Work in recent decades has demonstrated a robust relationship between tropical precipitation and the column relative humidity (CRH). This study identifies a similar relationship between CRH and the atmospheric cloud radiative effect (ACRE) calculated from satellite observations. Like precipitation, the ACRE begins to increase rapidly when CRH exceeds a critical value near 75\%. We show that the ACRE can be estimated from CRH, similar to the way that CRH has been used to estimate precipitation. Our method reproduces the annual mean spatial structure of ACRE in the tropics, and skillfully estimates the mean ACRE on monthly and daily time scales in six regions of the tropics. We propose that the exponential dependence of precipitation on CRH is a result of cloud-longwave feedbacks, which facilitate a shift from convective to stratiform conditions.

Mixed-phase clouds play an important role in determining Arctic warming, but are parametrized in models and difficult to constrain with observations. We use two satellite-derived cloud phase metrics to investigate the vertical structure of Arctic clouds in two global climate models that use the Community Atmosphere Model version 6 (CAM6) atmospheric component. We report a model error limiting ice nucleation, produce a set of Arctic-constrained model runs by adjusting model microphysical variables to match the cloud phase metrics, and evaluate cloud feedbacks for all simulations. Models in this small ensemble uniformly overestimate total cloud fraction in the summer, but have variable representation of cloud fraction and phase in the winter and spring. By relating modelled cloud phase metrics and changes in low-level liquid cloud amount under warming to longwave cloud feedback, we show that mixed-phase processes mediate the Arctic climate by modifying how wintertime and springtime clouds respond to warming.

Storage and subsequent release of water is a key function of catchments that moderates the impact of meteorological and climate extremes. Despite the fact that many key hydrological processes depend upon storage, there are relatively few studies that focus on storage itself. Storage is difficult to quantify due to catchment heterogeneity and the paucity of data on key catchment characteristics that largely determine storage, such as soil, hydrogeology, and topography. We adopt a multi-method approach to estimate the dynamic and extended dynamic storages using hydrometric data in 69 catchments in the Murray-Darling Basin in south-eastern Australia. We test relationships between the derived catchment storages and hydrological and physical characteristics that potentially control storage. The study catchments tended to have small dynamic storages relative to the extended dynamic storage; proportionally the dynamic storages were all less than 10\% of the extended dynamic storage. While storage estimates produced by the different methods and study catchments varied, the order in which they ranked was consistent. Correlations between catchment characteristics and estimates of storage were inconsistent; however, the results indicated that greater storage is strongly associated with steeper catchments and smoother hydrographs. This study highlights limitations in the current methodology to derive storage and the quality of widely applied hydrometric data. We reinforce the need to collect data that can validate storage estimates and call for new approaches that can broadly estimate storage at the catchment scale.

The causes of decadal variations in global warming are poorly understood, however it is widely understood that variations in ocean heat content are linked with variations in surface warming. To investigate the forced response of ocean heat content (OHC) to anthropogenic aerosols (AA), we use an ensemble of historical simulations, which were carried out using a range of anthropogenic aerosol forcing magnitudes in a CMIP6-era global circulation model. We find that the centennial scale linear trends in historical ocean heat content are significantly sensitive to AA forcing magnitude ($-3.0\pm0.1$ x10$^{5}$ (J m$^{-3}$ century$^{-1}$)/(W m$^{-2}$), R$^2$=0.99), but interannual to multi-decadal variability in global ocean heat content appear largely independent of AA forcing magnitude. Comparison with observations find consistencies in different depth ranges and at different time scales with all but the strongest aerosol forcing magnitude, at least partly due to limited observational accuracy. We find broad negative sensitivity of ocean heat content to increased aerosol forcing magnitude across much of the tropics and sub-tropics. The polar regions and North Atlantic show the strongest heat content trends, and also show the strongest dependence on aerosol forcing magnitude. However, the ocean heat content response to increasing aerosol forcing magnitude in the North Atlantic and Southern Ocean is either dominated by internal variability, or strongly state dependent, showing different behaviour in different time periods. Our results suggest the response to aerosols in these regions is a complex combination of influences from ocean transport, atmospheric forcings, and sea ice responses.

