Two sites in adjacent catchments located in eastern NSW provide hydrological data over 200 years since European settlement: (a) height of the Hawkesbury River at Windsor, within the Sydney Basin (HR); (b) level of the ephemeral Lake George, sited 100 km inland (LG). HR has experienced 43 moderate to major floods since 1799 with the timing of floods grouping into approximate 40-year segments of greater or lesser flood frequency. LG has a reconstructed history of annual levels (Short et al, 2020) which shows obvious spacings with range 50 to 80 years. Three features are clear. The close correlation in time between HR floods, and the deep LG records, in separate hydrological catchments, suggests that these were not random occurrences. The sunspot record shows clear correlation in timing of occurrence (but not of amplitudes) of anomalously weak sunspot maxima with high rainfall/flood-prone segments. High sunspot maxima are associated with dryer 40 yr segments. Both datasets yield meaningful spectra via Lomb-Scargle spectral analysis (the data lengths being too short for reliable Fourier spectra). These power spectra show maxima at periods 82-88 yr (HR) and 80 yr (LG). Subsidiary peaks at periods 50, 30, 20and 11 yr appear on both. These peaks align with the first three of the six named periodicities in solar activity; the Schwabe(11yr); Hale (22yr) and the Gleissberg (87 yr) periodicities. These three periodicities are present in the sunspot record from1609 CE, and in the cosmogenic (Be and C ) record of the past 50+ kyr where high sunspot activity correlates with low cosmic radiation and high total solar insolation (TSI). In particular HR for 1810-20 CE and LG for 1819-20 CE coincide with the last portion of the sunspot Dalton Minimum, the last of the “Little Ice Ages” experienced worldwide. The timing of HR floods correlates closely with La Nina events, and a subset correlates with solar cycle terminators described by Leamon et al (2021). We believe it is significant that a subset of terminators associated with dryer segments also approximate a pattern consistent with the 87 yr Gleissberg cycle. We conclude that just as solar cycle terminators appear to have predictive value for La Nina events, recognition of the Gleissberg cycle may have predictive value for ~80 yr cycles of flood-prone and drought-prone times.

On the 22nd of May 2021, although no alarming precursory unrest had been reported, Nyiragongo volcano erupted and lava flows threatened about 1 million of inhabitants living in the cities of Goma (Democratic Republic of Congo) and Giseny (Rwanda). After January 1977 and January 2002, it was the beginning of the third historically known flank eruption of Nyiragongo volcano and the first ever to be recorded by dense measurements both on the ground and from space. In the following days, seismic and geodetic data as well as fracture mapping revealed the gradual southward propagation of a shallow dike from the Nyiragongo edifice underlying below Goma airport on May 23-24, then Goma and Gisenyi city centers on May 25-26 and finally below the northern part of Lake Kivu on May 27. Southward migration of the associated seismic swarm slowed down between May 27 and June 02. Micro seismicity became more diffuse, progressively activating transverse tectonic structures previously identified in the whole Lake Kivu basin. Here we exploit ground based and remote sensing data as well as inversion and physics-based models to fully characterize the dike sized, the dynamics of dike propagation and its arrest against a structural lineament known as the Nyabihu Fault. This work highlights the shallow origin of the dike, the segmented dike propagation controlled by the interaction with pre-existing fracture networks and the incremental crater collapse associated with drainage which led to the disappearance of the world’s largest long-living lava lake on top of Nyiragongo.

In this study we introduce a pair of idealized tracers to quantify how changes in physical advection and mixing under climate change affect the nutrient supply, new production, and particulate export rates. The low cost and simplicity of these tracers allows us to explore the sensitivity of the model biogeochemistry, and in particular its response to a changing physical environment, to the choice of model parameters. Using CESM2.1 with active ocean and ice only, at nominal one-degree resolution, under initial conditions and forcing representative of 2000 and 2100, our idealized nutrient and particulate are within the spread of nitrate and export from CMIP5 models. The simple form of the tracers allows us to identify the physical controls on the changing rates of supply, production, and export throughout the year, which together form the different seasonal cycles. We find that the ocean basins with the largest changes in the seasonal cycle over the 21st century are the North Atlantic, the Arctic, and the eastern tropical Pacific. We present results comparing the controls across basins, focusing on shifts in the timing of deepening mixed layers and maximum production rate in the northern North Atlantic through the Arctic, and changes in the spatial and temporal patterns of vertical advective exchange in the tropics and subtropics of the Pacific and Indian Oceans. In both cases we discuss how much these changes depend on the biogeochemical model parameter values.

