The role of waves in the propagation, scattering and energization of electrons in the solar wind has long been a topic of interest. Conversely, understanding the excitation of waves by energetic electrons can provide us with a diagnostic for the processes that accelerate the electrons. We will discuss two different processes: (1) the interaction of narrowband whistler-mode waves with solar wind electrons, and (2) how periodic Type III radio bursts yield clues to small-scale acceleration of energetic electrons in the solar corona. Waveform captures in the solar wind at 1 AU obtained by the STEREO revealed the existence of narrowband large amplitude whistler mode waves, propagating at highly oblique angles to the magnetic field. Similar waves are less commonly seen inside .2 AU by Parker Solar Probe. The differences provide clues for understanding electron propagation, scattering and energization. Type III radio bursts have long been used as remote probes of electron acceleration in the solar corona. The occurrence of periodic behavior in Type III bursts observed by Parker Solar Probe, Wind and STEREO when there are no observable flares provides a unique opportunity to diagnose small-scale acceleration of electrons in the corona. Periodicities of ~ 5 minutes in the Solar Dynamics Observatory Atmospheric Imaging Assembly (AIA) Extreme Ultraviolet data in several areas of an active region are well correlated with the repetition rate of the Type III radio bursts. Similar periods occur in the Helioseismic and Magnetic Imager (HMI )data. These results provide evidence for acceleration by wave-modulated reconnection or small-scale size waves, such as kinetic Alfven waves, even during intervals with no observable flares. The possible connections between these two phenomena will be addressed.

Data maturity describes the degree of the formalisation/standardisation of a data object with respect to FAIRness and quality of the (meta-) data. Therefore, a high (meta-) data maturity increases the reusability of data. Moreover, it is an important topic in data management, which is reflected by a growing number of tools and theories trying to measure it, e.g. the FAIR testing tools assessed by RDA(1) or the NOAA maturity matrix(2). If the results of stewardship tasks cannot be shown directly in the metadata, reusers of data cannot easily recognise which data is easy to reuse. For example, the DataCite Metadata Schema does not provide an explicit property to link/store information on data maturity (e.g. FAIRness or quality of data/metadata). The AtMoDat project (3, Atmospheric Model Data) aims to improve the reusability of published atmospheric model data by scientists, the public sector, companies, and other stakeholders. These data are valuable because they form the basis to understand and predict natural events, including the atmospheric circulation and ultimately the atmospheric and planetary energy budget. As most atmospheric data has been published with DataCite DOIs, it is of high importance that the maturity of the datasets can be easily found in the DOI’s Metadata. Published data from other fields of research would also benefit from easily findable maturity information. Therefore, we developed a Maturity Indicator concept and propose to introduce it as a new property in the DataCite Metadata Schema. This indicator is generic and independent of any scientific discipline and data stewardship tool. Hence, it can be used in a variety of research fields. 1 https://doi.org/10.15497/RDA00034 2 Peng et al., 2015: https://doi.org/10.2481/dsj.14-049 3 www.atmodat.de

In 2019 sprite observations appeared on You-Tube showing green emissions in the top of some sprites and after the main sprite. The emissions were named green ghosts. We present here similar color camera observations made on 24 and 25 May 2020 from Lamy, NM. The recordings were made at 30 fps. The green ghost increased in brightness for 3 to 4 frames after the main ‘jellyfish’ sprite and decayed thereafter. The delayed green emissions are likely from atomic oxygen at 557.7 nm, the auroral green line, which is a forbidden atomic oxygen emission with a radiative life time of 0.7 s. In the atmosphere the emissions are affected by quenching and at the altitude of the green ghost the decay time constant is substantially less. We suggest that the green ghost is generated by super thermal electrons exciting ambient atomic oxygen (only 4.1 eV required). The electrons are energized by the large-scale sprite electric field, which initially caused the sprite, and decays over some time after the sprite. We present a simple model based on this idea. The model assumes an exponentially decaying sprite E-field and reproduces the observed delayed peak in the green emissions and the subsequent decay of the emissions.

