This study examines the impact of climate-sea level controls on the vegetation and evolution of the Niger Delta during the Late Quaternary. The extraneous controls on the environment outlined in this context confirm a direct link between vegetation dynamics (pollen data), sediment supply, and the landscape evolution of the Niger Delta between 20 ka and 6.5 ka. Two phases of sedimentation are recognized based on multiple proxies analyzed in three gravity cores obtained from the shallow offshore at ~40 m water depth. Phase I records abundant occurrences of Poaceae, Cyperaceae, and Podocarpus pollen from a dry hinterland, charred grass cuticles, nonmarine alga Pediastrum, high Ti/Zr ratio, and lower sedimentation from 20-11.7 ka. Phase II records an expansion of mangrove vegetation, high Fe/S ratio, and increase in planktonic foraminifera between 11.7 ka and 6.5 ka. This second phase is attributed to sea-level rise and higher sedimentation during the development of delta plain and mangrove vegetation on the gently sloping shelf. These sequential records provide a new clue about the link between the evolutionary stages of the Niger Delta landscape and vegetation dynamics during two distinct time-bound intervals, which potentially delineate the boundary between two Marine Isotope Stages: MIS2 (late glacial period) and MIS1 (interglacial period). Keyword: Sea level- climate change, Late Quaternary, mangrove pollen, biogeochemistry, Niger Delta, landscape evolution.

On steep alluvial fans, debris floods happen rarely but are often catastrophic. Debris floods and their associated hazards are well documented, but the time between flood events has generally been considered a period of ‘dormancy’, and thus ignored. Here, we present results from a series of four alluvial fan experiments in which we examine the inter-flood period processes and their influence at both event and fan evolution timescales. We built each fan from the same number of debris floods, and the same volume of sediment, but varied the duration of the inter-flood period. This duration had a fundamental influence on fan morphology: in particular fan slope and fan area varied between the experiments. In addition, longer inter-flood periods led to increased flow channelization and channel incision near the fan apex. Our findings challenge the notion that inter-flood periods on steep alluvial fans may be considered dormant. Moreover, the results suggest that longer inter-flood periods may act to contain subsequent debris flood events, shift the locus of debris flood hazard, and reduce their severity.

Over 95% of volcanism on Earth occurs at mid-ocean ridges (MORs) where tectonic plates diverge. How melt is produced depends on the mineral composition and water content. However, it has proven challenging to understand how melting changes when one or more minerals have completely melted. This project examines differences on MOR melting that come with different assumptions in solidus changes with exhaustion of one of the component minerals, clinopyroxene (cpx). To do this, we constructed 2D numerical models of temperature, mantle flow, and melt production at MORs. We ran several models with different amounts of temperature shift in the solidus with loss of cpx. Using zero shift as a baseline, melting starts around 80km depth and peaks at 35km, exhausting cpx, lowering melt output. A second smaller melting region develops more shallowly where there is no cpx. Additional trials in changing the shift in solidus with loss of cpx were done with varying amounts of mantle hydration. For all trials, total melt decreases with larger shifts in solidus. The shallower melting disappears as greater shifts are made. Increasing hydration allows melting to start at deeper depths, but has little effect on the total amount of melt production.

The climatology of atomic oxygen (O) in the MLT (mesosphere and lower thermosphere) is balanced by O production via photodissociation in the lower thermosphere and recombination in the upper mesosphere. The motivation here is to establish the intra-annual variation in the eddy diffusion coefficients and eddy velocity in the MLT based on the constituent climatology of the region. The analysis method, originally developed in the 60’s (Colegrove et al. 1965), was refined for a study of MLT global inter-annual variations in global mean values (Swenson et al. 2018, 2019, respectively) ,(S19). In the this study, the intra-annual cycle was divided into twenty-six (two-week) periods for each of three zones, the northern hemisphere (NH, 15 to 55 degrees ), southern hemisphere (SH, -15 to -55 degrees ), and the equatorial region (EQ, 15 to -15 degrees ). Sixteen years of SABER O density measurements (2002-2018) and MSIS 2.0 model N , O and T profiles (80-96 km) were determined for each of the periods and zones for determination of O eddy diffusion velocities and fluxes. Atomic oxygen diffusive fluxes ([O]*v, 80-96 km) are balanced by the continuity of chemical loss, but the intra-annual variation of k$_{zz}$ (determined from v ) and [O] are determined separately. The major findings include: 1) A dominant AO below 87 km in the NH and SH zones, with the largest variation in amplitude between winter and summer at 83 km. 2) A dominant SAO at all altitudes (80-96 km) in the EQ zone. 3) Intra-annual variability in the global average [O] and k$_{zz}$ contribute to variability of O eddy transport in the MLT.

