Deep-sea δ18O records show a pronounced difference in Milankovitch periodicity between the Early and Late Pleistocene. δ18O is interpreted as a proxy for ice sheet volume and temperature, which led to the conclusion that glacial-interglacial cycles considerably changed their rhythm during the mid-Pleistocene. This transition is referred to as the mid-Pleistocene Transition (MPT). Specifically, the precessional component of the Milankovitch cycles is absent in Early Pleistocene δ18O records, despite its continuous presence in solar insolation forcing to the ice sheets. Climate feedbacks involving (sea) ice, geological processes and carbon and nutrient cycling have been proposed as causes of this marked change. We however show that the absence of an Early Pleistocene precession signal in deep-sea δ18O records could be the result of destructive interference of the precessional cycle in the interior ocean. Such cancellation is caused by the anti-phasing of the precessional cycle between the North Atlantic and Southern Ocean deep-water sources (see Figure). We explore the potential for cancellation in the transient setup of the Total Matrix Intercomparison model for a wide range of source signal strengths. Our results show that cancellation can cause the absence of the precessional signal due to cancellation in the interior South-Atlantic, Indian and Pacific basins. Cancellation is especially widespread for a relative end-member contribution typical for the Early Pleistocene. We therefore conclude that the precessional component is likely incompletely archived in Early Pleistocene δ18O records, and appears as an actual change in Milankovitch periodicity across the MPT. Proxies not susceptible to cancellation of precession (such as those currently retrieved across the MPT from Antarctica) would be able to verify to what extent deep-sea δ18O correctly represents Pleistocene climate.

To understand the relationships between eclogite-facies mineral assemblages, deformation microstructures, and the seismic properties of subducting oceanic crust, eclogites from the Yuka terrane, North Qaidam ultrahigh-pressure metamorphic belt, NW China were studied. Observations of mineral textures, deformation microstructures, and petrofabrics in the eclogites indicate that garnet, omphacite, and phengite were deformed by intra-crystalline deformation (i.e., dislocation creep) during prograde metamorphism. In contrast, amphibole, which was formed by the topotactic replacement of omphacite at fluid-present conditions, is considered to have been deformed by diffusional flow (dissolution–precipitation creep) during amphibolite-facies retrogression associated with exhumation. Based on the petrofabrics in the samples, the seismic properties of the eclogites were calculated depending on eclogite-facies mineral assemblages such as garnet + omphacite (GO), garnet + omphacite + phengite (GOP), garnet + omphacite + phengite + lawsonite (GOPL), garnet + omphacite + phengite + amphibole (GOPA), and garnet + omphacite + amphibole (GOA). We found that the seismic signatures of each of the eclogite-facies mineral assemblages were different. In particular, phengite-bearing eclogites (the GOP/GOPA assemblages), depending on phengite content, produced the strongest seismic anisotropy (AVp and AVs), with a strong polarization anisotropy, that was at least three times higher than bimineralic (phengite-absent) eclogite (GO assemblage). Our results show that phengite, as a stable phase at high pressure and temperature conditions, can play an important role in the creation of trench-parallel seismic anisotropy in the eclogite-facies mineral assemblages found in subduction zones.

The Wang-Sheeley-Arge (WSA) model estimates the solar wind speed and interplanetary magnetic field polarity at any point in the inner heliosphere using global photospheric magnetic field maps as input. WSA employs the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models to determine the Sun’s global coronal magnetic field configuration. The PFSS and SCS models are connected through two radial parameters, the source surface and interface radii, which specify the overlap region between the inner SCS and outer PFSS model. Though both radii are adjustable within the WSA model, they have typically been fixed to 2.5 R sol. Our work highlights how the solar wind predictions improve when the radii are allowed to vary over time. Data assimilation using particle filtering (sequential Monte Carlo) is used to infer the optimal values over a fixed time window. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model generates an ensemble of photospheric maps that are used to drive WSA. When the solar wind model predictions and satellite observations are used in a newly-developed quality-of- agreement metric, sets of metric values are generated. These metric values are assumed to roughly correspond to the probability of the two key model radii. The highest metric value implies the optimal radii. Data assimilation entails additional choices relating to input realization and timeframe, with implications for variation in the solar wind over time. We present this work in its theoretical context and with practical applications for prediction accuracy.

