Using principal component (PC) analysis of 16 years of monthly series of nitrogen dioxide (NO2) from the Ozone Monitoring Instrument on the Aura satellite, we show that it is the third PC (PC3) from the deseasonalized hierarchy of principal modes that is best coupled with the economic indicators. This coupling is positive, i.e. PC3 and economic indicators manifest positive covariance. However, the economic variability can explain only 40% of the information in PC3. Furthermore, this mode by itself explains only 3% of the total deseasonalized NO2 variability. We thus conclude that, while having an unambiguous impact, the economy can be awarded at best third order of importance in the NO2 departures from the seasonal averages. Once we identified PC3 as the NO2 mode that is coupled with the economic variability, we use this mode as an indicator and look for rapid climate adjustments to that part of NO2 variability that we are confident is coupled with the economic variability. We focus on observational data from the Atmospheric Infrared Sounder (AIRS) on board of NASA Aqua satellite, decompose series of surface skin temperature and clear-sky outgoing longwave radiances (OLR) into principal components, and identify potential impacts of NO2 PC3 on these climate variables.

Fault zone usually presents a granular gouge, coming from the wear material of previous slips. Considering a mature fault gouge with mineral cementation between particles, we aim to understand the influence of these cohesive links on slip mechanisms. As cohesion is difficult to follow and to quantify with Lab or in-situ experiments, we choose to use Discrete Element Method that has already shown its ability to represent granular gouges with relevant kinematics and rheology. In this work, we consider a dry cohesive contact model in 2D (2x20mm²) involving two rough surfaces representing the rock walls separated by the granular gouge (5000 particles, grain size 27- 260 μm). A step forward compared to literature is to add cohesion on real angular and faceted grains that modifies contact between particles. Focusing on physics of contacts inside the granular gouge, we explore contact interactions and friction coefficient between the different bodies. To represent the cementation we set up a Bonded Mohr-Coulomb law, considering that inter-particular bridges and particles are made with the same material. This numerical model is displacement-driven and is implemented to study the peak of static friction (shape, slope, duration) under a confined pressure of 40 MPa. Depending on the compacity and on the cohesion level of each model, the peak strength may be sharp, short, and intense for dense and highly cohesive cases or smooth, delayed with moderate amplitude for mid-dense and moderately cohesive cases. Three main behaviors are observed: a non-cohesive regime where the added cohesion is too small to truly disturb the global slip mechanism (Couette flow), an intermediate cohesive regime with clusters of cohesive grains, changing the granular flow and acting on slip weakening mechanisms (Riedel shear band R1) and an ultra-cohesive regime where gouge behaves as a brittle material with several Riedel shear bands emergence. We also investigate the role of cohesive bonds in energy budget, focusing on fracture energy term. Three mechanisms are playing a role in fracture energy evolution: the rupture of cohesive bonds, the dilatancy of the gouge and Coulomb dissipations due to friction. These factors are linked to the initial percentage of cohesion inside the sample and help characterize the mechanisms at stake in the initiation of sliding.

Freshwater is limited in the semi-arid Arequipa region in Southern Peru that is home to more than 1.3 million people, agricultural and industrial sectors. To address water demand, eight reservoirs and more than 200 km of water diversion tunnels and canals have been implemented in the Quilca and Camaná river basins, resulting in severely modified hydrology and interconnection of the two basins. The Soil and Water Assessment Tool (SWAT) was used to simulate the current hydrological status and potential alternative management scenarios for the two interconnected basins. Simulation challenges include scarcity of data on soil and land cover to run SWAT, which was addressed by developing publicly available regional soil and land cover databases. A representation of water infrastructure required a complex model structure incorporating point sources to represent water transfers and reservoir outflows and water withdrawals at 17 locations. The developed model is used to provide a comprehensive understanding of water availability in the region under current and alternate scenarios for water regulation. The impact of current water infrastructure on minimum streamflow is explored in the Quilca and Camaná river basins. Results were shared with the local water authorities and the public via an online tool called HidroAQP to support water allocation and related water resource decisions.

