This repository creates a GUI (graphical user interface) for the BALTO (Brokered Alignment of Long-Tail Observations) project. BALTO is funded by the NSF EarthCube program. The GUI aims to provide a simplified and customizable method for users to access data sets of interest on servers that support the OpenDAP data access protocol. This interactive GUI runs within a Jupyter notebook and uses the Python packages: ipywidgets (for widget controls), ipyleaflet (for interactive maps) and pydap (an OpenDAP client). The Python source code to create the GUI and to process events is in a module called balto_gui.py that must be found in the same directory as this Jupyter notebook. Python source code for visualization of downloaded data is given in a module called balto_plot.py. This GUI consists of mulitiple panels, and supports both a tab-style and an accordion-style, which allows you to switch between GUI panels without scrolling in the notebook. You can run the notebook in a browser window without installing anything on your computer, using something called Binder. Look for the Binder icon below and a link labeled “Launch Binder”. This sets up a server in the cloud that has all the required dependencies and lets you run the notebook on that server. (Sometimes this takes a while, however.) To run this Jupyter notebook without Binder, it is recommended to install Python 3.7 from an Anaconda distribution and to then create a conda environment called balto. Simple instructions for how to create a conda environment and install the software are given in Appendix 1 of version 2 (v2) of the notebook.

Dynamic topography, defined as the deflection of the Earth’s surface due to the convecting mantle, causes changes in vertical land motions (VLM). We aim to estimate the effect of dynamic topography on VLM along the North American Atlantic Coast, which is a region where land subsidence influences relative sea-level rise and other coastal hazards. The contribution of dynamic topography to VLM continues to be debated since previous studies show a range in the rate change of dynamic topography for this region, which are in part due to uncertainties in Earth’s rheology. In this investigation, we model global mantle convection to better assess the role of dynamic topography on VLM along the North American Atlantic Coast. We are implementing a time-dependent approach using the finite element code ASPECT (v2.2.0). We constrain our initial temperature conditions using the tomography models SAVANI, GYPSUM, S40RTS, and TX2008 and then explore both linear and non-linear rheological models. The two rheological models allow us to assess differences in the rate change of dynamic topography globally with a nonlinear rheology compared to a linear rheology. We expect this work will allow us to better understand the contribution of dynamic topography to VLM along the North American Atlantic Coast.

Within the Western Branch of the East African Rift (EAR), volcanism is highly localized, which is distinct from the voluminous magmatism seen throughout the Eastern Branch of the EAR. Voluminous magmatism in the Eastern Branch results from plume-lithosphere interactions, but the origin of magmatism in the Western Branch remains enigmatic. Previous investigations of melt generation beneath the Rungwe Volcanic Province (RVP), the southernmost volcanic center in the Western Branch, suggest plume materials are present. Here, we develop a model of tomography-based convection (TBC) with melt generation to test the hypothesis that melt beneath the RVP is sourced from plume materials. To test our hypothesis, we use seismically constrained lithospheric thickness and sublithospheric mantle structure to develop a fully adiabatic 3D thermomechanical model of TBC with melt generation using ASPECT. We test a range of mantle potential temperatures and find values ranging from 1250-1350 °C are unable to generate melt beneath the RVP. However, when the sublithospheric mantle temperature is increased by ~250 K based on constraints from shear wave velocity anomalies, decompression melt generation occurs at a maximum depth of ~150 km beneath the RVP. Our work suggests that excess sublithospheric mantle temperatures are necessary for melt generation beneath the RVP, and that shear wave velocity anomalies can provide a first order estimate of these anomalous mantle conditions. Excess sublithospheric mantle temperature in the RVP suggests the influence of a plume-source for the seismic anomalies and supports existing geochemical interpretations of a mantle plume contribution to magmatism in the RVP.