A direct comparison of hydrometeor types (HMT) from state-of-the-art hydrometeor classification schemes (HMC) with modelled hydrometeors (ICOL-LAM, operational weather predictions model of the German Weather Service) is challenging, e.g. due to different HMT definitions and numbers and difficulties to identify dominant types in mixtures of hydrometeors. A comparison of published HMCs even revealed significant differences between the membership functions used for the same hydrometeor types (Figure 1), emphasizing again the high uncertainty in scattering simulations for ice hydrometeors because of their complex geometries, dielectric properties, and largely unknown size and orientation distributions. The HMCs were applied to perturbed polarimetric variables observed by the X-band Radar in Bonn (BoXPol) to test their robustness against measurement errors and show that especially in the regions with solid precipitation misclassification in hydrometeor typing occurs often. Thus, a dual strategy to evaluate the hydrometeor type representation in ICON-LAM is presented: i) Classification after clustering of the data is assumed to reduce the sensitivity of the decision to the uncertainty of scattering simulations. First an agglomerative hierarchical clustering of the radar pixels based on their similarity in multi-dimensional polarimetric signatures is applied, and afterwards for each identified cluster a comparison of the distributions of polarimetric moments with scattering simulations or membership functions for different HMT is performed. ii) A direct comparison of multivariate simulated and observed distributions of polarimetric moments. These comparisons will be performed for different heights and/or space-time subsets, and for clusters with similar HMT in the model and the observations as identified with the advanced radar-based hydrometeor classification scheme. Results for a set of case studies observed with the polarimetric X-band radar composite in Bonn, Germany, will be presented.

Understanding spatiotemporal patterns and trends of Indian Summer Monsoon extremes have always been an important task mostly because the impacts of extreme events have an enormous effect on agriculture, economy, life and eco-system. In general, findings from the exploration of extreme events with limited data will have high uncertainty, and it is important to investigate the trends with a high long-term dataset for improved understanding of extreme events. Further, the patterns and interactions become further unusual, unexpected and unpredictable, coupled with the existing challenges of global warming-induced climate change. Hence, the study was primarily prompted by these realizations and an implied aspiration to quantify spatiotemporal patterns and trends of Indian Summer Monsoon extremes. In the present study, Extreme rainfall is defined in three categories, namely severe (99th percentile), very high (95th percentile) and high (90th percentile) during the monsoon season in each year. The temporal changes in extreme rainfall have been detected over the period 1901–2019 using non-parametric Mann-Kendall and Sen’s slope estimator tests, respectively. The analysis revealed significantly intensifying rainfall magnitudes in Jammu and Kashmir, parts of Gujarat, Rajasthan and Peninsular India. The outcomes indicate that the magnitudes of extreme rainfall are likely to increase in future in these regions. On the contrary, Central and some regions of North-eastern India shows deceasing trends in the extreme rainfall significantly. Consistency of the trends, both temporally and spatially has been explored considering three time windows with an overlap of 10 years. The findings of the temporal evolution of extreme rainfall reveal spatiotemporal pattern is not consistent in different periods of the study. The results of the present study will provide an improved understanding of spatiotemporal patterns of the daily rainfall extremes during the Indian summer monsoon.