Wetlands represent an essential ecosystem, providing flood control, carbon storage, and supporting biodiversity. In particular, the Everglades is a Ramsar Wetland of International Importance, supporting several threatened and endangered species of flora and fauna, and is especially important for wintering birds. Understanding and monitoring wetlands like the Everglades requires the ability to accurately identify and measure wetland extent and change in extent on short time scales. However, in situ methods are difficult given the nature of the surrounding environment, and optical methods of remote sensing are unable to see through dense vegetation. NASA’s Cyclone Global Navigation Satellite System (CYGNSS) has shown promising results using GNSS Reflectometry to identify the presence and extent of inland water. Utilizing GNSS as a signal of opportunity in an L-band passive bistatic radar, it can penetrate rain, clouds, and vegetation. Its 8-satellite constellation exhibits daily or sub-daily revisit rates, enabling the observation of dynamic changes on short time scales. In this work, we utilize a combination of CYGNSS data, ancillary information, and simulations to understand the observability of inundation beneath vegetation. Simulations were used to predict the received power using a water mask derived from Landsat imagery over the Everglades. By analyzing the differences between expected and actual received power, we identified areas of flooded vegetation. These differences were then combined with ancillary data sets to measure seasonal changes and create a seasonal map of open water and inundated vegetation throughout the Everglades network. We also investigated the ability of CYGNSS to discern and measure different vegetation types. Results were then compared with optical and radar imagery and verified with truth data from the Everglades Depth Estimation Network (EDEN) and littoral vegetation maps from the South Florida Water Management District. By leveraging CYGNSS’s high temporal frequency of observations and ability to see under vegetation, measurements of inundated vegetation and its change can complement other remote sensing and in situ methods of wetland monitoring.

Soil erosion is a worldwide agricultural and environmental problem that threatens food security and ecosystem viability. In arable environments, the primary cause of soil loss is short and intense storms that are characterized with high spatiotemporal variability. The complex nature of these erosive events imposes a great challenge for erosion modeling and risk analysis. Accurate high-resolution measurement of rain intensity is often lacking or sparsely available. As a result, many studies rely on coarser-resolution rainfall data that often fail to address the impact of intra-storm properties. In this study, based on a novel statistical method, we quantify the discrete and cumulative multiannual impact of rainstorm regime on runoff and soil erosion to better understand the most important rainstorm properties on erosion rate and amount, and, to provide storm-scale risk analyses. Central to our analyses is the coupling of a processes-based crop-land erosion model, Dynamic Water Erosion Prediction Project (DWEPP), with a stochastic rainfall generator that produces localized rainfall statistics at 5-min resolution (CoSMoS). To our knowledge, this is the first study that calibrated DWEPP runoff and sediment at the plot-scale on cropland. The model had an acceptable fit with measured event runoff and sediment data collected in northern Israel (NSE = 0.79 - 0.82). We then generated 300-year stochastic simulations of event-based runoff and sediment yield and used them to estimate erosion risk and calibrate a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. Results indicate that in the study area, high erosion rate events are characterized by intense rain bursts of short duration (shorter than the usually adopted erosivity index of 30-min), and not necessary by events of large volume accumulation or long duration. On these bases, we proposed an optimal rainfall erosivity index that combines intra-storm properties for the study area. As changes in rainstorm properties are expected under a changing climate, we expect our methodology to be a valuable tool for investigating the global concerns about future changes in soil erosion rate.

