Tropical cyclones are severe weather events which have massive human and economic effect, so it is important to be able to understand how their location, frequency and structure might change in future climate. Here, a lightweight Deep Learning model is presented which is intended for detecting the presence or absence of tropical cyclones in running numerical simulations. This model has been developed to investigate the avoidance of saving vast amounts of data for analysis by filtering data during simulations so as to save only relevant data. Subsequent analysis workflow can target that data, avoiding the need to save all simulation outputs for cyclone analysis. The model was trained on ERA-Interim reanalysis data from 1979 to 2017 and the training concentrated on delivering the highest possible recall rate (successful detection of cyclones) while rejecting enough data to make a difference in outputs. When tested using data from the two subsequent years, the recall rate was 92% and the precision was 36%. For the desired filtration application, if the desired target included relevant meteorological events, the effective precision was 85%. The recall rate compares favourably with other methods of cyclone identification having the best Area Under Curve for the Precision/Recall (AUC-PR) and using the smallest number of parameters for both training and inference.

The Southern Ocean (SO) connects major ocean basins and hosts large air-sea carbon fluxes due to the resurfacing of deep nutrient and carbon rich waters, driven by strong surface winds. Vertical mixing in the SO, induced by breaking waves excited by strong surface winds and interaction of tides, jets and eddies with rough topography, has been considered of secondary importance for the global meridional overturning circulation. Its importance for biological cycles has largely been assumed to be due to the role of mixing in changing the underlying dynamics on a centennial timescale. Using an eddy-resolving ocean model that assimilates an extensive array of observations, we show that altered mixing can cause up to a 40\% change in SO air-sea fluxes in only a few years through altering the distribution of dissolved inorganic carbon, alkalinity, temperature and salinity. Such enhanced mixing may be induced by the propagation of tidal waves from around the globe to the SO as well as the flux of wave energy from the deep SO to shallow depths. Such processes are unresolved in climate models, yet essential.

Probabilistic tsunami hazard analysis (PTHA) due to submarine landslides is much less developed than PTHA for earthquake sources. This is partly because of less constrained data on source probability, and partly due to lack of knowledge related to the tsunami generation process due to landslide dynamics. This study provides a basis for estimating the uncertainty related to landslide dynamics for PTHA from submarine landslides based on a new landslide database in the Gulf of Cadiz. The establishment of this new database is described herein. We use submarine landslide run-out statistics from this database to calibrate landslide parameters and related uncertainties using the cohesive landslide model BingClaw. In turn, coupling the landslide motion to tsunami genesis is used to characterise the inferred tsunami uncertainties. Important parameters that can explain the large tsunami uncertainties are the initial water depth of the landslide and the slope, the landslide volume, and the initial yield strength of the landslide material. Kinematic properties such as the initial landslide acceleration or the Froude number are found to strongly correlate with tsunami genesis. In this study, we show how the fitting process of numerical models landslide run-out can be casted into uncertainty in maximum sea surface elevations heights. This can in turn be an to a future PTHA for spanning uncertainty ranges due to the landslide dynamics on tsunami-genesis, constrained by landslide run-out data.

The relationship between dissolved solute concentration (C) and discharge (q) in streams, i.e., the C-q relationship, is a useful diagnostic tool for understanding biogeochemical processes in watersheds. In the ephemeral glacial meltwater streams of the McMurdo Dry Valleys [MDVs], Antarctica, studies show significant chemostatic relationships for weathering solutes and NO3-. Dissolved organic carbon (DOC) concentrations here are low compared to temperate streams, in the range of 0.1 to 2 mg C L-1, and their chemical signal clearly indicates derivation from microbial biomass. Many MDV streams support abundant microbial mats, which are also a source of organic matter to underlying hyporheic sediments. We investigated whether the DOC generation rate from these autochthonous organic matter pools was sufficient to maintain chemostasis for DOC despite these streams’ large diel and interannual fluctuations in discharge. To evaluate the DOC-q relationship, we fit the long-term DOC-q data to two models: a power law and an advection-reaction model. By using model outputs and other common metrics to characterize the DOC-q relationship, we found that this relationship is chemostatic in several MDV streams. We propose a conceptual model in which hyporheic carbon storage, hyporheic exchange rates, and net DOC generation rates are key interacting components that enable chemostatic DOC-q behavior in MDV streams. This model clarifies the role of autochthonous carbon stores in maintaining DOC-q chemostasis and may be useful for examining these relationships in temperate systems, where autochthonous organic carbon is readily bioavailable but where its signal is masked by a larger allochthonous signal.