Clouds cover on average nearly 70% of Earth’s surface and regulate the global albedo. The magnitude of the shortwave reflection by clouds depends on their location, optical properties, and three-dimensional (3D) structure. Due to computational limitations, Earth system models are unable to perform 3D radiative transfer calculations. Instead they make assumptions, including the independent column approximation (ICA), that neglect effects of 3D cloud morphology on albedo. We show how the resulting radiative flux bias (ICA-3D) depends on cloud morphology and solar zenith angle. Using large-eddy simulations to produce 3D cloud fields, a Monte Carlo code for 3D radiative transfer, and observations of cloud climatology, we estimate the effect of this flux bias on global climate. The flux bias is largest at small zenith angles and for deeper clouds, while the negative albedo bias is most prominent for large zenith angles. In the tropics, the radiative flux bias from neglecting 3D radiative transfer is estimated to be 4.0 +/- 2.4 Wm-2 in the mean and locally as large as 9 Wm-2.

The continuous estimation of changes in seismic velocity and seismic scattering property by passive interferometry using seismic ambient noise is a promising tool for monitoring volcanoes. To improve the usefulness of this method, it is necessary not only to detect subsurface structural changes but also to quantitatively compare the estimated changes in seismic wave velocity and seismic wave scattering property with other observations such as ground deformation. We applied passive interferometry to continuous seismic records from Suwanosejima volcano, Japan, recorded between April 2017 and December 2021. We detected repeated significant waveform decorrelations in seismic ambient noise cross-correlation functions, indicating seismic scattering property changes in the shallow areas of the volcano. These decorrelations were observed from 2 week to a few days before the increase in the number of explosions, suggesting that seismic scattering properties changed significantly during that period. We found that the timing of the decorrelation in seismic ambient noise cross-correlation functions and tilt changes related to magma accumulation and injection beneath Suwanosejima were well synchronized. The high correlation between the amounts of decorrelation and tilt change during the magma accumulation period suggests that a large volume of accumulated magma caused great changes in the scattering property. These results provide a significant first step toward a quantitative comparison of the amount of changes in the scattering property with the amount of magma accumulation beneath volcanoes.

Construction with freeboard – vertical height of a structure above the minimum required – is commonly accepted as a sound investment for flood hazard mitigation. However, determining the optimal height of freeboard poses a major decision problem. This research introduces a life-cycle benefit-cost analysis (LCBCA) approach for optimizing freeboard height for a new, single-family residence, while incorporating uncertainty, and, in the case of insured homes, considering the costs from losses, insurance, and freeboard (if any) to the homeowner and National Flood Insurance Program (NFIP) separately. Using a hypothetical, case study home in Metairie, Louisiana, results show that adding 2 ft. of freeboard at the time of construction might be considered the optimal option given that it yields the highest net benefit, but the highest net benefit-cost ratio occurs for the 1 ft. freeboard. Even if flood loss reduction is not considered when adding freeboard, the savings in annual insurance premiums alone are sufficient to recover the construction costs paid by the homeowner if at least one foot of freeboard is included at construction. Collectively, these results based on conservative assumptions suggest that at the time of construction, even a small amount of freeboard provides a huge savings for the homeowner and (especially) for the financially-strapped NFIP. For community planners, the results suggest that wise planning with reasonable expectations on the front end makes for a more sustainable community.

For science to reliably support new discoveries, its results must be reproducible. This has proven to be a challenge in many fields including fields that rely on computational methods as a means for supporting new discoveries. Reproducibility in these studies is particularly difficult because they require open, documented sharing of data and models and careful control of underlying hardware and software dependencies so that computational procedures executed by the original researcher are portable and can be run on different hardware or software and produce consistent results. Despite recent advances in making scientific work more findable, accessible, interoperable and reusable (FAIR), fundamental questions in the conduct of reproducible computational studies remain: Can published results be repeated in different computing environments? If yes, how similar are they to previous results? Can we further verify and build on the results by using additional data or changing computational methods? Can these changes be automatically and systematically tracked? This presentation will describe our EarthCube project to advance computational reproducibility and make it easier and more efficient for geoscientists to preserve, share, repeat and replicate scientific computations. Our approach is based on Sciunit software developed by prior EarthCube projects which encapsulates application dependencies composed of system binaries, code, data, environment and application provenance so that the resulting computational research object can be shared and re-executed on different platforms. We have deployed Sciunit within the HydroShare JupyterHub platform operated by the Consortium of Universities for the Advancement of Hydrologic Science Inc. (CUAHSI) for the hydrology research community and will present use cases that demonstrate how to preserve, share, repeat and replicate scientific results from the field of hydrologic modeling. While illustrated in the context of hydrology, the methods and tools developed as part of this project have the potential to be extended to other geoscience domains. They also have the potential to inform the reproducibility evaluation process as currently undertaken by journals and publishers.