River corridors, the spatial domains around rivers in which river water interacts with surrounding sediment and rock, are important components of watersheds. They comprise extremely complex ecosystems: heterogeneous at all spatial scales with strong temporal dynamics, coupled biological, geochemical, and hydrologic processes, and ubiquitous human impacts. We present several ways that our project, focused around the 75 km Hanford Reach of the Columbia River but with multiple connections to other systems, is addressing this challenge. These include 1) deployment of intensive, automated sensor networks supplemented by data from the Hanford Environmental Information System (HEIS) for hyporheic zone monitoring 2) data assimilation of these and other data into models using joint hydrologic and geophysical inversion, 3) integrating MASS2 model outputs and bathymetry data using machine learning to classify hydromorphologic features, 4) a community-based effort to develop broad understanding of organic carbon biogeochemistry and microbiomes in diverse river systems, and 5) use of multi-‘omics data to develop new biogeochemical reaction networks. These underpin the incorporation of process understanding and diverse data into high-resolution mechanistic models, and employment of those models to develop reduced-order models that can be applied at large scales while retaining the effects of local features and processes. In so doing we are contributing to reduction of uncertainties associated with major Earth system biogeochemical fluxes, thus improving predictions of environmental and human impacts on water quality and riverine ecosystems and supporting environmentally responsible management of linked energy-water systems.

The zone of interaction between the Cocos (CO), Caribbean (CA) and North America (NA) plates in Guatemala is defined by the sub-parallel Motagua and Polochic strike-slip faults, a series of north-south-trending extensional grabens immediately south of the Motagua Fault, the Middle America trench, and faults within the Middle America volcanic arc. Historical earthquakes associated with these faults include the destructive 1976 Mw 7.5 earthquake along the Motagua fault and the 2012 Mw 7.5 Champerico thrust earthquake. The latest published GPS-based present-day kinematic model of the region shows that about two-thirds of the strain accumulation from the NA/CA relative motion concentrates on the Motagua fault and one third across the Polochic fault, suggesting that slip varies with time as a result of mechanical interactions within the Motagua-Polochic fault system. As part of the efforts to quantify the present-day kinematics and slip behavior of these faults, we use interferometric synthetic aperture radar (InSAR) to measure the strain rates across faults in Guatemala and to constrain slip partitioning among them. We processed L-band ALOS-1 images spanning from 2006 to 2011, and C-band Sentinel-1 images spanning from 2015 to 2019, from ascending and descending tracks covering the Polochic and Motagua faults, the Ipala and Guatemala City grabens, and part of the volcanic arc to the south. We are using the New Small temporal and spatial baselines (NSBAS) workflow to compute the interferograms, make tropospheric and ionospheric corrections, and perform time-series analysis. We present the first InSAR-based maps of interseismic velocity for this region, which will contribute to the refinement of interseismic locking estimates across the Motagua-Polochic fault system, the subduction zone, and other nearby faults.

Land surface features such as elevation, soils, land use, and vegetation fluctuate on scales ranging from millimeters to hundreds of kilometers. The state of the land surface and many hydrological processes vary accordingly. Land surface temperature (LST) is a crucial factor determining the interactions between the land surface and the atmosphere (i.e., energy, water, and carbon fluxes). Decades of global satellite remote sensed LST fields are now available, constituting an unprecedented opportunity to understand better the factors influencing hydrological variability from regional to global scales. An important under-researched aspect regarding variability, at least over continental extents, is determining the scales for which hydrological variations are spatially and temporally related. These scales would serve as indicators for the required time and spatial resolution for observational systems. This presentation will address this gap in understanding across scales through a comprehensive analysis of spatial and temporal correlation lengths of LST across the contiguous United States (CONUS). Correlation lengths (CLs) are measures of the stationarity of a property distribution both in space and time. They reveal the scales of variability for fields thus, contributing to estimating the stationarity of the property. Temporal correlation lengths (tCLs) express the property changes in time for a fixed location, providing a measure of the persistence or variability of the time series. On the other hand, spatial correlation lengths (sCLs) depict the spatial patterns of the property over a predefined area by representing the distance for which variations are spatially related. As part of our evaluation, we will analyze derived fields of tCLs and sCLs for the ~2x2 km2 GOES-16 LST hourly product over CONUS. A 0.25-degree regular grid over CONUS will be defined, and an hourly time step between 2017 and 2021 will be used for the analysis. The obtained CLs will be assessed in terms of the time of the day and season. Additionally, we propose a comparison of well-known spatiotemporal influencing factors of LST such as land cover, surface thermal properties, topography, incoming solar radiation, and meteorological conditions.