There are records of past Earth climates that were ice-free all the way to the poles (Barron 1983), which can be described as “hothouse” climates. These hothouse climates can be contrasted with an “all-tropics” planet, where the tropics are defined by the atmospheric dynamics, i.e. the Hadley Cell extent (Faulk et al. 2017). This classification is thus primarily dependent on a planet’s rotation, rather than its ice-free extent or surface temperatures. We investigate the parameter space between Earth and an all-tropics world using the open-source GCM Isca, developed by Vallis et al (2018). We take an Earth analog and perform a parameter sweep in two dimensions: global reservoir depth (10m, 1m, 1cm) and rotation period (8 days, 4 days, 1 day). The sweep will allow us to explore the effects of surface liquid coverage and large-scale atmospheric circulation on an Earth-like climate. To better represent the distribution of surface water, we utilize the surface hydrology scheme developed by Faulk et al. (2020) for the Titan Atmosphere Model. In this presentation we provide a status report and analysis of initial findings.

In the first several hours following an earthquake, municipalities are often forced to rely upon reports from first responders, reconnaissance along disrupted roadways by emergency personnel, or wait for aerial surveillance and remote sensing. The latter is expected to take at least 12 hours, a crucial period following a major earthquake in which situational awareness can be greatly improved using existing seismic risk modelling tools. This work presents a new initiative to develop a rapid disaster modelling protocol for earthquakes in British Columbia (BC). We explore best practices and the feasibility of using immediately available seismic data in the existing OpenQuake Canada framework to model the impacts to people, the built environment, and the economy from an earthquake in near real-time. The current prototype integrates observed ground motion data from regional strong motion seismometers, like the BC Smart Infrastructure Monitoring System, with physical exposure data from Natural Resources Canada’s Human Settlement Layer to report on key metrics for early response: collapsed buildings, entrapment injuries, hospital demand surge, roadway debris which may block response, and immediate mass care needs like shelter requirements. These indicators will be ported to the British Columbia Common Operating Picture Portal, the online situational awareness and mapping platform for authoritative, collaborative and coordinated distribution of emergency management information in the province. These outputs could be made available within tens of minutes of the earthquake occurring, potentially affording emergency managers the opportunity to best direct resources to save lives and reduce suffering.

The NOAA Physical Sciences Laboratory produces the Global Ensemble Forecasting System (GEFS) which comprises 11 ensemble members (1 control and 10 perturbation runs) for over a 36-year period (December 1984 to present), with forecasts initialized every day for the next 16 days (first 8-day forecasts obtained from a high-resolution grid and the next 8-day forecasts from a low-resolution grid). The system provides 36 variables related to a wide range of hydrometeorological processes. In this study, we assess the predictability of precipitation within the context of statistical downscaling using a minimum set of predictor variables (precipitation and temperature). We use feedforward backpropagation neural networks with a suite of training algorithms to determine which variables (features) are of most relevance at different forecast lead times. The outcome of this study will significantly benefit short-term flood forecasting using GEFS data.

COVID-19 is a deadly pandemic affecting cities in the US, which slows down life and has affected many different sectors of our daily lives such as business, travel, hospitality, and education. With the growing COVID-19 cases, some of the states have issued advisories to the people to stay home and keep social distancing. It has been observed that people have followed the social distancing regulations in some states, whereas in others the regulations were not heeded. We have analyzed various atmospheric parameters over the capital cities of the US during the COVID-19 lockdown. We have carried out an analysis of the daily Aerosol Optical Depth (AOD) and Nitrogen Dioxide (NO2) data derived from the MODIS Terra, Aqua, and AIRS satellite, which could provide information about the decline in traffic emissions during the period January – June 2020. Comparison of this data with the same period of 2019 shows a decline in AOD and NO2 which can be due to the fact that some of the US capitals have strictly followed social distancing and some of the states ignored and as a result the COVID-19 cases have surged in many cities. We have studied PM2.5 using the published data from the Environmental Protection Agency (EPA) and the total column of ozone retrieved from OMI AURA satellite. A decline in the particle matter (PM2.5) and observed an increase in the total column of ozone. The COVID-19 lockdown shows an improvement in air quality, good for human health but on the other hand, lockdown has seriously impacted the day to day life.

