taklimakan Desert (TD), China. The observed LSEs (EOBS) are thus used in this study as the reference to evaluate the quality of Combined ASTER MODIS Emissivity over Land (CAMEL). Analysis of these data shows four main results. Firstly, the CAMEL appears to capture the spatial variations of LSE from the oasis to the hinterland of TD well, especially in the quartz reststrahlen band 8.1 mm, 8.6 mm and 9.1 mm. From site 1 at the south edge of the TD to site 10 at the north edge, the EOBS and the corresponding CAMEL in the quartz reststrahlen band firstly decrease and reach their minimum around sites 4-6 at the hinterland of the TD. Then the LSE increases gradually and finally gets their maximum at site 10 with clay ground surface, which is higher at the edges of the desert and lower in the center. Second, the CAMEL at 8.3 mm has a Zonal distribution characteristic of northeast-southwest strike. Third, the unrealistic variation of original EOBS can be filtered out with useful signals remaining by the first 6 principal components from PCA upon the laboratory measured hyperspectral emissivity spectra (ELAB). Fourth, the CAMEL correlates well with the measured LSE at the ten observation sites, with the EOBS slightly smaller than CAMEL in general.

A document by Allison Kelley. Click on the document to view its contents.

Spatial econometric models estimated on the big geo-located point data have at least two problems: limited computational capabilities and inefficient forecasting for the new out-of-sample geo-points. This is because of spatial weights matrix W defined for in-sample observations only and the computational complexity. Machine learning models suffer the same when using kriging for predictions; thus this problem still remains unsolved. The paper presents a novel methodology for estimating spatial models on big data and predicting in new locations. The approach uses bootstrap and tessellation to calibrate both model and space. The best bootstrapped model is selected with the PAM (Partitioning Around Medoids) algorithm by classifying the regression coefficients jointly in a non-independent manner. Voronoi polygons for the geo-points used in the best model allow for a representative space division. New out-of-sample points are assigned to tessellation tiles and linked to the spatial weights matrix as a replacement for an original point what makes feasible usage of calibrated spatial models as a forecasting tool for new locations. There is no trade-off between forecast quality and computational efficiency in this approach. An empirical example illustrates a model for business locations and firms’ profitability.

This is a laboratory zonal-jet study using a rotating water tank. The bottom topography has a tent-shaped radial cross section designed to generate two critical latitudes, i.e. two positions where βe, the radial gradient of the potential vorticity (PV), changes sign. This configuration is motivated by observations indicating Jupiter and Saturn have not only multiple zonal jets, but multiple stable critical latitudes. It is known that “supersonic” critical latitudes (with respect to Rossby waves) are stable, whereas “subsonic” critical latitudes are posited to be unstable. Because Rossby waves are uni-directional, “supersonic” critical latitudes come in two varieties: Rossby Mach number MR > 1 and MR < 0, where the latter holds when the waves are directed downstream. Experiments focus on: i) how do zonal jets emerge from localized forcing in a system with alternating PV gradients? and ii) what differences are there between the evolution of various types of critical latitudes? The water is forced by mass injection along one radius. Laboratory altimetry provides accurate, unobtrusive records of the circulations that reveal the emergence of counter-propagating β-plumes (Rossby-wave envelopes), which expand into tank-encircling zonal jets. The tank’s negative βe annulus is characterized by MR ~ 1, which is the condition surmised for Jupiter and Saturn. The weaker critical latitude (in terms of jumps in the PV-gradient) adjusts its position by ~4% of the tank radius and maintains MR ~ 1. In contrast, the stronger one vacillates while maintaining |MR| << 1, and may be relevant to steep oceanic seamounts.

Preferential flow processes are controlled by subsurface structures with the hierarchical organization across scales, but there is a lack of multiscale model validation using the field data. In this study, using a comprehensive dataset collected in the forested Shale Hills catchment, we tested and validated preferential flow occurrence by 2-dimension HYDRUS-2D at the hillslope scale, and in comparison, with 1-dimension HYDRUS-1D at the pedon scale and 3-dimension HYDRUS-3D at the catchment scale. There was good agreement between the 1D simulations and measurements of soil moisture in the soil profile, which was mainly affected by the vertical change in porosity/permeability with depth and precipitation characteristics; however, short-term fluctuations due to preferential flow were poorly captured. Notably, 2D and 3D simulations, accounting for preferential flow controlled by slope positions and shallow fractured bedrock, provided better results than the 1D simulations. Furthermore, a dual-porosity or anisotropic model provided more accurate predictions of soil moisture than a single-porosity or isotropic model due to a more realistic representation of local soil and fractured shale structure, which is also the premise of preferential flow (PF) occurrence. Consequently, our study reflected the central importance of multi-dimensional model approaches while highlighting the quantification of the soil structure and fractured nature of the bedrocks itself is essential to the simulation of preferential flow. The multi-dimensional modeling approaches can provide the mechanic presentation of PF pathways to the first-order stream and the necessity of the 3D simulation with detailed information to identify the dominant hydrological process.

Dynamics of polar outlet glaciers vary with ocean tides, providing a natural laboratory to understand basal processes and ice rheology. We apply Terrestrial Radar Interferometry to close the spatiotemporal gap between GNSS and satellite observations. Three-hour flowfields collected over an eight day period at Priestley Glacier, Antarctica, validate and provide the spatial context for concurrent GNSS measurements. Ice flow is fastest during falling tides and slowest during rising tides. Principal components of the timeseries prove upstream propagation of tidal signatures $>$ 10 km away from the grounding line. Hourly, cm-scale horizontal and vertical flexure patterns occur $>$6 km upstream of the grounding line. Vertical uplift upstream of the grounding line is consistent with ephemeral re-grounding during low-tide impacting grounding-zone stability. Taken together, these observations identify tidal imprints on ice-stream dynamics on new temporal and spatial scales providing constraints for models designed to isolate dominating processes in ice-stream mechanics.

The southeastern part of the Solomon Islands, a highly seismically active area in the southern Pacific, experienced two moderate earthquakes (Mw 6.3 and 6.0) on January 27th and 29th, 2020. The regional seismic network, operational since October 2018, recorded the entire foreshock-main-shock-aftershock sequence, allowing for a new 1D velocity model and relocation of events. Based on the spacial distribution of the foreshock-aftershock sequence, together with focal mechanism data from the Global CMT database, we suggest that there is a near-vertical slab tear at the southern end of the South Solomon subducting slab, abutting a zone of strike-slip faulting that links it to the Vanuatu subduction zone to form a Subduction-Transform Edge Propagator fault. Our new data also indicates that a seismic gap occurs at depths from 25 to 35 km within the southern part of the South Solomon slab.