Atomic Hydrogen (H) is the most abundant constituent of the terrestrial exosphere. Its charge exchange interaction with ring current ions (H+ and O+) serves to dissipate magnetospheric energy during geomagnetic storms, resulting in the generation of energetic neutral atoms (ENAs). Determination of ring current ion distributions through modeling depends critically on the specification of the exospheric H density distribution. Furthermore, theoretical studies have demonstrated that ring current recovery rate after the storm onset directly correlates with the H density. Although measurements of H airglow emission at altitudes [3,6] Re exhibit storm-time variations, the H density distributions used in ring current modeling are typically assumed to be temporally static during storms. In this presentation, we will describe the temporal and spatial evolution of ring current ion densities in response to a realistically dynamic exospheric H density distribution using the Comprehensive Inner Magnetosphere-Ionosphere Model (CIMI). The exospheric densities used as input to the model are fully data-driven, derived as global, 3D, and time-dependent tomographic reconstructions of H emission data acquired from Lyman-alpha detectors onboard the NASA TWINS satellites during the geomagnetic storm that occurred on March 17, 2013. We will examine modeled ring current recovery rates using both dynamic and static reconstructions and evaluate the impact of realistic storm-time exospheric variability on the simulations.

We performed LES simulation of tropical cumulus clouds initialized with soundings from the RICO field project (vanZanten et al. 2011, JAMES). Our analysis concentrated on thermodynamic characteristics of convective clouds, specifically on relationships between the condensation/evaporation rates and cloud micro-physical and dynamical parameters. Such relationships are important for developing parameterizations of the sub-grid latent heat release on the grid size typical for a mesoscale model. The simulation was conducted using an integration domain of 50km; about 2000 clouds were selected for analysis over the course of the 28 hour simulation. The condensation/evaporation rates were analyzed by stratifying the clouds by their size (cloud top). The analyzed parameters included, among others, integral mass and buoyancy flux, cloud and rain water, supersaturation. The results of the analysis revealed a rather remarkable relationship between integral latent heat released in a cloud and cloud’s integral mass flux. This relationship may form the basis for parameterization development of latent heat release.

Sand dams, a water harvesting system built in arid or semi-arid regions, collect and store water in saturated sands to increase water availability in dry seasons, while avoiding evaporation and reducing water-borne disease vectors. The capacity of the dam to store water depends on the texture of the sediment accumulated in the reservoir. An ideal sand dam is expected to wash fine-grained particles, especially silt and clay out of the reservoir, collecting only coarse particles to provide for maximum open pore space and minimum capillary retention (the water is typically extracted via an open well). Although conceptually simple, sand dam commonly failed due to the retention of fine particles. It has been recommended to build sand dams in stages to overcome this problem, with each stage low enough so that the shear forces of flow will keep silt and clay mobile, and pass them out of the reservoir. Although it is effective, this method is not preferred in terms of cost and time spent (repeatedly re-mobilizing a team to add to the dam). We present a new approach to the siltation problem by seeking an ideal shape (weir) cut in the face of a sand dam designed to provide shear forces such that coarse particles accumulation while washing the finer materials such as silt and clay. This will be done by finding a relation between the cut-outs of in the face of the dam and the sediment transport rates. Challenges in predicting sediment transport rate are investigated using both numerical and experimental modeling. We seek to reduce the failure rate of sand dams, and also provide for a method to re-establish sediment fills behind existing dams.

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.

Eutrophication-induced hypoxia in a coastal estuarine system results in the deterioration of water quality, which is a growing issue worldwide. In early August 2016, an anoxic event caused the mortality of up to 75 percent of cultured oysters in aquaculture leases of northern Tracadie Bay, New Brunswick (TNB). Field observations revealed that, although the occurrence of summer hypoxia in north TNB is linked with anthropogenic stressors, changes in the geomorphology of one of the bay’s inlet are likely to play a significant role in escalating the eutrophic conditions. However, adequate information on the circulation dynamics of TNB estuarine system was lacking. To address this knowledge gap, a high-resolution spatially-explicit hydrodynamic model was developed for TNB to evaluate the possible physical processes involved in generation of hypoxia leading to oyster mortality. The model showed high skill (0.93) in south TNB in simulating water level elevations and slightly lower skill (0.85) in north TNB. Findings from modeling scenarios based on past, present and future inlet geomorphology suggest that it has strong consequences on intricate circulation patterns, renewal of water and transport. Further, the model is coupled with a volume advection-dispersion tracer module to track the dissemination of effluent and identify areas at risk of hypoxia. Residual flow estimates revealed poorly-circulated stagnant areas, consistent with hot spots in sediment organic matter content. Outcomes from this study will be of relevance for the management of water quality and aquaculture practices.