The Lee and Heghinian’s bayesian approach was applied to CRU TS 3.1 grid precipitation data to detect change points at the Congo watershed scale. The locations that were sensitive to change point have been widely detected during 1969 and have been grouped in two zones that are located mainly in (a) the sub-basins of Bangui and (b) the Kasai and in the Cuvette Centrale. The signal of the persistence over two zones has been estimated at 8 years and 15 years covering respectively the period 1966-1973 (78% of the years on the total area) and 19661-1975 (68% of the years on the total area). Moreover, the change points over mentioned zones are respectively associated with 85% and 77% of the negative values of the shift magnitude. However, about 20.0% and 10.6% of the total area of the Congo watershed were sensitive to change points and the base of precipitation, respectively.

Estimates of fluvial sediment discharge from in situ instruments are an important component of large-scale sediment budgets that track long-term geomorphic change. Suspended sediment load can be reliably estimated using acoustic or physical sampling techniques; however, bedload is difficult to measure directly and can consequently be one of the largest sources of uncertainty in estimates of total load. We propose a physically-informed predictive empirical model for bedload sand flux as a function of variables that are measured using existing acoustic or physical sampling techniques. This model depends on the assumption that concentration and grain size in suspension are in equilibrium with reach-averaged boundary conditions. Bayesian inference is used to fit model parameters to data from eight sand-bed rivers and to simulate bedload flux over the available gage record at one site on the Colorado River in Grand Canyon National Park. We find that the cumulative bedload flux during the nine year period from 2008 to 2016 was 5\% of the cumulative suspended sand load; however, instantaneous bedload flux ranged from as little as 1\% of instantaneous suspended sand load to as much as 75\% of instantaneous suspended sand load due to fluctuations in flow strength and sediment supply. Changes in bedload flux at a constant discharge are indicative of short-term sediment supply enrichment and depletion. Long-term average bedload flux cannot be expected to remain constant in the future as the river adjusts to changes in sediment runoff and the dam-regulated discharge regime.

This study investigates how course design for a first year introductory class on climate change impacts student understanding of this global issue. The course was developed to situate the scientific knowledge of climate change alongside the political, economic, and social dimensions of this human-caused crisis. This intentional course development was to give students a more holistic understanding of the causes, impacts, and solutions. The curriculum is widely interdisciplinary with scientific concepts, like the functioning of the climate system and tools of climate system research, taught alongside politics, economics, media analysis, and social justice. A teaching as research project was conducted to assess how adding the sociopolitical context impacted student's ability to situate their knowledge of the scientific basis of climate change using systems thinking. As climate change, and scientific research, operate within the social and political landscape students became more informed citizens through learning these connections. Student participants in the study have a range of backgrounds and were all majors within the college of natural sciences during their first semester of college, though not all majoring in earth sciences