Studying of solar ionizing environment for the interstellar plasma inside the heliosphere is an unavoidable aspect of the interpretation of the full solar cycle of IBEX observations. We present a recent revision of the observation-based model of the ionization rates inside the heliosphere discussed by Sokół et al. 2020 (ApJ 897:179). The solar wind (SW) and the extreme ultraviolet (EUV) radiation affect fluxes of interstellar atoms inside the heliosphere both in time and in space. We present a Sun–Heliosphere Observation-based Ionization Rates (SHOIR) model based on the SW and EUV data available in solar cycle 24. We revised the in-ecliptic variation of the SW parameters, the latitudinal structure of the SW speed and density, and the photoionization rates. The revision most affects the SW out of the ecliptic plane during solar maximum and the estimate of the photoionization rates, the latter because of a change of the reference data. The changes are not constant and vary in time and in latitude. Our study shows that the polar SW is slower and denser during the solar maximum of solar cycle 24, and that the current estimates of the total ionization rates are higher than the previous ones for H, O, and Ne, and lower for He. The changes for the in-ecliptic total ionization rates are less than 10% for H and He, up to 20% for O, and up to 35% for Ne compared to the previous estimates.

Previous studies have estimated that 25% to 35% of Amazonian precipitation comes from evapotranspiration (ET) within the basin. However, due to simplifying assumptions of traditional models, these studies primarily focus on large spatial and temporal scales. In this work we use the Weather Research and Forecast (WRF) regional climate model with the added capability of water vapor tracers to track the moisture from Amazonian ET at the native WRF resolution. The tracers reveal that the well-mixed assumption of simpler models does not hold, as local ET is more efficiently rained out of the atmospheric column than remote sources of moisture, particularly in the eastern part of the basin. Recycled precipitation shows a strong annual and semi-annual signal, associated with the passage of the Inter-Tropical Convergence Zone. The tracers also reveal a strong diurnal cycle of Amazonian water vapor related to the diurnal cycle of ET, convective precipitation and advected moisture. ET increases from early morning into the afternoon, some of this moisture is rained out through convective storms in the early evening, while later in the night strong winds associated with the South American Low Level Jet advect moisture downwind. Visualizing the Amazonian water vapor highlights its diurnal beating pattern and suggests that the Amazon has “younger” water than other regions in the globe, with very efficient recycling of local moisture.

The COVID-19 virus was first detected in Wuhan, China and its genesis was traced to infected bats, passed through an intermediate host to humans. COVID-19 or “Coronavirus” reached approximately 4 million confirmed cases in the United States by July 2020. The spread of this virus has affected both social and economic affairs on a global scale with more than 15 million confirmed cases worldwide in July 2020. The pandemic has proven a global public health and socio-economic crisis. In addition, the shelter-in-place orders provide an unprecedented opportunity for examining the resulting reduction in greenhouse gases and aerosols on the atmosphere. The Sentinel-5P satellite has shown distinct changes in atmospheric aerosols over the COVID-19 epicenter in Wuhan. After Texas, U.S. established similar shelter-in-place orders to prevent the spread of the virus, the state’s industrial activity experienced an economic slowdown. This paper quantifies the changes in atmospheric aerosols associated with the COVID-19 slowdown over major cities in Texas and compares it to similar changes in Wuhan, China using satellite imagery.

Across geospatial domains and practices, there is a pressing educational need for engagement with and understanding of computational and technical advancements relevant to geospatial work. Computational skills and practices, like working with big data, creation and management of machine learning algorithms, work with automation in data analysis and management, and many others, are growing as fundamentals to conducting geospatial scientific research, and to learning in the geospatial classroom. The Hour of CyberInfrastructure (Hour of CI) project aims to create learning materials for use in diverse learning contexts to provide learners a base to build their practice in eight core areas of cyber literacy pertinent to geographic information science (GIS) and geospatial practice. Leveraging the affordances of Jupyter notebooks and cloud computing, we discuss the design, development, and deployment of introductory lessons in these areas. We report the educational design strategies behind development of these lessons, discuss the technical development and support required to use these in an interactive Jupyter notebook enabled space, and report on the deployment of these lessons in initial classroom testing environments. By sharing components of the entire process in developing Hour of CI lessons, we aim to outline our experiences, share best practices and pitfalls, and consider feedback from initial testing. These results will support other efforts in computer-based STEM education by providing feedback and results from an interwoven, cross-discipline geospatial, GIS, and computer science context.