The urban environment directly influences the evolution of the Urban Boundary Layer (UBL). Heat adaptation strategies proposed to help cities respond to global change and urban induced warming, are also expected to reduce the intensity of convective mixing and decrease UBL depth, thereby reducing the volume of air available to pollutant dilution and dispersion. We use 20 km resolution WRF-ARW decadal scale simulations that account for end of 21st century greenhouse gas emissions, urban expansion and intensive and uniform implementation of cool roofs, green roofs and street trees to investigate the individual and combined impacts of these drivers on the dynamics of the UBL over the Conterminous US (CONUS). Results indicate that combined impacts of climate change and urban expansion are expected to increase summer (JJA) daytime UBL depth in the eastern regions of CONUS (peak value: Δh ≅ 80 m over Atlanta metro area). When adaptation strategies are applied, summer daytime UBL depth is reduced by a few hundred meters (peak value: Δh ≅ -310 m over Dallas and Fort Worth metro areas) in all CONUS regions as a consequence of decreased surface sensible heat fluxes. Adaptation impacts are greater inland and smaller over coastal cities. In arid regions, the adaptation induced increase in latent heat fluxes can counterbalance the projected decrease in UBL depth. Furthermore, adaptation strategies are expected to increase the static stability of both daytime and nighttime UBLs and decrease the magnitude of vertical winds, inducing earlier and stronger subsidence (peak value: Δm/s ≅ -0.05 m over Phoenix and Tucson metro areas). In light of these findings, ongoing work addressing these aspects with convection resolving, high-resolution simulations is needed to determine whether the widespread implementation of urban adaptation measures could have deleterious effects for urban air quality in the cities of the future Contiguous US.

Hollow glass microspheres (HGMs) are promising materials for arctic ice restoration. When spread in a thin layer on top of ice, these materials can increase the albedo of arctic ice, potentially slowing the rate of ice melt and enhancing the formation of multiyear ice in the polar region.[1] The effect of particle diameter and wall thickness of glass for backscatter efficiency in the visible and IR regions is evaluated by Mie scattering calculations and UV-Vis spectrophotometry of several candidate materials. The design of HGMs for highest backscatter efficiency and albedo enhancement is discussed. For use in arctic environments, both the fate of HGMs and their ecotoxicological impact must also be considered. HGMs with density <1 g/cc are preferred as they will float on the surface of melted ice pools. However, HGMs with very low density and thin walls may not be sufficiently robust to withstand significant weathering in the environment. Design considerations of tradeoff for density, reflectivity, and crush strength will be discussed. [1] Field, L., Ivanova, D., Bhattacharyya, S., Mlaker, V., Sholtz, A., Decca, R., et al. (2018). Increasing Arctic sea ice albedo using localized reversible geoengineering. Earth’s Future, 6, 882–901. https://doi.org/10.1029/2018EF000820