Managing river temperature in highly urbanized stream systems is critical for maintaining aquatic ecosystems and associated beneficial uses. Elevated river temperatures arise from warm surface inflows from impervious areas, channelization, the absence of riparian forests, and the lack of groundwater-surface water interactions. In the current work, we utilize a mechanistic river temperature model, i-Tree Cool River, to evaluate the cooling impacts of alternative ecological restoration scenarios: a) shading effects of tree planting in riparian areas and b) alternative streambed materials. The model was calibrated and validated on a 4.2 km reach of the Compton Creek in the Los Angeles (LA) River watershed, California, for low and high flow periods. The Arroyo Chub and Stickleback were considered the target species for analyzing thermal habitat suitability. River temperature simulations showed that like the ambient air temperature. The thermal response of the river in high flow periods was a function of upstream river temperature , where in low flow periods river water temperature was most affected by the tested restoration scenarios. Tree planting in the riparian corridor decreased the median thermal metrics: Max Weekly Max, Max Weekly Average, and Min Weekly Min Temperatures by an average of 3 ℃ (13%) to 20.4 ℃, 19.7 ℃, and 17.8 ℃, respectively. Using limecrete as an alternative bed material to the current concrete bottom decreased the median thermal metrics by an average of 0.9 ℃ (4%) to 22.7 ℃, 22 ℃, and 19 ℃, respectively. Combining the two scenarios decreased the river temperature metrics by an average of 4 ℃ (18%) to 18.2 ℃. Besides riparian vegetation, altering bed material is an impactful option in case of groundwater contamination and if channelized urban corridors lack the substrate to support vegetation. The use of ecological restoration scenarios resulted in summertime temperatures were within the documented spawning temperature thresholds and therefore temperature would not be a limiting factor in the potential reintroduction of the Arroyo Chub and Stickleback to Compton Creek. This tributary could be considered as a potential refuge and improved fish habitat in the LA basin during low flow periods.

Greenhouse gas (GHG) emission metrics, that is, conversion factors to evaluate the emissions of non-CO2 climate forcers on a common scale with CO2, serve crucial functions upon the implementation of the Paris Agreement. While different metrics have been proposed, they have not been investigated under a range of pathways, including those significantly overshooting the temperature targets of the Paris Agreement. Here we show that cost-effective metrics that minimize the overall cost of climate mitigation are time-dependent, primarily determined by the period remaining before the eventual stabilization, and strongly influenced by temperature overshoot. Our study suggests that flexibility should be maintained to adapt the choice of metrics in time as the future unfolds, if cost-effectiveness is a key consideration for global climate policy, instead of hardwiring the 100-year Global Warming Potential (GWP100) as a permanent feature of the Paris Agreement implementation as is currently under negotiation.

Diverse, complex data are a significant component of Earth Science’s “big data” challenge. Some earth science data, like remote sensing observations, are well understood, are uniformly structured, and have well-developed standards that are adopted broadly within the scientific community. Unfortunately, for other types of Earth Science data, like ecological, geochemical and hydrological observations, few standards exist and their adoption is limited. The synthesis challenge is compounded in interdisciplinary projects in which many disciplines, each with their own cultures, must synthesize data to solve cutting edge research questions. Data synthesis for research analysis is a common, resource intensive bottleneck in data management workflows. We have faced this challenge in several U.S. Department of Energy research projects in which data synthesis is essential to addressing the science. These projects include AmeriFlux, Next Generation Ecosystem Experiment (NGEE) - Tropics, Watershed Function Science Focus Area, Environmental Systems Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE), and a DOE Early Career project using data-driven approaches to predict water quality. In these projects, we have taken a range of approaches to support (meta)data synthesis. At one end of the spectrum, data providers apply well-defined standards or reporting formats before sharing their data, and at the other, data users apply standards after data acquisition. As these projects continue to evolve, we have gained insights from these experiences, including advantages and disadvantages, how project history and resources led to choice of approach, and enabled data harmonization. In this talk, we discuss the pros and cons of the various approaches, and also present flexible applications of standards to support diverse needs when dealing with complex data.