The Surface Biology and Geology (SBG) mission is one of the core missions of NASA’s Earth System Observatory (ESO). SBG will acquire high resolution solar-reflected spectroscopy and thermal infrared observations at a data rate of ~10 TB/day and generate products at ~75 TB/day. As the per-day volume is greater than NASA’s total extant airborne hyperspectral data collection, collecting, processing/re- processing, disseminating, and exploiting the SBG data presents new challenges. To address these challenges, we are developing a prototype science pipeline and a full-volume global hyperspectral synthetic data set to help prepare for SBG’s flight. Our science pipeline is based on the science processing operations technology developed for the Kepler and TESS planet-hunting missions. The pipeline infrastructure, Ziggy, provides a scalable architecture for robust, repeatable, and replicable science and application products that can be run on a range of systems from a laptop to the cloud or an on-site supercomputer. Our effort began by ingesting data and applying workflows from the EO- 1/Hyperion 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. We have fully implemented the first stage of processing, from the raw data (Level 0) to top-of-the-atmosphere radiance (Level 1R). We plan to begin reprocessing the entire 55 TB Hyperion data set by the end of 2021. Work to implement an atmospheric correction module to convert the L1R data to surface reflectance (Level 2) is also underway. Additionally, an effort to develop a hybrid High Performance Computing (HPC)/cloud processing framework has been started to help optimize the cost, processing throughput and overall system resiliency for SBG’s science data system (SDS). Separately, we have developed a method for generating full-volume synthetic data sets for SBG based on MODIS data and have made the first version of this data set available to the community on the data portal of NASA’s Advanced Supercomputing Division at NASA Ames Research Center. The synthetic data will make it possible to test parts of the pipeline infrastructure and other software to be applied for product generation.

Basaltic melts are produced when convection adiabatically brings deep and hot mantle to lower pressures. Such primary melts were extracted from the mantle of Mars, crystallized near the surface and progressively built the Martian crust. This process displaced a large fraction of the heat producing elements from the mantle to the crust and created an insulating layer that slowed down further cooling of the mantle. The complex crust-mantle system controlled many aspects of the geologic history of Mars, including the development of an atmosphere and whether conditions favorable to life could have existed. Our knowledge of the mineralogy, chemical composition and physical properties of the crust of Mars is rapidly expanding. Global geodynamical models can be used to interpret the available data and constrain the processes of crust-mantle differentiation. However, existing models still treat melting in a simplified way. For example, the degree of melting is often assumed to increase linearly above the solidus temperature, while the density of the residue is assumed to decrease linearly. Calculating the density of the residual mantle more accurately is critical because the compositional buoyancy that develops during partial melting fundamentally modifies mantle dynamics. Here, we present an improved parametrization of partial melting of the Martian mantle, which will be combined with the convection code Gaia. We created a new empirical model of melting that calculates the composition of the extracted melts and, when combined to thermodynamic models (e.g., Perple_X), the density of the corresponding residual mantle. Another advantage of the new melting parametrization is that the major-element composition of partial melts can be tracked and used to constrain the petrogenesis of surface rocks. Preliminary results will be compared to available Martian rocks believed to represent primary mantle melts or melts affected by minor fractional crystallization.

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.

Dynamical downscaling of Indian summer monsoon rainfall (ISMR) by using regional climate models (RCMs) portrays the inability of the RCMs in simulating the ISMR, and certain systematic biases appear in the seasonal monsoon rainfall climatology. The inconsistency in RCMs simulation of ISMR can be due to the improper representation of convection by convective and/or microphysical parameterization schemes in different RCMs. In this study, we conducted convection permitting simulations in WRFv3.8.1 and compared with parameterized simulations, to understand the difference of reproducibilities of time-space patterns in the ISMR. Our experimental set-up consists of two sets of simulations with parameterized and explicit convection on a grid resolution of 25 km. The simulations are conducted for three different monsoon seasons: flood, drought, and normal years, to ascertain robustness in the analysis of the model output. These simulations are forced by using ERA-Interim reanalysis as the lateral boundary and large-scale forcing input. The mean large-scale circulation, the spatial distribution of rainfall, seasonal northward propagation of rain bands, and magnitude-phase of the Indian summer monsoon rainfall are verified against the JRA55 reanalysis and India Meteorological Department gridded rainfall datasets. The results show that regional simulations with explicit convection have benefited in the simulation of ISMR features. Simulated seasonal mean rainfall in parameterized convection shows positive bias over Gangetic plains and the Western Ghats. The same bias reduced in explicit simulations and seasonal mean ISMR behaves realistically concerning IMD observations. The added value in the simulation of ISMR in explicit experiments is found to be consistent during the flood, drought, and normal monsoon seasons. Further evaluation of the results reveals that over Indian region, explicit convection simulations of Indian summer monsoon are more realistic than parameterized convection simulations. Therefore, the current study tried to show up the uncertainties in ISMR simulation associated with parameterizations, and explicit convection experiments highlight the reduction of these uncertainties.