Fuego volcano in Guatemala began its current eruptive episode in 1999. From 2008-2015 we observed repeating and near-repeating seismic events in the long period (LP: 0.5-5 Hz) and very long period (VLP: 100-10s) bandwidths. Two separate types of repeating VLP events indicate pressurization within the shallow conduit prior to explosions with different surficial expressions, including emissions from two separate vents from at least 2008-2012. Between explosions, repeating LP events which do not have associated visible emissions provide a mechanism for small magnitude degassing. The seismic amplitudes of the LP events are 1-3 orders of magnitude lower than the amplitudes of the VLP events. The coefficient of variation of the interevent times for these repeating LP events in 2012 were all above 1.5, which suggests a renewal process driven by interactions of more than one factor. Based on the at least eight-year stability of both the LP and VLP signals and coupled with various other visual datasets, we present an updated model of the shallow conduit dynamics controlling explosive events. In this model, the VLP source acts as a possible constriction point allowing for crystal and volatiles to form local concentrations out of an otherwise steady supply of magma. High water content leads to undercooled magma and promotes rapid crystallization and the formation of partial seals within the conduit. Pressurization due to and breaking of these seals results in the modeled VLP source. Strain along the conduit margins promotes the formation of fracture networks which facilitate degassing, the opening and closing of which are sources for the LP signals. Small fluctuations in magma ascent rates therefore have drastic effects on changes in shallow magma rheology and eruption style. These small fluctuations average out over the intermediate term (week to month) to maintain observed, stable, long-term (year to multi-year) degassing rates from the volcano.

Polygonal Fault Systems (PFS) are an enigmatic class of small non-tectonic extensional faults. PFS are predominantly hosted in fine-grained sedimentary tiers and are prevalent along many continental margin basins. The genesis of PFS is widely debated and little is known about the timeframe for polygonal fault growth. We present the first measurements of throw rates for polygonal faults by measuring the vertical offset of seven age-calibrated horizons mapped using three-dimensional seismic reflection data from the Norwegian Sea. Individual polygonal faults exhibit a range of throw rate profiles through time, ranging from near linear to singly or multiply stepped. The stepped profiles have a range of short-term throw rates ranging from 0 to 18 m/Ma. Time-averaged throw rates of 180 polygonal faults over the entire 2.61-0 Ma interval are normally distributed and range between 1.4-10.9 m/Ma. We convert our PFS throw rates to displacement rates and compare these to published displacement rates for gravity driven and tectonic normal faults. We find that the displacement rates of polygonal faults mark the lower limit of a continuous spectrum of extensional fault displacement rates; they are up to two orders-of-magnitude slower than gravity-driven faults, and up to three orders-of-magnitude slower than the fastest growing tectonic faults. We attribute the ultra-slow kinematic behaviour to the non-tectonic nature of polygonal faults where throw accumulates primarily through dewatering of the largely fine-grained sediments comprising the host layers for the PFS, and differential volumetric strain between the fault footwalls and hangingwalls.

Terrestrial-aquatic interfaces such as salt marshes, mangroves, and similar wetlands provide an optimum natural environment for the sequestration and long-term storage of carbon (C) from the atmosphere, commonly known as coastal blue carbon. There are over 4 million acres of salt marsh in the US and over half of these are along the east coast of the US. Due to anthropogenic activities, this area presents the greatest nitrogen (N) pollution problem in coastal ecosystems in the U.S. as part of atmospheric N deposition, runoff, and riverine export. Ammonia (NH3) is the most abundant alkaline gas in the atmosphere. Agricultural intensification is the primary anthropogenic source of NH3 leading to a doubling of reactive nitrogen (Nr) entering the biosphere. Despite this, there are limited atmospheric measurements of NH3 concentrations in coastal areas along the east coast. The objective of this study is to advance our process-level understanding of NH3 air-surface exchange over a tidal salt marsh at the Saint Jones Reserve (DE), which is part of the National Estuarine Research Reserve System (NERRs). Continuous and high temporal resolution measurements of atmospheric NH3 concentrations were measured using a cavity ring-down spectrometer, reporting 30 min concentration averages. These high temporal resolution measurements allowed the estimation of the average diurnal cycle of NH3 fluxes using a new analytical methodology. Micrometeorological measurements were also measured using the eddy covariance system operated concurrently above the tidal marsh at the research site, which is part of the AmeriFlux network (US-StJ). This pilot study represents one of the few atmospheric measurements of NH3 over a tidal salt marsh in the eastern U.S. Such measurements are important to characterize the processes that influence the exchanges of NH3 between the atmosphere and the aquatic surface and provide baseline data to form more reliable parameterizations to simulate NH3 deposition and emissions in tidal salt marshes using surface-atmosphere transfer models.

Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM2.5. The 24-hour average concentration of PM2.5 from all sources in 12-km gridded output from all sources in California (2007–2013) was 4.91 μg/m3. The average concentration of fire-PM2.5 in California by year was 1.22 μg/m3 (~25% of total PM2.5). The fire-PM2.5 daily mean was estimated at 4.40 μg/m3 in a high fire year (2008). Based on the model-derived fire-PM2.5 data, 97.4% of California’s population lived in a county that experienced at least one episode of high smoke exposure (“smokewave”) from 2007–2013. Photochemical model predictions of wildfire impacts on daily average PM2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m3 bias) and 2013 (1.6 µg/m3 bias) while underestimating for 2009 (−2.1 µg/m3 bias). The modeling system isolated wildfire and PM2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts.

We employ Magnetospheric Multiscale, Geostationary Operational Environmental and Los Alamos National Laboratory satellites, as well as the ground magnetometer networks over Greenland and North America to study a substorm on 9 August 2016 between 9 and 10 UT.We found that during the substorm two earthward flows, whose dipolarization-injection fronts exceeded 6.5 and 4 Earth’s radii (RE) in YGSM, impinged and rebounded from Earth’s dipolar field lines at L = 6–7 downtail, where L is the McIlwain number. The impingements and rebounds ended with a substorm current system of downward R1 and upward R2 currents which grew to azimuthally cover the whole North American continent. At the fronts, regions of enhanced negative j·E′ were formed and peaked toward the end of the impingements. These regions appeared to be conjugate with eastward moving aurora (along the growth phase arc and together with eastward drifting energetic electrons at geosynchronous equatorial orbit), which manifests ionospheric Ohmic losses.

It was investigated that the reproducibility of surface wind and tracer transport simulations over complex terrain in wintertime using high-resolution (5-km, 3-km, and 1-km grid) weather and transport models, in which radioactive cesium (Cs-137) emitted from the Fukushima nuclear power plant was used as a tracer. Fukushima has complex terrain, such as mountains and valleys. The model results were validated by observations collected from the national networks of the automated meteorological data acquisition system and the hourly air pollution sampling system. The reproducibility depended on the model resolution, topographic complexity, and synoptic weather conditions. Higher model resolution led to higher reproducibility of surface winds, especially in mountainous areas when the Siberian winter monsoon was disturbed. In contrast, the model improvement was negligible or nonexistent over plain/coastal areas when the synoptic field was steady. The statistical scores of the tracer transport simulations often deteriorated due to small errors in the plume locations. However, the higher-resolution models advantageously performed better transport simulations in the mountainous areas because of the lower numerical diffusion and higher reproducibility of the mass flux. The reproducibility of the tracer distribution in the valley of the Fukushima mountainous region was dramatically improved with increasing model resolution. In conclusion, a higher-resolution model is definitely recommended for tracer transport simulations over mountainous terrain at least in the range of mesoscale model resolutions (commonly 1~10 km grids).

