Gaussian decomposition and Singular Value Decomposition combined with Non-Negative Least Squares (SVD-NNLS) method are compared and combined to estimate the concentration of 18 phytoplankton pigments (names and abbreviations are displayed in Table 2) from phytoplankton absorption spectra. Results show that both methods tend to overestimate pigment concentration. Gaussian decomposition method provides robust estimation of TChl-a, TChl-b, Chl-c1/2, PSC and PPC. The estimates of TChl-a, Fuco, Diato, $\beta$-Caro, Prasino, TChl-b, Zea, Viola and Lut from SVD-NNLS show reasonable estimation accuracy, while the other pigments are subjected to relatively large prediction errors. The estimated pigments concentrations are further exploited based on Diagnostic Pigment Analysis to derive four phytoplankton functional types, i.e. diatoms, prymnesiophytes, green algae and prokaryotes. By the application of these two methods to the particulate absorption spectra collected by underway spectrophotometry during three summer cruises in 2015 - 2017 in the Fram Strait, continuous surface phytoplankton functional types are estimated along the cruise course.

Several models relating remote sensing reflectance to water inherent optical properties (IOPs) have been developed. In particular, the reflectance is expressed as a function of a parameter u which is related to the absorption and backscattering coefficients. We note that the quadratic model reported by Gordon et al (1988) has been widely accepted and validated. A more recent model by Lee et al (2004) separated the contributions by water and particle scattering. Most models however, only consider oceanic waters where scattering is low. This is not the case in coastal or inland waters with high suspended sediment load. Using HydroLight simulations in waters with high scattering coefficient values, we found that the quadratic relation is not sufficient to describe the corresponding remote sensing reflectance. A polynomial of at least fourth degree is required to fit the simulation results at high u. Monte Carlo simulations were conducted to investigate the relation between the remote sensing reflectance and the u parameter at similar IOP values. Results of Monte Carlo simulations confirm the quartic relation derived from HydroLight. Application of this derived relationship in relating IOPs to remote sensing reflectance will avoid significant errors in waters of high turbidity.

Insights from the RAPID–MOCHA observation network in the North Atlantic have motivated a recent focus on the South Atlantic, where water masses are exchanged with the neighboring Indian and Pacific ocean basins. Moreover, the South Atlantic meridional overturning circulation basin-wide array (SAMBA) was recently launched to monitor variability in the South Atlantic MOC (SAMOC) at 34.5ºS. In this study, we are interested in understanding the processes which generate volume transport variability that would be observed at this latitude band. To perform this attribution, we compute sensitivities of the SAMOC at 34ºS to atmospheric state variables (e.g. wind stress, precipitation) using the adjoint of a global ocean model which is fit to a vast number of ocean observations over the past 20 years. These sensitivities isolate the impact from each atmospheric variable, and highlight the oceanic mechanisms, such as Kelvin and Rossby waves, which carry atmospheric forcing perturbations to the SAMOC. The domain of influence for the SAMOC is shown to be quite broad, covering neighboring ocean basins even on short time scales. This result differs from what has previously been shown in the North Atlantic, where Atlantic meridional overturning circulation (AMOC) variability is largely governed by dynamics confined to that basin. We convolve historical forcing variability from ERA-Interim with the computed sensitivities in order to attribute seasonal to interannual SAMOC variability to each atmospheric component. The seasonal cycle of the SAMOC is therefore shown to be largely driven by local zonal wind forcing. Interannual variability, however, is shown to have originated from remote locations across the globe, including a nontrivial component originating from the tropical Pacific. We conclude with preliminary results which employ both modeling results and an analysis of modern altimetry observations to show how El Niño Southern Oscillation variability might influence the South Atlantic.

We present a theory of pressure-dependent melting temperature to describe the physical fact that both cooling and pressurization can cause the solidification of liquid metal. Based on the Force-Heat Equivalence Energy Density Principle, an equivalent relationship between the heat energy variations during cooling and the mechanical work during pressurization is established as the molten metal solidifies. Then, this equivalent relationship is applied to develop a pressure-dependent melting temperature model without any adjustable parameter for metals. The model reveals the inner relationship between melting temperature, pressure, the bulk modulus and its first pressure derivative at zero pressure. The predicted results by our model are in good agreement with the available experimental data. Moreover, this study provides insights into the fundamental understanding of quantitative effect of pressure on melting temperature, which is in contrast to the well-known Lindemann's and Simon's equations that are both empirical melting temperature equations. It is worth noting that the melting curve of metals to very high pressure can be well predicted by our model only needing two experimental data at low pressures.

