The boreal forests of Alaska have been experiencing a changing fire regime which threatens human lives and vulnerable ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition could provide guidance for decision support. Such insight may be especially useful in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium, or large fires with 50.4 ± 5.2% accuracy in cross-validation. This was accomplished using two variables: vapor pressure deficit (VPD) and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, which accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires. The overprediction is explained by (1) suppression of those fires and (2) the fact that ignitions in more human-influenced areas occurred during periods of higher VPD on average. Overall, this type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.

Volcanic activity occurring in tropical moist atmospheres can promote deep convection and trigger volcanic thunderstorms. Intense heating at ground surface and entrainment of moist air generates positive buoyancy, rapidly transporting volcanic gases and ash particles up to the tropopause and beyond. Volcanically-induced deep convection, however, is rarely observed to last continuously for more than a day and so insights into the dynamics, microphysics and electrification processes are limited. Here we present a multidisciplinary study on an extreme case, where this phenomenon lasted for six days. We show that this unprecedented event was triggered and sustained by phreatomagmatic activity at Anak Krakatau volcano, Indonesia from 22-28 December 2018. During this period, a deep convective plume formed over the volcano and acted as a ‘volcanic freezer’ producing ~3 × 10⁹ kg of ice on average with maxima reaching ~10¹⁰ kg. Our satellite analyses reveal that the convective anvil cloud, reaching 16-18 km above sea level, was ice-rich and ash-poor. Cloud-top temperatures hovered around -80 °C and ice particles produced in the anvil were notably small (effective radius from 20-30 μm). Our modelling suggests that ice particles began to form above 5 km and experienced vigorous updrafts (>30 m/s). These findings explain the impressive number of lightning strikes (~100,000) recorded near the volcano during this time. Our results, together with the unique dataset we have compiled, provide new insights into volcanic and meteorological thunderstorms alike.

Oxygen-isotope proxies for air temperature in Greenland ice cores, with time resolutions of years to decades, document 25 periods from 120,000 to 14,000 BP when air temperatures warmed 5 to 16 oC within decades and cooled slowly, incrementally, over millennia back down into ice-age conditions. These clearly-observed Dansgaard--Oeschger events averaged 4000 years in length but were highly erratic in time of onset, intensity, and duration. They were typically associated with volcanic sulfate deposits and floods of fresh water into the North Atlantic. They appear to be caused primarily by sub-glacial basaltic eruptions in Iceland, the most intense of which lasted from 12,000 to 9500 BP, long enough to warm the oceans out of the last ice age. Similar sequences of current and warmer temperatures are observed in fine-layered sediments in the Eocene Green River Formation where erratic sequences averaged 5000 years. The most rapid and intense changes in sedimentation and fossils in the geologic time scale are contemporaneous with massive basaltic lava flows covering millions of square kilometers of continental rifts at the end of the Paleozoic, Carnian, Triassic, Pliensbachian, Albian, Mesozoic, Paleocene, Eocene, etc. Large, explosive, subduction-related volcanic eruptions form aerosols in the lower stratosphere cooling the globe 0.5 oC for a few years. Modelling shows that such short-term cooling of the whole ocean surface affects ocean temperatures for as long as a century. In this way, several major explosive eruptions per century over millennia cause slow, incremental cooling down into ice-age conditions as clearly resolved in deep ocean cores. It is very hard to explain these well-observed footprints of climate change using greenhouse gases. While Pinatubo erupted as much as 234 megatons of CO2 in 1991, concentrations at Mauna Loa slowed their rise due to cooling of the ocean surface. A set of 16 short videos, numerous papers, a book, and dozens of web pages all referenced at WhyClimateChanges.com document evidence for major effusive basaltic lava flows being the primary cause of fast global warming and sequences of major explosive volcanic eruptions being the major cause of slow incremental global cooling. Furthermore, they explain why greenhouse-warming theory is not only mistaken, it is Physically-Impossible.com.