Hydrological observation networks are inadequate and declining, hindering advancements in hydrology, particularly in hydrological budgeting, where interception loss remains unmeasured, and a subjective loss figure is assumed. Measuring net rainfall reaching the ground surface is crucial for precise water balance estimates. This involves measuring throughfall & stemflow fractions of precipitation on the canopy. Current methods use collector channels and static storage systems requiring periodic visits for measurements, which becomes extremely difficult and unsafe in inaccessible forests, leading to data losses. For time-resolved data, an array of standard rain gauges is placed under the canopy, or water is collected by troughs for throughfall (and collars for stemflow measurement), draining into a central pipe and directed into a tipping bucket flow gauge. Commercial flow gauges are expensive for use in throughfall & stemflow measurement, since, multiple instruments are required in each study location to capture the variability of the canopy. To address this, we designed and fabricated an open-source, low-cost Tipping Bucket Flow Gauge to automatically monitor flow rates of throughfall & stemflow. It is designed to have a larger adjustable tipping resolution (10 ml – 200 ml). The open-source Arduino-based data logger automatically collects time-resolved data and is powered using solar energy, ensuring remote functionality even in harsh environments. A modular electronics approach was followed for designing the datalogger, facilitating rapid prototyping, easy repair, and upgrades, enabling someone with even an introductory knowledge in Arduino to implement the design. Almost 75% of the instrument is 3D printed and can be fabricated using any standard desktop FDM 3D printer and assembled by hand. The instrument showed 86% accuracy in preliminary testing at a calibrated tipping resolution of 120ml. The cost of prototyping was 100$ - 120$, thus proving cost-effective for accurate hydrological budgeting as compared to the cost of the nearest available commercial solution (~1800$). Through our research and product design, we intend to reduce the barrier of entry and simplify the steep learning curve faced in developing hydrological instrumentation.

Crystalline basement aquifers are characterized by complex flow pathways controlled by varying overburden stratigraphy and thickness as well as fracture network and connectivity within the crystalline rocks. Understanding the hydraulic connection within the fracture network and the overburden regolith is critical to predicting recharge/discharge and contaminant transport pathways. In this study, we combined geophysical imaging with multiple hydraulic testing to quantify hydraulic connectivity within the crystalline basement aquifers at the Ibadan Hydrogeophysical Research Site (IHRS) in Ibadan, Nigeria. The 50 m × 50 m field experimental site is first of its kind established in 2019 to investigate hydrological dynamics within these complex crystalline basement aquifers in sub–Saharan Africa. We acquired multiple parallel 2D electrical resistivity profiles which were also jointly inverted to obtain multiple 2D and 3D electrical resistivity tomograms of the subsurface. The resistivity tomograms were later constrained with lithological profiles from 4 test wells installed down to depths of 30 m at the site to create a conceptual model elucidating potential flow pathways. We also performed a series of 12 hours pumping tests and a NaCl tracer test to estimate flow and transport parameters including hydraulic conductivity, aquifer storage, yield, and groundwater travel time and to assess connection between the four test wells. The resistivity tomograms show 3 major resistivity zones interpreted as a clay-rich topsoil, a saturated weathered overburden, and a fractured basement rock. The delineated fractured bedrock shows an undulating topography with several primary fracture successions at 9, 14, 16 and 22 m. Hydraulic conductivities from pumping tests range from 2.6 x 10-7 to 1.2 x 10-5 m/s for the fractures and 1.7 x 10-10 to 6.4 x 10-6 m/s for the matrix while specific storage range from 3.5 x 10-8 to 1.8 x 10-3. Preferential flow is also observed with stronger connection between wells A and C. Results of this study provide a basis for detailed numerical study which will be focused on predicting recharge and solute transport under different flow and climate regime. This work will provide a scalable framework for a sustainable management of groundwater resources within the crystalline basements of Nigeria.