Hurricane Michael in 2018 was one of the strongest storms to impact the coastal U.S. and was unusual given that it occurred in October (i.e., late in the hurricane season) and intensified over the continental shelf. A potential contributor to this extreme event was thought to be anomalously high heat content on the shelf of the Mississippi Bight, a shelf region significantly impacted by freshwater discharge. Using available long-term time series of regional meteorological and oceanic measurements, water column conditions during the run-up to the rapid intensification of Hurricane Michael were compared to historical conditions in the region. Data for the water column heat content in the western Mississippi Bight were available at a mooring site on the 20 m isobath (Site CP) during August-October of 2018. Unusually high heat content was observed, relative to the typical summer conditions of previous years (N = 13), which resulted from the compounding effects of atmospheric events in the preceding months (August and September): a series of smaller mixing events (e.g., passage of Tropical Storm Gordon) in conjunction with a regional heatwave during most of September. Tropical Storm Gordon traveled across the shelf of the Mississippi Bight, disrupting the stratified water column as observed at Site CP. The stratification breakdown mixed the upper water column heat content deeper into the water column and subsequently allowed for the anomalously warm atmospheric conditions in September to effectively transfer heat deeper into the water column. While the mooring site was significantly distant (250 km) from the center of Hurricane Michael, these processes observed in the western Mississippi Bight likely occurred in the eastern portion of the basin as well. As a result of these compounding atmospheric effects, the shelf water column was primed to support the intensification of following tropical storms, which highlights the need for coupled oceanic-atmospheric forecast models to capture the interaction between the ocean and atmosphere and its effect on water column conditions on the shelf.

Soil water is essential for maintaining global food security and for understanding hydrological, meteorological, and ecosystem processes under climate change. Successful monitoring and forecasting of soil water dynamics at high spatio-temporal resolutions globally are hampered by the heterogeneity of soil hydraulic properties in space and complex interactions between water and the environmental variables that control it. Current soil water monitoring schemes via station networks are sparsely distributed while remote sensing satellite soil moisture maps have a very coarse spatial resolution. In this study, an empirical surface soil moisture (SSM) model was established via data fusion of remote sensing (Sentinel-1 and Soil Moisture Active and Passive Mission - SMAP) and land surface parameters (e.g. soil texture, terrain) using a quantile random forest (QRF) algorithm. The model had a spatial resolution of 100 m and performed moderately well across the globe under cropland, grassland, savanna, barren, and forest soils (R = 0.53, RMSE = 0.08 m m). SSM was retrieved and mapped at 100 m every 6-12 days in selected irrigated cropland and rainfed grassland in the OZNET network, Australia. It was concluded that the high-resolution SSM maps can be used to monitor soil water content at the field scale for irrigation management. The SSM model is an additive and adaptable model, which can be further improved by including soil moisture network measurements at the field scale. Further research is required to improve the temporal resolution of the model and map soil water content within the root zone.

We analyze a new model for growing networks, the constrained Leath invasion percolation (CLIP) model. Cluster dynamics are characterized by bursts in space and time. The model quantitatively reproduces the observed frequency-magnitude scaling of earthquakes in the limit that the occupation probability approaches the critical bond percolation probability in d=2. The model may have application to other systems characterized by burst dynamics.

Surface winds around the Antarctic continent control coupled ocean-ice processes that influence the climate system, including bottom water production, heat transport onto the continental shelf and sea ice coverage. Few studies have examined projected changes in these winds, even though it would aid in the interpretation and understanding of the ocean’s response to climate change. In this work we examine historical changes in the near-Antarctic surface winds using Coupled Model Intercomparison Project Phase 6 models and reanalysis data, and quantify projected changes to the end of the 21st Century. These changes include a significant reduction in both the easterly and meridional wind components, which under the high emission scenario amounts to 23% and 7% respectively, most of which occurs during the summer season. The projected weakening of surface winds are coherent with a trend towards a positive Southern Annular Mode and a reduction of the pole-to-coast meridional pressure gradient.