The digital zenith camera VESTA (VErtical by STArs) was designed by the Institute of Geodesy and Geoinformatics (GGI) of the University of Latvia and completed in 2016. Since that more than 300 terrestrial vertical deflection measurements were observed in the territory of Latvia. These observations were post-processed by the GGI developed software and the accuracy was evaluated at 0.1 arc seconds. Terrestrial observations were compared with global geopotential models, e.g. GGM+ and EGM2008. The results show a better correspondence with GGM+ model by evaluating the standard deviation: 0.314 and 0.307 arcseconds for ξ and η components respectively in comparison to 0.346 and 0.358 arcseconds for ξ and η components for EGM2008 model. The comparisons of average and minimum/maximum differences are introduced in this study for better evaluation of the results. Moreover, vertical deflections have been used as additional terrestrial data in DFHRS (Digital Finite-element Height Reference Surface) software v. 4.3 in combination with GNSS/levelling data (B, L, h|H) and global geopotential model EGM2008 for gravity field and quasi-geoid improvement (www.dfhbf.de). The results of the computed quasi-geoid models using different types of data are introduced in this research, representing several solutions, as well as these solutions are compared with the national quasi-geoid model LV’14. In the middle of 2019, the new upgraded version of digital zenith camera was developed by the scientific staff and the accuracy of the measurements of improved camera was evaluated at 0.05 arcseconds, which is two times better than previous one. The improvements of new digital zenith camera are also discussed in this research. It is important to point out that according to our observations the application of digital zenith camera reveals a new capabilities for studies of mass distribution beneath earth.

Recent fast developments of satellite magnetic observations facilitate global Lithospheric Magnetic Field (LMF) modelling and their applications to subsurface tectonics. Here, the vertical component (Bz) of LMF at an altitude of 200km in Mainland China and surroundings is calculated from two global LMF models NGDC-720 and EMM2017. Next, Bz is used to invert the Curie Point Depth (CPD) by Equivalent Source Dipole (ESD) forward and Nonlinear Conjugate Gradient Method (NCGM) inversion scheme. Then, the surficial Heat Flux (HF) is derived by a simple one-dimensional steady heat conduction equation from the CPD distribution. At last, the continental seismicity is compared statistically to Bz, CPD and HF. Our essential conclusions are as follow: 1) Histograms and boxplots show that most (81.8%) earthquakes (EQs, Ms≥5.0) occurred in negative Bz areas, and more than a half (53.2%) number of EQs (corresponding to an energy percent of 94.6%) occurred inside areas with Bz between -5 and -3nT, in a period between 2004 and 2007, which is the same with the satellite data collection. When the time span is extended (most to 110 years), these phenomena maintain while weaken; 2) Most (88%) EQs occurred in areas with CPD between 10 and 30km, while only a few (7% and 5%) occurred in shallow (<10km) and deep (>30km) CPD areas, in a period between 2000 and 2010; 3) EQs seldom occurred inside cold areas (HF<50mW/m2), and are prone to occur in warm areas (HF>120mW/m2). EQs are also prone to occur along the boundaries of warm or cold areas. The mechanism of the correlations between EQs and Bz, CPD and HF maybe the lithospheric strength jumps caused by the temperature variations at boundaries between blocks with different CPDs.

Old abandoned coal working create major hazards in the form of subsidence of the coalfields. To avoid such hazards, there is need to detect these cavities prior to start of deeper seam mining. There are number of geophysical techniques available for detecting subsurface cavity. High-resolution seismic survey is one such technique which provides accurate results as compared to others. Usually, most of the seismic processing and interpretation of these cavity detection was performed based on stacked data only. To understand these signatures more precisely, in our study, an attempt has been made to image these cavities with the help of Reverse Time Migration (RTM) combined with Full Waveform Inversion (FWI). RTM mostly used for hydrocarbon exploration targets with low central frequency as source. Application of this method to shallow subsurface exploration is still in research stage. Like the same way for velocity model updating, FWI gives mostly appropriate optimization results as compare to other techniques, but it also has the limitation to application of low frequency only. In this paper we first develop a 2D realistic Water Filled Cavity (WFC) model with a work flow of RTM combined with FWI in a high-frequency Ricker source wavelet as 100 Hz. In order to provide a velocity model with high accuracy for RTM, we apply FWI to estimate the subsurface velocity by considering an initial smooth velocity model with addition of 30 % Gaussian noise. The conventional RTM fails to image the cavities and yield a large amount of low frequency back scattered noise at shallow depth during the time of cross correlation due to time/space lag. To avoid these situation, we introduced an automatic shift operator at the time of imaging condition that operates automatically both in time or space. It leads to reduce the lag and improve the results by minimizing the noises at shallow subsurface. By comparing both the results it is observed that most of the noises in the migrated section of conventional method were eliminated by the improved form of RTM with the help of FWI velocity model estimation.

