We present the first water vapor profiles encompassing the upper mesosphere of Mars, 100–120 km, far exceeding the maximum altitudes where remote sensing has been able to observe water to date. Our results are based on solar occultation measurements by Atmospheric Chemistry Suite (ACS) onboard the ExoMars Trace Gas Orbiter (TGO). The observed wavelength range around 2.7 μm possesses strong CO2 and H2O absorption lines allowing sensitive temperature and density retrievals. We report a maximum H2O mixing ratio varying from 10 to 50 ppmv at 100–120 km during the global dust storm (GDS) of Martian Year (MY) 34 and around southern summer solstice of MY 34 and 35. During other seasons water remains persistently below ~2 ppmv. We claim that contributions of the MY34 GDS and perihelion periods into the projected hydrogen escape from Mars are nearly equivalent.

Tephra layers are often used to reconstruct past eruptions. However, accurate interpretation of tephra layers depends on their degree of preservation. We asked: how much volcanological information do terrestrial tephra layers typically retain? We addressed this question with a study of the tephra layer produced by the May 1980 eruption of Mount St Helens, comparing historical records of deposit thickness and grain size distribution with measurements made four decades after the eruption. Using published isopach maps as a guide, we looked for the tephra layer in locations 15 – 600 km from Mount St Helens, selecting sample locations we judged to have high preservation potential. We found that preservation of the 1980 tephra deposit was often extremely good: observed thickness, mass loading and grain size distributions were similar to equivalent measurements made in 1980. However, we also observed high variability in preservation on small spatial scales, and our results indicate that landscape-scale volcanological reconstruction is sensitive to sample number and location, even when many sites display excellent preservation. Tephra preservation is clearly a complex and contingent process influenced by climate, biology, topography, parent material (i.e., grain size, morphology and geochemistry) and time. The relative importance of these factors will vary from place to place. We propose that the only way to tease apart these factors – and to fully understand the information content of tephra layers - is through direct observation of tephra deposits (whether natural or experimental) over extended time periods.

Unmanned Aerial Vehicle (UAV) based Structure-from-Motion (SfM) techniques have renovated 3D topographic monitoring of earth surface, offering low-cost, rapid and reliable data acquisition and processing. Multi-temporal models of the river environment can be produced by autonomous operation in order to determine erosion, subsidence, landslide, soil transport and surface deformation in the riverbeds. Herein, the acquisition of repeated topographic surveys helps us to characterize the flow regime and to monitor the sediment dynamics. This study presents the hydromorphological changes of the meandering structures by using UAV-generated point clouds and Digital Surface Models (DSMs) produced by SfM at different times in the Büyük Menderes Basin located in the western part of Turkey. The processing of the data obtained with the flights were made in January and June 2018 at selected three meander locations with the highest visible changes according to the long-term satellite imageries. Especially, riverbank erosion along the river was determined by digitizing the edges and volumetric calculations of the eroded/deposited sediments derived from UAV-based measurements. In addition to the periodic volumetric differences of the meander structures, the differences in volumetric comparison methods for the same meander structures have been evaluated. Ultimately, the sediment profiles were extracted along the river banks at the selected part of the meanders and the amount of deposited sediments were determined to increase in a range between 1.5% and 3.3% of the total sediment. In conclusion, it is estimated that UAVs will be used instead of conventional photogrammetry aircraft in many future projects, considering the data production times and costs in large areas. Further, various digital cameras and sensors can be mounted on UAVs in order for examining the sediment effect on the health and productivity of plants in agricultural areas around the meanders.

