On decadal timescales, the greenhouse gas methane (CH4) is ~100 times more potent than carbon dioxide. Its abundance is increasing, many of its sources are temperature dependent. The Arctic is the site of the fastest warming globally. Feed-backs between Arctic temperature and CH4 emissions and concentrations need investigation. Unfortunately, available Arctic in situ data are extremely sparse with no marine observations outside summer. Satellite instruments measuring solar radiation reflected from the surface are ineffective in the Arctic. Thus, we leverage satellite data from AIRS, IASI-1, and IASI-2 Thermal Infrared (TIR) spectrometers, which provide year-round, day/night CH4 observations. Available in situ high latitude NOAA/ESRL surface coastal (50-85°N) flask atmospheric CH4 concentrations were compared with satellite data. We find: 1) remote sensing data revealed 150% (IASI-1, mid-upper troposphere) and 80% (surface data for Arctic stations) increases in atmospheric CH4 concentration growth rates between 2010-2014 and 2014-2017 time spans. Global NOAA/ESRL surface concentration rates increased by 90% for the same period; 2) maximum CH4 seasonal emission from the Arctic land occurs in boreal summer, while that from the Barents Kara Sea (BKS) occurs in boreal winter (Nov–Mar). Total annual Arctic Ocean CH4 emissions are preliminary estimated as ~40% of all land emissions North of 50°N; 3) marine emissions are concentrated in shelf areas within ~100 km of the coasts of major Arctic BKS lands; 4) CH4 anomalies over BKS, defined as surplus over its concentration at the North Atlantic area, grew after 2014; 5) the strongest SST increase was observed every year in the southeast Barents Sea in June due to strengthening of the warm Murman Currents and in the south Kara Sea in Sept. Direct in situ CH4 flux measurements during polar night over sea are necessary to test the satellite results.

Tides influence the allocation of river discharge to distributary channels interconnected by tidal junctions. Geometrical properties of distributary channels and nearshore coastal morphology might also play a significant role in tidal propagation, and hence control river discharge division and tidal energy transport at tidal junctions. Model simulations reveal how under different river discharge regimes, the discharge division is controlled by the tidal behavior at the junctions. Furthermore, analysis of tidal energy at the junctions indicates that the side distributaries drain or add tidal energy to the main river channel depending on the upstream discharge condition.

This study aims to give a brief overview of an ensemble of regional climate model (RCM) simulations with bias correction for daily precipitation for the Carpathian Region located in Central/Eastern Europe. Within the international initiation called the COordinated Regional Downscaling Experiment (CORDEX) EURO-CORDEX and Med-CORDEX provide RCM simulations targeting Europe as a whole or in a part at the grid resolutions of 0.44o (~50 km) and 0.11o (~12 km). The ensemble of RCMs provides a huge amount of data, which are however prone to biases compared to high resolution observations. Percentile-based bias corrections of the daily precipitation output of EURO-CORDEX and Med-CORDEX RCM ensemble at a common 0.11o × 0.11o horizontal grid resolution are performed based on the high-resolution, high-quality observational dataset: CARPATCLIM. The region covered by the CARPATCLIM dataset can be considered as the Carpathian Region for which the RCM ensemble (consisting of total six members at 0.11o resolution) of a historical period (1976-2005) and under the Representative Concentration Pathway 8.5 over two future time slices (2021-2050 and 2070-2099) are assessed. The present study focuses on precipitation climate indices over the entire Carpathian Region and two subregions representing high- and lowlands within the target region. The analyzed indices are: frequency of rainy days (RR1, days with a total rainfall of at least 1 mm), heavy precipitation days (RR10, days with a total rainfall of at least 10 mm), highest daily precipitation (RX1), maximum consecutive dry days (CDD, the duration of the longest period with < 1 mm total daily precipitation), maximum consecutive wet periods (CWD, the duration of the longest period with > 1 mm total daily precipitation). The key findings are as follows: (1) the influence of orography on seasonal precipitation change is evident throughout the analyzed periods, (2) precipitation change holds an unequivocal seasonality as most models estimate significant winter (DJF) precipitation increase (~30%), while in general drier (~20%) summers (JJA) are projected over most part of the Carpathian Region by the end of the 21st century, (3) over the subregions RR10 shows a clear signal of increase in all seasons (10-50%), except summer (~-15%), while RX1 shows increase in all seasons.

