Dome Fuji, inland East Antarctica is one of only few regions where 1.5-Ma old ice can be preserved for investigating the mid-Pleistocene Transition. We used stochastic simulation and various radar datasets to generate a bed topography ensemble with the continuous, realistic roughness necessary to assess basal conditions. Ensemble analysis reveals the magnitude and spatial distribution of topographic uncertainty, facilitating uncertainty-constrained assessments of subglacial drainage and topographic adjustments to geothermal heat flow. We find that topographic variability can lead to widespread local geothermal heat flow variations of ± 20% the background value, which aggregate to raise the regional value and suggest previously underestimated distributions and rates of basal melting. We also find that survey profile spacing has an increasing influence on topographic uncertainty for rougher bed, deriving an empirical relationship that could guide future survey planning based on uncertainty tolerance.

A document by Viacheslav Titov. Click on the document to view its contents.

The vertical opacity structure of the martian atmosphere is important for understanding the distribution of ice (water and carbon dioxide) and dust. We present a new dataset of extinction opacity profiles from the NOMAD/UVIS spectrometer aboard the ExoMars Trace Gas Orbiter, covering one and a half Mars Years (MY) including the MY 34 Global Dust Storm and several regional dust storms. We discuss specific mesospheric cloud features and compare with existing literature and a Mars Global Climate Model (MGCM) run with data assimilation. Mesospheric opacity features, interpreted to be water ice, were present during the global and regional dust events and correlate with an elevated hygropause in the MGCM, providing further evidence for the role of regional dust storms in driving atmospheric escape as reported elsewhere. The season of the dust storms also had an apparent impact on the resulting lifetime of the cloud features, with events earlier in the dusty season correlating with longer-lasting mesospheric cloud layers. Mesospheric opacity features were also present during the dusty season even in the absence of regional dust storms, and interpreted to be water ice based on previous literature. The assimilated MGCM temperature structure agreed well with the UVIS opacities, but the MGCM opacity field struggled to reproduce mesospheric ice features, suggesting a need for further development of water ice parameterizations. The UVIS opacity dataset offers opportunities for further research into the vertical aerosol structure of the martian atmosphere, and for validation of how this is represented in numerical models.

A growing body of literature investigates convective organisation, but few studies to date have sought to investigate how wind shear plays a role in the spatial organization of shallow (trade-wind) convection. The present study hence investigates the morphology of precipitating marine cumulus convection using large-eddy-simulation experiments with zonal forward and backward shear and without shear. One set of simulations includes evaporation of precipitation, promoting for cold-pool development, and another set inhibits evaporation of precipitation and thus cold-pool formation. Without (or with only weak) subcloud-layer shear, conditions are unfavourable for convective deepening, as clouds remain stationary relative to their subcloud-layer roots so that precipitative downdrafts interfere with emerging updrafts. Under subcloud-layer forward shear, where the wind strengthens with height (a condition that is commonly found in the trades), clouds move at greater speed than their roots, and precipitation falls downwind away from emerging updrafts. Forward shear in the subcloud layer appears to promote the development of stronger subcloud circulations, with greater divergence in the cold-pool area downwind of the original cell and larger convergence and stronger uplift at the gust front boundary. As clouds shear forward, a larger fraction of precipitation falls outside of clouds, leading to more moistening within the cold pool (gust front).