This study investigates the timing of development of the oligotrophic conditions and thickening of the West Pacific Warm Pool (WPWP) during the Pliocene. It has been hypothesized that the evolution of the WPWP and the establishment of equatorial Pacific zonal gradients are closely related to the narrowing of the Indonesian seaway (IS) as well as the closure of the Panama gateway; however, the timing of these events remain debated. Here we analysed planktic foraminiferal abundances combined with stable oxygen and carbon isotope ratios since the Pliocene at ODP Hole 807A, western Pacific and DSDP Site 214, eastern Indian Ocean. A comparison of the population of mixed-layer species (MLS) from both study sites shows a significant increase between ~3.15 and 1.6 Ma. On the contrary, shows a decrease in its population during this time, indicating oligotrophic conditions in the western tropical Pacific. The dC ratio of epibenthic foraminiferal species shows a decreasing trend from ~3.15 to ~2.0 Ma, indicating the lowering of productivity during this interval. Our data suggest that the WPWP developed ~3.15 Ma and was closely linked to the gradual closure of the IS.

Disturbances in the magnetosphere-ionosphere system cause changes in the geomagnetic field that result in ground induced currents (GICs) that are potentially hazardous to electrical systems on Earth. Harmful GICs are driven by magnetic field fluctuations with timescales generally falling in the range of 1-10 minutes; much less attention has been placed on geomagnetic field fluctuations with short timescales (< 60 seconds) because they cause transient induced currents (TICs) that have not been considered to pose a legitimate threat to electrical systems since they are similar to electrical transients due to lightning. On the contrary, short-timescale magnetic field fluctuations have been found to be capable of coupling directly to power grids and electrical systems, inducing substantial voltages without first flowing in the ground. This ionospheric current coupling poses a potential threat to any of these systems, especially electronic equipment with low operating voltage or that does not have surge protection. Transmitting devices that are at risk by such currents are becoming increasingly more prevalent in society with the growth of the Internet of Things (IoT) network. Our characterization of transient magnetic field perturbations provides detail on short-timescale changes of the magnetosphere-ionosphere coupled system and supports the assessment of possible hazards to technological infrastructure on Earth. This research is enabled by modern magnetometers, both ground- and space-based, with high sampling rate capabilities that allow for the measurement of transient surface magnetic field fluctuations with short-timescales. We present the characteristics of transient magnetic field changes observed by the MACCS array in Arctic Canada by selecting events recorded on the ground and analyzing the behavior of the electromagnetic fluctuations within the ionosphere and magnetosphere during such events.

Global mean surface air temperature (T) variability on subdecadal timescales can be of substantial magnitude relative to the long-term global warming signal and such variability has been associated with considerable environmental and societal impacts. Therefore, probabilistic foreknowledge of short-term T evolution may be of value for anticipating and mitigating some course-resolution climate-related risks. Here we present an empirically-based methodology that utilizes global spatial patterns of annual surface air temperature to predict subsequent annual T anomalies via Partial Least Squares Regression. The method’s skill is achieved via information on the state of long-term global warming as well as the state and recent evolution of the El Niño-Southern Oscillation and the Interdecadal Pacific Oscillation. We test the out-of-sample skill of the methodology using a “forecast mode” where statistical predictions are made precisely as they would have been if the procedure had been operationalized starting in the year 2000. The forecast errors for lead times of 1 to 4 years are smaller than naïve benchmarks using persistence and perform favorably relative to most dynamical Global Climate Models retrospectively initialized to the observed state of the climate system. Thus, this method can used as a computationally-efficient benchmark for dynamical model forecast systems.

The New England region in the Northeast U.S. receives high annual precipitation as rain and snow, which results in floods that endanger people and infrastructure. Owing to the complexity of hydrologic systems, increases in the frequency and intensity of large precipitation events do not always translate into increases in surface runoff measured as event flow at the basin outlet. However, recent studies have recognized positive trends in the frequency and magnitude of high-flow events in New England. For high-flow events of equal or greater than 2-year daily runoff, the runoff coefficients, or the fraction of precipitation converted into surface runoff during an event, were determined for 28 undisturbed New England basins with natural flow conditions. Results indicated that runoff coefficients increase in magnitude and variability with distance from the Atlantic coast toward the north and west. The average runoff coefficient of high-flow events across all basins is 0.90, while there exist many high-flow events with runoff coefficients greater than one. Also, runoff coefficients were generally stationary showing that flood events in undisturbed basins have remained proportional to precipitation inputs, despite increases in extreme precipitation, possibly due to shifts in evapotranspiration, snowpack, and soil moisture. Flood management efforts should continue to focus on large springtime precipitation events, which generate the highest runoff coefficients. Finally, this study can serve as a reference point for future exploration of the flood susceptibility of basins with anthropogenic alterations like dam construction or land use change.