Explosive, ash-producing volcanic eruptions are a significant natural hazard with the potential for loss of life, economy, and infrastructure. Turrialba is an active stratovolcano located in the Central Cordillera of Costa Rica. The edifice is located only 35 km east-northeast of Costa Rica's capital city and poses a threat to its central valley, the social and economic hub where more than half of the population resides. The most recent eruption took place in 2016-2017, consisting of four eruption phases. Preliminary observations using SEM show significant morphological differences between the various eruption phases, including the amount of dust and crystals that are present. The morphology of volcanic ash is fundamental to our understanding of magma fragmentation, and in transport modeling of volcanic plumes and clouds. The chemistry of the ash particles produced by fragmenting magmatic foams may affect their evolving morphology throughout the various stages of eruption. In addition, eruption energetics may play a role in ash morphology. Separating the roles of chemical heterogeneity and evolving energetics requires careful examination of ash morphology and its relation to composition. In this way, we take some initial steps in closing the knowledge gap between eruption mechanisms and how and why these mechanisms are exhibited in the morphology of ash during explosive eruptions.

Deep carbon is terrestrial carbon that is not in the atmosphere or oceans or on the surface. We have a great deal of knowledge about the properties of near surface carbon, but relatively little is known about the deep carbon cycle. The Deep Carbon Observatory, was founded in 2009, to address major questions about deep carbon. Where are the reservoirs of carbon? Is there significant carbon flux between the deep interior and the surface? What is deep microbial life? Did deep organic chemistry have a role in the origin of life? This project is directed toward documenting and describing of the history of deep carbon science. The narrative begins in 1601, when William Gilbert suggested that Earth's interior behaves like a giant bar magnet. We trace across three centuries the slow evolution of thought that led to the establishment of the interdisciplinary field of Earth System Science. The concept and then development of the deep carbon cycle of burial and exhumation dates back at least two hundred years. We identify and document the key discoveries of deep carbon science, and assess the impact of this new knowledge on geochemistry, geodynamics, and geobiology. A History of Deep Carbon Science is in preparation for publication by Cambridge University Press in 2019. Its illuminating narrative highlights the engaging human stories of many remarkable researchers who have discovered the complexity and dynamics of Earth's interior.

In this study, we detail a new prediction-oriented procedure aimed at volcanic hazard assessment based on geophysical mass flow models with heterogeneous and poorly constrained output information. Our method is based on an itemized application of the empirical falsification principle over an arbitrarily wide envelope of possible input conditions. In particular, instead of fully calibrating input data on past observations, we create and explore input values under more general requirements of consistency, and then we separately use each piece of empirical data to remove those input values that are not compatible with it, hence defining partial solutions to the inversion problem. This has several advantages compared to a traditionally posed inverse problem: (i) the potentially non-empty intersection of the input spaces of partial solutions fully contains solutions to the inverse problem; (ii) the partial solutions can provide hazard estimates under weaker constraints potentially including extreme cases that are important for hazard analysis; (iii) if multiple models are applicable, specific performance scores against each piece of empirical information can be calculated. We apply our procedure to the case study of the Atenquique volcaniclastic debris flow, which occurred in the State of Jalisco (MX), 1955. We adopt and compare three depth averaged models currently implemented in the TITAN2D solver, available from vhub.org. The associated inverse problem is not well-posed if approached in a traditional way. However, we show that our procedure can extract valuable information for hazard assessment, allowing the exploration of the impact of model flows that are similar to those which occurred in the past, but differ in plausible ways.

