Over the past 15 years climate tipping points (CTPs) – which are reached when change in a climate subsystem (the ‘tipping element’) becomes self-perpetuating independent of the original forcing and results in a regime shift to a new subsystem state – have emerged as a source of scientific and public concern. Some CTPs are estimated to be reachable within the 1.5-2oC Paris Agreement range, with many more accessible by the ~3-4oC of warming possible on current policy trajectories. Recent work has also hypothesised that CTPs could ‘cascade’ – with the impacts of triggering one tipping element sufficient to trigger the next and so on – resulting in an emergent global tipping point. However, much discussion relies on a tipping element characterisation that is now over a decade old, which itself was based on an expert elicitation exercise in 2005. Since then there have been substantial advances in our understanding of CTP dynamics based on results from coupled and offline models, observations, and palaeoclimate studies. The tipping cascade hypothesis has also not yet been rigorously tested, with the suggestion of 2oC as a global tipping point remaining speculative. Furthermore, CTP definitions are often inconsistent, with some purported globally-impactful CTPs more accurately represented as either localised CTPs or even threshold-free feedbacks. Here we undertake an updated review of CTPs based on a wide range of recent literature. We estimate ranges for each proposed element’s tipping threshold, timescales, and impact on global and regional warming, as well as if evidence exists for self-perpetuation, rate-dependence, or hysteresis. Each proposed element is then catalogued with reference to a clear tipping point definition, separating global ‘core’ and regional ‘impact’ tipping elements from threshold-free feedbacks. Our estimates confirm that current global warming (~1.2oC) already lies within the lower end of some CTP threshold ranges, and several CTPs become likely or possible within the 1.5-2oC Paris range. In further work we use these estimates to test the potential for and impact of tipping cascades in response to global warming scenarios using a stylised model.

Most major strike slip fault systems are surrounded by narrow zones of damaged rocks that can have a crucial effect on earthquake dynamics. Owing to the limited timescale of seismic observations, the structural evolution of this damaged zone and its long-term effects are not well understood. We study the mechanical response of damage evolution and healing over multiple earthquake cycles using fully dynamic earthquake cycle simulations in a 2D vertical strike-slip fault. We use a spectral element method to discretize the domain and a rate-state dependent friction on the fault to simulate all the stages of the seismic cycle, including interseismic slip, earthquake nucleation, rupture propagation and postseismic slip. A narrow, compliant fault-parallel elastic layer with low seismic wave velocities is introduced to emulate near-fault damage. The low-velocity layer reflects waves during the seismic period giving rise to stress heterogeneities that persist through multiple seismic cycles. We introduce a scalar damage multiplier ‘d (01)‘ that reduces the effective shear modulus during the earthquake and increases it during the interseismic period. We study different realizations of d and h through time: the simplest model consists of a constant increase in damage and healing over each seismic cycle and the more complex model includes a heterogeneous damage proportional to the peak slip velocity along the fault. The distribution and evolution of dynamic parameters (shear stresses and slip velocities) and static earthquake parameters (cumulative slip and static stress drops) as a function of the damage is shown and compared to the existing continuum damage rheology models and field geologic observations. These simulations will provide a better insight into the partitioning of damage and healing during seismic cycles and the saturation of damage in mature fault zones.

On November 4, 2013, residents near a quarry in the western suburbs of Chicago felt shaking from a rare, small earthquake. The USGS reported a magnitude of 3.2 and Dr. Robert Herrmann reported a dip-slip source mechanism from analyzing surface wave amplitudes recorded by USArray stations. With the goal of detecting potential aftershocks in this region of low seismicity and possibly gaining more insight into the source mechanism, a broadband seismic station was installed in the source region by researchers of Northwestern University. Due to the station’s suburban setting and proximity to various transportation arteries, industrial operations, and city infrastructure including a deep tunnel and reservoir, detecting and discriminating small earthquakes from urban noise events poses a serious challenge. Average daily noise levels can be 50 dB above typical noise levels for broadband seismometers in Illinois in pertinent frequency bands, so aftershock signals can be buried deep within the noise, rendering typical STA/LTA detection methods relatively ineffective. A preliminary analysis of several months of waveform data identified seismic signals from ~1000 events. None of these events occurred on a Sunday or at night, implying an anthropogenic origin and further illustrating the challenge. Recorded signals from these events span a wide range of waveforms, rendering popular detection methods like template matching less effective than in other settings. We aim to define and engineer a set of waveform features to aid with seismic event detection using data from a single broadband station in a noisy, urban environment. To identify useful spectral parameters, we first computed power spectral density (PSD) estimates using segments ranging from the hour-scale to the second-scale. Week-long spectrograms of the PSD estimates revealed characteristic frequencies that are likely associated with routine quarry operations. Select features were then tested for their ability to detect regional and local seismic events for one month of data. We will present the results of this analysis, including the performance of several features and discuss their respective benefits and limitations for seismic event detection in an urban environment.