During the last century, descriptions of sediment transport on the surface of Earth have been mostly deterministic and strongly influenced by concepts from continuum mechanics. The assumption that particle motions on hillslopes and in rivers satisfy the continuum hypothesis has provided an important foundation for this topic. Recent studies, however, have recognized that bed load and hillslope sediment transport conditions often are rarefied and do not satisfy continuum assumptions, therein pointing to the need for new ways of describing particle motions and transport. The problem of rarefied sediment transport is probabilistic in nature, and emerging methods for describing particle motions hark back to the pioneering work of Einstein (1938), who conceptualized bed load transport as a probabilistic problem. Here we provide a data set of particle travel distances and supplemental high-speed videos of particle-surface collisions collected during laboratory experiments to assess a theoretical formulation of the probabilistic physics of rarefied particle motions and deposition on rough hillslope surfaces. The formulation is based on a description of the kinetic energy balance of a cohort of particles treated as a rarefied granular gas, and a description of particle deposition that depends on the energy state of the particles. Both laboratory and field-based measurements are consistent with a generalized Pareto distribution of travel distances and predicted variations in behavior associated with the balance between gravitational heating and frictional cooling by particle-surface collisions. These behaviors vary from a truncated distribution associated with rapid thermal collapse to an exponential distribution representing approximately isothermal conditions to a heavy-tailed distribution associated with net heating of particles. The transition to a heavy-tailed distribution likely involves an increasing conversion of translational to rotational kinetic energy leading to larger travel distances with decreasing effectiveness of collisional friction. The analysis points to the need for further clarity concerning how particle size and shape in concert with surface roughness influence the extraction of particle energy and the likelihood of deposition.

Variability in precipitation frequency, intensity and duration deeply affect vegetation and erosion yields. Under climate change scenarios, alterations in precipitation are expected but it is not well understood how it could affect erosion rates and what is the role of vegetation on landscape geomorphic response. Traditional erosion models normally include basic representations of vegetation that do not account for the dynamic character of biomass variability and feedbacks with hydrological and erosion/deposition processes. Hence, using a new modelling frameworks that account for the effect of varying vegetation cover on erosion, and that includes climate change scenarios is needed. Here we use a new model: COPLAS, a tool that couples a Landform Evolution Model with dynamic vegetation and carbon pools modules to investigate the response of landscapes to climate change. The vegetation module includes a coupled photosynthesis-stomatal conductance representation that responds to climatic data inputs as temperature, CO2 concentration and water availability. We use the model to simulate the erosional and geomorphic responses of dynamic vegetation in Howard Springs (Australia) to predicted changes in daily precipitation under future CO2 concentrations of about 940 ppm. The model was calibrated using Ozflux site historical data. Catchment scale simulations were run for a period of 100 years for three scenarios (bare soil, constant and dynamic vegetation) using a daily time step. We found that, for our study case, bare soil produces on average 139% more erosion than the constant vegetation case and 124% more than the dynamic vegetation case. Moreover, an increase in precipitation of around 23% induces an increase of 25%, 35% and 43% in the erosion rates for dynamic vegetation, constant vegetation and bare soil respectively, while a decrease in 26% reduces it in 36%, 60% and 59%. This could be explained by the nonlinear relation between erosion and vegetation (higher rainfall induces higher erosion potential which can be counteracted by an increase in vegetation cover leading to a decrease in soil erodibilty). This finding highlights the importance of considering the dynamic character of vegetation in order to understand the nonlinear relations between fluvial erosion and vegetation cover.