Satellite observations are used to establish the dominant magnitudes, scales, and mechanisms of intraseasonal variability in ocean dynamic sea level (ζ) in the Persian Gulf over 2002-2015. Empirical orthogonal function (EOF) analysis applied to altimetry data reveals a basin-wide, single-signed intraseasonal fluctuation that contributes importantly to ζ variance in the Persian Gulf at monthly to decadal timescales. An EOF analysis of Gravity Recovery and Climate Experiment (GRACE) observations over the same period returns a similar large-scale mode of intraseasonal variability, suggesting that the basin-wide intraseasonal ζ variation has a predominantly barotropic nature. A linear barotropic theory is developed to interpret the data. The theory represents Persian-Gulf-average ζ () in terms of local freshwater flux, barometric pressure, and wind stress forcing, as well as ζ at the boundary in the Gulf of Oman. The theory is tested using a multiple linear regression with these freshwater flux, barometric pressure, wind stress, and boundary ζ quantities as input, and as output. The regression explains 70%+/-9% (95% confidence interval) of the intraseasonal variance. Numerical values of regression coefficients computed empirically from the data are consistent with theoretical expectations from first principles. Results point to a substantial non-isostatic response to surface loading. The Gulf of Oman ζ boundary condition shows lagged correlation with ζ upstream along the Indian Subcontinent, Maritime Continent, and equatorial Indian Ocean, suggesting a large-scale Indian-Ocean influence on intraseasonal variation mediated by coastal and equatorial waves, and hinting at potential predictability. This study highlights the value of GRACE for understanding sea level in an understudied marginal sea.

Deformation bands are the main structural element of fault damage zones within sandstone reservoirs. The prediction of band occurrence and their petrophysical impacts is based largely on the understanding that the yield and deformation mechanism of sandstones is primarily controlled by porosity and mean grain size. Whilst this is supported by field observations within aeolian successions, where bands are predictably favoured within coarse-grained, high-porosity sandstones, the prediction of deformation bands within texturally complex mixed aeolian-fluvial reservoirs on the basis of porosity and grain size alone, may be unreliable. The effect of grain sorting on the mechanical behaviour of sandstones is not well understood, although it is generally regarded that deformation band formation is inhibited in texturally immature sandstones with a poor level of sorting. We examine the effect of sorting on both the inelastic yield of sandstones, the dominant deformation mechanism by which yield occurs, and the textural and microstructural changes with deformation, using a series of triaxial experiments on unconsolidated quartz sands. Hydrostatic experiments were conducted on over-consolidated samples of very well- to moderately-sorted sands with a range of mean grain sizes from 128-700µm. We report accurate prediction of P* using porosity x grain radius, with P* reduced with decreased sorting. Constant displacement rate triaxial experiments are performed at up to 10% axial strain to explore yield behaviour in both the brittle dilatant regime and shear-enhanced compactive regime. Experiments were repeated with systematically varied grain sorting whilst mean grain size and porosity was maintained. The textural and petrophysical changes are observed and quantified using pore volumometry, back scattered electron microscopy, digital image analysis and point counting. Results show that in well-sorted sands, localised cataclasis and deformation band formation is the dominant deformation mechanism. In poorly-sorted sands deformation occurs through a combination of grain boundary sliding and randomly distributed pockets of cataclasis. Using grain size analysis we identify greater levels of cataclasis and production of fines in well-sorted sands, resulting in permeability reduction up to one order of magnitude more than that of poorly-sorted sands deformed at the same conditions. We hypothesise that band formation within poorly sorted sandstones may be promoted by the formation and propagation of bands in adjacent well sorted sandstones where band formation is favoured. These results give insight into the deformation, textural changes, and permeability impact of both unconsolidated and consolidated siliciclastic reservoirs.