The NASA’s Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR) mission was launched on February 11, 2015 to the Sun-Earth Lagrangian L1 point where it began to collect radiance data of the entire sunlit Earth every 65 to 110 min in June 2015. It provides imageries in near backscattering directions at ten ultraviolet to near infrared narrow spectral bands. The DSCOVR EPIC science product suite includes vegetation Earth System Data Record (VESDR) that provides leaf area index (LAI) and diurnal courses of normalized difference vegetation index (NDVI), sunlit LAI (SLAI), fraction of incident photosynthetically active radiation (FPAR) and Directional Area Scattering Function (DASF). The parameters at 10 km sinusoidal grid and 65 to 110 minute temporal frequency generated from the upstream DSCOVR EPIC BRF product are available from the NASA Langley Atmospheric Science Data Center. Whereas LAI is a standard product of many satellite missions, global diurnal courses of NDVI, FPAR, SLAI and DASF are new satellite derived products. Sunlit and shaded leaves exhibit different radiative response to incident Photosynthetically Active Radiation (400-700 nm), which in turn triggers various physiological and physical processes required for the functioning of plants. LAI, SLAI and FPAR are key state parameters in most ecosystem productivity models and carbon/nitrogen cycle. DASF provides information critical to accounting for structural contributions to measurements of leaf biochemistry from remote sensing. This poster provides an overview of the EPIC VESDR research. This includes a description of the algorithm and its performance, details of the product, initial assessment of its quality and obtaining new information on vegetation properties from the VESDR product.

CUMULOS is a tiny three-camera VIS/SWIR/LWIR sensor system flying as a hosted payload on the NASA/JPL ISARA mission, a 3U CubeSat. The CUMULOS sensors provide a small-aperture, large field-of-view, remote sensing payload suitable for testing the performance of passively-cooled commercial sensors for weather and environmental monitoring missions. The CUMULOS consists of a 0.4-0.9 µm visible CMOS camera, a 0.9 -1.7 µm short-wave infrared InGaAs CMOS camera, and a 7.5-13.5 long-wave infrared VOx microbolometer camera. All three cameras and associated electronics fit into less than 1U of spacecraft volume and were accommodated on the ISARA mission on a non-interference basis. CUMULOS is designed for point-and-stare imaging and acquires almost simultaneous 3-band coverage of regions approximately 200 x 150 kilometers in size, at ground sample distances from 130 to 400 meters from an orbital altitude of 450km, 52° inclination. Remote sensing applications being investigated include: hotspot detection (including fires, gas flares, and volcanic activity), detection of nighttime lights, cloud cover detection, surface temperature characterization, and airglow phenomenology. Operational since June 2018, the sensors have taken sample daytime and nighttime cloud imagery including, notably, the detection of airglow-illuminated clouds by the SWIR camera operating in high-sensitivity mode. The LWIR microbolometer camera provides useful single-band cloud and earth surface thermal imagery. The visible camera can provide daytime pictures as well as high-sensitivity nightlights imagery. The combination of all three cameras working together has proven quite successful for characterizing nightlights and thermal hotspots in manner similar to the much larger VIIRS payload that flies on JPSS, and for researching compact sensor nighttime weather imaging possibilities. We present example results on nightlights mapping of urban areas and road networks, detection of gas flares and other industrial heat sources, detection of urban heat islands, and demonstrate how the combination of sensors work together to map light and thermal features of rapidly developing urban areas. CubeSats sensors, such as CUMULOS, can complement existing of larger space sensors, such as VIIRS, by acting as testbeds for new spectral bands, imaging at higher resolutions over smaller fields of view, and flying in different orbits to measure nightlights signatures at different times during the night. The CUMULOS is also an engineering test bed for developing techniques for the calibration of small sensors in space, demonstrating a calibration and georegistration data pipeline, and automating CubeSat remote sensing data collection. These experiences, lessons and procedures will be described as well.

In this study, we use a doubly stochastic model to develop a short-term eruption forecasting method based on precursory signals. The method enhances the Failure Forecast Method (FFM) equation, which represents the potential cascading of signals leading to failure. The reliability of such forecasts is affected by uncertainty in data and volcanic system behavior and, sometimes, a classical approach poorly predicts the time of failure. To address this, we introduce stochastic noise into the original ordinary differential equation, converting it into a stochastic differential equation, and systematically characterize the uncertainty. Embedding noise in the model can enable us to have greater forecasting skill by focusing on averages and moments. In our model, the prediction is thus perturbed inside a range that can be tuned, producing probabilistic forecasts. Furthermore, our doubly stochastic formulation is particularly powerful in that it provides a complete posterior probability distribution, allowing users to determine a worst-case scenario with a specified level of confidence. We verify the new method on simple historical datasets of precursory signals already studied with the classical FFM. The results show the increased forecasting skill of our doubly stochastic formulation. We then present a preliminary application of the method to more recent and complex monitoring signals.