Field reversals are some of the most prominent and commonly known temporal variations of the geomagnetic field. Polarity changes have been observed in seafloor magnetisation patterns, volcanic records, sediment sequences, speleothem records, and have been reported in geodynamo simulations. However, open questions remain concerning the phenomenology and underlying causes of this process. In particular, there is currently no consensus about the temporal scales over which geomagnetic reversals occur. Numerical simulations aimed at understanding Earth’s million-year evolution have predicted a time scale on the order of thousands of years. On the other hand, analysis of a lacustrine sequence in the central Italian Apennines suggests that the most recent geomagnetic reversal (the Matuyama-Brunhes) took place in as short as 13 years, requiring VGP latitudinal changes of the order of 10 degrees/yr [Sagnotti, L. et al. (2015). GJI, 204(2), 798-812]. This extremely short decadal time scale challenges our current understanding of the geodynamo and present-day numerical models. Here we derive fluid flows at the top of Earth’s outer core that optimise either the rate of dipole decay or directional changes local to the Italian Apennines, subject to a minimal number of physical ingredients. Specifically, we neglect the internal dynamics and prescribe a total flow kinetic energy that is consistent with observational bounds. Our optimal flows can drive an instantaneous VGP latitudinal change of at most 5 degrees/yr during the Matuyama-Brunhes transition. Extending the methodology to account for the spatio-temporal evolution of the magnetic field, we find that this solution does not drive a global reversal, but only changes that are highly localised around the Mediterranean and West-African regions. Solutions that optimise the rate of dipole decay suggest that full reversal would take at least 380 years.

Although mass and energy in Jupiter's magnetosphere mostly come from the innermost Galilean moon Io's volcanic activity, solar wind perturbations can play crucial roles in releasing the magnetospheric energy and powering aurorae in Jupiter's polar regions. The relative importance of solar wind and internal processes in driving Jupiter's auroras remains poorly understood. Recently, the contemporaneous measurements from NASA Juno mission and the Hubble Space Telescope provide an unprecedented opportunity to determine the magnetospheric drivers of auroral variations at Jupiter, and key evidence on how solar wind would affect the auroral brightening. In this presentation, we will discuss several important advances on several distinctive auroral morphologies at Jupiter, i.e., auroral dawn storm, the main auroral brightening and auroral injection processes. We find that magnetic reconnection and dipolarization play crucial roles in driving these auroras, and the auroral drivers for the Earth and Jupiter have more in common than ever expected.

The east coast of India is prone to tropical cyclones. During pre-monsoon and post-monsoon seasons, almost every year, cyclones are developed over the Bay of Bengal and Andaman Sea. On 20 May 2020, tropical cyclone Amphan made initial landfall at Bakkhali in the West Bengal, India at 2:30 PM (local time) with wind velocity more than 175 km/h, which further intensified and moved into adjoining Bangladesh coastal areas on 21 May 2020 with highest wind speed 260 km/h. The cyclone formed on 16 May 2020 and dissipated finally on 21 May 2020. More than 22,000 houses in Coastal parts of West Bengal, and nearly 220,000 houses in Bangladesh coastal areas were damaged, and approximately 4.2 millions of people in both the countries were relocated to safe places. This cyclone affected many of the eastern states of India and 9 coastal districts of Bangladesh due to heavy rainfall that caused deadly flood. In West Bengal, Kolkata airport was flooded, and all the flights were closed. We have carried out analysis of meteorological and atmospheric parameters that helped in formation of the cyclone. Detailed analysis of multi satellite sensors, ground and Argo data have been carried out that show pronounced changes in ecological, atmospheric and ocean color parameters. The ocean parameters such as chlorophyll concentration, dissolved oxygen, salinity, sea surface and sub-surface temperature show strong changes in ocean ecology that have serious impacts on the marine life. Strong stratospheric-tropospheric exchange caused the rise in various trace gases close to the ground. A detailed damage analysis along the Eastern part of India and Bangladesh coast and major nearby cities and migration of the population from the affected region will be discussed.