Mooring observations of tidal currents in Prydz Bay, East Antarctica are presented here. They were found to be mixed diurnal-semidiurnal over the continental shelf, with significant seasonality. Barotropic tides dominated the tidal currents at the calving front of the inner continental shelf of the Amery Ice Shelf (AIS), except at the western corner of the AIS where the seabed is abruptly deeper. The spatial and temporal averaged magnitude of tidal currents for all the current meter records was only 2.58 cm s-1, much weaker than in the Ross or Weddell seas. However, the observed maximum tidal current was about 13.12 cm s-1 at the AIS calving front. In addition, the ratio of the tidal heat flux standard deviation to the residual heat flux standard deviation could be up to 41% at the AIS front, implying the tides have the potential to modulate the heat content of the AIS cavity. To identify the footprints of the tidal influences on the AIS basal mass balance, we further assessed the temperature and salinity records from six boreholes drilled through the AIS. Interestingly, tide-like pulsing was identified in the ocean layer adjacent to the AIS basal surface, highlighting the potential tidal influences on the heat exchanges at the ice-ocean interface. Our assessment of the tidal currents in Prydz Bay underlines that the critical role of tides should be highlighted in investigations of interactions between the ocean and the AIS, and other ice shelves.

Peatland carbon may enter long-term storage in sedimentary basins preserved as either coal or lignite. To understand the process by which this happens requires extrapolation of our understanding of peatland carbon accumulation over timescales that greatly exceed those of Holocene peat. By applying this extrapolation, we deduce that the amount of time required to account for the carbon in 1 – 10 m thick coal seams must represent 105 to 106 years, an order of magnitude more than assumed in current interpretations of stratigraphic frameworks. Extrapolating peat growth to periods of 106 years requires consideration of the conditions of landscape, hydrology, accommodation space and crustal deformation required to ensure the sustained growth and accommodation of peat deposits. We conclude that the generation of accommodation space at low rates (0.1 to 0.2 mm/yr) can adequately accommodate thick peat accumulation over periods >105 yrs. However, generation of accommodation space at high rates (>1mm/yr) cannot accommodate significant peat accumulation. Key to this process is the maintenance of a saturated peat body above the level of clastic deposition. This long-term stability of the system has implications for our understanding of the processes that limit peatland growth under very low accommodation rates and the long-term validity of current peat growth models.

After 35 years of fairly steady lava effusion from the Pu’u ‘O’o vent along Kilauea’s mid portion of the East Rift Zone, a drastic change in the volcano’s behavior was initiated in May 2018. A series of new fissures opened between May 3rd and May 9th along the eastern end of the subaerial ERZ ( >40 km from the summit caldera), feeding a few short lived, relatively small volume flows. The products from the early phase of the eruption were dominated by plagioclase and clinopyroxene phenocrysts, gabbroic glomerocrysts and other crystal clots likely picked up prior to eruption. The initial activity transitioned between May 12th and around May 28th to steadier fountaining, higher effusion rate activity, leading to the formation of larger volume lava flows and the ensuing destruction of hundreds of houses and structures within the Puna area. This period marked the arrival of olivine-bearing Pu’u ‘O’o-like magma to the eruption site. Since the end of May, activity has focused on a unique vent (Fissure 8). This contribution examines the crystal cargo from the different magmas involved in the initial four weeks of the eruption, and their history through chemical zoning patterns of crystals. We discuss the magmatic origin of mineral assemblages from the evolved basalt end-member, and present initial results on timescales of magma interactions prior to their arrival at the surface from diffusion modeling in olivine.

Quantifying warming of the Earth’s climate system since the late 19th century and the ratio of regional to global warming are required when examining implications of Paris Agreement global warming targets. To estimate these terms reliably, the limitations in quality and length of observed records, differences between climate models and observations, and different results dependent on temporal and forcing contexts must be taken into account. Here we use observational datasets currently available back to 1860 and the latest set of global climate model simulations from CMIP5/6 to examine the warming of Australia in the past and projected future. We find that Australia has warmed by 1.5 °C (1.3–1.8 °C) during 1850 - 2019, at a ratio of ~1.4 times the global warming of ~1.1 °C. Models generally produce a lower ratio of Australian to global warming than in observations, which may be related to model biases or internal climate variability.