Various recent studies have shown that basalt formations have the capacity for long-term secure CO2 storage through carbon mineralization. Many of these studies have demonstrated extremely rapid rates of mineralization, but the underlying mechanism enabling these elevated reaction rates, and their relation to the processes occurring in proposed basaltic reservoirs, remain poorly constrained. In this work, a 3D micro-continuum reactive transport model was designed to investigate the impact of alkalinity on basalt interactions with CO2-rich fluids. Reactive transport models were developed in PFLOTRAN based on 3D imaging data from high-temperature, high-pressure flow-through experiments (Luhmann et al. (2017) Chemical Geology, Water Resources Research). Mineral reactive surface areas in the model were adjusted to produce agreement with chemistry of output fluids sampled during the experiments. The benchmarked model showed that no considerable carbonate was formed during interaction with the relatively low alkalinity, low pH solutions, regardless of the enrichment of basalt-derived Na+, Mg2+, and Fe2+ ions in the reactant fluid. Increasing the alkalinity of the injected fluids consistently yielded higher rates of carbon mineralization. Similarly, introducing a small initial volume fraction of carbonate minerals into the system contributed to increased carbon mineralization, because of the increased fluid alkalinity. These results thus reinforce a conceptual understanding of carbonate mineralization in basalt-hosted CO2 storage reservoirs that emphasizes the importance of aquifer fluid alkalinity, and caution against extrapolating results from elevated-alkalinity CO2 storage reservoirs and experiments to others where this is less likely to be representative.

Brazil’s Amazon deforestation is one of the world’s great environmental problems, and the fate of the “TransPurus” region – the vast block of intact forest to the west of the Purus River in Brazil’s state of Amazonas – will be the deciding factor in maintaining Amazonia’s biogeochemical cycles and associated ecosystem services, including carbon storage and water cycling and biodiversity. The Purus River effectively divides Brazilian Amazonia between its eastern side (where the forest has been heavily affected by deforestation, fragmentation and degradation), and the western side (where the forest is largely intact due to lack of accessibility by road). This situation in western Amazonia is likely to change radically if the proposed AM-366 and associated roads are built, opening this block of forest with a connection to Highway BR-319 (Manaus-Porto Velho). The AM-366 would cross the Purus River at Tapauá and link BR-319 to Tefé, Coarí and Juruá. BR-319 is a highway that was-abandoned in 1988 but that has been “maintained” since 2015 while awaiting approval of a federal environmental impact assessment (EIA) before being “reconstructed.” Another threat comes from the “Solimões Sedimentary Basin” project that would open a substantial part of the TranPurus area to oil and gas drilling, potentially totaling thousands of wells. This would greatly increase the probability of roads being built to reduce the costs of servicing these wells. Roads are the primary drivers of deforestation in Brazil. The TransPurus area would be subject to invasion by actors ranging from landless farmers to large “land grabbers” (grileiros), and would be likely to attract oil palm and logging interests. Logging can potentially provoke large-scale forest degradation in conjunction with its increasing the vulnerability of forest to fire. Should the huge area of intact forest in this region be lost, potential release of greenhouse gases would be of a scale that could be a key factor in pushing global temperatures beyond a “tipping point” leading to global warming escaping from human control to begin a “runaway greenhouse” ending in a “hothouse Earth.” It would also threaten the source of water vapor for the “flying rivers” – winds that carry water vapor recycled through Amazonian trees to São Paulo and other parts of Brazil and neighboring countries.

The surface is the interface through which the bedrock interacts with the boundary-layer. Here, living organisms of various shapes, sizes, and function intermingle with the mineral soil, organic residue, and canopy air space that reside there. Together, they breath, absorb momentum, exchange water and gases, and bask in the heat from the sun and clouds above and thermal reservoirs below. While many of these functions are well understood, we knew less about how those functions operate and behave at different spatial and time scales. More intriguing, surface variance with scale influences scales of motion in the atmosphere. Here, I present a generalized look at how land and atmosphere scales interact, focusing on the lens of the surface energy budget. These processes are investigated through intensive measurements and high-resolution models conducted at the CHEESEHEAD19 field experiment in Wisconsin. A combination of airborne and tower eddy covariance networks, drone and airborne canopy imaging, and turbulence resolving simulations reveal persistent mesoscale contributions in the atmosphere enabled by surface heterogeneity.