‘Every Earthquake a Precursor According to Scale’ (EEPAS) is a model to forecast earthquakes within the coming months, years and decades, depending on magnitude. EEPAS performs well for seismically active regions including New Zealand (NZ) and has been formally evaluated in Collaboratory for the Study of Earthquake Predictability (CSEP) centres in NZ and California, USA. It has been used for practical forecasting in NZ for nearly a decade. An EEPAS forecast is formed by accumulating the contributions from past earthquakes to the expectation of future earthquakes. It uses the precursory scale increase (Ψ) phenomenon along with three predictive spatial, temporal and magnitude scaling relations. For a particular mainshock, Ψ is identified as a prior sharp increase in the occurrence of minor earthquakes. Each identification is represented by a value of precursor magnitude MP, precursor time TP and precursory area AP. An algorithm to automatically identify Ψ was developed and applied to real and synthetic earthquake catalogs. Multiple identifications of Ψ were obtained for most mainshocks. A trade-off between AP and TP was observed among such multiple identifications. Here, we examine the implications of the trade-off for the EEPAS temporal and spatial scaling parameters aT and σA. The EEPAS parameters were initially fitted to the NZ earthquake catalog from 1986-2006. The EEPAS parameters are now refitted with a sequence of fixed values for aT and then for σA. The range of fixed values constrain the respective temporal and spatial scales to vary by a factor of a hundred. Results confirm the existence of a similar space-time trade-off in EEPAS as in Ψ, with large aT values being associated with small σA values and vice versa. We conclude that the space-time trade-off is an intrinsic feature of precursory seismicity. This exists independently of other influences, such as the local strain rate, that may contribute to scatter in the predictive scaling relations. Mixing EEPAS models with parameters along the trade-off line should improve forecasting.

In this study, we revisit the role of curvature in modifying frontal stability. We first consider the statement “fq < 0 implies potential for instability”, where f is the Coriolis parameter and q is the Ertel potential vorticity (PV). This is true for any inviscid baroclinic flow. It is also evident in the transition of a governing equation for circulation within a front from elliptic to hyperbolic form as the discriminant changes sign. However, for curved fronts, an additional scale factor enters the discriminant owing to conservation of absolute angular momentum, L, leading to Solberg’s (1936) generalization of the Rayleigh criterion. In non-dimensional form, this expression also generalizes the classical instability criterion of Hoskins (1974) by accounting for centrifugal forces: modification of the front’s vertical shear and stratification owing to curvature tilts the absolute vorticity vector away from its thermal wind state and, in an effort to conserve the product of non-dimensional PV (q’) and absolute angular momentum (L’), this alters Rossby and Richardson numbers permitted for stable flow. The criterion, Φ’=L’q’ < 0, is then investigated in non-dimensional parameter space representative of low-Richardson-number vortices. An interesting outcome is that, for Richardson numbers near one, anticyclonic flows increase in q’, while cyclonic flows decrease in q’. Though stabilization is muted for anticyclones (owing to multiplication by L’), the de-stabilization of cyclones is robust, and may help to explain an observed asymmetry in the distribution of submesoscale coherent vortices in the global ocean.

Post-seismic deformation following large earthquakes offers insights into the rheology of the lithosphere and upper asthenosphere. The Mojave, in southern California, is one of the best studied regions on Earth, yet key questions, about fault slip rates and rheological heterogeneity, remain unanswered. Unprecedented geodetic coverage of the 2019 Ridgecrest earthquakes provides an opportunity to test whether rheological models developed for the Mojave, from the Landers, Hector Mine and El Major Cucapah earthquakes, are applicable north of the Garlock fault, and to place bounds on the effects of local rheological heterogeneties associated with the Coso volcanic field. This volcanic field, which is located to the NW of the Mw7.1 rupture trace, is a region of high heat flow and geothermal activity. The locally high temperatures in the Coso volcanic field are likely to be associated with low viscosities compared to the surrounding regions, and high pore pressures due to the hydrothermal activity. The aftershock sequence associated with the Ridgecrest earthquakes shows a notable absence of large magnitude earthquakes in this region. We use variational Bayesian independent component analysis to isolate postseismic deformation in GPS time series around the earthquakes. We present models of the possible poroelastic, afterslip and viscoelastic response driven by coseismic stress changes in the July 2019 Ridgecrest earthquakes and investigate the possible effect of the Coso volcanic field. By modelling a series of different afterslip geometries, and viscoelastic rheologies we identify features of the GPS- and InSAR-derived surface deformation which are diagnostic of different post-seismic mechanisms and rheological heterogeneities.