Data repositories and research networks worldwide are publishing a diverse array of long-term and experimental data for meaningful reuse, repurpose, and integration. However, in synthesis research the largest time investment is still in discovering, cleaning and combining primary datasets until all are completely understood and converted to a usable format. To accelerate this process, we have developed an approach to define flexible domain specific data models and convert primary data to these models using a light-weight and distributed workflow framework. The approach is based on extensive experience in synthesis research workflows, takes into account the distributed nature of original data curation, satisfies the requirement for regular additions to the original data, and is not determined by a single synthesis research question. Furthermore, all data describing the sampling context are preserved and the harmonization may be performed by data scientists that are not specialists in each specific research domain. Our harmonization process is 3-phased. First, a Design Phase captures essential attributes, considers already existing standardization efforts, and external vocabularies that disambiguate meaning. Second, an Implementation Phase publishes the data model and best practice guides for reference, followed by conversion of relevant repository contents by data managers, and creation of software for data discovery and exploration. Third, a Maintenance Phase implements programmatic workflows that run automatically when parent data are revisioned using event notification services.In this presentation we demonstrate the harmonization process for ecological community survey data and highlight the unique challenges and lessons learned. Additionally, we demonstrate the maintenance workflow and data exploration and aggregation tools that plug in to this data model

Bayesian methods play a prominent role in parameter estimation and uncertainty quantification. In a typical application of Bayes theorem, a prior distribution over the parameters is updated through a likelihood function to obtain the posterior distribution. In the absence of any prior knowledge, a non-informative prior is chosen to express lack of any preference by assigning a uniform distribution over the possible ranges of parameters. However, the validity of uniform priors as being truly non-informative is seldom questioned. The objective of this study is to test this assumption while estimating soil saturated hydraulic conductivity using data from infiltration experiments. The concept of a non-informative prior using an information theoretic approach is pursued for this application, and the results compared to those obtained from assignment of a uniform prior. Non-informative priors obtained by the information theoretic approach are different from a uniform prior, and estimates of the posterior distribution are influenced by the choice of the prior, especially when data are limited. Examples from both hypothetical and real data are utilized to highlight the importance of selecting truly non-informative priors.

To understand the causes of climate change, it is necessary to consider the relationship between the various physical fields of our planet. The relationship between variations in atmospheric circulation and the magnetic field has received little attention.We studied changes of atmospheric circulation in the lower troposphere and geomagnetic field in the Northern Hemisphere during the 20th and beginning of the 21th centuries to determine spatial-temporal relations between variations of these fields . Integral characteristics of atmospheric circulation and geomagnetic field have been investigated in the latitudinal band 40-70o N , applying the same approach. In the indicated latitudinal range, the main centers of action of the atmosphere in the Northern Hemisphere are located (Canadian and Siberian anticyclones, North Atlantic ridge, and Icelandic and Aleutian depressions and European trough), as well as global geomagnetic anomalies (Canadian and Siberian). For the analyzed time period there is the most complete set of observational data, which ensures high reliability of the results obtained. The time diagrams were plotted for atmospheric circulation and magnetic field by their integral characteristics. Their comparison showed that the minima and maxima of the pressure field and the full vector of the geomagnetic field coincide quite well. This allows to assume that trends in changes in the geomagnetic field and atmospheric circulation, which were outlined at the beginning of this millennium, will continue in the coming decades. For prediction of global changes of the air pressure and geomagnetic fields in the future it is possible using the same methodology.

