In the paper summarized by this presentation we trace how maps aided the conceptualization and ensuing debate over one of the first inherently spatial and multiscale environmental issues, acid rain. Through interviews with early acid rain ecologists and a critical cartographic analysis of printed maps, we show that mapping was central for constructing this environmental issue. Rather than static representations of a scientific reality, acid rain maps were interconnected and relational processes that operated within political and economic discourses. Accordingly, we suggest that increased critical engagement and participation with the process of mapping can productively aid dialog on many issues, including other current multiscale environmental issues, such as climate change.

Observation of earthquake-induced changes in well water levels provides an opportunity to study the effects of seismic activity on the groundwater system. In this study, we used data from a plain-scale well network in the alluvial Canterbury Plain of New Zealand's South Island to document sustained and complex changes in well water levels, following the 2010 Darfield earthquake. We interpret that the sustained increases in well water levels in the midstream area, as well as sustained decreases in the downstream area, resulted from decreases in plain-scale permeability. These decreases in permeability were caused by the consolidation of the liquefied sediments following the earthquake. These results may provide a better understanding of the effects of large earthquakes on groundwater systems and resources, especially in liquefaction areas.

Over recent years, remote sensing of sea ice has advanced at a rapid pace. However, there are inherent limitations in the ability of existing space and airborne sensors to observe changes in the properties of near-shore sea ice, especially over short (hourly) time scales. This information is of critical importance to the livelihood of local communities and to meteorologists who depend on knowledge of near-shore ice conditions for weather prediction. The use of near-real-time data from coastal seismic arrays promises to advance coastal ice observations by measuring the amplitude of background seismic noise, known as microseism. The microseism signal is generated by interactions between oceanic waves, the ocean floor, and the shoreline. Previous studies have shown that along polar coastlines the microseism is modulated by the presence of sea ice. In this feasibility study, we explore the use of power spectral density (PSD) measurements from the Utqiagvik station of the EarthScope Transportable Array (TA) to provide information about sea ice conditions off the northern coast of Alaska. PSD signals are compared with daily estimates of near-shore ice extent and concentration within the Beaufort and Chukchi seas. These are derived from satellite passive microwave radiometer data as well as visible and short-wave infrared imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments. The amplitude of microseism at a frequency near 1 Hz is statistically correlated with ice coverage to determine if microseismic signals from a coastal station can be used to reliably identify particular ice events, including the onset date of summer melt, fast-ice breakup and formation, and the development of near-shore flaw-leads and polynas. Data from the Utqiagvik TA station is compared with observations from other northern coastal stations to determine if sea ice related microseismic signals are consistent across a range of geological and topographical environments. The expansion of the EarthScope TA seismic network to the Arctic coastline since 2011 presents a developing approach to sea ice observation. In the future it may complement established remote sensing techniques to provide a more complete picture of coastal ice conditions as they evolve.

A method is presented to address model state uncertainty in hydrologic model simulation. This is achieved by introducing tuneable parameters that allow adjustments to the model states. Excessive dimensionality is avoided by introducing only a limited number of parameters that control the index (timing) and size of the state adjustments. The method is designed to compensate for issues with hydrologic model structures, particularly those relevant to the soil moisture state in a rainfall-runoff model. In the context of water resource planning and management, errors in the model states have often been overlooked as an important source of uncertainty and have the potential to significantly degrade model simulations. A synthetic study shows that a classical parameter estimation approach will produce biased distributions when state errors exist, and that the proposed state and parameter uncertainty estimation (SPUE) can remove the bias in parameter estimates for improved model simulations. In a real case study, SPUE and the classical approach are implemented in 46 sites around Australia. The results show that hydrologic parameter distributions for a selected conceptual model can be significantly different when accounting for state uncertainty. This has large implications for scenario modelling since it puts into dispute how to determine appropriate parameters for such studies. SPUE parameters outperform the classical approach in a range of metrics including the Akaike Information Criterion. Additionally, SPUE parameters performed better during validation periods. Future work involves testing SPUE with different hydrologic model and likelihood formulations, and enhancing rigor by explicitly accounting for observational data uncertainty.