The current contribution presents wintertime climatology from 2012 to 2020 of mixed-phase clouds and their radiative effects when coupled to the sea ice states. Measurements from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) at the North Slope Alaska (NSA) site in Utqiagvik, Alaska are being analyzed.Classification of cloud hydrometeors in the liquid, ice or mixed-phase states was primary determined by the Cloudnet algorithm, developed by the Finish Meteorological Institute, and applied to a set of ground-based remote sensing instruments from NSA . To evaluate the influence by sea ice, which plays an important role on the Arctic surface-atmosphere interaction, the statistics are separated into cases when clouds are coupled or decoupled to specific sea ice conditions, like presence of leads or polynyas in the vicinity of NSA .We found that clouds coupled to sea ice with presence of leads have shown distinguished features like the increase of total liquid content, lower cloud base heights and less ice content when compared to decoupled cases. Nevertheless, these results rely on Cloudnet accurately detecting cloud droplets within mixed-phase clouds. Arctic cloud radiative effects (CRE) have already been studied from short expeditions like the SHEBA campaign (Shupe et al., 2004) and middle-term ground observations in Barrow (Shupe et al., 2015) and Ny-Ålesund, Svalbard (Ebell et al., 2020). We extend similar CRE studies for 8 years during wintertime, where longwave up- and down-welling flux measurements from NSA are used to estimate surface net fuxes and other cloud radiative features for cases when clouds are coupled or decoupled to sea ice conditions and their sensitivity to different gradients of air-surface temperature when leads or polynyas are present. 

In past global dust storms, no long lasting anomalies in the pressure cycle had been observed. The Global Dust Storm of Mars Year 34 (MY34), however, left behind an average surface pressure lower than what was expected based on the the values recorded on previous years by the Rover Environmental Monitoring Station (REMS) on Curiosity. The main signal contribution to the daily average surface pressure is the CO2 cycle, which is controlled by the Polar ice sublimation and freezing cycles. We used REMS and Mars Climate Sounder (MCS) data to search for correlations between the REMS anomaly and anomalies in the circulation compared to MCS observations from previous years. The findings include an early start of the retreat season for the Northern Polar cap, followed by the longest period of growth for the Southern Polar (SP) cap ice expansion since Curiosity had landed and then, during the dust storm, the longest retreat season of the Southern Polar cap. We also find a larger Northern Polar Cap extension after the storm, suggestive of a larger deposition of CO2 ice. The changes in length of the SP growth and retreat seasons might be consequence of the response of the zonal mean circulation to the dust storm. Changes in the structure of the zonal mean circulation compared to previous years are found in MCS data and presented. The combination of these anomalies constraint what physical processes may have caused this response in surface pressure after the dust storm.

Geophysical methods are very useful in archeological prospection by providing an inexpensive, non-invasive view of the subsurface, and, helping the archeologists to better target their excavation efforts. Ecuador’s past is very rich, with many archeological sites still unexplored. Manteño culture prevailed in the province of Manabí in a series of large coastal towns and along the river valleys and ridges of the Chongón-Colonche coastal mountains of what is now Ecuador from around 500 CE to 1532 CE. They were one of the last prehistoric cultures and the Inca Empire never conquered them directly, which meant their culture developed independently. Thousands of carefully arranged stone foundation have been documented across the abrupt landscape that has been intentionally modified for large scale agriculture. In this work, we present the results of Electrical Resistivity Tomography (ERT) and magnetometry surveys at the Río Blanco archeological area close to the coastal city of Puerto Lopez. The area includes one of the largest unexcavated archeological remains known in Ecuador. It consists of alluvial terraces modified by the Manteño people scattered with numerous ruins. The archeological structures are often delimited by buried rock blocks that sometimes outcrop in the surface. We made 2 ½ D ERT with dipole-dipole array configuration and ground magnetometry surveys at three locations which were identified earlier by archeologists as buried buildings, with one of them being previously partially excavated. The measurement grid for each structure was designed according to their size. For magnetometry, a base station measurement was taken after finishing each survey line in order to be able to remove diurnal variations from the magnetometry readings. All tested structures showed internal variations within them related to differences in electrical resistivity and magnetic susceptibility. According to our preliminary interpretation, some of these anomalies are from the wall rocks and some suggest the presence of buried objects as well as potential locations of fireplaces. The locations of the buried objects are intended to be later verified by archeological excavation.