The ability to access time series data with one API would significantly enhance science data interoperability. The Heliophysics Application Programmers Interface (HAPI) is a simple, standardized mechanism for exposing time series data through a service. HAPI is being adopted by data centers within the Planetary and Heliophysics communities, especially for plasma, particle and field datasets. At the recent COSPAR meeting, the Panel on Space Weather passed a resolution encouraging data providers to have at minimum a HAPI server to deliver time series data. The COSPAR is now considering the resolution for full organizational endorsement. HAPI standardizes the two key parts of a data service: the request interface and the result format. The request interface is very simple and captures the common features of many existing data access services. For result formats, the HAPI specification allows several options, all of them streaming. Servers must provide a Comma Separated Value (CSV) result format, but may optionally provide a JSON or binary stream as well. The details of the request and result formats are described in the current version of the specification document, which is available at GitHub: https://github.com/hapi-server/data-specification. Several institutions have recently added HAPI-compliant access. These include the large Heliophysics archive at Goddard’s Coordinated Data Analysis Web (CDAWeb), as well as the Planetary Plasma Interactions node of the Planetary Data System, the Laboratory for Atmospheric and Space Physics at CU Boulder, the University of Iowa, George Mason University, and the Johns Hopkins University Applied Physics Lab. Multiple client options are available for accessing HAPI data from the growing number of servers. Autoplot (Faden, et al, 2010) and SPEDAS (http://spedas.org/wiki) both read HAPI data, and other clients (Java, Python, Matlab, IDL) can be downloaded from the HAPI Github project. The ease with which various providers have adapted existing servers to create a HAPI-compliant capability shows that it does capture a useful way to represent time series data. Because clients for reading HAPI data are also easy to create, we anticipate significant growth and interest in this emerging standard. Faden, et al, Earth Sci Inform (2010) 3:41–49, DOI 10.1007/s12145-010-0049-0

Pressure ridges are deformation features within the sea ice pack created through the collision of sea ice floes. Pressure ridges play an important role in ice drift and influence the mass and energy budgets of the Arctic Ocean. Over the past decade annual airborne surveys over Arctic sea ice have been conducted in late winter (March and April) by NASA’s Operation IceBridge (OIB) mission. A total of 74 OIB flights between 2010 and 2018 surveyed tens of thousands of kilometers of sea ice, providing observations of pressure ridges at a higher spatial and temporal resolution than previous airborne studies. Here we utilize Digital Mapping System (DMS) imagery to identify shadows cast by pressure ridge sails and, then, use these shadows to derive sail height. Over 64,000 DMS images were analyzed, allowing for more than 33 million individual sail height measurements to be calculated. We present the full sail-height distributions of new pressure ridges recently formed across a range of ice conditions on first-year (FYI) and multiyear ice (MYI), and we assess year-to-year variability. We find distinct characteristics depending on the ice type in which the pressure ridge formed. The mean and standard deviation of sail heights on FYI is ~20-30 cm lower than those formed on MYI. Maximum sail heights on FYI are ~1.5 m lower on average. Arctic sea ice is getting younger, shifting from predominantly MYI to predominantly FYI. Our results may inform new model parameterizations of pressure ridges on sea ice in the changing Arctic, thereby supporting advances in sea ice forecasting.

Multiple generations of ductile and brittle deformation recorded in the Obsidian Dome lava, California, inform on the rheological complexities of silicic lava emplacement. Understanding the non-linear rheological evolution of advancing lava is key to improving understanding of the durations, extents, and explosive hazards of future eruptions. Numerous studies of silicic lavas, at Obsidian Dome in particular, have focused on micro-scale textures and features interpreted to record flow within the conduit, primarily. How the lava flowed as a growing mass outside the conduit is largely unconstrained. Field observations at Obsidian Dome identify cycles of ductile flow followed by brittle fracturing, followed by relaxation and continued flow. Mode 1 vertical fractures often served as conduits for tephra venting, presumably following spontaneous exsolution-driven vesiculation and volume expansion deeper in the lava. Tephra, often tack-welded to the fracture surfaces, are preserved in many fractures that clearly closed-up on relaxation of the obsidian. Therefore, crossing the glass transition was likely strain rate driven, rather than cooling- or exsolution-driven that would have inhibited relaxation after the stress was released. The interplay between flow and fracturing is also evident in the ubiquity of crease structures at decimeter to decameter scales over all of Obsidian Dome. Unraveling the complexities of flow and fracturing in obsidian lavas will require and enable improved understanding of similarly non-linear rheological evolutions in ice, salt, the mid crust, and the asthenosphere.

