Clouds in the tropical western Pacific are dominated by reflective deep convective cores with gradually thinning trailing anvil clouds, which play a crucial role in determining tropical cloud radiative effects. The microphysical controls of the thinning process and its changes when subjected to a future warmer climate are still very uncertain.We use the high resolution version of the Exascale Earth System Model (E3SM) to study the thinning process in present day and future climate. We apply Lagrangian forward trajectories starting at peaks of convective activity of the detected mesoscale convective systems (MCS) and track detrained ice crystals to better understand the processes controlling the transition of a thick detrained anvil cloud into a thin cirrus cloud. The trajectories are computed offline from the 1-hourly model-calculated velocity fields and ice crystal sedimentation velocities. The modeled MCS in present day climate have a comparable time evolution to those observed by Himawari geostationary satellite data, with an average lifetime of about 10-15 hours, which accounts only for the optically thick part of the cold cloud shield. However, E3SM fails to simulate the strongest storms, which is reflected by an underestimation of albedo and overestimation of outgoing longwave radiation. The analysis of ice sources (detrainment, vapor deposition, new nucleation events) and sinks (sublimation, aggregation, sedimentation) along trajectories highlights the crucial role of the balance between depositional growth and precipitation formation for the maintenance of aging anvil clouds. Interestingly, deposition of ice on detrained ice crystals contributes to the majority of the upper tropospheric ice mass. On the other hand, about 80% of the initial cloud mass is removed in the form of precipitation within the first 10 hours of the detrainment event, changing its radiative effect from net negative to net positive. The future climate simulation shows an increase in storm frequency and intensity, an increase in ice water content and albedo in convective cores and thick anvils. The trajectory calculations reveal a 15% decrease in cloud lifetime due to climate change, suggesting a decrease in thin high clouds due to a higher precipitation efficiency and a shift to more negative net cloud radiative effects.

Carbon sequestration in soils represents an important opportunity to reduce the amount of greenhouse gases in the atmosphere and thereby offsetting the effects of climate change. To monitor carbon sequestration accurate measurements of soil carbon are needed that can be repeated over several growing cycles. Furthermore, soil carbon is an important indicator of soil health; accurately measuring carbon distribution is therefore important for informing land use management practices. We are developing a new instrument that images a volume of approximately 50 cm × 50 cm × 30 cm (depth) with a few centimeters resolution by applying neutron scattering techniques. Contrary to current coring methods, this approach is non-destructive, samples a large area, and allows real-time analysis of the soil carbon density. In this technique a neutron and an alpha particle are created in a deuterium-tritium fusion reaction. Due to momentum conservation the two particles move in opposite directions. Creating the particles in a small point source allows us to calculate the direction in which the neutron is moving by tracking the associated alpha particle using a position sensitive detector. The neutron can then enter the soil and inelastically scatter off atoms in the soil, creating an isotope-specific gamma ray in the process. Measuring the energy of the gamma ray allows identification of the isotope. Measuring the time-of-flight between the alpha detection and the gamma detection together with the direction of travel of the neutron allows the calculation of the 3D position of the scattering center. Using this Associate Particle Imaging (API) technique 3D density plots of carbon, oxygen, silicon, and aluminum can be obtained. In this poster we present first results from applying API to pre-mixed and standard soil samples in a laboratory setting (field tests are planned in the future). We will compare measured data to neutron-transport simulations and discuss our data analysis algorithm to reconstruct the carbon density in the soil from API data. We will further discuss achievable resolution and time requirement for measurements in the field. The information, data, or work presented herein was funded by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Contract No. DE-AC02-05CH11231.

Human activities constantly produce air pollutants, which may greatly impact climate change. Elucidating the relationship between air quality and temperature change is essential to gain a better understanding of climate change. Up until now, machine learning algorithms have been deployed to big data analysis in various fields. Here, we use the machine learning algorithms to analyze temperature and air quality data of different cities across China. Multiple linear regression and tree-based methods, including bagging, boosting and random forest, are used to train the model. With the tree-based methods, the factors highly associated with temperature change will be elucidated, which indicate their significant impact on temperature change. The results in this study demonstrate the possibility of using machine learning in atmospheric science field to predict air quality and temperature change, and how different algorithms perform regarding temperature and air quality predictions, which is informative for future air quality prediction research. The relationship between air quality and temperature change can also provide guidance to policymakers.