The potential commonality of prebiotic chemical processes on Titan and the primitive Earth makes Titan a prime body of astrobiological interest. Amino acid synthesis can occur if the abundant simple organics on Titan’s surface can mix with liquid water. Because events that melt surface ice, such as impacts, are rare, it is essential to recognize how long the synthesized molecules remain intact on Titan’s surface. The degradation of biomolecules in extraterrestrial environments can be estimated by combining theoretical work about energy deposition on the surface with experimental results from irradiation of organic molecules. We modelled the destruction of amino acids on the surface of Titan, something absent in current literature. We chose Glycine, Alanine, and Phenylalanine as our molecules of interest due to relevant experimental results for their radiation stability at Titan temperatures. Titan’s thick atmosphere prevents solar radiation and energetic particles trapped in Saturn’s magnetosphere from reaching the surface. The dominant source of energetic radiation at the surface of Titan is the diminished flux of Galactic Cosmic Rays (GCR’s) that penetrate the atmosphere. Sittler Jr et al. (Icarus, 2019) modeled surface GCR flux to be ~10^-9 ergs/cm^3/s. Using the GCR flux, in conjunction with the half-life doses at T=100 K from Gerakines et al. (Icarus, 2012), we estimate the half-lives to be 7.69 x 10^12;, 5.07 x 10^12, and 5.82 x 10^12 years for Glycine, Alanine and Phenylalanine, respectively. These extraordinarily long half-lives on Titan’s surface, as compared to similar calculations for amino acids on Mars, Europa, or Pluto, are directly the result of reduced energy deposition due to the atmosphere. We thus conclude that the degradation of these three amino acids by GCR flux is insignificant over geological time, and will not be an essential factor in interpreting the chemistry from Titan’s surface samples from future missions, such as Dragonfly.

Studies on the molecular mechanisms of microbial adaptation in chaotropic and low water activity (aw) environments are poorly understood. Chaotropic environments are characterized as salt rich, MgCl2 and CaCl2, which lowers the availability of water for biological processes. PATRIC, an integrated genomic browsing tool containing vast libraries of sequenced genomes, can help us identify unique genetic markers in chaophilic and xerophilic microbes. Halophilic microbes are characterized as obligate hypersaline with the ability to tolerate exposure to chaotropic agents. Microbes with the greatest tolerance in these extreme environments must have advanced adaptive methods. Halobacterium salinarum and Haloquadratum walsbyi are chaotolerant and well adapted to low water activity. Haloquadratum walsbyi is unique among the halophilics as having the highest tolerance for chaotropes and its square shape. Performing comparative genomics using fully sequenced halophilic archaea such as Halobacterium salinarum NRC-1, a model halophile, and Haloquadratum walsbyi C23, we were able to identify genes that confer adaptation to chaotropic and low aw environments, as well as individual adaptations that may be responsible for the varying levels of tolerance in chaotropic environments . Characterizing genes associated with chaotolerance and low aw adaptations can help elucidate the cellular functions that make these microbes unique. Chaotropic brines may be used as analogs to study the origin of life and the possibility of suitable environments hosting extremophilic microbes on other planets like the Martian brines and the icy moons of Europa; therefore, studying the microbiome of chaotropic environments are essential in the field of astrobiology.

We present a new approach for the analysis of high-resolution digital camera photographs taken by photographers who have fortuitously been able to capture rare events such as the glowing sky phenomenon known as STEVE. This method is especially effective with a time lapse series of images of the night sky taken under constant camera settings with a steady pointing. Stars, planets and satellites seen in such images can be used to determine precise and accurate registration of camera pixels to coordinates of angular altitude and azimuth. The location of satellites in the image enables precise and accurate synchronization of the images. We apply these techniques to the series of photographs of STEVE taken on 25 July 2016. We confirm the altitude structure previously found for STEVE. We find it most likely that the green picket fence features often seen during STEVE events are produced by auroral electron precipitation. With the precipitation assumption, we are able to extract novel information about the energy spectrum of the particles responsible for the production of STEVE luminosity in this particular event. Similar analyses of archived digital photographs may constitute a treasure trove of important data for improved understanding of rare and transient events such as STEVE.