The devastating impacts of the widespread flooding and landsliding in Puerto Rico following the September 2017 landfall of Hurricane Maria highlight the enhanced hazard potential from increasingly extreme storms in mountainous humid-tropical climate zones. Long-standing conceptual models for hydrologically driven hazards in Puerto Rico posit that hillslope soils remain wet throughout the year and antecedent soil wetness imposes a negligible effect on hazard potential. Our post-Maria in situ hillslope hydrologic observations indicate that while some slopes remain wet throughout the year, others exhibit appreciable seasonal and intra-storm subsurface drainage. Therefore, we used receiver-operating characteristic analysis and the Threat Score (TS) skill statistic to evaluate the performance of hydro-meteorological (soil wetness and rainfall) versus intensity-duration (rainfall only) hillslope hydrologic response thresholds that identify the onset of positive pore-water pressure, a predisposing factor for widespread slope instability in this region. We found that the hydro-meteorological thresholds outperformed intensity-duration thresholds for a seasonally wet, coarse-grained soil (TS = 0.8 vs. 0.6, respectively), although they did not outperform intensity-duration thresholds for a perennially wet, fine-grained soil (TS = 0.2 vs. 0.2, respectively). These soils types may also produce radically different stormflow responses, with subsurface flow being more common for the coarse-grained soils underlain by intrusive rocks versus infiltration excess and/or saturation excess for the fine-grained soils underlain by volcaniclastic rocks. We conclude that variability in soil-hydraulic properties, as opposed to the humid-tropical climate zone, is the dominant factor that controls runoff generation and modulates the importance of antecedent soil wetness for our hillslope hydrologic response thresholds. Our findings encourage further deployment of continuous in situ hydrologic monitoring to facilitate the development of empirical hillslope hydrologic response and landslide thresholds for regional-scale hazard warning systems that must account for spatially variable soil types.

Traditionally, NOAA NESDIS has distributed GOES imagery as small sector images, usually a jpg or gif. With the launch of GOES-16, NESDIS has embraced a more modern approach to serving this imagery: NOAA Satellite Maps is a geospatial data Map Service to access imagery from the geostationary and polar satellites in our fleet. We support open information sharing and integration through this RESTful Service, which can be used by a multitude of GIS software packages and web map applications (both open and commercially licensed) for free. One of the most important features of the Satellite Maps layers service is the interoperable nature of its data. Users can combine georeferenced data layers from other datasets together with the Satellite Maps data, allowing infinite opportunities for providing meaning and value to NOAA data. For example, GOES East infrared Band 10 data can be combined with Doppler radar data and Lightning data to see how cloud cover and instances of rain align during a critical weather event. In this poster we will discuss the architecture and application development that were used to generate the image services and how the public is accessing and downloading GOES imagery.

In recent decades, climate change has lengthened wildfire seasons globally and doubled the annual area burned. Thus, capturing fire dynamics is critical for projecting Earth system processes in warmer, drier, more fire prone future. Recent advances in fire regime modeling have linked land surface and Earth system models with fire behavior models. Such models often rely on fine surface fuels to drive fire spread, and while many models can simulate processes that control how these fuels change through time (i.e., fine fuel succession), fuel loading estimates remain highly uncertain. Uncertainties are amplified in climate change forecasts when initial conditions and feedbacks are not well represented. The goal of this review is to highlight fine fuel succession as a key uncertainty in model systems. We review the current understanding of mechanisms controlling fine fuel succession (with an emphasis on decomposition), describe how these mechanisms are incorporated into models, and evaluate the strengths and uncertainties associated with different approaches. We also use three state-of-the-art fire regime models to demonstrate the sensitivity of decomposition projections to both parameter and model structure uncertainty and show that sensitivity increases dramatically under future climate warming. Given that many of the governing decomposition equations are hard-coded in models and often based on individual case studies, substantial uncertainties are currently ignored. To understand future climate-fuel-fire feedbacks, it is essential to be transparent about model choices and uncertainty. This is particularly critical as the domain of Earth system models is expanded to include evaluation of future wildfire regimes.

In recent years, the Southern Ocean has experienced unprecedented surface warming and sea ice loss—a stark reversal of sea ice expansion and surface cooling trends that prevailed over preceding decades. The most dramatic changes occurred in the austral spring of 2016 when Antarctic sea-ice extent (SIE) reached a record minimum as sea surface temperatures (SST) climbed to a near-record high. In late 2019, another circumpolar surface warming event spanned the Southern Ocean, albeit with no appreciable decline in Antarctic SIE. A mixed layer heat budget analysis reveals that these recent circumpolar surface warming events were triggered by a weakening of the circumpolar westerlies, which decreased northward Ekman transport and accelerated the seasonal shoaling of the mixed layer. The latter effect amplified the surface warming effect of air-sea heat fluxes during months of peak solar insolation. More generally, summertime SST across the Southern Ocean is sensitive to the timing of the springtime shoaling of the mixed layer, which is controlled by the strength and temporal variance of the circumpolar westerlies. An examination of the CESM1 large ensemble demonstrates that these recent circumpolar warming events are consistent with the internal variability associated with the Southern Annual Mode (SAM), whereby negative SAM in austral spring favors shallower mixed layers and anomalously high summertime SST. Thus, future Southern Ocean surface warming extremes will depend on the evolution of regional mixed layer depths and interannual SAM variability.