It is now known that many spiral density waves in Saturn’s C ring are forced by resonant gravitational interactions with the planet’s nonradial oscillations. Observations of their periods have the power to reveal new information concerning subtle aspects of the planet’s internal structure. The properties of a certain class of nonradial oscillations, consisting of the inertial and rotational normal modes (i-modes and r-modes), are particularly sensitive to small departures of the internal density stratification from adiabatic, and may be especially useful in revealing such departures and their implications for any compositional gradients residing inside Saturn. We calculate the frequencies and eigenfunctions (shapes) of the i-modes and r-modes for a given suite of internal structure models and determine the Lindblad resonance locations and periods of the density waves they excite in the C ring. We find that for reasonable models of Saturn’s internal structure, the i-mode and r-mode frequencies overlap the range of frequencies of the slowest density waves observed in the C ring, that is, those having pattern speeds similar to Saturn’s rotation rate. In addition, the presence of observable density waves forced by r-modes requires Saturn to possess (at least) two statically stable (non-convective) regions, one in the deep interior and the other in the outer molecular hydrogen envelope. The inner zone is most likely stabilized by a significant compositional gradient, the outer zone by a compositional gradient, by baroclinic processes, or both. Unresolved questions remain. Currently, the model predicts that if energy is equipartitioned among the i-modes, then some slow density waves should be detectable at radii inside ~84500 km in the C ring. None have been observed inside this radius. In addition, the source of excitation of the normal modes remains to be identified. We are currently exploring whether they can draw their energy from baroclinic instability in the outer stable zone. These questions will be addressed at length at the meeting. This work is supported by the NASA SSW program.

Sustained serpentinization of peridotite within the oceanic lithosphere requires effective supply of water to systems that experience continuous expansion of the solid volume. Hence, serpentinization preferentially occurs along ridge axes and in subduction zones where tectonic activity is intense and fracturing helps generating and sustaining the permeability required to connect seafloor-near environments to depth. The slowest mid-oceanic ridges produce little melt leading to discontinuous magmatic activity with very thin to no crust along most of the ridge length and up to 8 km thick crust focused around local magmatic centers. Three types of ultra-slow ridge sections can be distinguished: i) amagmatic, characterized by scarce basaltic crust and deep seismic activity, ii) magmatic, characterized by a thin basaltic crust and intermediate depth seismic activity, and iii) volcanic, characterized by a thick basaltic crust and shallow seismic activity. At amagmatic and magmatic ridge types, aseismic zones are identified above the seismic zone. The lower limit of the aseismic zone along amagmatic sections is thermally controlled and follows a 400-500˚C isotherm corresponding to the upper temperature limit for the onset of serpentinization. This observation suggests that the aseismic zone is significantly serpentinized with ample supply of water to the peridotite-serpentine interface. Based on recorded seismic activity, we estimate the associated rock volume affected by brittle damage for the different ultra-slow ridge types. We show that damage produced by seismic activity sustains pervasive serpentinization along amagmatic and magmatic types, while it is limited in the case of volcanic sections.

CO2 enhanced oil recovery (EOR) is being increasingly deployed for the exploitation of depleted conventional oil and gas fields, due to the twofold benefit of improved recovery efficiency and reduction in carbon dioxide emissions. Geomechanics starts playing an increasingly important role with the injection of CO2 in the subsurface and the subsequent pore pressure buildup. However, the release of pressure through oil production enables a higher amount of CO2 to be introduced into the ground without causing undesirable effects. Understanding the stress perturbation due to fluid injection and withdrawal aids in comprehending the fault activation mechanism and the risks of induced seismicity. The current study evaluates the geomechanical influence of CO2 injection for enhanced oil recovery in a depleted oil field, and assesses the risk of injection and production induced seismicity as a constraint in geologic containment of CO2. The Ankleshwar field in Cambay basin in India is chosen for the study. The field is a potential CO2 EOR site due to its excellent permeability and recovery efficiency. Coupled multiphase fluid flow modeling and geomechanical analysis were carried out to study the hydro-mechanical characteristics of CO2 injection and fluid production. The rise in pore pressure near the injection site induces stress changes even far away from the site of injection due to poroelastic coupling in rocks. The risk of induced seismicity was then analyzed through simulation of fault slip potential in the field. FSP analysis suggests orientation of faults along with proximity to injection site are key parameters influencing fault stability in the Ankleshwar field.

Observations and cloud-resolving simulations suggest that a convective updraft structure drawing mass from a deep lower-tropospheric layer occurs over a wide range of conditions. This occurs for both mesoscale convective systems (MCSs) and less-organized convection, raising the question: Is there a simple, universal characteristic governing the deep inflow? Here we argue that nonlocal dynamics of the response to buoyancy are key. For precipitating deep-convective features including horizontal scales comparable to a substantial fraction of the troposphere depth, the response to buoyancy tends to yield deep inflow into the updraft mass flux. Precipitation features in this range of scales are found to dominate contributions to observed convective precipitation for both MCS and less-organized convection. The importance of such nonlocal dynamics implies thinking beyond parcel models with small-scale turbulence for representation of convection in climate models. Solutions here lend support to investment in parameterizations at a complexity between conventional and superparameterization.