The potential of high resolution 3D datasets is being increasingly realized in an expanding number of geoscience applications. However, sharing of these datasets and interpretations requires end-users to have specialty software programs and high-end processing computers. Although user-friendly technological advances, such as uninhabited aerial vehicles (UAVs or drones) and structure-from-motion (SfM) photogrammetry, provide geoscientists with tools to easily collect, process, and analyze 3D models at multiple scales, dissemination of results to the general public commonly revert to conventional 2D formats, such as (static) 2D maps, figures, and rigid animations/videos. To facilitate dissemination of complete 3D datasets and interpretations to a wider audience, we review three modern platforms that enable visualization, sharing, and publishing of various 3D formats. We demonstrate the capabilities and limitations of each visualization platform by presenting a 3D digital outcrop model (DOM) of an extensive exposure of fluvial channel belt deposits in a 1 km2 area of Dinosaur Provincial Park (Alberta, Canada) generated from UAV-SfM photogrammetry. Each visualization platform provides intuitive controls and accessibility on standard desktop computers through web-based browsers (e.g., Sketchfab and potree) or a standalone executable file developed through videogame engines, such as Unity or Unreal Engine. Proprietary viewers allow straightforward sharing of 3D models, but limit size, detail, and resolution and also have restricted means for accommodating interpretations. Open-source platforms afford more functionality, facilitate additional 3D datasets, and can provide customized visualization experiences for end-users, but may require more advanced coding experience. Visualization platforms examined within this study offer access to large 3D datasets without the need for specialized software and advanced computing hardware. Further development and use of such platforms has potential to enhance student education and improve scientific communication through unique customizable experiences that allow for democratization of high resolution 3D datasets.

This project aims to quantify the resiliency of prairie ecosystems in the U.S. Pacific Northwest (PNW) to climate change. Prairies in this region sustain over one million beef cows, and cow­-calf production costs are expected to increase to offset warming-induced plant productivity loss. We investigated the above- and belowground effects of experimental warming in prairie ecosystems by assessing biogeochemical controls on and patterns of asymbiotic nitrogen fixation (ANF), plant species diversity, and legume cover to address a major challenge for sustainable agriculture in the region. We hypothesize that the effect of warming on prairie functional diversity increases soil asymbiotic nitrogen inputs by decreasing legume cover and soil nitrogen availability. We quantified the effects of decadal warming stress (+2.5ºC) on soil biogeochemical properties and plant species and functional diversity during fall and spring seasons in three sites along a 520­km latitudinal gradient—from central Washington to southern Oregon—representing a drought severity gradient. At each site, we collected composite soil samples from five co-­located prairie plots under control (ambient) and warming conditions. We incubated these soils using 15N-labeled dinitrogen (15N2), and quantified total soil carbon­, total and available nitrogen, and available phosphorus and iron pools to better understand the underlying mechanisms governing warming-­induced changes in ANF. We used a point intercept technique to survey plot-level plant community composition and calculate Shannon’s diversity index and percent cover of legumes (members of Fabaceae according to the Integrated Taxonomic Information System). Warming significantly decreased plant species diversity which also decreased along the drought severity gradient. Legume cover significantly increased from 3.1% in the north to 9.2% in the south. ANF response to warming varied by season and site, where rates increased with the drought severity gradient in the fall but decreased during the spring. Total soil inorganic nitrogen availability was the strongest predictor of ANF response to warming in the spring but not in the fall. Our study highlights the importance of using soil-plant-atmosphere interactions to assess prairie ecosystem resilience to climate change in the PNW.