The remediation of chromium (Cr) contaminated sites presents a complex challenge due to the hazardous nature of Cr compounds and their adverse impacts on human health and the environment. In addressing this pressing concern, the present study endeavors to contribute to the understanding of technology suitability for effective Cr-contaminated site remediation through a comprehensive Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis. Drawing upon an exhaustive review of the existing literature, this research first identifies and evaluates the strengths of various technologies commonly employed in Cr-contaminated site remediation. These strengths encompass the capacity of technologies to efficiently reduce Cr concentrations, promote sustainable remediation practices, and ensure minimal collateral damage to surrounding ecosystems. Furthermore, the analysis delves into the weaknesses of these technologies, highlighting potential limitations that may impede their optimal performance. The study then explores the opportunities that arise from implementing these technologies, including advancements in remediation processes, novel materials, and cutting-edge monitoring and assessment tools. Additionally, the research critically assesses the threats posed by the application of these technologies, encompassing potential economic, technical, and environmental challenges that may hinder their widespread adoption. By synthesizing these key findings, the study aims to provide valuable insights into the selection and deployment of appropriate remediation technologies tailored to Cr-contaminated sites. Furthermore, the SWOT analysis offers a structured framework for decision-makers, environmental practitioners, and policymakers to make informed choices concerning the most suitable technology options for site-specific circumstances. In conclusion, this research illuminates the diverse landscape of technologies available for Cr-contaminated site remediation, accentuating their respective strengths, weaknesses, opportunities, and threats. As such, this SWOT analysis serves as a vital resource in the ongoing efforts to remediate and restore Cr-contaminated sites, thereby safeguarding public health and the environment for future generations. Article in AGU23 Website

Climate change is impacting polar regions at an accelerated rate, causing rapid changes in land cover and biodiversity. One case is the “greening up” of the Western Antarctic Peninsula (WAP), the result of receding glacial fronts exposing substrate for plants and soil development, together with higher temperatures and potential increases in cloud-free conditions conducive to plant growth. The 2019/2020 austral summer was the warmest on record for the WAP, yet the controls on land surface temperature (LST) here are not well understood. We investigated the relationships between land cover type, solar radiation, and LST for several vegetated coastal outcrops (0.3 to 0.5 ha) distributed from 64 to 65°S along the WAP. Remote sensing data was collected in February/March 2020 using a consumer-grade unmanned aerial vehicle (UAV), additionally equipped with near-IR and thermal-IR sensors. Digital surface models produced from the UAV imagery were used to calculate surface solar radiation. NDVI was used to identify four land cover classes: healthy vegetation, unhealthy vegetation, loose substrate, bedrock. Thermal-IR data provided sub-decimeter LST mapping. LST ranges varied depending on atmospheric conditions. A site surveyed under cloud-free conditions and air temperature of 6.6°C showed a 37.2°C range in LST, while a nearby site surveyed the next day under overcast conditions and air temperature of 2°C showed a 10.4°C range in LST. Vegetation at these two sites reached maximum temperatures of 27°C and 11.6°C, respectively. We found little within-site difference in either mean or range of LST among the land cover classes. Using linear regression, solar radiation explained less than 50% of the observed LST. Healthy vegetation showed the strongest relationship between solar radiation and LST. It was determined that LST in the WAP was strongly affected by factors other than solar radiation, implying latent heat effects. As the abundance of healthy vegetation increases in these areas, LST may show a stronger relationship with solar radiation, thus effecting local feedbacks to warming. This study presents the first application of UAV-derived thermal-IR data for the analysis of LST controls in Antarctica, highlighting the capability of UAV as a data collection platform for use in remote and relatively data-poor environments.