The EarthCube BALTO broker (Brokered Alignment of Long-Tail Observations) provides streamlined access to both long-tail and big data using Web Services through several distinct mechanisms. First, we updated the OPeNDAP framework Hyrax, software that serves big data from USGS, NASA, and other sources, with a BALTO extension that tags dataset landing pages with JSON-LD encoding automatically. Therefore, the big data made available through Hyrax are now searchable via EarthCube GeoCODES (formerly P418) and Google Dataset Search. The BALTO broker extension to Hyrax makes thousands of datasets easily searchable and accessible. Second, we focused our efforts on a geodynamics use-case aimed at advancing our understanding of continental rifting processes through the use of an NSF mantle convection code called ASPECT. By addressing this use-case, we implemented a web services brokering capability in ASPECT that allows for remotely accessing datasets via a URL defined in an ASPECT parameter file. Third, through another use-case in ASPECT aimed at testing hypotheses involving global mantle flow, we developed a brokering mechanism for a “plug-in” that accesses NetCDF seismic tomography data from the NSF seismology facility IRIS, then transforms it into the format needed by ASPECT to run global mantle flow models constrained by seismic tomography. Fourth, we demonstrate methods to allow any scientist or citizen scientist to make their in-situ IoT based sensor data collection efforts available to the world. Finally, we are developing a Jupyter Notebook with a GUI that allows for users to search Hyrax servers for big datasets and long-tail data. These cyberinfrastructure developments comprise the entire EarthCube BALTO brokering capabilities.

The Rungwe Volcanic Province (RVP) is a volcanic center in an anomalous region of magma-assisted rifting positioned within the magma-poor Western Branch of the East African Rift (EAR). The source of asthenospheric melt for the RVP is enigmatic, particularly since the volcanism is highly localized, unlike the Eastern Branch of the EAR. Some studies suggest the source of asthenospheric melt beneath the RVP arises from thermal perturbations in the upper mantle associated with an offshoot of the African Superplume flowing from the SW, while others propose a similar mechanism, but from the Kenyan plume diverted around the Tanzania Craton from the NE. Another possibility is decompression melting from upwelling asthenosphere due to lithospheric modulated convection (LMC) where the lithosphere is thin. We test the hypothesis that asthenospheric melt feeding the RVP can be generated from LMC. We develop a 3D thermomechanical model of LMC beneath the RVP and the entire Malawi Rift that incorporates melt generation. We assume a rigid lithosphere with laterally varying thickness and use non-Newtonian, temperature-, pressure- and porosity-dependent creep laws of anhydrous peridotite for the sublithospheric convecting mantle. We find decompression melt associated with LMC upwelling (~3 cm/yr) occurs at a maximum depth of ~150 km localized beneath the RVP. We also suggest asthenospheric upwelling due to LMC entrains plume materials that do not penetrate the transition zone into the melt. Decompression melting associated with upwelling due to LMC may also provide melt sources for other continental regions of thinned lithosphere.

ASPECT (Advanced Solver for Problems in Earth’s ConvecTion) is an analysis tool that simulates convection in the Earth’s mantle and other planets. The BALTO project has extended the ASPECT software so it can read data used to perform the simulations from the BALTO brokering server. These additions to the ASPECT codebase allow data to be remotely accessed and then processed as if the data were stored on the user’s local computer. The additions to ASPECT can be split into two distinct sections: a URL reader and a netCDF reader/translator. The URL reader uses the Data Access Protocol (DAP) to access remote data from supported web servers. Data values are transferred from the BALTO broker and converted within the URL reader plugin to match the format that is expected by the rest of the ASPECT code. Similarly, the netCDF plugin reads data stored using netCDF from the BALTO broker and transforms these data into the sph file format required by ASPECT to perform global mantle convection. The netCDF plugin can use either local or remote data. Once the NetCDF data are read, the plugin combines and formats the required variables (longitude, latitude, seismic velocity, and depth). These newly formatted values are then converted into the sph internal representation to be used as spherical harmonic data by ASPECT. The conversion and processing of data all takes place within the ASPECT program. Both plugins have been integrated to allow the user to lookup remote data in a seamless fashion and broaden the types of data that can be requested by the user.