Low-cost air quality monitors (LCAQMs) are promising supplements to regulatory monitors for PM2.5 exposure assessment. However, the application of LCAQM in spatially extensive exposure modeling is hindered by the difficulty in performing calibration at large spatial scales and the adverse influence of LCAQM residual uncertainty after calibration. We aimed to develop an efficient spatially scalable calibration method for LCAQM and design a residual uncertainty-derived down-weighting strategy to optimize the use of LCAQM data with regulatory monitoring data in PM2.5 modeling. In California, for each monitor from PurpleAir, a global LCAQM network, we identified a station within a 500-m radius from the Air Quality System (AQS), a U.S. regulatory monitoring network. Regional calibration of PurpleAir to AQS was performed at the hourly level with Geographically Weighted Regression (GWR). The calibrated PurpleAir measurements were down-weighted according to their residual uncertainty and then incorporated into a Random Forest (RF) prediction model as a dependent variable to generate 1-km daily PM2.5 exposure estimates. The state-level PurpleAir calibration reduced the systematic bias to ~0 ug/m3 and decreased the random error by 38%. The considerably large samples also enabled quantitative analyses regarding potential factors related to the PurpleAir bias. The RF-based model with both AQS and down-weighted PurpleAir data outperformed the RF model based solely on AQS with an improved CV R2 of 0.86, an improved spatial CV R2 of 0.81, and a lower prediction error of 5.40 ug/m3. The down-weighting allowed the prediction model to show more spatial details of PM2.5 and to better detect pollution hot-spots. Our spatially scalable calibration and down-weighting strategies, for the first time, allowed an effective application of a state-level LCAQM network in high-resolution PM2.5 exposure modeling. The proposed framework can be generalized to regions worldwide for advancing the evaluation of heavy PM2.5 episodes and health-related applications.

The Advanced Topographic Laser Altimeter System (ATLAS) on ICESat-2 offers a new remote sensing capability to measure complex sea ice surface topography. We demonstrate the retrieval of six sea ice parameters from ICESat-2/ATLAS data: surface roughness, ridge height, ridge frequency, melt pond depth, floe size distribution and lead frequency. Our results establish that these properties can be observed in high fidelity, across broad geographic regions and ice conditions. We resolve features as narrow as 7 m, and achieve a vertical height precision of 0.01 m, representing a significant advance in resolution over previous satellite altimeters. ICESat-2 employs a year-round observation strategy spanning all seasons, across both the Arctic and Southern Oceans. Because of its higher resolution, coupled with the spatial and temporal extent of data acquisition, ICESat-2 observations may be used to investigate time-varying, dynamic and thermodynamic sea ice processes.

Solar Radiation Management (SRM) geoengineering is a proposed response to anthropogenic global warming (AGW)1. Stratospheric aerosol injection (SAI) is one proposed method, reliant on lofting particles into the stratosphere. Engineering reviews related to this technology approach have been sparse, with most major primary analyses now at least five years old. We attempt to bridge this gap – with a short, mainly qualitative review of recent developments in fields of engineering with potential applicability to stratospheric aerosol injection. Our analysis shows that a new conventional aircraft design is still likely to be the most dependable and affordable technology solution, with hybrid airships a potential challenger. Rockets, gas guns and MAGLEV/coilguns show some potential, although they lack the level flight capability preferred for direct aerosol distribution, without substantial additional engineering. Should very high-altitude access be required, rockets, hybrid rockets, and light-gas guns offer the required capability. Costs and performance for tethered balloons remain highly uncertain. No other methods are found to be promising. Nevertheless, the extreme accessibility of disposable balloons suggests that this method may be used primarily for reasons of political leverage, as opposed to being an optimal engineering solution.