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

A growing literature emphasizes the importance of integrating climate change impacts into electricity system planning. Rising average temperatures can increase and shift electricity demand while reducing generator and transmission efficiency. Changes to water availability and quality can reduce the output of thermally cooled generators and hydropower. Electric power grids across the US and globally are undergoing transformational changes that present new opportunities and challenges to reliability assurance. However, electric utilities and system operators have limited internal capabilities to incorporate these effects into planning practices. This work addresses gaps in utility and system planner practices by integrating climate-water-electricity expertise from universities and U.S. Department of Energy National Laboratories with electricity system planners and stakeholders in the Western Electricity Coordinating Council (WECC). Using a highly collaborative approach, global climate model data, high-resolution hydrology models, and long-term electric sector capacity expansion tools are employed to analyze a range of climate outcomes for future electricity scenarios aligned with recent WECC planning studies. Doing so allows WECC to expand its climate-agnostic planning assessments to consider how future temperature and precipitation patterns could influence generation and transmission planning. We explore how changes to climate-water conditions can affect power plant investment and operation, system economics, and environmental impacts, providing an expanded perspective on interconnection-wide decision making under climate uncertainty.

Increasing competition for water resources in the United States could create future challenges for allocating and using thermal cooling water in the U.S. electric power sector. While thermal power plant retirements and the growth of wind and solar technologies can reduce national aggregate power sector cooling water use, local water constraints and growing demand for agricultural or municipal supply could create greater needs for higher-cost alternative water supplies such as groundwater or recycled wastewater. For some regions, these incentives could change future electricity planning and operational decisions. These relationships and impacts are studied here using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS), a national electric sector planning model that has recently been upgraded to include a highly detailed representation of thermal cooling water demand and supply. Thermal power technologies are differentiated by both cooling technology and water source type to track and constrain thermal cooling water use in a way that incorporates both physical and legal water considerations in the United States. This capability is exercised under a range of electricity sector futures with alternative technology costs, fuel prices, and water constraints to illustrate ways that U.S. electric sector water use could evolve under uncertain future electric sector drivers. In exploring changes to regional generation and transmission planning and operation, water requirements, and cost, we highlight the environmental and economic impacts of future power sector water decisions.

The rapid retreat of tropical glaciers in the Cordillera Blanca, Peru, results in significant changes to the quality and quantity of the streamflow below. Debris-covered glaciers are a common feature in this region but have previously only been studied in terms of their geomorphology and surface characteristics. Short term studies have used hydrochemical mixing models to estimate contributions of melting glaciers to down valley streams. The progressive impact that these glaciers have on streamflow and water chemistry as climate change continues to force glacier loss has yet to be examined. Here we analyze a 16-year dataset (2004-19) of water samples collected from glacierized tributaries of the Santa River draining the Cordillera Blanca, Peru to evaluate inter-annual to decadal differences in hydrochemistry in the outflows below debris-covered glaciers and debris-free glaciers. This unique dataset consists of annual dry season samples from 48 sites within 20 tributaries with different amounts of glacier coverage that provide the isotopic and ionic composition of the water, allowing for analyses of patterns within catchments and comparisons between them over time. Within the Llanganuco catchment, the Kinzl glacier tongue descending from Peru’s highest summit of Huascaran is heavily debris covered (4350-5200 m). Samples directly from the Kinzl effluent stream show the most negative (δ18O = -16.79‰) and variable isotope values (δ18O difference = 3.84‰) compared to less glacierized points within the watershed. In contrast, the Broggi drainage displays the least negative (δ18O = -14.10‰) and variable isotope values (δ18O difference = 2.80‰). Finally, to gain a regional perspective we use the synoptic samples throughout the Callejon de Huaylas watershed to provide a comparison to previous estimates of specific discharge from glacier melt.