New geophysical data from Antarctica’s Ross Embayment reveal the structure and subglacial geology of extended continental crust beneath the Ross Ice Shelf. We use airborne magnetic data from the ROSETTA-Ice Project to locate the contact between magnetic basement and overlying sediments. We delineate a broad, segmented basement high with thin (0-500m) non-magnetic sedimentary cover which trends northward into the Ross Sea’s Central High. Before subsiding in the Oligocene, this feature likely facilitated early glaciation in the region and subsequently acted as a pinning point and ice flow divide. Flanking the high are wide sedimentary basins, up to 3700m deep, which parallel the Ross Sea basins and likely formed during Cretaceous-Neogene intracontinental extension. NW-SE basins beneath the Siple Coast grounding zone, by contrast, are narrow, deep, and elongate. They suggest tectonic divergence upon active faults that may localize geothermal heat and/or groundwater flow, both important components of the subglacial system.

We investigate the flow-wise variation of the hydraulic conductivity inside a non-uniformly shaped fracture with permeable walls. Using lubrication theory for viscous flows, in conjunction with the Beavers–Joseph–Saffman boundary condition at the permeable walls, we obtain an analytical expression for the velocity profile, conductivity, and wall permeation velocity. These predictions highlight the effects of geometric variation (through the local slope of the aperture’s flow-wise variation), the permeability of the walls (through a dimensionless slip coefficient), and the effect of flow inertia (through a Reynolds number). The theory is validated against an OpenFOAM(R) solver for the Navier–Stokes equations subject to a tensorial slip boundary condition, showing good agreement. The mathematical results have implications on system-level (multiscale) modeling of hydraulically fractured reservoirs, in which the Darcy conductivity of each non-uniform passage must be accurately accounted for, throughout the fractured porous rock.

Earth’s internal heat drives its dynamic engine, causing mantle convection, plate tectonics, and the geodynamo. These renewing and protective processes, which make Earth habitable, are fueled by a primordial (kinetic) and radiogenic heat. For the past two decades, particle physicists have measured the flux of geoneutrinos, electron antineutrinos emitted during β − decay. These ghost-like particles provide a direct measure of the amount of heat producing elements (HPE: Th & U) in the Earth and in turn define the planet’s absolute concentration of the refractory elements. The geoneutrino flux has contributions from the lithosphere and mantle. Detector sensitivity follows a 1/r 2 (source detector separation distance) dependence. Accordingly, an accurate geologic model of the Near-Field Lithosphere (NFL, closest 500 km) surrounding each experiment is required to define the mantle’s contribution. Because of its proximity to the detector and enrichment in HPEs, the local lithosphere contributes ∼50% of the signal and has the greatest effect on interpreting the mantle’s signal. We re-analyzed the upper crustal compositional model used by Agostini et al. (2020) for the Borexino experiment. We documented the geology of the western Near-Field region as rich in potassic volcanism, including some centers within 50 km of the detector. In contrast, the Agostini study did not include these lithologies and used only a HPE-poor, carbonate-rich, model for upper crustal rocks in the surrounding ∼150 km of the Borexino experiment. Consequently, we report 3× higher U content for the local upper crust, which produces a 200% decrease in Earth’s radiogenic heat budget, when compared to their study. Results from the KamLAND and Borexino geoneutrino experiments are at odds with one another and predict mantle compositional heterogeneity that is untenable. Combined analyses of the KamLAND and Borexino experiments using our revised local models strongly favor an Earth with ∼20 TW present-day total radiogenic power. The next generation of geoneutrino detectors (SNO+, counting; and JUNO, under construction) will better constrain the HPE budget of the Earth.

The discipline of land change science has been evolving rapidly in the past decades. Remote sensing played a major role in one of the essential components of land change science, which includes observation, monitoring, and characterization of land change. In this paper, we proposed a new framework of the multifaceted view of land change through the lens of remote sensing and recommended five facets of land change including change location, time, target, metric, and agent. We also evaluated the impacts of spatial, spectral, temporal, angular, and data-integration domains of the remotely sensed data on observing, monitoring, and characterization of different facets of land change, as well as discussed some of the current land change products. We recommend clarifying the specific land change facet being studied in remote sensing of land change, reporting multiple or all facets of land change in remote sensing products, shifting the focus from land cover change to specific change metric and agent, integrating social science data and multi-sensor datasets for a deeper and fuller understanding of land change, and recognizing limitations and weaknesses of remote sensing in land change studies.