Spectrometer/Telescope for Imaging X-rays is one of the instruments on-board the Solar Orbiter mission. It will be launched in 2020 into heliocentric orbit, with perihelion distance ~0.3 AU. The instrument is a Fourier X-ray imager operating within a range of 4-150 keV. The heliocentric orbit of the spacecraft can be highly affected by streams of solar energetic particle. This will affect the instrument operation by distorting obtained spectra and will complicate image reconstruction. Therefore we performed Geant4 simulation of particles interaction with the instrument, assuming realistic scenarios SEP events. We calculated direct detectors hits as well as secondary radiation from instrumental parts. We have found that the latter may highly influence measured X-ray spectra and reconstructed images, and have to be taken into account during data reduction.

Extension and rifting of the lithosphere is fundamental to the evolution of the continents, but the mechanism by which the lithosphere thins remains enigmatic. Using new dense magnetotelluric array data collected within the rifted margin and adjacent areas of Southeast China, we resolve the three-dimensional electrical structure of the lithosphere to constrain the process of rifting and thinning. Our measurements discover a brittle-ductile transition zone featuring low electrical resistivity and low seismic velocity in the Cathaysia Block. A southeast-directed dip is resolved for the Jiangshan-Shaoxing Fault that documents the Neoproterozoic suturing of the Yangtze and Cathaysia Blocks, and has been reactivated by the Early Paleozoic and Early Mesozoic intracontinental orogenies. It acted as a low-angle detachment fault during the Mesozoic-Cenozoic extension and rifting. Given the asymmetries of topography, electrical resistivity, Bouguer gravity anomaly and Mesozoic volcanism across the Gan-Hang Rift, an asymmetric simple shear extension model is proposed for the South China Mesozoic-Cenozoic rift system. Water content of up to 0.1 wt% and melt fraction of up to 1% are estimated at 70 km depth beneath the central Wuyi Mountains, suggesting hydration of the mantle lithosphere. The hydration weakening of the mantle lithosphere promoted both the gravitational instability and convective removal of the lowermost lithosphere in South China.

The application of a physics-based earthquake simulation algorithm to the central Apennines region, where the 24 August 2016 Amatrice earthquake (Mw6.2) occurred, allowed the compilation of a synthetic seismic catalog lasting 100,000 years, and containing more than 300,000 M ≥ 4.0 events, without the limitations that real catalogs suffer in terms of completeness, homogeneity and time duration. The seismogenic model upon which we applied the simulator code, was derived from the DISS 3.2.1 database (http://diss.rm.ingv.it/diss/), selecting all the fault systems that are recognized in the central Apennines region, with a total of 54 fault rectangular segments. The physical model on which the last version of our simulation algorithm is based includes, besides tectonic stress loading and static stress transfer as in the previous versions, also the Rate & State constitutive law. The resulting synthetic catalog exhibits typical magnitude, space and time features, which are comparable with those of real observations. These features include (i) an earthquake magnitude distribution departing from the linear Gutenberg-Richter distribution in the moderate and higher magnitude range, (ii) long–term pseudo-periodicity of strong earthquakes and (iii) short- and medium-term earthquake clustering. We found in our synthetic catalog a clear trend of long-term acceleration of seismic activity preceding M ≥ 6.0 earthquakes and quiescence following those earthquakes. A typical aspect of the observed seismicity in Italy and of the Central Apennines region in particular, is the occurrence of multiple events of M ≥ 5.5 earthquakes close to each other in space and time. A special attention was devoted to verify if the synthetic catalog includes this feature. On this purpose, we applied a specific code written in “Mathematica” to count the number of multiple events contained in a seismic catalog under a quantitative definition, finding that the synthetic catalog contains a large number of multiple events but not as frequently as in the real catalog. Lastly, as an example of a possible use of synthetic catalogs, a ground motion prediction equation was applied to all the events reported in the synthetic catalog for the production of PSHA maps (in terms of PGA).