Glaciers act as hydrologic reservoirs in mountain environments around the world. In regions that are particularly water-stressed, such as the Andes, glaciers contribute significantly to water resources in downstream communities. As these glaciers recede rapidly throughout the Andes under climatic changes, the surface composition of their ablation zones appears to be shifting from predominantly clean-ice to debris-covered ice. Determining what climatological and topographical factors control debris-coverage in the ablation zones of glaciers throughout the Andes will assist in understanding why these glaciers are becoming increasingly covered by debris and how this debris coverage will continue in the future. By exploring multiple drainage basins across the Andes, this study will discover which regions are most impacted by this transition. Debris-coverage is known to have varying impacts on the ablation rates of glaciers and likely alters the sub-glacial and pro-glacial hydrology of the drainage basin they reside in. With debris-covered glaciers becoming more prevalent across the Andes, it is imperative to gain a better understanding of the hydrology of these complex cryospheric features. Through the use of terrestrial photogrammetry and hydrological techniques, this study will investigate the controls of debris coverage and assess the hydrological impacts of this debris on glaciers throughout the Andes.

With the improvement in numerical weather prediction models and high-performance computing technology, ensemble modeling and probabilistic forecasts have taken on some of the most challenging tasks, such as weather model uncertainty estimation and the global climate projection. High-resolution model simulations that were deemed impossible to complete within a reasonable amount of time in the old days are now running as an ensemble to better characterize the model uncertainty. However, with advances in computation which make large parallel computing widely accessible, important questions are being increasingly addressed on how to interpret each forecast ensemble member, instead of relying on a summarization of all ensemble members. The analysis of individual ensemble members allows for an in-depth analysis of specific possible future outcomes. Thus, it is desirable to have the ability to generate a large forecast ensemble in order to help researchers understand the forecast uncertainty. But it is also crucial to determine which ensemble members are the better ones and to identify metrics to assess the uncertainty captured by each ensemble member. This work proposes the Empirical Inverse Transform (EITrans) function to address these questions. EITrans is a technique for ensemble transformation and member selection based on knowledge from historical forecasts and the corresponding observations. This technique is applied to a particular ensemble forecast to select ensemble members that would offer a sharper and more reliable distribution without compromising the accuracy of the prediction.

Changing irrigation water demand (IWD) and supply (IWS) patterns (size and time) under increased climate variability and socio-economic development is significantly effecting the water and food production in the densely populated South Asia (SA). Considering food security paradigm of SA, where rice and wheat are major staple and water-intensive crops, this study aims to investigate the linkages in IWD by crops and IWS by sources (surface and groundwater) using integrated climate and socio-economic projections. The novel aspect of this study is to explore IWD and IWS pattern shifts during critical crop growth stages (CW’s), which is previously less studied with no remarkable research evidence for IGB region. Quantification of shifts in IWD and IWS patterns in future is crucial for long-term integrated water resources and agricultural planning. For this, LPJmL crop-water model is forced with an ensemble of eight state of the art downscaled GCM at 5 arc-min resolution. To assess the combined impacts of climate and socio-economic changes, RCP-SSP framework is used. Our statistical analysis results show that IWD is higher in vegetative stage (CW1) than the reproductive stage (CW2) during both Rabi and Kharif cropping seasons. Water demand is decreasing in future for wheat while increasing for rice. IWS is decreasing substantially from surface while increasing largely from groundwater resources during Rabi. Though, IWS during kharif season is increasing largely from both surface and groundwater resources. There is mismatch in demand and supply as evident from the results suggesting 10 days early wheat planting reduces IWD by 8.0% in F1, 18.7% in F2 and 28.4% in F3 during CW1 with a decrease of 7%, 30 % and 62.56% during F1, F2 and F3 in CW2. Increased IWS with larger contribution from groundwater resources is projected for both crops in future. Water gap between demand and supply during both CW’s in future is increasing for Rabi and Kharif suggesting 10 days early planting of wheat while 20 days delay in kharif planting. Estimation of IWS by sources helped in assessing shifts in percent (%) dependency of water supply from different sources. Moreover, Spatio-temporal mismatch between water demand and supply help exploring geospatially driven water gap trends consequently, highlighting water stress hotspots during CW’s in future.