Around the world there is a consensus of the importance of knowladge the ice thickness distribution and total ice volume for estimating future glacier change for both glaciological and hydrological application, especially the Polar Regions for being important regulators of the global climate system and response rapidly to climate change. This work aimed to estimate the ice thickness distribution and total ice volume of Znosko glacier (King George Island, Antarctic Peninsula) using Glacier Bed Topography (Glabtop) model and ground data. Ground penetrating radar (GPR) measurements were collected in two field campaigns. GPR measurements were used to validate, calibrate (shape factor) and improve the accuracy of the ice thickness distribution model. The ice thickness (GPR) distribution is not uniform over the glacier, which varies from 0 to 155 m. The total stored ice volumen of Znosko glacier in 2020 is estimated to be 0.11 km3. Additionally, the model bounded areas in the bedrock topography below sea level, as a sign of future lake formation. Sensitivity analysis reveal that Glabtop model with a shape factor (f) = 0.5 gave best results when compared with ground penetrating radar (GPR) data measured on Znosko glacier and has an uncertainty range of ± 20.5%.

A challenge to managing water resources is characterizing the scale-dependent heterogeneity created by the interactions among hydrological, ecological and anthropological processes. It is often difficult to collect sufficient empirical data over the range of scales required to construct mathematical models that facilitate robust bottom-up descriptions or predictions. An alternative is identifying emergent properties of complex systems, whose components self-organize into novel structures or processes via their collective interactions with each other and the environment. A new level of organization and complexity emerges that cannot be predicted from or attributed to the components alone. Emergence offers a number of perspectives from which to interpret, if not predict, the behavior of complex water resource systems. One of these is entropy, which maximizes the options for system components to alter their interactions and, thus, permits variability and adaptability. At the scale of watersheds, increased entropy is pertinent because of its relationship to information (as probability functions), which is transmitted through connected components of a watershed in a manner such that the accrued information gives rise to emergent properties. Hence, analyzing the behaviors of a system according to emergence introduces the possibility of evaluating the information content via its interconnected components. Connectivity then assumes an integral role in a hydrologic system’s response to natural or anthropogenic disturbances (e.g., climate change, land use). Replacing the details of multi-scale heterogeneity and causal mechanisms with the functions that watersheds perform allows processes such as stream flow rate/duration and flood frequency to be construed as emergent spatiotemporal patterns. A reductionist or bottom-up approach to assessing the behavior of aquatic systems shifts to a functional or top-down approach that does not depend upon an understanding of all the physical, chemical or biological mechanisms involved. This latter approach could supplement conventional water resource descriptions and predictions via more comprehensively characterizing watershed or aquatic ecosystem functions.

Rapid economic development and expansion of the human population in China have made China currently the world’s largest producer and consumer of reactive Nitrogen (Nr), leading to severe damage to human and ecosystem health. In this context, managing N is fundamental to sustainable development in China. An accurate N budget is a basis for effective N management and evidence-based decision-making to tackle both food security and environmental protection challenges. However, significant disparities exist among previous estimates of N budgets and fluxes flow. This study attempts to advance understanding of uncertainties in China’s N budget using the Coupled Human And Natural Systems (CHANS) model and Monte Carlo simulation from 1980 to 2018. Results show that the spatial and temporal variations in agricultural and industrial activities and insufficient knowledge on N cycling parameterization are the two dominant causes of uncertainties in the N budget in China. Uncertainties of N inputs generally are <10%, while they are <30% for N outputs and >30% for N accumulations. Uncertainty of nitrogen oxides emission is more sensitive to energy consumption due to the large contributions from industry and transportation, while the uncertainty of ammonia emission is predominantly affected by agricultural activity. Combining surface measurements, satellite observations, and atmospheric simulation models enables cross-check of N fluxes in multiple systems and reduce uncertainties of the N budget.