Over–the–Horizon (OTH) communication is strongly dependent on the state of the ionosphere, which is susceptible to solar flares. Trans–ionospheric high frequency (HF) signals experience a strong attenuation following a solar flare, commonly referred to as Short–Wave Fadeout (SWF). In this study, we examine the role of dispersion relation–collision frequency formulations on the estimation of flare–driven HF absorption seen in Riometer observation using a data assimilation framework. Specifically, the framework first uses modified solar irradiance models (such as EUVAC, FISM), which incorporate high–resolution solar flux data from GOES satellite X-ray sensors, to compute the enhanced ionization produced during the flare events. The framework then uses different dispersion relation–collision frequency formulations to estimate enhanced HF absorption. Finally, the modeled HF absorption is compared against the data to determine which combination of dispersion relation–collision frequency formulation best reproduces the Riometer observations. From the modeling work, we find that the Appleton–Hartree dispersion relation in combination with Schunk–Nagy collision frequency profile produces the best agreement with Riometer data.

Topographic features are commonly interpreted to represent interactions between tectonic and climate-driven processes. However, recent work has highlighted how drainage reorganization from river capture may produce landscapes that resemble those generated by changing tectonic conditions and emphasized the importance of developing tools and metrics to identify the source of landscape transience (Yang et al., 2015; Whipple et al., 2017). While few studies have sought to estimate the rates and magnitudes of increased transient incision resulting from river capture (e.g. Prince et al., 2011, Yanites et al., 2013), the ability to quantify river capture-related incision is vital to improve our characterization of landscape responses to transience. This work tests the hypothesis that the observed incision and distribution of knickpoints in the Sutlej river network of the western Himalaya is the result of an ongoing transient response to a large-scale river capture event that occurred in the late Pleistocene. A combination of topographic analyses using digital elevation models, knickpoint propagation modeling, 1-D numerical incision modeling, and landscape evolution modeling are used in conjunction with new and existing field-derived data (e.g. cosmogenic radionuclide-derived erosion rates and (U-Th)/He and fission track thermochronology) to quantify the magnitude and timing of the transient landscape response. Redistribution of drainage area and the subsequent enhancement of incision along the Sutlej may explain the increased amounts of Himalayan detritus delivered to the Indus fan since 5 Ma (Clift and Blusztajn, 2005). Similar large-scale river capture events proposed throughout the Himalaya (e.g. Garzione et al., 2003; Van Der Beek et al., 2018), suggest that capture events may be a regional phenomenon inherent to the Himalayan orogen and imply that river capture may be an important contributor to the distribution of sediment along collisional margins.

This study determines the rates of subsidence or uplift in coastal areas of SE Texas by comparing recent GNSS measurements to the original orthometric heights of 340 previously installed National Geodetic Survey (NGS) benchmarks. Understanding subsidence rates in coastal areas of SE Texas is critical when determining its vulnerability to local sea level rise and flooding, as well as for accurate elevation control for flood risk maps. The study area includes major metropolitan and industrial areas as well as more rural areas at risk for flooding and hurricane storm surge. The resurveying methods used in this RTK GNSS study allow a large area to be covered relatively quickly with enough detail to determine subsidence rates that are averaged over several decades, and identify at-risk regions that can be monitored more closely with permanent or campaign-style measurements. Overall, vertical rates vary from -6 to -15 mm/yr subsidence in Port Arthur, Nederland, and other areas of Jefferson County, as well as in areas northwest of Beaumont, Texas. Other areas with subsidence rates between -10 and -4 mm/yr include parts of the Bolivar Peninsula in Galveston County, northeastern Chambers County, and the Mont Belvieu area just east of Houston. Current benchmark elevations were as much as -0.86 m lower than the original, illustrating the need for height modernization surveys in the area. Surprisingly, areas of uplift, with rates as great as +5 mm/yr, were found in some parts of the study area. Several of the counties in the study area are experiencing inundation and erosion from global sea level rise, with local subsidence exacerbating the problem. Many of the counties in the study area were also affected by the storm surge from Hurricane Ike and flooding from Hurricane Harvey. Understanding the current elevation in these areas, as well as the rates of change in elevation, is critical for creating updated flood plain maps and surge inundation models, as well as planning how these maps and models will likely change in the future. Understanding how rapidly the elevations are changing is also critical for planning and maintaining flood and surge protection infrastructure projects such as levees, dune restoration, marsh restoration, and raising of structures to prevent flooding well into the future.