Relative sea-level rise is a major coastal hazard affecting about half the population of the United States. The Chesapeake Bay is characterized by the fastest rate of sea-level rise along the Atlantic coast of North America, in part because of land subsidence. Previous studies have quantified a range of land subsidence rates in the Chesapeake Bay (~1-4 mm/yr) from various measurement techniques that contribute to high rates of relative sea-level rise. In this study, we present progress towards developing a new vertical land motion map for the Chesapeake Bay region to provide more robust constraints on estimates of relative sea-level rise. We are using a combination of GNSS observations and InSAR interferograms. Available continuous GNSS data in the region that span November 2014 - September 2020 are processed with GAMIT-GLOBK to align temporally with available Sentinel-1 InSAR satellite data. We are using an approach that combines the two geodetic observations to provide a new solution of vertical land motions for the Chesapeake Bay. Additionally, this project is collecting new campaign GNSS observations across the Chesapeake Bay each fall for 5 years, beginning in 2019. We will also present about the 2020 and planned 2021 campaign GNSS observations, which will ultimately be incorporated into our new map of vertical land motions for the region. The impacts of this work will be improved flooding and inundation hazard maps, as well as updated projections for municipal flood mitigation planning that will be created using the new dataset.

Continental rifting is a critical component of the plate tectonic paradigm, and occurs in more than one mode, phase, or stage. While rifting is typically facilitated by abundant magmatism, some rifting is not. We aim to develop a better understanding of the fundamental processes associated with magma-poor (dry) rifting. Here, we provide an overview of the NSF-funded Dry Rifting In the Albertine-Rhino graben (DRIAR) project, Uganda. The project goal is to apply geophysical, geological, geochemical, and geodynamic techniques to investigate the Northern Western Branch of the East African Rift System in Uganda. We test three hypotheses: (1) in magma-rich rifts, strain is accommodated through lithospheric weakening from melt, (2) in magma-poor rifts, melt is present below the surface and weakens the lithosphere such that strain is accommodated during upper crustal extension, and (3) in magma-poor rifts, there is no melt at depth and strain is accommodated along pre-existing structures such as inherited compositional, structural, and rheological lithospheric heterogeneities. Observational methods in this project include: passive seismic to constrain lithospheric structure and asthenospheric flow patterns; gravity to constrain variations in crustal and lithospheric thickness; magnetics to constrain the thermal structure of the upper crust; magnetotellurics to constrain lithospheric thickness and the presence of melt; GNSS to constrain surface motions, extension rates, and help characterize mantle flow; geologic mapping to document the geometry and kinematics of active faults; seismic reflection analyses of intra-rift faults to document temporal strain migration; geochemistry to identify and quantify mantle-derived fluids in hot springs and soil gases; and geodynamic modeling to develop new models of magma-poor rifting processes. Fieldwork will begin in January 2022 and the first DRIAR field school is planned for summer 2022. Geodynamic modeling work and morphometric analyses are already underway.

The EarthCube BALTO (Brokered Alignment of Long-Tail Observations) project is aimed at developing new cyberinfrastructures that enables brokered access to diverse geoscience datasets. Towards achieving this BALTO objective, we developed a plug-in for the community extensible NSF open-source code ASPECT (Advanced Solver for Problems in Earth’s Convection) that permits ASPECT to read data from the BALTO server (OPeNDAP’s Hyrax open-source data server) over the web. We present a use-case of the BALTO-ASPECT client, which accesses lithospheric structures from the BALTO server to constrain a 3-D lithospheric modulated convection (LMC) modeling and melt generation beneath the Rungwe Volcanic Province (RVP) and the Malawi Rift. We test the hypothesis that at least part of the melt feeding the RVP is generated from LMC. In the model, we assume a rigid lithosphere, while for the asthenosphere we use non-Newtonian, temperature-, pressure- and porosity-dependent creep laws of peridotite. We find that a significant percentage of decompression melt from LMC occurs at a maximum depth of ~200 km beneath the axis of the Malawi Rift, consistent with the location and maximum depth of imaged low velocity zones. At shallower depths (~100 km), the melting region is focused beneath the RVP where there is rapid (~3 cm/yr) upwelling. Our results suggest that asthenospheric upwelling due to LMC is the main source of melt beneath the RVP and might also entrain the plume head materials with reported high 3He/4He values. We, therefore, propose that part of the melt beneath the northern Malawi Rift feeding the RVP can be generated by LMC without necessitating plumes impinging the base of the lithosphere at present. This use-case demonstrates the capability of the BALTO-ASPECT client to accelerate research by brokering input data from the BALTO server for modeling LMC and melt generation.