The Campanian Ignimbrite was emplaced during the 39-ka caldera-forming eruption of Campi Flegrei near Naples, Italy. This eruption deposited a trachytic ignimbrite up to 80 km from the caldera and co-ignimbrite fallout more than 2300 km to the northeast. The pyroclastic density current was dilute and mobile, overtopping kilometer-high mountains up to 60 km from the vent. Stratigraphic units within the proximal and distal deposits of the Campanian Ignimbrite have never been definitively correlated due to their very dissimilar appearances and the lack of medial exposure. Correlation of the ignimbrite, specifically which proximal units formed simultaneously with the majority of the distal deposits, is necessary to understand the events that formed this dilute current. The co-ignimbrite lag breccia (Breccia Museo), which represents the caldera collapse, and an earlier eruptive phase that formed a high-grade ignimbrite (Piperno) are potential proximal correlates to the main distal ignimbrite unit. Juvenile matrix material includes pumice and scoria fragments and bubble-wall shards. A distal outcrop at 970 m asl, thought to represent deposits from the upper transport system of the main pyroclastic flow, is dominated by bubble-wall shards. At all other sites, most juvenile ash shards show textures similar to associated pumice lapilli. We suggest that much of the ash was from abrasion of pumice, but the upper current had few pumice clasts and thus less abrasion-derived ash. Preliminary analyses indicate that early units have limited chemical compositional ranges (predominantly Na2O 4-7% and K2O 5-9%), whereas the Piperno and the dominant distal unit both have a broader geochemical range that extends to roughly 9% Na2O and 2% K2O. The uppermost proximal unit has the most extreme compositions, approximately 2-6% Na2O and 6-11% K2O. These observations are consistent with the source of the eruption being either a large stratified magma chamber that underwent pre-eruptive mingling, or several semi-isolated magma bodies. Proximal deposits include spatter from local vents that may have tapped isolated magma bodies. Study of pyroclasts from the Campanian Ignimbrite allow both correlation of proximal and distal deposits and a characterization of some aspects of the pyroclastic current.

Topography is critical information for water resources management in lakes, and remote sensing provides a unique opportunity to estimate it in ungauged regions. We introduce here a new method which estimates near shore topography of water bodies based on a flood frequency map and time series of water levels by assuming the equivalence between flood frequency and water level exceedance probability at a given area. Test cases are performed for two lakes and 12 hydropower reservoirs in Brazil using the proposed Flood2Topo app. This new application generates the bottom level pixel by pixel and a level-area-active storage relationships directly from the topography map, without the need to fit functions. Flood extent estimates from the Landsat based JRC Global Surface Water (GSW) dataset, current state-of-the-art, were used to run Flood2Topo, together with water levels from satellite altimetry and in-situ gauges. Results show bottom level root mean square deviation (RMSD) values of 18.5 cm and 146 cm for Lake Poopó (Bolivia) and Lake Curuai (Amazon basin), respectively. For reservoir active storage, RMSD normalized values ranged from 2% to 11.09% for 11 reservoirs (average NRMSD of 6.39 %). The method can be applied to any area seasonally flooded, for instance, it is applicable in 35.8 % (86%) of the global water surface area mapped by occurrence map from GSW dataset, when considering the number of pixels with occurrence between 0 and 95% (99%) over 35 years. This is a promising tool for obtaining data for hydrodynamic simulations and monitoring of ungauged water bodies.

We analyze two preindustrial experiments from the Community Earth System Model version 2 (CESM2) to characterize the impact of sea ice physics on regional differences in coastal sea ice production around Antarctica and the resulting impact on the ocean and atmosphere. The experiment in which sea ice is a “mushy” mixture of solid ice and brine has a substantial increase in coastal sea ice frazil and snow ice production that is accompanied by decreasing congelation growth and increasing bottom melt. With mushy ice physics, the subsurface ocean is denser and saltier, there is a statistically significant increase in Antarctic Bottom Water Formation by ~0.5 Sv, but differences in ocean biogeochemistry are minimal and only in regions where the summer ice state differs. While there are no significant changes in the atmospheric circulation, using “mushy” ice physics results in decreased turbulent heat flux, atmospheric convection, and low level cloud cover.

Grappling with systemic discrimination and bias in geosciences can be overwhelming to the point that one may feel powerless to fix them. Despite the sweeping nature of this challenge, faculty, principal investigators, and other scientists with leadership roles have unparalleled power to mitigate harm in environments they oversee. Here, we identify ways that scientists in these roles can immediately address bias in three common spaces --- the lab, field, and classroom. We highlight key actions that can be taken to improve the quality of life of marginalized students and other trainees quickly, while important but comparatively slow institutional changes proceed.