Lava­­-water interactions (LWIs) are rarely considered in lava flow hazard assessments or emergency planning scenarios, though they can generate a range of secondary hazards, including tephra blasts, rootless eruptions, disruption to water supplies, and flooding. These hazards may endanger life, damage property, and hinder evacuation or rescue efforts, so identifying the signs of LWI in the products of past eruptions may help emergency planners identify potential hazards for future eruptions. The physical products of LWI, such as abundant hyaloclastite, high proportions of fine ash, lava pillows, and irregular columnar jointing, have long been recognized in the field. However, remote sensing offers the opportunity to assess whole lava fields relatively quickly and cheaply, and allows investigation of inaccessible lava fields and planetary volcanism. In addition, the large-scale view can reveal features that are not immediately visible in the field, and tools like LiDAR can be used to strip away vegetation to show hidden morphology and structure. We present features indicative of LWI that can be identified by remote sensing techniques and discuss what they can and can’t tell us about LWI in past eruptions. We illustrate these with data from the well-documented 1783-84 Laki fissure eruption, supplemented with other case studies from Iceland, Hawai’i and the Pacific NW. In particular, the size, type and spacing of rootless cones can tell us about the availability of water and intensity of rootless eruptions. When examined in conjunction with lava flow morphology and local topography, we can learn about the local lava flux and the likely water sources and pre-eruptive landscape. In the absence of rootless cones, dendritic textures on the lava flow surface may indicate passive LWI. These textures are found across the Laki lava field, commonly in areas where the lava encountered rivers or floods, and match those at other lava basaltic flows known to have interacted with water, including the 2018 eruption of Kilauea. Together, these features are useful indicators for identifying and interpreting past LWIs, both as a complement to field observations and when field studies are not feasible.

The Biosphere 2 (B2) is a large-scale research facility owned by the University of Arizona that comprises seven enclosed biomes. Among these is the Tropical Rainforest (TRF), where environmental factors such as temperature and rainfall are managed in order to simulate a natural ecosystem. Controlling the elements that define a biotic community provides the opportunity to use B2 as a model to study the effect of climate change on carbon cycling and GHG emissions. Large amounts of carbon are stored in tropical soils, proceeding form organic compounds and metabolites that are released into the soil by plant roots. These exudates along with other plant and animal residues and living microbial biomass constitute soil organic matter. Since C released from soils contributes to a positive feedback loop of changing climate, this study seeks to characterize organic metabolites from root, rhizosphere, and bulk soil in the TRF of B2. Water extractable organic matter (OM) from collected root, rhizosphere, and bulk soil samples were cleaned up using Solid Phase Extraction prior to analysis with Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and subsequently, bioenergetic potentials (nominal oxidation state of carbon (NOSC) and Gibbs Free Energy of OC oxidation (ΔG°Cox) half reactions) of the detected compounds were calculated. We observed major differences in OM composition throughout the sampled roots, rhizosphere and bulk soil, with root and rhizosphere displaying similar chemical composition when compared to bulk soil. High amounts of lipids and proteins in the bulk soil were indicative of microbial biomass residues, suggesting that OM is utilized and transformed by microbial communities. Lignins, tannins, and condensed hydrocarbons revealed plant inputs into surface soil. After comparing estimated values of NOSC and ΔG°Cox, we concluded that OM in roots have the lowest bioenergetic potentials and are first picked up by microorganisms to undergo transformations. Moving from rhizosphere to bulk soil, the bioenergetic potential of the OM increases, indicating the refractory nature of the OM in the bulk soil. This data provides further insight to understand belowground biogeochemical cycles in soil and C cycling under extreme weather scenarios.