57 years of qualitative ship-board weather reports are used to assess apparent trends in precipitation occurrence over the global oceans. Positive trends of up to ~15% per decade, relative to the long term mean precipitation frequency at a location, are found over most tropical and temperate ocean areas, with negative trends of up to ~5% per decade being found principally at higher latitudes. While it cannot be ruled out that the observed trends are an artifact of gradual changes in shipboard weather reporting habits or procedures over time, no specific candidate for such a change has been identified that could explain the existence of robust positive and negative trends and their apparent geographic coherence.

The EarthCube Data Discovery Studio (DDStudio) integrates several technical components into an end-to-end data discovery and exploration system. Beyond supporting dataset search across multiple data sources, it lets geoscientists explore the data using Jupyter notebooks; organize the discovered datasets into thematic collections which can be shared with other users; edit metadata records and contribute metadata describing additional datasets; and examine provenance and validate automated metadata enhancements. DDStudio provides access to 1.67 million metadata records from 40+ geoscience repositories, which are automatically enhanced and exposed via standard interfaces in both ISO-19115 and in schema.org markup; the latter can be used by commercial search engines (Google, Bing) to index DDStudio content. For geoscience end users, DDStudio provides a custom Geoportal-based user interface which enables spatio-temporal, faceted, and full-text search, and provides access to additional functions listed above. Key project accomplishments over the last year include: - User interface improvements, based on design advice from a Science Gateways Community Institute (SGCI) usability team, who conducted user interviews, performed usability testing, and analyzed a dozen of other search portals to identify the most useful features. This work resulted in a streamlined user interface, particularly in presentation of search results and in management of thematic collections. - The earlier effort to publish DDStudio content using schema.org markup resulted in significant usage increase. With over 900K records indexed by Google, nearly half of the roughly 1000 unique users per month are now accessing DDStudio via referrals from Google. - The added ability to harvest and process JSON-LD metadata makes it possible to integrate EarthCube GeoCodes content into DDStudio, and work with this content using DDStudio’s user interface. - New application domains include joint work with the library community, and interoperation with DataMed, a similar system that indexes 2.3 million biomedical datasets.

Saturn’s moon Enceladus has a global subsurface ocean and a porous rocky core in which water-rock reactions likely occur; it is thus regarded as a potentially habitable environment. For icy moons like Enceladus, tidal heating is considered to be the main heating mechanism, which has generally been modeled using viscoelastic solid rheologies in existing studies. Here we provide a new framework for calculating tidal heating based on a poroviscoelastic model in which the porous solid and interstitial fluid deformation are coupled. We show that the total heating rate predicted for a poroviscoelastic core is significantly larger than that predicted using a classical viscoelastic model for intermediate to large (> 10 14 Pa.s) rock viscosities. The periodic deformation of the porous rock matrix is accompanied by interstitial pore fluid flow, and the combined effects through viscous dissipation result in high heat fluxes particularly at the poles. The heat generated in the rock matrix is also enhanced due to the high compressibility of the porous matrix structure. For a sufficiently compressible core and high permeability, the total heat production can exceed 10 GW-a large fraction of the moon’s total heat budget without requiring unrealistically low solid viscosities. The partitioning of heating between rock and fluid constituents depends most sensitively on the viscosity of the rock matrix. As the core of Enceladus warms and weakens over time, pore fluid motion likely shifts from pressure-driven local oscillations to buoyancy-driven global hydrothermal convection, and the core transitions from fluid-dominated to rock-dominated heating.