Quantifying forest biomass is an important part of determining the regional carbon balance, but currently there is little knowledge regarding forest carbon storage at a high spatial resolution. Here, we combined a deep learning (DL) algorithm with field measurements, light detection and ranging (LiDAR) observations, Landsat and ALOS/PALSAR images to develop a spatially explicit estimate of forest aboveground carbon density at a 30 m spatial resolution for northeast China, home to nearly one-third of China’s forested area. We also conducted an uncertainty analysis using the bootstrap method. The DL method performed well, with a high coefficient of determination (R2) of 0.84 and a relatively low root mean squared error of 6.28 MgC ha-1, and is superior to traditional machine learning methods such as random forest, support vector machine and artificial neural network. The forest carbon storage is estimated to be 2.43 ± 0.10 PgC, and increases along the latitude gradient. Among climatic factors, the wettest month precipitation and annual mean temperature stand out in explaining the spatial variation of forest carbon density, with contributions reaching 15.8% and 10.8%, respectively. A model-data comparison shows that current ecosystem models generally capture the spatial pattern of forest carbon density but underestimate the forest carbon storage by 22.2%, partially due to the overestimation of high-temperature inhibition, highlighting the need to re-parameterize such temperature effects in forest carbon simulations.

Coastal vegetated habitats, including mangroves, saltmarshes and seagrasses, mitigate climate change by storing atmospheric carbon. Previous blue carbon research has mainly focused on organic carbon stocks. However, recent studies suggest that lateral inorganic carbon export might be equally important. Lateral export is a long-term carbon sink if carbon is exported as alkalinity (TAlk) produced via sulfate reduction coupled to pyrite formation. This study evaluates drivers of pyrite formation in coastal vegetated habitats, compares pyrite production to TAlk outwelling rates, and estimates global pyrite stocks in mangroves. We quantified pyrite stocks in mangroves, saltmarshes and seagrasses along a latitudinal gradient on the Australian East Coast, including a mangrove dieback area, and in the Everglades (Florida, USA). Our results indicate that pyrite stocks were driven by a combination of biomass, tidal amplitude, sediment organic carbon, sedimentation rates, rainfall latitude, temperature, and iron availability. Pyrite stocks were three-times higher in mangroves (103 ± 61 Mg/ha) than in saltmarshes (30 ± 30 Mg/ha) and seagrasses (32 ± 1 Mg/ha). Mangrove pyrite stocks were linearly correlated to TAlk export at sites where sulfate reduction was the dominant TAlk producing process, however pyrite generation could not explain all TAlk production. We present the first global model predicting pyrite stocks in mangroves, which average 155 (range 128 – 182) Mg/ha. In mangroves, estimated global TAlk production coupled to pyrite formation (~3 mol/m2/y) is equal to ~24% of their global organic carbon burial rate, thus highlighting the importance of including TAlk export in future blue carbon budgets.

The flow of gas through shallow marine sediments is an important component of the global carbon cycle and affects methane release to the ocean and atmosphere as well as submarine slope stability. Seafloor methane venting is often linked to dissociating hydrates or gas migration from a deep source, and subsurface evidence of gas-driven tensile fracturing is abundant. However, the physical links among hydrate dissociation, gas flow, and fracturing has not been rigorously investigated. We used mercury intrusion data to model the capillary drainage curves of shallow marine muds as a function of clay content and porosity. We combined these with estimates of in situ tensile strength to determine the critical gas saturation at which the pressure of the gas phase would exceed the pressure required to generate tensile fractures. Our work demonstrates that tensile fracturing is more likely as clay content increases due to decreased pore sizes and increased capillary pressure, but tends to be restricted to the shallowest portion of the sediment column (<130 m below seafloor) except when the clay-sized fraction exceeds 50%. Dissociating hydrate may supply sufficient quantities of gas to cause fracturing, but this is only likely near the updip limit of the hydrate stability zone, where release of methane bubbles from discrete vents is to be expected due to the combination of weak sediments and significant gas expansion. Gas-driven tensile fracturing is probably a common occurrence near the seafloor, does not require much gas, and is not necessarily an indication of hydrate dissociation.