An upper-crustal intrusive network in the 201.5 Ma, rift-related Central Atlantic Magmatic Province is exposed in the western Newark basin (PA, USA). Alpha-MELTS modeling was used to track magma evolution starting with initial pyroxene crystallization at depth (1000-500 MPa); plagioclase crystallized during ascent in the upper crust. For magma emplaced at 5-6 km depth (170 MPa), six MELTS models were generated to bracket different composition, H2O (1-3 wt.%), and crystallinity (28-49 vol.%). Corresponding magma viscosities evolved from 3 to 1624 Pa-sec (predicted using Giordano et. al 2008; Moitra and Gonnermann 2014). Detailed crystal mush structures in a diabase sill are revealed in a dimension stone quarry. Ubiquitous asymmetric modal layers a few mm thick comprising plag-rich layers (PRL, 75% modal plag) overlying more pyx-rich layers outline the tops of hundreds of dm-m scale flow lobes in the quarry. Tabular plag in PRL show shape-preferred orientations, tiling, and pressure shadows around larger pyx that resemble analog experiments on particle slurries and indicate flow with limited mechanical compaction. During magma emplacement, recursive interactions of propagation, sorting, and crystallization self-organized as flow lobes with plag entrained and aligned along lobe tops. Our calculations show plag separation can reduce bimodal suspension viscosity; a positive feedback likely enhanced by shear thinning and crystal alignments. EDS analyses and X-ray maps show that plag has oscillatory-zoned cores (An82-67) with patchy-zoned mantles (An67) filled in by An66-63. In PRL, plag are cemented together by An62-55; Na-rich rims occur next to qtz-Kspar pockets. By the end of cementation, PRL liquid volume was significantly reduced to 11-18% compared with 28-45% in overall magma based on MELTS models for An62-55 plag. Diabase suspension viscosity increased to >6000 Pa-sec; PRL viscosity cannot be modeled by equations based on random packing. PRL with aligned interlocking crystals were more rigid and less permeable than surrounding diabase. Upward flow of magma after modal layer development was channelized into pipes truncated and deflected by PRL. Thus, lateral flow during emplacement developed sub-vertical heterogeneities that exemplify complex mush rheology over m-scale distances.

The community of Kotzebue, located on the coast of Kotzebue Sound, which is northeast of the Bering Straits adjacent to the Chukchi Sea, is reliant on the waters around Kotzebue Sound for food and economy. There have been reports of cyanobacterial blooms in these waters around Kotzebue but they have not been systematically studied yet, because the region is sparsely populated with few in-situ observations. Cyanobacteria often form surface blooms in freshwater and coastal ecosystems which can be detected using remote sensing techniques. Cyanobacteria are found to have low nutritional value and many species of cyanobacteria produce cyanotoxins, and thus can be harmful to aquatic life and cause public health hazards. In addition, consumption of decaying cyanobacterial blooms by microbes depletes oxygen level which can lead to hypoxia, adversely impacting the benthic community. As the Arctic is warming twice as fast as the rest of the planet due to climate change, thawing permafrost is releasing nutrients that might be enhancing cyanobacterial blooms in the coastal, marine and lacustrine waters of Alaska. In this study, we used remote sensing to study phytoplankton biomass, turbidity and cyanobacterial blooms between mid-June to end of September each year from 2013 to 2019 when the waters around Kotzebue are ice-free. Using images from Landsat-8 and Sentinel-2, processed using ACOLITE software, we investigated spatial and temporal changes in water quality parameters such as turbidity and chlorophyll concentration between June and September. We used a combination of true-color images and fai (floating algal index) to detect cyanobacterial blooms. There were about two scenes from Sentinel-2 and about one scene from Landsat-8, for a total of about three scenes every week between June and September. Of these, only 49% of the images were cloud-free. Of the cloud-free images, 29% were found to have a cyanobacterial bloom between August and September for an average of two to four scenes every year. Most of the cyanobacterial blooms were detected in Kobuk Lake near Kotzebue, and nearby sites in Hotham Inlet and Selawik Lake. In 2013, 68% of the images were cloudy which was the highest in the observed years and no cyanobacterial blooms were detected.