There are potential benefits from the addition of 3-C rotational motions to traditional 3-C translational displacements for moment tensor (MT) inversions. The rotational radiation pattern is orthogonal to the shear radiation pattern, thus incorporating rotations is equivalent to gaining another observation point on the focal sphere. We demonstrate this by simulating the curl and displacement wavefields in a half-space for a regional distance station. We also demonstrate the effect of velocity gradients beneath a station on rotational motions compared to displacements. Further investigation is needed to study how this affects the MT inversion. We added rotational Greens functions to regional long-period MT inversion computing spatial gradients from f- reflectivity synthetics. We used array derived rotational motions from the Piñon Flats Observatory Array in California and Golay arrays deployed during the IRIS Community Wavefield Demonstration Experiment in Oklahoma. Well-constrained MT solutions were estimated for three earthquakes using long-period regional waves with and without rotational ground motions as test cases. Prepared by LLNL under Contract DE-AC52-07NA27344. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL release number LLNL-ABS-781439. Index Terms: 7215 Earthquake source observations, 7290 Computational seismology Plain-Language Summary Scientists have traditionally used seismometers to record earthquake generated translational ground motions using three-dimensional axes typically oriented in a vertical, north-south and east-west directions in other words a “Cartesian coordinate system”. Recent advancements in seismometer development for recording rotational or twisting ground motions about the same three-axes provide additional information, which, in addition to translational seismometers can help resolve the radiation patterns of quakes. In cases where physical access is limited, the sparse distribution of seismometers caused by, for example, ocean coasts, islands, Lunar, and Mars surfaces can prevent the complete observation of the quake radiation pattern. The combination of these two types of seismometers at a single point are useful to infer faulting mechanisms of quakes or other seismic source types than using just one seismometer. Submitted to American Geophysical Union Fall Meeting, San Francisco, CA 9-13 December 2019. S032 – Rotation and Strain in Seismology – Applications, Instrumentation and Theory S21G-0589

Peatland soils are of great interest for study and management because of their high carbon contents and known role in the global carbon cycle. However, carbon stocks have yet to be constrained in many wetland ecosystems. Relative to bogs, fens and saline coastal ecosystems, less is known about carbon stocks in freshwater marsh soils despite their global prevalence, and it is not well understood how disturbance of freshwater marshes may affect carbon-climate dynamics. To better understand the potential for freshwater marshes to be net carbon sinks, we review how freshwater marshes and associated soils are classified, and synthesize available data on short- and long-term rates of carbon accumulation in freshwater marsh soils in temperate North America. Although often described as mineral-based, our findings suggest that freshwater marshes are not restricted to mineral substrates, and that inconsistencies in classification may underestimate presumed carbon stocks. Organic carbon contents and bulk density measurements are highly variable, and can range between 1-45% and 0.04-1.5 g cm-3, respectively. Moreover, rates of carbon accumulation in freshwater marshes are often measured over recent time scales (50-100 years; on average 155 +/- 74 g C m-2 yr-1), while long-term rates (measured over centuries and millennia; on average 51 +/- 38 g C m-2 yr-1) are much more scarce. We suspect that short-term rates are markedly greater than long-term rates of carbon accumulation because they do not account for long-term carbon loss and may reflect large increases in sedimentation since European settlement in North America. However, we also suspect that long-term carbon storage in freshwater marsh soils is underestimated, and that freshwater marshes can have long-term rates of carbon accumulation similar to those reported for temperate peatlands. In this presentation, we will show that variability of rates of carbon accumulation, rates of sediment accretion, bulk density and organic carbon content in freshwater marshes needs to be better constrained in order to accurately quantify their regional and global carbon pools. We will discuss the importance for scientists to specify timeframes over which they are measuring rates of carbon accumulation so that the capacity for wetlands to be net carbon sinks can be correctly understood.

Measurements of reflected solar radiation by imaging spectrometers allow to quantify water in different states (solid, liquid, gas) thanks to the discriminative absorption lines in the solar spectrum. We developed a retrieval method to quantify the amount of water in each of the three states from spaceborne imaging spectroscopy data, such as those from the German EnMAP mission. Our retrieval couples atmospheric radiative transfer simulations from the MODTRAN5 radiative transfer code to a surface reflectance model based on the Beer-Lambert law. The model is inverted on a per-pixel basis using a maximum likelihood estimation formalism. Based on a unique coupling of the canopy reflectance model HySimCaR and the EnMAP end-to-end simulation tool EeteS, we performed a sensitivity analysis by comparing the retrieved values with the simulation input leading to an R2 of 0.991 for water vapor and 0.965 for liquid water. Furthermore, we applied our algorithm to airborne AVIRIS-C data to demonstrate the ability to map snow/ice extents as well as to a CHRIS-PROBA dataset for which concurrent field measurements of canopy water content were available. The comparison between our retrievals and the ground measurements showed an overall R2 of 0.80 for multiple crop types and a remarkable clustering in the regression analysis indicating a dependency of the retrieved water content from the physical structure of the vegetation. In addition, our algorithm is able to produce smoother and more physically-plausible water vapor maps than the ones from the band ratio approaches used for multispectral data, since biases due to background reflectance are reduced. The demonstrated potential of imaging spectroscopy to provide accurate quantitative measures of water from space will be further exploited using upcoming spaceborne imaging spectroscopy missions like PRISMA or EnMAP.