Simple models of fluid and solid mechanics predict that the depressurization of a shallow reservoir that occurs during large effusive eruptions produces exponential trends in time series of both pressure drop and extruded volume. These models are attractive due to their simplicity and because they can explain geodetic and extruded volume data recorded at several volcanoes like at St. Helens and Cordón Caulle, regardless of their magma compositions. However, several lava and dome-forming eruptions like at Redoubt, Hekla and Santiaguito volcanoes do not show clear ground deformation coeval to lava and dome effusion despite the extrusion of at least 0.1 km3 DRE of magma. This apparent paradox can be explained by a variety of factors including deep magma sources and highly compressible magmas that leave no geodetic footprint. Here we explore the role of magma buoyancy with a reanalysis of ALOS-1, TerraSAR-X and RADARSAT-2 InSAR ground deformation and Pleiades DEM data of the VEI 5 Plinian and dome forming rhyolitic eruption of Chaitén volcano in 2008-2009. We show that almost all of the recorded ground deformation occurred during the first three weeks of the eruption, which implies that the extrusion of a rhyolitic dome (~0.8 km3 DRE) did not result in significant depressurization of a magma reservoir, despite the clear exponential trends in the extrusion data. Instead, we show that the exponential trend in the time series of extruded volume can be explained by magma ascending due its buoyancy instead of its overpressure. These results imply that ground deformation alone is not always indicative of the temporal evolution of an eruption and urges for the acquisition of denser time series of DEM data to calculate time-lapse extrusion rates.

Structural and lithological controls in mountain valleys have been shown to affect the erosional connectivity of hillslopes, tributaries and alluvial fans, as well as the formation and preservation of strath terraces. In this study we explore the synchronicity of fluvial bedload aggradation and bedrock incision in valleys of one river draining a collisional mountain belt through geomorphological, sedimentological and chronological datasets of strath terraces. Along the M’Goun River on the southern flank of the central High Atlas Mountains strath surfaces and bedload sediments are preserved in valleys with differing structure and lithology throughout the thrust front and wedge-top basin. We (1) extract terrace surface and river channel elevations from a digital elevation model and field mapping to reconstruct river long profiles; (2) collect grain size and lithology data from terraces to derive information on sediment source and transport; (3) constrain the timing of bedload aggradation within the two latest strath levels using a new approach to OSL dose rate correction of gravels. Strath terraces form in weak sedimentary bedrock in valleys confined by limestone and conglomerate units, and are capped by up to 3 to 10 m of gravel bedload and overbank sands. The record of strath burial and incision extends to 180 ka, but only includes one synchronous bedload aggradation event during the last interglacial maximum MIS 5a (~130-110 ka). Reconstructed paleo-river long profiles and chronology demonstrate time-transgressive bedrock incision through the thrust front and wedge-top basin on the order of 10^4 – 10^5 yrs, representing strath incision of 12 to 40 m. A lack of a downstream bedload grain-size trend and presence of locally derived clast lithologies indicate lateral input of gravel from valleys in addition to downstream transport. These results allow for the development of a conceptual model of asynchronous strath terrace formation in a collisional mountain belt.

Existing global FT records, derived from the Soil Moisture Active Passive (SMAP), the Advanced Scanning Microwave Radiometer (AMSR), and the Special Sensor Microwave Imager (SSM/I) produce relatively course spatial resolution (25-36km) binary FT classifications. These classifications can vary widely depending on the microwave bands used, topography, and land cover, leading to a somewhat ambiguous definition of ‘frozen’ and ‘thawed’ states. In this study, we assess the relationship between satellite observation derived FT products over North America compared to modeled near-surface temperatures and land surface temperature (LST) from the Geostationary Operational Environmental Satellite system (GOES). Utilizing the higher spatial resolution of these products (~4.5km), sub-grid scale variability and its relationship to courser microwave FT classifications was assessed. Through an analysis of spatial variability and uncertainty across North America, five focus study pixels each representing unique FT profiles were examined. These included pixels in: (1) Southern Plains (36, -97), (2) Tundra (61, -76), (3) Northern Forest (47, -74), (4) Northern Plains (52, -103), and Mountainous (38.9, -107.9). The model ensemble adequately captured near surface temperatures as they relate to FT classifications in Tundra, the Northern Plains, and Northern Forest regions. On average, 85.3% to 99.6% of sub-grid cells were below freezing when FT products classified the associated pixels as frozen. GOES - LST observations were shown to have the highest proportion of sub-grid cells below freezing on average, when classified as frozen by FT products (97.3% - 100%) across the same 3 focus locations. However, we also find that fractional FT products utilizing higher resolution data inputs, such as LST, would provide a considerable improvement in mountainous regions with high inter-grid cell heterogeneity, in regions characterized by ephemeral FT events (Southern Plains), as well as during freeze and thaw onset periods. These locations showed a significant reduction in the average temperature product frozen proportion associated with frozen classifications (as low as 5.8%). This study provides insight to improving representation of FT state and providing a clearer meaning of what constitutes a ‘frozen’ classification.