The Amatrice-Visso-Norcia seismic sequence struck Central Italy across the Apenninic normal faults system in 2016. Fluids likely triggered the sequence and reduced the stability of the fault network following the first earthquake (Amatrice, Mw6.0), with their migration nucleating the Visso (Mw5.9) and Norcia (Mw6.5) mainshocks. However, both spatial extent and mechanisms of fluid migration and diffusion through the network remain unclear. High fluid content, enhanced permeability and pervasive microcracking increase seismic attenuation, but each process contributes to different attenuation mechanisms. Here, we measured and mapped peak delay time and late-time coda attenuation, using them as proxies of seismic scattering and absorption before and during the sequence. Structural discontinuities and lithology control scattering losses at all frequencies, with the highest scattering delineating carbonate formations within the Gran Sasso massif. The Monti Sibillini thrust marks the strongest contrasts in scattering, indicating a barrier for northward fracture propagation. Before the sequence, low-frequency high-absorption anomalies distribute around the chain axis. A single high-absorption anomaly bounded north by the Monti Sibillini thrust develops NNW-SSE across the seismogenic zone during the sequence. This spatial expansion appears related to the deep migration of CO2-bearing fluids across the strike of the fault network from a deep source of trapped CO2 near the Amatrice earthquake. Migration develops primarily during the Visso sequence, followed by diffusion across the fault zones during the Norcia sequence. High-scattering and high-absorption focus below the carbonates south of Norcia during the sequence, mapping the progressive northern permeation of the seismogenic zone from south to north.

A reanalysis dataset produced by the Copernicus Atmosphere Monitoring service (CAMS reanalysis, 2003 - present day) augmented by ERA5 data for the years before 2003 is used to describe the evolution of the 2020 Arctic ozone season and to compare it with years back to 1979. Ozone columns over large parts of the Arctic reached record low values in March and April 2020 because of an exceptionally cold and persistent Arctic polar vortex. Minimum ozone columns were below 250 DU for most of March and the first half of April, with the lowest values of 211 DU in the CAMS reanalysis found on 18 March. Such low values are extremely unusual for the Arctic. The previous years with similarly strong Arctic ozone depletion were 2011 and 1997 with minimum values of 232 DU and 217 DU, respectively. The performance of the CAMS ozone analysis is assessed by comparison with ozone sonde data. We find a clear sign of chemical ozone destruction with ozone severely depleted in a layer between 80-50 hPa in late March and early April when partial pressure values below 2 mPa were observed. Profiles from the limb sounders ACE-FTS and MLS show clear signs of chlorine activation and the presence of polar stratospheric clouds. Monthly mean ozone columns in March 2020 were up to 180 DU or 40% lower than the CAMS climatology (2003-2019) while values for 2011 and 1997 were lower by 31% and 35% respectively.

The Fletcher-Ponnambalam (FP) method is an explicit stochastic optimization method for design and operations management of storage systems. It has been applied successfully in many real-world operations optimization problems (for example, the Great Lakes system and the Parambikulam-Aliyar project) and groundwater management problems. The FP method faces no curse of dimensionality unlike stochastic dynamic programming (SDP) and no need for scenarios generation as in implicit stochastic programming (ISP) methods. The paper introduces a novel implementation for the FP method by removing the need for nonlinear constraints and by decreasing the number of decision variables to just one third of its original value, significantly reducing solving time (~27 times faster than the original formulation). Additionally, new expressions derived for first and second moments of both reservoir release deficit and spill terms and the already-derived expression for second moments of reservoir storage are incorporated into the new formulation enabling the FP method to reach an improved optimality for a nonlinear objective function. The enhanced procedure is applied to solving a water reservoir operation optimization problem for a major dam in Brazil. The result comparisons made with SDP, two-stage stochastic programming and ISP along with a thorough analysis of release operation policies for both non-Gaussian correlated and Gaussian independent inflows prove the optimality of this highly numerically efficient and convenient-to-use FP method.

The effect of polar sea ice melt on low latitude climate is little known. In order to understand the response of Indian summer monsoon (ISM) to the sea ice melt, we have run a suite of coupled and uncoupled climate model simulations. In one set of simulations, the albedo of sea ice is changed in such a way that it would melt as a result of increased absorption of solar radiation. We find a substantial weakening of ISM in sea ice melt experiments. Further, the genesis frequency of monsoon low-pressure systems (LPS) declines by about 40% in the sea ice melt simulations. A weakening and equatorward shift of ITCZ causes the decline in LPS genesis. Overall, the response of ISM to the sea ice melt resembles the response to greenhouse gas induced warming.