Brief bursts of high frequency (HF) and very high frequency (VHF) radio emissions unaccompanied by strong low frequency radiation have been observed during initiation and propagation of lightning or thunderstorm electrical breakdown without leading to fully-fledged lightning. This paper investigates a physical mechanism to generate such radio bursts by electrical discharge activity inside a thundercloud. When a discharge consists of many high frequency emission sources, such as streamers, that generate currents in random directions, its radiation spectrum peaks in the HF and VHF bands, and the spectral magnitudes in low frequencies are much smaller or even negligible. Combined with recent observational findings, the present study suggests that lightning initiation may begin with a short burst of many randomly occurring small-scale discharges in a localized thundercloud region.

There is no consensus on the physical mechanisms controlling the scale at which convective activity organizes near the Equator, where the Coriolis parameter is small. High resolution cloud-permitting simulations of non-rotating convection show the emergence of a dominant length scale, which has been referred to as convective self-aggregation. Furthermore, simulations in an elongated domain of size 12228km x 192km with a 3km horizontal resolution equilibrate to a wave-like pattern in the elongated direction, where the cluster size becomes independent of the domain size. These recent findings suggest that the size of convective aggregation may be regulated by physical mechanisms, rather than artifacts of the model configuration, and thus within the reach of physical understanding. We introduce a diagnostic framework relating the evolution of the length scale of convective aggregation to the net radiative heating, the surface enthalpy flux, and horizontal energy transport. We evaluate these length scale tendencies of convective aggregation in twenty high-resolution cloud-permitting simulations of radiative-convective equilibrium. While both radiative fluxes contribute to convective aggregation, the net longwave radiative flux operates at large scales (1000-5000 km) and stretches the size of moist and dry regions, while the net shortwave flux operates at smaller scales (500-2000 km) and shrinks it. The surface flux length scale tendency is dominated by convective gustiness, which acts to aggregate convective activity at smaller scales (500-3000 km). We further investigate the scale-by-scale radiative tendencies in a suite of nine mechanism denial experiments, in which different aspects of cloud radiation are homogenized or removed across the horizontal domain, and find that liquid and ice cloud radiation can individually aggregate convection. However, only ice cloud radiation can drive the convective cluster to scales exceeding 5000 km, because of the high optical thickness of ice, and the increase in coherence between water vapor and deep convection with horizontal scale. The framework presented here focuses on the length scale tendencies rather than a static aggregated state, which is a step towards diagnosing clustering feedbacks in the real world. Overall, our work underscores the need to observe and simulate surface fluxes, radiative and advective fluxes across the 1km-1000km range of scales to better understand the characteristics of turbulent moist convection.

Over the last decades, environmental education – including the education about natural hazards - was focused solely on perspectives from the Earth sciences, on economic demands and societal challenges. Some scholars see the working programme for climate research of the EU as an example, which seems to be “characterized by its exclusion of human (cultural, ethical and spiritual) dimensions and is simply interested in monitoring and technical and socioeconomic engineering of solution policy” (Bergmann, 2010). Only recently cultural studies and theology have been introduced into relevant research, but a deeper understanding of “how human environmental attitudes get shaped and what causes those attitudes to change through time” (Kareiva; 2008) is still missing. While scientists agree, that there “… is also ample evidence that distinct cultural and religious values of individuals and whole societies influence their perception and tolerance of risk as well as their capacity to cope with environmental hazard” (Gerten, 2010), education and communication research have not yet focused on how these risks and hazards are transported into the public in respect to various socio-political environments. Within this presentation, we want to discuss ways to gain a better understanding of how cultural preconceptions influence science education and science communication.