In this paper we develop and test a rigorous modeling framework, based on Duhamel’s Theorem, for the unsteady one-dimensional transport and mixing of a solute across a flat sediment-water interface (SWI) and through the benthic biolayer of a turbulent stream. The modeling framework is novel in that it allows for depth-varying diffusivity profiles, accounts for the change in porosity across the SWI and captures the two-way coupling between evolving solute concentrations in both the overlying water column and interstitial fluids of the sediment bed. We apply this new modeling framework to an extensive set of previously published laboratory measurements of turbulent mixing across a flat sediment bed, with the goal of evaluating four diffusivity profiles (constant, exponentially declining, and two hybrid models that account for molecular diffusion and enhanced turbulent mixing in the surficial portion of the bed). The exponentially declining profile is superior (based on RMSE, coefficient of determination, AICc, and model parsimony) and its reference diffusivity scales with a dimensionless measure of stream turbulence and streambed permeability called the Permeability Reynolds Number, . The diffusivity’s dependence on changes abruptly at , reflecting different modes of mixing below (dispersion) and above (turbulent diffusion) this threshold value. The depth-scale over which the diffusivity exponentially decays is about equal to the thickness of the benthic biolayer (2 to 5 cm), implying that turbulent mixing, and specifically turbulent pumping, may play an outsized role in the biogeochemical processing of nutrients and other contaminants in stream and coastal sediments.

Advances in space weather science and small satellite (SmallSat) technology have proceeded in parallel over the past two decades, but better communication and coordination is needed among the respective worldwide communities contributing to this rapid progress. We identify six areas where improved international coordination is especially desirable, including: (1) orbital debris miti-gation; (2) spectrum management; (3) export control regulations; (4) access to timely and low-cost launch opportunities; (5) inclusive data policies; and (6) education. We argue the need for interna-tionally coordinated policies and programs to promote the use of SmallSats for space weather re-search and forecasting while realizing maximum scientific and technical advances through the inte-gration of these two increasingly important endeavors.

The Energetic Particle Detector (EPD) onboard Solar Orbiter is a suite of multiple sensors (Suprathermal Electrons Protons, STEP; Suprathermal Ion Spectrograph, SIS; Electron Proton Telescope, EPT; High Energy Telescope, HET), which measures particle intensities over a wide range of energies (from suprathermal to relativistic energies) and for different species (electron, protons, and heavy ions) in different directions. The EPD data center (http://espada.uah.es/epd) offers a primer venue to inspect the Solar Energetic Particle (SEP) activity, both to promptly check the most recent solar activity using quicklook plots based on low-latency data sets, and to perform deeper studies with data validated for scientific use. Among others, a series of plots and relevant information, such as the spacecraft maneuvers or sensor updates, are provided to the community. This facility gives access to all the data from the EPD sensors (which can be also found in the Solar Orbiter Archive), including Level 2 (calibrated) as well as more elaborated Level 3 data in the near future, which have further processing. An application programming interface (API) is also offered for accessing EPD data. Besides, during the first year and a half of observations, Solar Orbiter has completed three orbits, and EPD has measured several increases in particle fluxes, due to heliospheric and solar-origin events. Some of the events have been analysed and the flux enhancements have been tagged for future studies. This work aims to let the community know the availability of the instrument data products, and to explain how to properly use the provided data products and plots, as well as to summarise all the available studies published until now.

A simple yet flexible and robust algorithm is described for fully partitioning an arbitrary dataset into compact, non-overlapping groups or classes, sorted by size, based entirely on a pairwise similarity matrix and a user-specified similarity threshold. Unlike many clustering algorithms, there is no assumption that natural clusters exist in the dataset, though clusters, when present, may be preferentially assigned to one or more classes. The method also does not require data objects to be compared within any coordinate system but rather permits the user to define pairwise similarity using almost any conceivable criterion. The method therefore lends itself to certain geoscientific applications for which conventional clustering methods are unsuited, including two non-trivial and distinctly different datasets presented as examples. In addition to identifying large classes containing numerous similar dataset members, it is also well-suited for isolating rare or anomalous members of a dataset. The method is inductive, in that prototypes identified in representative subset of a larger dataset can be used to classify the remainder.