PM10 has natural and anthropogenic sources, it is an urban air pollutant from desertic areas or emitted by industry and traffic activities, it reduces visibility and threatens human wellbeing mainly in big cities. Casablanca concentrates many industrial units and a large vehicle fleet. The rate of urbanization in the metropolis and the population density are the highest in Morocco. Marrakech is one of the most populated cities in the country where the motorization rate has increased during recent years. The present work is based on PM10 daily measurements between 2013 and 2016. The main objective is to assess the concentrations of PM10 in Casablanca and Marrakech and study their relationship with the atmospheric circulation. First, we assessed PM10 correlations with climate indexes (NAO and MO), then we characterized the contribution of large-scale atmospheric patterns related to PM10 extreme events. The novelty of this research is the creation of a new climate index to characterize the oscillation, in the country’s southern desert, between the Saharan depression and the Azores high. The time series of the new Saharan Oscillation Index (SaOI) were calculated. This study has demonstrated the relationship between MO and PM10 averages and has shown that particulate pollution in the study area is partly induced by continental northeasterly to southwesterly flow. This flow is triggered by the Saharan trough and managed by the high-pressure area in the north. The assessed correlations related to the SaOI confirm the relationship between this index, PM10 averages, and MO and NAO indexes mainly in winter. The Saharan Oscillation is the new relevant key to understand worldwide pollution by fine particles.

Recent activity has provided new insights into the causes of surface deformation in and around the Yellowstone Caldera, a topic that has been debated since the discovery of caldera-floor uplift more than four decades ago. An episode of unusually rapid uplift (>15 cm/yr) centered near Norris Geyser Basin along the north caldera rim began in late 2013 and continued until a Mw 4.9 earthquake on 30 March 2014; thereafter, uplift abruptly switched to subsidence. Uplift at rates of several cm/yr resumed in 2016 and continued at least through the end of 2018. Modeling of Global Positioning System (GPS) and interferometric synthetic aperture radar (InSAR) data suggests an evolving process of deep magma intrusion during 1996-2001 followed by volatile ascent and accumulation at shallow levels, perhaps as shallow as a few hundred meters depth. The preferred deformation model in which the volatiles accumulated is a shallow uplifted (domed) reservoir. The depth of shallow volatile accumulation appears to have shallowed from the 2014 to the 2016 deformation episode, from 3.2 km depth to 1.8 km depth respectively, and frequent eruptions of Steamboat Geyser since March 2018 might be a surface manifestation of this ongoing process. Hydrothermal explosion features are prominent in the Norris Geyser Basin area, and the apparent shallow nature of the inferred volatile accumulation might represent an increased risk of hydrothermal explosions in the vicinity of Norris Geyser Basin.

The winter Arctic Oscillation (AO) is important for understanding the Northern Hemisphere climate variability and predictability. However, ENSEMBLES models produce inconsistent predictions when applied to the interannual variability of the 1962–2006 winter AO. In this study, the interannual increment of the winter AO index (DY_AOI) during 1962–2006 is first improved by a dynamical‐statistical model with two predictors: the preceding autumn Arctic sea ice and the concurrent winter ENSEMBLES‐predicted sea surface temperature over the North Pacific. Next, the improved final AOI is obtained by adding the improved DY_AOI to the preceding observed AOI. Because the interannual increment approach can amplify prediction signals and takes advantage from the previous observed AOI, this method shows promise for significantly improving the interannual variability prediction capabilities of the winter AO during 1962–2006 in the ENSEMBLES models. Therefore, this study offers important insights for AO predictions, even other climate variables predictions.