The combination of Sr and O isotopes allow for the determination of crustal homogenization and hybridization during magma accumulation. We present oxygen isotope values of mineral separates, whole rock and in situ Sr isotope ratios of plagioclase from <1 Ma andesitic to dacitic composition lava flows from four volcanoes in the Central Andes with geographic relationship to the Altiplano Puna Magma Body (APMB): Uturuncu (1.1 Ma to 250 ka), Ollagüe (1.2 Ma to 130 ka), Aucanquilcha (1.04 Ma to 240 ka) and Lascar (49 ka to 0 ka). Sr isotope ratios were determined in situ using both laser ablation and standard cation exchange methods of plagioclase phenocryst and on whole rock powders. Oxygen isotope analyses were determined by laser fluorination of mineral separates. Mineral separate O isotope data has been re-calculated to account for mineral-melt 18O/16O-fractionation at various SiO2 contents to better constrain magma source variations and magma isotope heterogeneity with time and space. Variation in δ18OWR values for each lava suite is relatively limited (Lascar - δ18OWR =7.4-9.0‰; Aucanquilcha- δ18OWR =8.2-9.2‰; Ollagüe- δ18OWR =7.9-9.4‰) with the exception of Uturuncu which displays a large O isotopic value range (δ18OWR =8.7-11.4‰). Whole-rock 87Sr/86Sr ratios show a correlation of the lowest ratios along the arc front and generally increase towards the center of the APMB. Lascar (87Sr/86Sr= 0.7057-0.7067) and Aucanquilcha (87Sr/86Sr= 0.7058-0.7068) rocks exhibit the most homogeneous Sr isotope ratios and δ18OPL values, while Uturuncu exhibits the largest range of ratios (87Sr/86Sr= 0.7101-0.7165). Furthermore, in situ 87Sr/86Sr ratios of Uturuncu plagioclase phenocrysts exhibit more variation within a single crystal (87Sr/86Sr= 0.7098-0.7165) than the observed at all four volcanoes. Uturuncu magmas contain the highest variability, both in plagioclase mineral separates and whole rock values, and therefore must contain high 18O crustal material. This hypothesis is further supported by the textures and isotopic variation within plagioclase phenocrysts suggesting repeated crustal contamination followed by mixing occurring in the shallow crustal reservoir. Conversely, the arc front source is more homogeneous and hybridized, and arc-front magmas assimilate similar composition crustal material.

In the present-day climate, cold air outbreaks occur when marine air intrudes over high-latitude continental interiors and radiatively cools, producing an abrupt drop in surface air temperature to as low as -40 C. But during the Eocene warm climate period, 55 million years ago, the presence of frost-intolerant species even at high latitudes in the Northern Hemisphere indicates that cold air outbreaks were suppressed. In projected future climate scenarios, relatively high surface temperatures at high latitudes are predicted as part of polar amplification. The lapse rate “feedback”, corresponding to enhanced warming of the lower troposphere, was found to be a major contributor [1]. The suppression of cold air in the Eocene is not well reproduced in global climate models (GCM) and the lapse rate feedback that contributes to polar amplification is still not well understood. Recent work hypothesized that the formation of low clouds as moist air flows from a warm ocean to a cold continental surface could suppress cold air outbreaks in warmer climates. Cronin and Tziperman, 2015, took a one-dimensional Lagrangian column model approach to track cloud formation and surface temperature as an air column migrates from a warm ocean surface to a cold continent [2]. Hu et al, 2018, followed up with an Eulerian analysis of GCM output over a range of cold and warm climates, looking at regional cloudiness, continental interior temperatures, and cold air extremes [3]. But neither approach is complete. The Lagrangian column model does not take into account mixing with surrounding air masses, while the Eulerian analysis does not explicitly follow the formation of clouds and their radiative impact as an air mass moves. In this work, we combine the two perspectives by studying cold air outbreaks in a variety of warm and cold climate scenarios using model output from the Community Atmosphere Model. After identifying cold air outbreaks, we backtrack trajectories for the air parcels that make up the entire cold air column. We then analyze the formation of clouds and the radiative budget to study the effects of clouds along each trajectory. Pithan, F. & Mauritsen, T. (2014). Nat Geo, 7, 181-184. Cronin, T. W. & Tziperman, E. (2015). PNAS, 112(37), 11490-11495. Hu, Z., Cronin, T. W. & Tziperman, E. (2018). JCLI, 31(23), 9625-9640.