We present a new analysis technique for estimating 2D neutral wind pattern using data from a single Scanning Doppler Imager (SDI) or a combination of SDIs, incoherent scatter radars (ISR) and Fabry-Perot interferometers (FPI) within overlapping field-of-views. Neutral wind plays an important role in ionospheric electrodynamics and Ionosphere-Thermosphere coupling, by for example affecting the Joule heating rates and plasma transport. However, reliable and extensive measurements of the neutral wind are rather difficult to obtain. Pointwise measurements can be obtained with ISRs or FPIs, but these measurements can not provide 2D latitude-longitude maps of the neutral wind pattern needed in mesospheric studies. A Scanning Doppler Imager can measure the line-of-sight (LOS) component of the neutral wind in dozens of directions simultaneously. However, further modeling is needed to convert the LOS velocities into 2D velocity maps. Unfortunately these maps are far from unique, as perpendicular velocities (e.g. rotation around the measurement site) are not visible in the LOS data. This can be mitigated by combining data from several nearby SDIs, or a combination of SDIs, FPIs and ISRs. Our analysis technique is based on fitting the LOS data with special vector basis functions called Spherical Elementary Current Systems (SECS). In this approach the wind is naturally divided into curl-free and divergence-free components, and there is no need to provide any explicit boundary conditions on the wind pattern. We present several synthetic test scenarios as well as first results using data from SDIs located in Alaska. Using the synthetic test scenarios we further estimate optimal locations for 2 or 3 SDIs that could be located around the future EISCAT_3D radar system in northern Scandinavia.

The southwestern U.S. has been experiencing prolonged drought conditions contributing to declines in snowpack and surface water supply. On the Navajo Nation (NN), the largest U.S. federally recognized sovereign tribal nation in land area, snowpack is an essential reservoir for surface water storage and aquifer recharge, but has not been extensively monitored. Within the NN, only two high elevation regions, Chuska Mountains and Defiance Plateau, have in-situ snow monitoring at eight sites (consisting of two SNOTEL stations and eight snow courses). With climate change contributing to long-term temperature increases, patterns of snowfall and snowmelt are changing and NN leaders are recognizing the need for more detailed and reliable monitoring systems. This study explored how NASA Earth Observations can be used to provide more frequent, high-resolution tracking of snow cover extent on the NN, and how those data can offer actionable insights for local water managers. The Normalized Difference Snow Index (NDSI), as derived from NASA MODIS products, was used to create daily cloud/gap-free images of Snow Covered Area (SCA) during the winter months (November – April) from 2002 to 2018. Aggregated weekly and monthly means were then constructed to study spatial and temporal anomalies in SCA. These data were compared with the available ground-based measurements of snow water equivalent (SWE). Results indicate that SCA anomalies can serve as a proxy for monitoring snowpack variability across all high-elevation areas of the NN. SCA anomalies also suggest that the NN snowpack is exhibiting increased variability during peak winter months, along with declines in the spring months, consistent with broader regional climate trends. This study aids in the establishment of remotely sensed snow monitoring on the NN. Further analyses would be improved through the use of additional snow products, such as the MODIS Snow Covered-Area and Grain size retrieval algorithm (MODSCAG) to estimate fractional snow cover and snow grain size, and NASA’s Airborne Snow Observatory (ASO) to estimate snow albedo and SWE.

Characterization of rocks from geothermal reservoirs is crucial to better understand their behavior. Los Humeros geothermal field contains one of the most important reservoirs in Mexico. This reservoir contains volcanic rocks product of various cooling processes. In the present study, we use four different samples, three distinct andesites and one highly altered volcanic rock from Los Humeros reservoir. We acquired 3D images using X-rays microtomography to visualize and estimate porosity in these rocks. In the three andesites, we used the maximum possible resolution of 0.5 micros/voxel. In the altered sample, we used four different resolutions of 0.5, 3, 14 and 53 microns/voxel and took physical and digital subsamples at various locations in the original core plug to compare and identify its heterogeneity. From the 3D images, image porosity after segmentation and fractal-scaling porosity were estimated. From the core plug, the experimental porosity was obtained by a collaborative lab (IPICYT). The fractal-scaling porosity approximates the fractal porosity under the assumption that all pores have the same size approximately equal to the box size, used in the box counting method. The calculations were done in all images at all resolutions. We found that the image porosity at the highest resolution is generally closer to the experimental porosity. However, the altered sample, even at this resolution, presents some variations. The image porosity of this sample at the other resolutions shows values far from the experimental porosity, as the pore space could not be fully capture. As a matter of fact, the fractal dimension increases from the lower resolution to the higher resolution as a mainly magnification effect, as well as the porosity. The fractal-scaling porosity, which uses the fractal dimension, the average spherical equivalent diameter, and the size of the image gives estimates of porosity very close to the image porosity. This demonstrates the fractal character of all these samples, implying that the pore structure in these rocks can be better evaluated using Fractal geometry. The different results obtained in the altered sample corroborates its diverse processes. To complete this study, we are working on finding potential correlations between these porous structures and permeability, and adding more samples.