The Intergovernmental Panel on Climate Change (IPCC) currently prepares its Sixth Assessment Report (AR6). Its authors assess peer-reviewed scientific literature and recent climate datasets to inform policy-makers about the current state of the science regarding climate change and its impacts, as well as adaptation and mitigation options. For AR6, efforts are underway to make its main results FAIR and preserve them in the TRUSTworthy repositories of the IPCC Data Distribution Centre (DDC), jointly managed by CEDA, DKRZ, and CIESIN. The AR6 FAIR initiative was kickstarted by the IPCC DDC and Working Group I (WGI) [Stockhause et al., 2019], then adopted by IPCC TG-Data (Task Group on Data Support for Climate Change Assessments) shortly after its creation. All three WGs have adopted the FAIR data guidelines. IPCC assessments are large and diverse in in terms of scientists involved as well as included scientific objects. Challenges for digital data curation are related to the scale and diversity of papers, reports, datasets, the variety of software, and the different familiarity of the scientists with these technical aspects. The following priority areas for improved data stewardship were selected based on the aims to enhance the traceability of AR6 key findings and their reusability: preserve figure datasets in the DDC; - preserve analysis software; . preserve main input datasets in the DDC; . assemble datasets and provenance information on the figure creation from IPCC authors; and . interlink datasets to the IPCC report. Datasets are transferred to the DDC at the end of AR6. The DDC partners are responsible to preserve the data for future reuse by different stakeholders and under a variety of current and future scientific and policy-related questions. As the role for the DDC expands within the IPCC, new partners are sought. The TRUST principles provide a framework for the communication of DDC tasks to different stakeholders, e.g. to countries interested to host a DDC. The presentation will give an overview over the IPCC AR6 approaches towards FAIR data maintained in TRUSTworthy repositories, their challenges, their approach to meet these challenges and open questions, e.g. the integration of digital data into the IPCC Error Protocol, targeted within TG-Data.

Soil moisture is an essential metric to understand crop condition throughout the growing season. Collecting soil moisture data by field observation is time-consuming and labor-intensive, especially for a CONUS geographic coverage. NASA’s SMAP Mission has been providing global mapping of soil moisture and freeze/thaw state at high spatial and temporal resolutions since 2015. However, handling SMAP data could be difficult for users who do not have technical background. Creating a soil moisture map with SMAP data contains a series of steps, including data retrieval, reformatting, reprojection, mosaicking, and clipping. Moreover, users need to install special software and configure the system environment to further perform geospatial analysis for SMAP data. To facilitate using of SMAP data, this paper presents a cloud-based web geoprocessing service system for disseminating and analyzing SMAP data products. This web service system serves a variety of data products, including 9-km SMAP Level-4 data, 1-km SMAP Hybrid data, and MODIS-based vegetation index data. The development of the geoprocessing services is based on the three-layer system architecture composed of an infrastructure layer, a data layer, and a service layer. The infrastructure layer manages the fundamental computing resources and offers the Platform as a Service (PaaS) to the data layer and service layer. The data layer stores all raw raster and vector data offered by the web service. The service layer handles all geospatial web services including map services and geoprocessing services. Both the data layer and service layer are deployed as instances of virtual machines on the top of the infrastructure layer. The system offers a variety of geoprocessing operations in the OGC Web Processing Service (WPS) interface standard. These operations are grouped into get file processes, geospatial statistics processes, map production processes, time-series profile processes, image composite processes, and miscellaneous processes. The proposed geoprocessing services have been implemented as a part of the Crop Condition and Soil Moisture Analytics (Crop-CAMSA) web service system and are interoperable with other web applications. The experiment result shows the geoprocessing service can significantly simplify the procedures of dissemination and analysis of SMAP data.