The future mass balance of the Antarctic ice sheet depends for an important part on the stability of the floating ice shelves that surround it, as these buttress the flow of grounded ice. Being situated relatively far north and near sea level, surface melt is a common but otherwise intermittent process on Antarctic ice shelves. Surface meltwater can form meltwater ponds, which can deepen existing crevasses that may eventually penetrate through the entire ice shelf. This process, called hydrofracturing, likely contributed to the recent disintegration of multiple ice shelves in the Antarctic Peninsula, most recently Larsen B ice shelf in 2002. A thorough understanding of surface melt processes is therefore key to improve our ability to predict future ice shelf stability and ice sheet mass loss. The snowmelt–albedo feedback plays a crucial role in Antarctic ice sheet surface melt: when snow melts, meltwater may refreeze in the snowpack, increasing the average grain size and lowering surface albedo. In turn, this enhances the absorption of solar radiation, further increasing surface melt rate. To investigate the importance of the snowmelt–albedo feedback for surface melt in Antarctica, we implemented an albedo parameterization in a surface energy balance model that calculates melt rates. In this parameterization, we can separate the impacts of dry and wet snow metamorphism on albedo evolution and melt rate. This allows us to quantify the snowmelt–albedo feedback, the results of which are presented here. Results for Neumayer Station on the Ekström ice shelf in Dronning Maud Land, East Antarctica, show that the snowmelt–albedo feedback results in a threefold increase in local melt rate compared to calculations in which the effect has been ignored. We also applied this method to weather station data from locations elsewhere in Antarctica. Finally, the same albedo parameterization was implemented in the regional climate model RACMO2. This provides the opportunity to extend this method to the entire Antarctic ice sheet, and to assess the temporal and spatial variability of the magnitude of the snowmelt–albedo feedback.

The Moon and Mars have strong regional crustal magnetic fields as shown by the observations of orbiting spacecraft. These crustal magnetic fields indicate that a core dynamo was present in the past, and it is believed that rocks formed from cooling lava retain a memory of the strength and orientation of the magnetic field that existed during their solidification. However, a major hurdle in understanding the crustal magnetic field structure is the low spatial resolution limited by the altitude of the orbiting spacecraft. Rovers are well suited for exploring the detailed structure of the crustal magnetic fields, but they also present a technical challenge due to the necessity that sources of magnetic interference from the rover be removed from the measurements. We designed a compact rover dedicated to measuring the detailed spatial distribution of the surface magnetic field. The rover is equipped with an array of magnetic sensors mounted in a rectangular grid that aims to differentiate the rover components’ own magnetic fields from the ambient magnetic field. Another magnetic sensor is placed on top of an extendable arm to provide additional measurements for verifying the ambient magnetic field inferred from grid-point measurements. The rover consists of four wheels, a Raspberry Pi single-board computer, control circuitry, and a chassis that holds the magnetometers in a rectangular array. In the prototype of the rover, commercial small-scale microelectromechanical systems (MEMS) magnetometers are used for magnetic field measurements. The test results from these design features can provide a useful reference for future lunar or Martian surface missions with rover-based experiments that measure crustal magnetic fields.

The Smithsonian – the world’s largest research, education, and museum complex – was established by the U.S. government as a public trust 175 years ago. Many of the geoscientists working for the Smithsonian’s National Museum of Natural History (NMNH) are federal employees. The federal setting offers both challenges and opportunities to actively combat structural racism, diversify our workplace, and to increase the inclusion, representation, and celebration of BIPOC in the geosciences. Our federal affiliation affords many opportunities. Smithsonian’s widely recognized brand and mission to engage diverse audiences allows our scientists to be highly visible to the public, and representation from underrepresented communities within our ranks has the potential to inspire broader participation in the geosciences. With a large and federally supported repatriation office, NMNH is in a position to lead the decolonization of geological collections and incorporate Indigenous knowledge into our collections information. NMNH fosters strong relationships with some tribal communities that provide us with excellent resources to engage Indigenous and local scientists in our research and field work. We enjoy transparency in many federal policies on hiring, promotion, salaries and benefits, and detailed equal employment opportunity (EEO) training is required for all supervisors. Federal status also presents challenges. Progress toward diversity and equity checks are tracked at the institutional level, but do not inform individual hiring decisions. There is no legal scope for targeted hires, and actions that might increase the “yield” on offers of employment, such as making an additional position for a partner, offering perks in the form of housing, child-care, higher salary, additional benefits, etc. are prohibited by federal regulation. Several future strategies emerged as priorities in our URGE pod. We will work to (1) ensure all interns receive equitable compensation and that we advertise internship availability to underrepresented communities; (2) require applicants to provide a Diversity, Equity, and Inclusion (DEI) statement for all geoscience positions; (3) implement EEO and bias training search committee members; and (4) include DEI elements in our annual performance plans.