Incoherent scatter radars (ISR) estimate the electron and ion temperatures in the ionosphere by fitting measured spectra of ion-acoustic waves to forward models. For radars looking at aspect angles within 5° of perpendicular to the Earth’s magnetic field, the magnetic field constrains electron movement and Coulomb collisions add an additional source of damping that narrows the spectra. Fitting the collisionally narrowed spectra to collisionless forward models leads to errors or underestimates of the plasma temperatures. This paper presents the first fully kinetic particle-in-cell simulations of ISR spectra with collisional damping by velocity dependent electron-electron and electron-ion collisions. For aspect angles between 0.5° and 2° off perpendicular, the damping effects of electron-ion and electron-electron collisions are the same and the resulting spectra are narrower than what current theories predict. For aspect angles larger than 3° away from perpendicular, the simulations with electron-ion collisions match collisionless ISR theory well, but spectra with electron-electron collisions are narrower than theory predicts at aspect angles as large as 5° away from perpendicular. At all aspect angles the particle-in-cell simulations produce narrower spectra than previous simulations using single particle displacement statistics. The narrowing of spectra by electron-electron collisions between 3° and 5° away from perpendicular is currently neglected when fitting measured spectra from the Jicamarca and Millstone Hill radars, leading to underestimates of electron temperatures by as much as 50% at these radars.

To estimate whole-stream metabolism, the open-channel oxygen method has traditionally provided underlying assumptions for modeled estimates of gross primary productivity (GPP) and ecosystem respiration (ER). The open-channel oxygen method employs the diel dissolved oxygen (DO) curve, which attributes stream metabolism to four processes: photosynthesis by primary producers, oxidative respiration, reaeration, and groundwater flux. Of these processes, groundwater flux is often assumed to be negligible when modeling whole-stream metabolism, which may introduce bias in estimates of GPP and ER. For example, if net groundwater flux is into the main channel, we may expect an overestimation of modeled ER due to dissolved oxygen dilution effects from influent groundwater. Although this error is recognized, there is a lack of continuous and spatial data that quantifies the extent of bias that is introduced by not including groundwater flux in model parameters. To investigate this bias, we measured whole-stream metabolism and groundwater flux in Como Creek, a headwater catchment 26 km west of Boulder, CO. DO sensors were deployed in the stream and groundwater wells in June 2018 at 3 sites along 500 m of the reach. BASE (Bayesian Single-station Estimation), a package available through R, was used for modeling whole-stream metabolism between peak streamflow and baseflow. BASE also optimizes the reaeration coefficient, which was estimated both including and neglecting groundwater discharge and DO concentration. Preliminary results indicate that Como Creek has a net groundwater flux out of the stream, resulting in higher rates of GPP in the groundwater-corrected model output, and indicating the potential for bias in uncorrected models.