A multi-stage fuzzy inference system (FIS), a symbolic knowledge-based artificial intelligence technique, is used to delineate exploration targets for rare earth elements (REEs) associated with carbonatite-alkaline complexes in NE India. A conceptual REE mineral systems model was used to identify the following targeting criteria for REE deposits. The multi-stage FIS was structured based on the mineral systems model. The first stage of the multi-stage FIS comprised of three individual FIS to represent (1) plume-metasomatised SCLM in an extensional regime that make up fertile source regions for REE-bearing fluids and favourable geodynamic settings; (2) trans-lithospheric structures that provide favourable lithospheric architecture for the transportation of REE-enriched alkaline-carbonatite magma and (3) near-surface higher-order structures that make up a shallow crustal architecture facilitating emplacement of alkaline-carbonatite complexes. The targeting criteria were represented by their spatial proxies in the form of GIS layers derived using spatial analyses and geoprocessing tools for inputting to the FIS. The outputs of the FIS were mapped to generate prospectivity maps that were analysed to identify exploration targets for REE in the study area. The uncertainties in the outputs of the FIS were quantified using Monte-Carlo-based simulations. Exploration targets at low uncertainty levels were delineated around Sung valley and Jasra carbonatite-alkaline-complexes. Areas around the carbonatite-alkaline complex around Swangkre and to the south of the Nongstoin town were identified as high-uncertainty targets. It is recommended that ground follow-up exploration should be carried out in the former targets, and more data should be collected to increase confidence in the latter targets.

Understanding the effects of water, energy, and food (WEF) consumption and production on socio-economic and environmental indicators has become a strategic issue for all countries, especially the developing ones, that depend on natural resources to promote economic growth. Our main objective with this study is to quantify and understand the interconnections (Nexus) of WEF production and consumption with regional economic growth and social development in Brazil. We use a multi input-output approach based on a Data Envelopment Analysis (DEA) model to calculate efficiency indicators over time for various municipalities in Brazil. We assume that a high input-output efficiency level indicates that a certain municipality can reach larger output benefits with less WEF consumption. The time-based approach using the Malmquist Index model enables us determining whether cities’ WEF input-output efficiencies have been rising or declining over time. The time-spatial analysis is appropriate to indicate the level of interdependence between WEF-Nexus and the demographic, economic, and environmental systems in Brazil. We expect that our results can help policymakers establishing regional and city-level policies that can benefit a more efficient use of WEF resources.

Global storm-resolving model (GSRM) simulations (kilometer-scale horizontal resolution) of the atmosphere can capture the interaction between the scales of deep cumulus convection and the large-scale dynamics and thermodynamic properties of the atmosphere. Here, we assess the vertical structure of tropical temperature change in the GSRM X-SHiELD, developed by the Geophysical Fluid Dynamics Laboratory, perturbed by a uniform sea surface temperature (SST) warming and/or increased CO2 concentration. The simulated response to SST warming shows weakly amplified warming from the surface through the mid-troposphere before increasing to a factor of about 2.5 near the tropopause. This combination of muted warming in the mid-troposphere and amplified warming aloft is within the range of CMIP6 models at individual pressure levels but, taken together, is distinctive behavior. The response to CO2 increase with unchanged SST is an approximately vertically uniform warming, comparable to CMIP6 models, and is linearly additive with the SST-induced warming in X-SHiELD.

Seismic velocity structures have been estimated using ambient noise records observed by distributed acoustic sensing (DAS) technology. Previous studies have obtained S-wave velocity (Vs) structures along submarine cables using surface waves; however P-wave velocity (Vp) structure have seldom been constructed because ambient noise primarily contains surface waves. Here, we show P and Rayleigh wave extractions from ambient seafloor noise observed by DAS, and also estimate the Vp and Vs structures along a submarine cable deployed off Cape Muroto in the Nankai subduction zone, Japan. To extract the P waves, we calculated the cross-correlation functions (CCFs) of the ambient noise and applied a frequency-wavenumber filter to the CCFs to remove the effects of slower surface waves. The results indicate that similar features can be obtained in the Vp and Vs profiles, and that the P wave extractions can be performed on days with poor weather conditions.