Aerosols interact with radiation and clouds. Substantial progress made over the past 40 years in observing, understanding, and modeling these processes helped quantify the imbalance in the Earth’s radiation budget caused by anthropogenic aerosols, called aerosol radiative forcing, but uncertainties remain large. This poster presents the outcome of an international workshop and subsequent review paper, which quantify the likely range of aerosol radiative forcing over the industrial era based on multiple lines of evidence, including modelling approaches, theoretical considerations, and observations. Improved understanding of aerosol absorption and the causes of trends in surface radiative fluxes narrow the range of the forcing from aerosol-radiation interactions compared to the latest assessment by the Intergovernmental Panel on Climate Change (IPCC). A robust theoretical foundation and convincing evidence constrain the forcing caused by aerosol-driven increases in liquid cloud droplet number concentration. However, the influence of anthropogenic aerosols on cloud liquid water content and cloud fraction and on mixed-phase and ice clouds remains poorly constrained. Observed changes in surface temperature and radiative fluxes provide additional constraints. These multiple lines of evidence lead to total aerosol radiative forcing ranges that are of similar width to the last IPCC assessment but more clearly based on physical arguments.

The IRIS Data Management Center (DMC) maintains a large assemblage of pre-computed and dynamically generated quality assurance metrics for seismic data by means of its MUSTANG system. Freely accessible through web services at http://service.iris.edu/mustang, this collection of measurements includes basic statistics, data latency, data availability, miniSEED flag counts, Power Spectral Densities (PSD), Probability Density Functions (PDF), and more. The metrics produced are suitable for a wide range of uses such as data selection for research projects, identification of data and metadata problems, assessment of station health and upgrades, and characterization of environmental noise, among others. Currently, MUSTANG measurements for seismic channels span our entire primary data repository from the year 1972 to the present. We are expanding MUSTANG’s utility to the broader geosciences community by calculating measurements on our active source, PH5 data repository and by working towards including other types of data such as infrasound. We will also present improvements to metric visualization and quality assessment tools like the MUSTANG Databrowser (basic metric plots and boxplots), MUSTANGular (map-based metric plots), and ISPAQ (a stand-alone Python utility for calculating metrics for miniSEED data stored locally or at any FDSN data center).

Researchers using climate data are facing challenge to analyze the data they need. Data volumes are increasing very rapidly, and the ability to download all needed data is often not a possibility anymore. A platform called climate4impact (C4I) has been designed and developed to enhance the use of research data, to support researchers with analytics and to support other climate portals. It is currently under development within the European Project IS-ENES3 and builds on previous developments from previous IS-ENES projects, CLIPC and C3S-Magic. C4I offers a front-end and standard services (with APIs) on top of the climate data infrastructure, and it can be visited at https://climate4impact.eu. The current version provides processing services include climate indicator calculations, country based statistics and polygon extraction. C4I makes use of the DKRZ Birdhouse framework, which is an extendable and modular processing framework based on PyWPS. Data is obtained from various ESGF nodes using secure OpenDAP. C4I provides a personal basket where users can upload their own data and do research with the provided tools. The software is open, reusable, modular and packaged. Components are available via docker containers to enable easy re-use. The on-demand calculations are taking place on the front-end server, and this is not scalable and can lead to performance problems. Within the DARE project, delegation of the calculations on the DARE Platform using the DARE API has been implemented and tested in a prototype, using EUDAT B2DROP as an intermediate storage service. It is to be noted that the DARE Platform as well as the EUDAT B2 Services should be interoperable with the European Open Science Cloud (EOSC). This prototype service delegation will be made operational during the upcoming year. In the IS-ENES3 project, the web portal will be redesigned with a completely new architecture using a micro-services and containerized approach, building on experience gained during the previous projects. The next version of the portal will be built using the React framework, which allows for creating large web applications which can change data, without reloading the page. We are actively seeking input from current as well as potential users at this time, to make the next version of C4I useful to as many people as possible. The material presented here is made possible because the IS-ENES3 project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°824084.