One of the prominent effects of space weather is the variation of electric currents in the magnetosphere and ionosphere, which can cause localized, high amplitude Geomagnetic Disturbances (GMDs) that disrupt ground conducting systems. Because the source of localized GMDs is unresolved, we are prompted to model these effects, identify the physical drivers through examination of the model we use, and improve our prediction of these phenomena. We run a high-resolution configuration of the Space Weather Modeling Framework (SWMF) to model the September 7, 2017 event, combining three physical models: Block Adaptive Tree Solar wind Roe Upwind Scheme (BATS-R-US), an ideal magnetohydrodynamic model of the magnetosphere; the Ridley Ionosphere Model (RIM), a shell ionosphere calculated by solving 2-D Ohm’s Law; and the Rice Convection Model (RCM), a kinetic drift model of the inner magnetosphere. The configuration mirrors that which is used in Space Weather Prediction Center (SWPC) operations; however, the higher grid resolution can reproduce mesoscale structure in the tail and ionosphere. We use two metrics to quantify the success of the model against observation. Regional Station Difference (RSD) is a metric that uses dB/dt or geoelectric field to pinpoint when a single magnetometer station records a significantly different value than others within a given radius, indicating a localized GMD. Regional Tail Difference (RTD) performs the same calculation using relevant variables in the magnetosphere at points that map down along field lines to the magnetometer station locations on the ground. We theorize two distinct causes of RSD, the first being small-scale structure in the tail and the second being station field lines mapping to spatially separated locations in the tail. We examine the differences between RSD spikes that we can reproduce in the model and those that we cannot. We categorize spikes by cause of localized GMDs to examine model capability for each theorized cause. We investigate the improvements in our model when we switch from empirical specification of ionosphere conductance to a physics-based one, MAGNetosphere-Ionosphere-Thermosphere (MAGNIT) Auroral Conductance Model. For small-scale effects we cannot reproduce, we explore the deficiencies in our model.

Libraries are local community centers and hubs for learning, with increasing numbers of public libraries responding to the need to increase science literacy and support 21st century skills by adding STEM programs and resources for patrons of all ages. The Institute for Global Environmental Strategies (IGES), through the NASA Earth Science Education Collaborative (NESEC) cooperative agreement, is working with several libraries to pilot and implement collaborative models for engaging their local communities in STEM and citizen science. During spring and summer 2019, eight public library systems across the United States piloted activities and programs related to NASA’s GLOBE Observer citizen science app, which enables citizen scientists to contribute observations that complement NASA Earth observations. These include activities related to citizen scientist observations of Clouds (photographing clouds and recording sky observations), Mosquito Habitat Mapper (identifying water sources that are potential mosquito habitat and the presence of mosquito larvae; sampling and counting larvae; and using a clip on magnifier to identify the type of mosquito), and Land Cover (photographing the landscape and classifying land cover). Examples include the Pioneer Library System in Oklahoma, Southwest Oklahoma City Public Library, that is implementing GO Oklahoma! a citizen science campaign to collect GLOBE Observer Mosquito Habitat Mapper observations to support research by partner scientists at University of Oklahoma-Norman and Southern Nazarene University. The Los Angeles Public Library System has been field testing GLOBE Observer activities as part of its Neighborhood Science Program and will be incorporating these resources into circulating kits the library is developing for citizen scientists related to GLOBE Clouds and Mosquito Habitat Mapper that they will be piloting with Los Angelenos during fall 2019. Insights from the library pilot testing and programs include promising practices, requested resources, programming ideas and approaches, and particularly approaches to leveraging NASA subject matter experts and networks, to support local library programming.

The vicinity of the electron diffusion region (EDR) at the core of magnetic reconnection is frequently characterized by agyrotropic electron velocity distributions such as perpendicular velocity-space crescents [J. L. Burch et al., Science, DOI:10.1126/science.aaf2939 (2016)]. Although the evolving EDR is not itself an equilibrium state, its evolution may be slow on electron-cyclotron time scales. When this is the case, homogeneous equilibrium models are limited in their ability to model dynamical processes, such as instabilities and wave generation, in the presence of agyrotropic populations. In order to better study these processes, we initiate implicit PIC simulations with inhomogeneous kinetic equilibria built upon agyrotropic electron velocity distributions measured by the FPI spectrometers on MMS. The methodology involves the following elements: 1. Modeling the observed agyrotropic (e.g., crescent) and background plasma distributions 2. Numerically evaluating self-consistent inhomogeneous equilibria – including anisotropy 3. Initializing 1D, 2D, and 3D PIC simulations with the equilibria 4. Evaluating the simulation output for instabilities and the persistence of the crescents Particle tracing and other visualization tools will be employed to illustrate the underlying dynamics of particles and fields – and their interactions.