As part of the Norwegian SI-ARCTIC Program, in late summer of 2014 and 2015 acoustic data (18, 38 and 120 kHz) for the estimation of the distribution and abundance of zooplankton and fish were collected from regions west and north of Svalbard, to examine high latitude epipelagic and mesopelagic scattering structures. The deep scattering layer biological constituents were determined from vertical and oblique hauls with zooplankton nets and pelagic trawls. There was strong patchy scattering in the upper part of the epipelagic zone (<50 m) throughout the area due to 0-group fish that were particularly abundant west of the Spitsbergen Archipelago and by copepods, krill, and amphipods. The distinct Off-shelf deep scattering layer (DSL) occurred between 200 and 600 m and contained a range of larger longer lived organisms (mesopelagic fish and macrozooplankton). In eastern Fram Strait, the DSL also included larger fish close to the shelf/slope break that were associated with Warm Atlantic Water moving north towards the Arctic Ocean, but switched to dominance by species having weaker scattering signatures further offshore. The Weighted Mean Depths of the DSL were deeper (WMD >440 m) in the Arctic habitat north of Svalbard compared to those south in the Fram Strait west of Svalbard (WMD ~400 m) and the mesopelagic nautical area scattering coefficient was a factor of approximately 6-10 lower around Svalbard compared to the areas in the south-eastern part of the Norwegian Sea ~62º30’N. The DSL displayed a clear ascending and descending diel movement. The high-light WMD with respect to backscattered energy was statistically deeper than the low-light WMD for the locations studied. This behavior of the DSL was consistent both when the sun was continuously above the horizon and after it started to set on 1 September, and both in open water and sea ice covered waters.

Our study uses field training data, airborne LiDAR (Light Detection and Ranging), imaging spectroscopy, and a Convolutional Neural Network (CNN) classifier to identify individual tree species in a mixed conifer forest in the Southern Sierra Nevada Mountains. The remote sensing data was collected on the National Ecological Observatory Network (NEON) Airborne Observation Platform in 2017. We trained the classifier using existing field plot data, and an independently collected validation dataset which identifies trees location of the 7 dominant species (Pine, Fir, Cedar and Oak), including condition and ‘live’ or ‘dead’ status. The LiDAR canopy height model was used to identify tree crowns and imaging spectroscopy data around these crowns were created as image ‘labels’. These species level ‘labels’ were used to train, test and validate a CNN tree species classifier. Our method achieved greater than 63-90% accuracy for all field validated stems and worked best for large diameter trees. On an independent tree stem dataset, we performed a species-level logistic regression to study which cases the classifier works most and least effectively. Spatially, in the southern areas scattered Black Oak were present and tree species often were confused with shrub species or covered by adjacent conifer species. In the north where the upper elevation forest is dominated by red and white fir the classifier achieved greater than 96% accuracy for larger canopy trees, with accuracy degrading to about 59-70% when smaller trees are included in the model. There is also genus level mis-classification, particularly between Red and White Fir species. There was high tree mortality in this forest and the classifier was effective in detecting large tree mortality, which also varies as a function of species and size of trees. This work leverages newly developed ‘deep learning’ tools which have yet to be extensively applied to the remote detection of large trees or in plant biogeography generally. This research is a proof-of-concept for forest community ecologists who want accurate ‘tree species maps’ to study how plants are distributed across space. Generally, this method will be of interest to biogeographers or remote sensing scientists looking to apply novel classification methods to problems beyond remote tree species identification.