Perseverance landed at the Octavia E. Butler landing site next to the Séítah dune region in Jezero crater on 18 February 2021, in close proximity to the largest exposed carbonate deposit on Mars. These carbonate signatures have been shown to be associated with the strongest olivine signatures at Jezero crater (Goudge+ 2015, Brown+ 2020). Alteration of olivine can lead to carbonate+H2 production, an energy source for microbes (Mayhew+, 2013). The question of the origin of the olivine-carbonate unit represents both an opportunity and a challenge for the rover mission and future sample return efforts. Carbonate The landing site is not near the region of carbonate detections (Figure 1), however the rover’s westward traverse will take us over the carbonates on approach to the crater rim. No reliable indications of the 2.5 μm carbonate band have yet been convincingly detected by the SCAM VISIR instrument. Olivine Studies of the olivine-carbonate unit concluded the olivine is relatively Fe-rich and coarse grained (mm: Poulet+ 2007, Clenet+ 2013). The strongest in-situ olivine signatures are found in dune material analysed by LIBS/VISIR (Beyssac+ Mandon+ this conf). This grain size characterization work may be used to investigate the interaction of olivine with water and CO2 (Escamilla-Roa+ 2020). These surface-gas processes are enhanced when olivine is in fine grain form. Ash dispersal modeling is ongoing (Ravanis+ this conf) to determine the range different sized ash particles could have traveled on ancient Mars. We cannot directly compare the 1 μm band for CRISM and VISIR, so we developed a new method that measures the curvature of three points on the absorption bands to assess their relative Fo# shifts and applied it to both datasets. Lab spectroscopy will be used to assess spectral variations with composition versus grain size. Two key factors driving the Fo# are mantle composition and melt temperature. Brown+ (2020) estimated a range of Fo44-65 for the most redshifted olivine observed by CRISM. McGetchin+Smythe (1978) showed that an Fe-rich mantle composition would produce highly viscous lavas and suggested an upper bound of Fo70 for olivine. Understanding the astrobiological potential of the olivine-carbonate unit is a priority of M2020 (Farley+ 2020) and we will speculate on potential formation models in this contribution.

Automated classification of remote sensing data is an integral tool for earth scientists, and deep learning has proven very successful at solving such problems. However, building deep learning models to process the data requires expert knowledge of machine learning. We introduce DELTA, a software toolkit to bridge this technical gap and make deep learning easily accessible to earth scientists. Visual feature engineering is a critical part of the machine learning lifecycle, and hence is a key area that will be automated by DELTA. Hand-engineered features can perform well, but require a cross functional team with expertise in both machine learning and the specific problem domain, which is costly in both researcher time and labor. The problem is more acute with multispectral satellite imagery, which requires considerable computational resources to process. In order to automate the feature learning process, a neural architecture search samples the space of asymmetric and symmetric autoencoders using evolutionary algorithms. Since denoising autoencoders have been shown to perform well for feature learning, the autoencoders are trained on various levels of noise and the features generated by the best performing autoencoders evaluated according to their performance on image classification tasks. The resulting features are demonstrated to be effective for Landsat-8 flood mapping, as well as benchmark datasets CIFAR10 and SVHN.

Within a year of its launch date, the ATLAS altimeter on board ICESat-2 is already providing a wealth of critical data of interest across and beyond the cryospheric sciences. With the satellite returning nearly 1 TB of raw data per day, traditional practices of individual research groups downloading large granules of data and then subsetting, processing, and storing them locally are ultimately impractical. We are leading the development of icepyx (formerly icesat2py), an open source Python library designed to easily query, filter, download, and pre-process ICESat-2 datasets. The project’s documentation will include interactive Jupyter Notebook examples, providing a starting point for researchers to create and customize workflows to address their research questions. We actively invite contributions from the community to ensure the project develops in a way that meets a wide range of research needs. The project aims to leverage existing libraries that enable easy parallelization and can be run locally or on cloud-based platforms. As a result, researchers will ultimately download and store minimally-sized subsets of ICESat-2 data and have the opportunity to contribute their code to an established open science project. This presentation will serve to introduce icepyx to the cryosphere community and encourage early adoption of the library by researchers with all levels of coding experience.