Open source in-situ environmental sensor hardware continues to expand across the geosphere to a variety of applications. These systems typically perform three fundamental tasks: sample sensors at a specified time or period, save data onto retrievable media, switch power to components on and off in between sample cycles to conserve battery energy and increase field operation time. This is commonly accomplished through integrating separate off-the-shelf components into the desired system such as: power relays, SD card hardware, Real-Time Clocks (RTCs), and coin cell batteries. To enable faster prototyping, the Openly Published Environmental Sensing Lab abstracted all of these requirements into a single PCB that can be dropped into any project to achieve these commonly-required capabilities. The hardware is laid out in a “Feather” form factor, a popular configuration in the open-source hardware community, to easily mate with other industry standard products. The onboard RTC acts as an alarm clock that wakes a user-attached micro controller from low-power sleep modes in between sample cycles. By integrating all these components into a single PCB, we save cost while significantly reducing physical system size. The design as well as a suite of code functions that enable the user to configure all the Hypnos board features are detailed. For more information, please visit open-sensing.org/projects.

Disaster risk reduction relies on quantitative estimates of the future impacts and consequences of known hazard threats in order to evaluate proposed mitigation and adaptation measures. Natural Resources Canada is collaborating with the Global Earthquake Model Foundation on the first ever national seismic risk assessment in Canada to inform disaster risk reduction planning by individuals, businesses and organizations working across all jurisdictional levels. The 2020 National Seismic Risk Model incorporates the 6th Generation National Seismic Hazard Map, a novel physical exposure model for the entire country, localized exposure models based on a machine learning approach to building categorization, and HAZUS-based earthquake building performance functions. Before results can be transmitted to end users, the model must be validated in a Canadian context using observations from real world disaster events or pre-existing catastrophic risk models. This study focuses on benchmarking the 2020 Canadian National Seismic Risk Model using shaking intensities and physical impacts recorded from the 2001 Mw 6.8 Nisqually and 2012 Mw 7.8 Haida Gwaii events, and the results of a 2013 catastrophic risk assessment performed by AIR Worldwide to evaluate the potential impact of major earthquakes in eastern Quebec and Cascadia. We compute anticipated building damage, economic loss, and fatalities for these benchmark scenario earthquakes using the OpenQuake engine and the national exposure dataset. Preliminary results indicate that the model results are largely consistent with observed or predicted impacts of these earthquakes in Canada, after adjusting for economic and population growth. Subsequently, we will evaluate the impact of running the Cascadia scenario using a regional building-level exposure database versus the national level inventory. Ultimately, this work will assess the ability of the National Seismic Risk Assessment to reproduce expected results, to ensure the applicability of this model in anticipating future outcomes at the national and local level.

Years of the Maritime Continent or YMC was designed to improve our knowledge of the weather-climate systems over the MC and their numerical simulation and prediction skill. Since its first field campaign in November 2017, many intensive observations have been carried out under the coordination with the MC countries. Although currently some observations have been postponed due to COVID-19 pandemic, field campaigns are expected to continue beyond 2021. Up to now, some key information could be obtained, which suggest future approaches. In particular, diurnal cycle of rain near the coast is one of major targets, as they are dominant component of precipitation in this region. Some studies suggest the important role of temperature contrast between land and ocean, and inaccurate initial sea surface temperature conditions might cause a delay of offshore propagation of rainfall region. This fact provides a clue to improve simulation of precipitation behavior over the MC. In addition, during the campaign, several new observation tools have been introduced. For example, autonomous surface vehicle (ASV) had been deployed and measured surface meteorology as well as sea surface condition. Besides, GNSS-derived water vapor measurement was successfully carried out. Those results suggest that such ASVs equipped with new tools can be used to monitor accurate sea surface condition without significant cost and time. However, usually those instruments are not allowed to operate freely in the MC. Thus, based on collaboration with the MC countries, researchers in the MC are highly expected to take this role as regional representative. In this presentation, we will also show other results which provide tips for future direction.