Southern Africa is facing unprecedented strains on its agriculture, including a rapidly increasing population and demand for cereals. The global issues of climate change, water scarcity, and soil erosion are also affecting southern Africa, which expects a drier climate in the future. A promising tool in the fight for food security is Conservation Agriculture (CA), a technique based on minimum soil disturbance, mulching using crop residues, and crop rotation and/or intercrops. CA is promoted by organisations including the United Nations due to its potential to increase crop yields in arid/semi-arid climates; increase drought resilience; and increase infiltration of rainwater, reducing flooding and erosion. Despite its benefits and promotion, little is understood of the hydrodynamics of soils under CA cultivation. In order to investigate these hydrological processes, we installed Electrical Resistivity Tomography (ERT) monitoring systems (PRIME, developed by BGS) at three agricultural research sites in southern Africa (Zambia, Malawi, & Zimbabwe) under CA and conventional tillage systems. The sites are also instrumented with soil temperature, moisture, and matric potential sensors, as well as monitored groundwater boreholes, enabling comparison between monitoring techniques and the tracking of water from the ground surface to depth. ERT deployments for the respective sites include surface 2D, shallow cross-borehole 3D, and surface 3D electrode arrays. Each PRIME system is configured for twice daily data collection, and uses data telemetry for remote data retrieval. ERT monitoring allows us to monitor the hydrodynamics from the root zone, through the soil profile and vadose zone, to the aquifer. Initial results show variability between the sites, and heterogeneous nature of the vadose zone within the sites. This heterogeneity has been shown to influence preferential fluid flow pathways in the vadose zone. Monitoring over rainfall events has shown a strong, rapid response of pronounced, shallow wetting fronts, with limited changes at depth. We are beginning the process of comparing the hydrodynamics between CA and conventional plots, and the procedure of optimising data processing to enable better imaging of soil moisture changes at depth in the presence of rapid near surface changes.

Atmospheric nitrous oxide (N2O) is, after carbon dioxide and methane, the third most important long-lived anthropogenic greenhouse gas in terms of radiative forcing. Since preindustrial times a rising trend in the global N2O concentrations is observed. Anthropogenic emissions of N2O, mainly from agricultural activity, contribute considerably to this trend. Sparse observational constraints have made it difficult to quantify these emissions. The few studies on top-down approaches in the U.S. that exist are mainly based on Lagrangian models and ground-based measurements. They all propose a significant underestimation of anthropogenic N2O emission sources in established inventories, such as the Emissions Database for Global Atmospheric Research (EDGAR). In this study we quantify anthropogenic N2O emissions in the Midwest of the U.S., an area of high agricultural activity. In the course of the Atmospheric Carbon and Transport – America (ACT-America) campaign spanning from summer 2016 to summer 2019, an extensive dataset over four seasons has been collected including in-situ N2O aircraft based measurements in the lower and middle troposphere onboard NASA’s C-130 and B-200 aircraft. During fall 2017 and summer 2019 we conducted measurements onboard the NASA-C130 with a Quantum-Cascade-Laser-Spectrometer (QCLS) and on both aircraft over the whole campaign flask measurements (NOAA) were collected. More than 300 joint flight hours were conducted and more than 500 flask samples were collected over the U.S. Midwest. The QCLS system collected continuous N2O data for approximately 60 flight hours in this region. The Eulerian Weather Research and Forecasting model with chemistry enabled (WRF-Chem) is being used to quantify regional agricultural N2O emissions using the spatial characteristics of these atmospheric N2O mole fraction observations. The numerical simulations enable potential surface emission distributions to be compared to our airborne measurements, and source estimates can be adjusted to minimize the differences, thus quantifying N2O sources. These results are then compared to emission rates in the EDGAR inventory.