Ocean heat analyses of the North Atlantic Ocean based on the new high-resolution Northwest Atlantic (NWA) Regional Climatology (RC) developed at the NOAA’s National Centers for Environmental Information (NCEI) revealed decadal variability of the Eighteen Degree Water (EDW) depth that may be instrumental for understanding the localized heat accumulation in the NWA. The EDW is an important element of the Northwest Atlantic heat balance and an indicator of the ocean-atmosphere interaction in this region. The EDW deepening, or “heaving”, on decadal timescales are most likely caused by increasing Ekman pumping due to changes in the wind stress curl pattern over the NWA. The NCEI’s NWARC has also revealed that the highest rates of heat gain occur in the Sargasso Sea, southeast of the Gulf Stream path in the region occupied by the EDW. The volume of EDW depends on many factors, of which the most important are: Ekman pumping, heat fluxes at the air-sea surface, and heat advection within the Gulf Stream and the subtropical recirculation gyre. However, heat accumulation in several “pockets” southeast of the Gulf Stream and its extension seem to be most closely connected to EDW heaving. The depths of EDW for two independent ~30-year periods and their differences were computed and analyzed in conjunction with the changes in the curl of wind stress. As the comparison between the EDW depths mapped on three different spatial grids with 1°x1°, 1/4°x1/4°, and 1/10°x1/10° resolutions illustrate, the grid resolution does matter for mapping EDW on decadal timescales. The 30-year climate shift of the EDW depths between 1985-2010 and 1955-1984 compares quite well with the climatic shift in Ekman vertical velocities derived from the changes in the wind stress curl over the same time period. Comparing the eddy-permitting EDW heaving inferred from the NCEI’s NWARC and the ~30-year shift of the curl of wind stress, and consequently Ekman pumping, confirms a strong resemblance of the eddy-permitting and eddy-resolving EDW heaving patterns with two tightly localized pockets of heat accumulation southeast of the Gulf Stream and its extension.

Studies of interior air exposures to various human and non-human components has largely been restricted to industrial exposures for the purpose of regulation. In contrast, little attention has been paid to exposure at the residential scale, where people spend much of their day and may be exposed to particulate sources ranging from known toxins, such as lead, arsenic, and asbestos, to human-produced chemicals of yet unknown toxicity, such as flame retardants. To capitalize on experience with citizen science initiatives as they pertain to environmental health, researchers formed an international network called 360 Dust Analysis, which provides guidance on citizen science and interior dust collection, as well as research tools to examine dust through analysis in regional labs. We present initial results from the July 2018 launch of this program in the USA, called DustSafe USA and operated under approved human subjects protocols by Indiana University (http://www.urbanhealth.iupui.edu/). We launched via multiple media strategies, including an extended television news segment, an article in several Indiana newspapers, appearances in several statewide radio shows, and via a widely distributed press release. As of this abstract submission, well over 300 queries were received, and after only two weeks of the launch the lab has received nearly 100 dust samples. Participants are largely from central Indiana where most of the media play occurred, but samples have also come from all over the country. We will present geochemical and compositional results from the dust analysis, but perhaps more importantly we will discuss how citizens were engaged, how the funding model for such efforts might be developed, and the general approach to research translation and citizen science.

Geothermal or ground source heat pumps (GSHPs) are among the growing renewable energy technologies used for heating and cooling of buildings. However, little work has been done to investigate their geo-environmental effects within the subsurface, especially in contaminated environments. This research uses FEFLOW software, to simulate heat and mass transport of a vertical closed-loop GSHP system. Transient flow and heat transport results for a multiple borehole system are presented for a hypothetical building located in Toronto, Canada, and shows long-term effects on subsurface temperature. Moreover, the impact of heat exchanged with the subsurface on biodegradation kinetics is examined in a contaminant transport simulation, to evaluate the possibility of utilizing this heat as a remediation strategy. The results revealed that temperature changes caused by GSHP operation can significantly enhance biodegradation of hydrocarbon contaminants. For instance, elevated subsurface temperature resulted in 96% reduction in benzene concentration, after one year of GSHP simulated operation for an office building located in Toronto, Canada.