Carbon isotope (δ13C) records from marine sediments have been extensively used in Cenozoic chemostratigraphy. The early Paleogene interval in particular has received exceptional attention because negative carbon isotope excursions (CIEs) documented in the sedimentary record, e.g. at the Paleocene Eocene Thermal Maximum (PETM), ca ~56 Ma, are believed to reflect significant global carbon cycle perturbations during the warmest interval of the Cenozoic era. However, while bulk-carbonate δ13C values exhibit robust correlations across widely separated marine sedimentary sections, their absolute values and magnitude of CIEs vary spatially. Moreover, bulk-carbonates in open-marine environments are an ensemble of different components, each with a distinct isotopic composition. Consequently, a complete interpretation of the bulk δ13C record requires an understanding of co-evolution of these components. In this study, we dissect sediments, from early Paleogene interval, at ODP Site 1209, Shatsky Rise, Pacific Ocean to investigate how an evolving bulk-carbonate ensemble influences the overall carbon isotope record. A set of 45 samples were examined for δ13C and δ18O compositions, as bulk and individual size fractions. We find a significant increase in coarse-fraction abundance across PETM, driven by a changing community structure of calcifiers, modulating the size of CIE at Site 1209 and thus making it distinct from those recorded at other open-marine sites. These results highlight the importance of biogeography in marine stable-isotope record, especially when isotopic excursions are driven by climate- and/or carbon-cycle changes. In addition, community composition changes will alter the interpretation of weight percent coarse fraction as conventional proxy for carbonate dissolution.

During the Arctic night, clouds regulate surface energy budgets through longwave warming alone. During fall, any increase in low-level opaque clouds will increase surface cloud warming and could potentially delay sea ice formation. While an increase in clouds due to fall sea ice loss has been observed, quantifying the surface warming is observationally challenging. Here, we quantify surface cloud warming using spaceborne lidar observations. By instantaneously co-locating surface cloud warming and sea ice observations in regions where sea ice varies, we find October large surface cloud warming values (> 80 W m-2) are much more frequent (~+50%) over open water than over sea ice. Notably, in November large surface cloud warming values (> 80 W m-2) occur more frequently (~+200%) over open water than over sea ice. These results suggest more surface warming caused by low-level opaque clouds in the future as open water persists later into the fall.

There are growing evidences that the warming marginal seas impact the torrential rainfall events in many parts of the world. The sea surface temperature (SST) in the East Asian marginal seas (EAMS) exhibits rapid rise during the last decades compared to the global mean, but its impact is still a matter of debate. Here we assess the impact of the recent warming trend of the EAMSs on the torrential rainfall event that caused devastating flooding and landslides in Kyushu Island located in the western part of Japan in July 2017, using a high-resolution cloud permitting model. The warming trend of EAMS with atmospheric warming since 1980s increases the simulated 12-hr precipitation to 6.8%, corresponding to approximately 10% increase per 1 K of SST rise, consistent with the previous data analysis study. Slight increase in heat and moisture supplies due to the warming EAMS has impacted a conditionally unstable condition of air masses flowing into an area of the precipitation, leading to more vigorous convective systems. Moisture budget analysis indicates that the changes in the amount of precipitation is not responsible for the availability of precipitable water but the intensification of the convective system. Since the change in precipitation amount exhibits high sensitivity to the SST trends, use of multiple SST datasets is desirable to provide a more reliable estimate and its uncertainty.

This paper presents an observational dataset on submesoscale eddies, which obtains from high-resolution chlorophyll-a distribution images from GOCI I. We employed a combination of digital image processing, filtering, YOLOv7-X, and small object detection techniques, along with specific chlorophyll image enhancement processing, to extract information on submesoscale eddies, including their time, polarity, geographical coordinates of the eddy center, eddy radius, coordinates of the upper left and lower right corners of the prediction box, area of the eddy's inner ellipse, and confidence score, which covers eight daily periods between 00:00 and 08:00 (UTC) from April 1, 2011, to March 31, 2021. We identified a total of 19,136 anticyclonic eddies and 93,897 cyclonic eddies at a confidence threshold of 0.2. The mean radius of anticyclonic 15 eddies is 24.44 km (range 2.5 km to 44.25 km), while that of cyclonic eddies is 12.34 km (range 1.75 km to 44 km). The unprecedented hourly resolution dataset on submesoscale eddies provides information on their distribution, morphology, and energy dissipation, making it a significant contribution to submesoscale eddies of study. The dataset is available at https://doi.org/10.5281/zenodo.7694115.