The relationships between deformation and erosion in transpressive systems are still poorly understood. Here, we present a new set of analog models to investigate how the tectonic and surface processes present at transpressive plate boundaries interact to shape topography. The experimental setup comprised a 2 x 1 x 0.5 m3 plexiglass box fit with a plexiglass board cut to 20º obliquity. A motor pulled a mylar sheet beneath the board to generate a velocity discontinuity at the interface. We loaded a ~5 cm thick layer of a granular material onto the board and sheet composed of 40 wt. % silica powder, 40 wt. % glass microbeads, and 20 wt. % PVC powder (cf. CMII in Reitano et al., 2020, doi: 10.5194/esurf-8-973-2020). This setup allows deformation to nucleate at the velocity discontinuity and naturally form a transpressional wedge. The model was monitored with digital cameras and a laser scanner to conduct particle image velocimetry and digital elevation model analysis, respectively. To explore surface processes associated with mass transport and erosion, we used a sprinkler system that casts a uniform mist across the model surface. We allowed ~1 cm of relief (equivalent to ~10 cm of convergence) to form before misting began to ensure the formation of realistic drainage networks. Before misting, experiments evolved in 3 stages: 1) distributed strain, 2) strike-slip faulting along synthetic structures, and 3) uplift and formation of a wedge along bivergent thrust structures. After misting, strike-slip deformation was still fully partitioned to synthetic structures and thrust sheets propagated in the prowedge direction. As the experiment continued, sub-longitudinal drainage systems formed with their orientation controlled by synthetic structures. Strike-slip displacement along these structures interrupted transverse streams, which ultimately captured the sub longitudinal systems. On the retrowedge, a longitudinal basin formed along a coalesced extensional structure, which also was later captured by transverse channels. These and other interactions between fault structures and channel networks provide insight into erosion and mass transport in transpressional systems and the nature of the complex reorganization of stream networks in response to deformation.

We have shown that far-ultraviolet emissions of atomic hydrogen, oxygen, and carbon in the near-nucleus coma of comet 67P/Churyumov-Gerasimenko result primarily from electron impact dissociative excitation of H2O, CO2, and O2. Our initial detection of gas outbursts was based on detection of enhanced atomic oxygen emissions relative to those expected from H2O or CO2 and were attributed to electron impact on O2. This spectral signature of O2 was also observed in long-term limb observations. Molecular oxygen was first reported to be a significant constituent of the coma from Rosetta/ROSINA mass spectrometer measurements. Of the remote sensing instruments on Rosetta, only the Alice far-ultraviolet spectrograph is capable of measuring spatial and temporal variations of O2, both from atomic emissions as well as from stellar absorption measurements. Here we report on the detection and use of the far-ultraviolet emissions to estimate the abundance of O2 relative to H2O along lines-of-sight above the limb, and its variation over the period February 2015 to January 2016, corresponding to heliocentric distances within ~2.0 AU.

Expansion of unplanned agriculture and urbanization increases the danger of extreme flood and sedimentation. The Upper Awash basin has been under tremendous influence of human activities in the last five decades. The historical land use/land cover (LULC) change analysis was made by processing multi-temporal Landsat images and the future LULC was predicted using the Land Change Modeler. The LULC transition between a pair of classified LULC maps and driver variables were combined to predict the future LULC scenario. The five different LULC change and future land management scenarios are LULC 1974, LULC 2014, increase in the urban area, riparian and steep slope afforestation, and predicted future LULC 2045. The LULC change scenarios together with other spatial and climate data were used to simulate the hydrology, and sedimentation at four main subbasins using the calibrated soil and water assessment tool (SWAT) model. The mean monthly change in the water balance components and sedimentation have indicated higher rates of fluctuation due to LULC change. The riparian and steep slope reforestation scenario has reduced the mean annual surface runoff volume by 9.3% and sedimentation yield by 6.1% from the baseline LULC 2014. Moreover, the frequency of estimated 100-year annual extreme daily discharge reveals significant variation among the LULC scenarios. Notably, the future LULC 2045 has indicated a higher increase of extreme daily discharge by 23.5% at Homole subbasin. The study outlined the impact of land management on the flood events and sedimentation in the large basin, and spatial variation of LULC change impact has been presented. It suggests that the increase in deforestation due expansion of cropland and urbanization will intensify floods, whereas, riparian and steep slope reforestation has significantly reduced the peak discharge and sedimentation. Therefore, the future land management plans should consider appropriate vegetative conservation measures in the upland areas.