Current machine learning methods for discharge prediction often employ aggregated basin-wide hydrometeorological data (lumped modeling) for parametric and non-parametric training. This approach may overlook the spatial heterogeneity of river systems and their impact on discharge patterns. We hypothesize that integrating temporal-spatial hydrologic knowledge into the data modeling process (distributed/disaggregated modeling) can improve the performance of discharge prediction models. To test this hypothesis, we designed experiments comparing the performance of identical Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) models forced with either lumped or distributed features. We gather meteorological forcing and static attributes for the Mackenzie basin in Canada- a large and unique basin. Importantly, discharge performance is assessed out-of-sample with k-fold replication across gauges. Results reveal a 9.6% improvement in the mean Nash-Sutcliffe Efficiency (NSE) and a 4.6% improvement in mean Kling-Gupta Efficiency (KGE) when LSTMs are trained with distributed information. Notably, the models exhibit consistently unbiased predictions, with a negligible relative bias (RBias ≈ 0.0) across all predictions. These experiments and results demonstrate the importance of integrating topologically guided geomorphologic and hydrologic information (distributed modeling) in data-driven discharge predictions.

Soils of mountain regions are estimated to contain large amounts of organic matter (OM), equivalent to stocks found in high-latitude boreal and tundra soils. Mountain environments are also experiencing profound changes in land management under the influence of socio-economic pressures as well as the need to adapt to climate change, which is occurring at a faster rate than in lowland areas. These anthropogenic impacts are expected to strongly affect soil OM storage. Most studies of land-use change have however focused on topsoil OM; whether similar trends will hold true for subsoil OM remains unknown. Using Rock-Eval pyrolysis as a proxy for soil OM dynamics, we showed that the hierarchy of controls on OM properties and transformations varied greatly with increasing soil depth. In the topsoil, OM properties were related to the nature of plant inputs, their degree of in-mixing with the mineral matrix and the occurrence of seasonal water saturation. In the subsoil however, the foremost predictors of OM properties were geochemical parameters. This shift in the nature of determinants of OM dynamics indicates that shallow and deep soil OM pools should respond differently to external forcings. Podzolic profiles showed the strongest decoupling of topsoil and subsoil OM properties. We focused on this soil type to specifically investigate the effects of land use on subsoil OM. We selected field sites from the Coastal Range of British Columbia, Canada and the Pennine Alps, Switzerland representing undisturbed and managed forest, shrubland and pasture. Samples were analyzed for organic C content, OM quality and reactive mineralogy. Results showed that herbaceous cover was associated with an increase in topsoil but not subsoil OM. In the subsoil, variations in OM content and properties were associated with changes in reactive Al and Fe mineral phases. Overall, our data indicate that organo-mineral and organo-metal interactions are of prime importance to OM accumulation in the subsoil, and that understanding the response of deep soil C stocks to land use change will require consideration of the geochemical and mineralogical environment. Our results further suggest that so-called reactive mineral phases may themselves be impacted by land use, in turn affecting deep soil C stabilization and destabilization processes.

As wildfires become more prevalent and destructive, it is imperative to understand the impacts they have on the watersheds they burn. One particularly understudied aspect of wildfire-associated water quality impairment is the generation of polycyclic aromatic hydrocarbons (PAHs), a class of organic contaminants with carcinogenic, mutagenic, and ecotoxic properties. As a case study, we investigate PAH impacts associated with the 2018 Woolsey Fire, which burned over half of the Malibu Creek Watershed near Los Angeles, California. We collected soil and water samples periodically and during rain events over three years following the fire. Sampling sites were distributed through the watershed to incorporate samples from all major tributaries of Malibu Creek and to capture varying topography, geology, land use, and fire intensity. We found PAH concentrations exceeding EPA Ambient Water Quality Criteria, primarily during rain events, through the second wet season after the fire. Using molecular ratio approaches, the PAHs detected in water samples were directly linked to burned soil. Elevated PAH concentrations were associated with suspended particulate matter, which was in turn directly related to stream discharge and precipitation intensity. However, significant geographic variability was observed during the second wet season, suggesting topography, burn intensity, and other factors play a role in post-fire recovery and the persistence of fire-derived PAHs in the watershed. We investigated the contribution of these factors through a combination of long-term soil and water sampling, assessment of suspended particulate material, analysis of the variation and evolution of PAH compound distributions, and evaluation of geographic controls. Results suggest that an interplay of multiple geographic factors contribute to the observed variations. Understanding these complex mechanisms is critical to predicting long-term wildfire impacts to water quality in diverse settings.