Axial Seamount is the most active submarine volcano in the NE Pacific Ocean, and is monitored by instruments connected to a cabled observatory (the US Ocean Observatories Initiative Cabled Array), supplemented by autonomous battery-powered instruments on the seafloor (at ~1500 m depth). Axial is a basaltic hot spot volcano superimposed on the Juan de Fuca spreading ridge, giving it a robust and apparently continuous magma supply. It has had three effusive eruptions in the last 21 years: in 1998, 2011, and 2015. Deformation measurements have been conducted at Axial Seamount since the late 1980’s with bottom pressure recorders (BPRs) that can detect vertical movements of the seafloor with a resolution of ~1 cm. This monitoring has produced a 22+ year time-series including co-eruption rapid deflation events of 2.5-3.2 meters, separated by continuous gradual inter-eruption inflation at variable rates between 15-80 cm/yr. The overall pattern appears to be inflation-predictable, with eruptions triggered at or near a critical level of inflation. Using this pattern, the 2015 eruption was successfully forecast within a one-year time window, 7 months in advance. As of December 2019, Axial Seamount has re-inflated 1.98 m (~78%) of the 2.54 m it deflated during the 2015 eruption. We are exploring several methods to forecast the next eruption, including daily extrapolation of the average rate of inflation from OOI BPR data during the last 3 months forward in time until it intersects the threshold reached before the 2015 eruption. Using this method with the difference in inflation between two OOI BPR instruments located 3.5 km apart removes noise from tidal residuals and oceanographic signals that are common to both instruments. This method suggests the next eruption is likely between 2020 and 2024. However, this simple method is complicated by uncertainties in the next inflation threshold (the volcano inflated 20 cm higher before the 2015 eruption compared to 2011), changes in the rate of inflation with time, and by intermittent pauses in the inflation (and seismicity) observed since 2015 that have lasted from a week to several months.

To trace the Gulf Stream (GS) path across five decades from 1965 to 2017, we mapped the annually averaged positions of the Gulf Stream North Wall (GSNW) defined by the 15°C isotherm at 200 m depth computed using in situ seawater temperature records from the World Ocean Database 2018 (WOD18). Inter-annual GSNW variability is noticeably different west and east of ~50°W. There are two distinct variability zones west and east of that longitude—a zone with a rather narrow envelope (~3° of latitude-wide) west and a zone with a twice as wide envelope (~ 6° of latitude-wide) east of that longitude. The more disperse annual pathways are near the Mid-Latitude Transition Zone. Moreover, within the ~50-year timeline, the quasi-decadal period of 2005–2017 is marked by far larger spread in the annual GSNW positions than the previous decades, especially between 50°W and 40°W. The principal conclusion of our analysis, is that the GS between Cape Hatteras and the Grand Banks (west of 50°W) is not only stiff but maintains its position with astounding resiliency. The GSNW average position along that stretch of longitudes migrates slowly northward as a whole, but it is unlikely that such a slow and spatially insignificant migration could cause substantial changes in the Atlantic Meridional Overturning Circulation (AMOC). In contrast, near the Grand Banks (east of 50°W), the GSNW northward shift is quite noticeable—over 2.6° in latitude over ~50 years—and thus could have some impacts on the AMOC long-term dynamics. There are significant correlations between the GSNW and Ocean Heat Content (OHC) variability east of 50°W that may be critical for the GS path resilience and its future changes over decadal and longer time scales. Furthermore, the significant correlations between OHC and GSNW in the extension zone rose from r=0.5 for annual to r=0.8 for pentadal to r=0.9 decadal time scales. We assert that the OHC may become the best indicator of the GS path’s variability on decadal and longer time scales.

New Caledonia owns about 25% of the world’s nickel resources, and around 9% of the world’s reserves, distributed over 300,000 hectares of concessions allocated to date (18% of the total surface of the main island). Supergene weathering of ultramafic rocks have led to the genesis of lateritic nickel-rich ores of garnierite type (NiO> 1.5%) and / or iron oxi-hydroxide type (NiO <1.5%) under tropical lateritic conditions that have prevailed over 30 millions of years. These conditions have shaped the landscapes while offering Ni-rich regolith easy to exploit by open pit mining. Since 1880, nickel has been so far used as an economic driver and a societal development impetus. Since 1998, three worldwide projects have been developed, using pyrometallurgy (Ni-Si) and more recently hydrometallurgy (Ni-Fe) ore processes. However, natural erosion, anthropogenic disturbances (climate change, fires, urbanization, mining) can add up to disrupt the whole terrestrial and marine ecosystem functioning at the regional scale.This critical mined zone is covered by terrestrial ecosystems of great endemic biodiversity and adjoining a lagoon that has been listed as a UNESCO World Heritage Site in 2008. Such ecosystems are a valuable natural resource for the sustainable future for the next generations. Are mining and preserving ecosystems compatible, and for what economic and societal model? The conference reviews a collective research approach (mining, terrestrial and marine ecosystems impacts, restoration, biorecycling) to address this question. The corpus of acquired knowledge allows to propose an inclusive model of responsible mining activity, based on the “co-valorization” of both non-renewable and renewable primary resources through the development of circular economy and bio-economy principles, and applied all along the “mining ecosystem” project management. Considering i)the present day low GDP input of nickel mining in New Caledonia, the 98% dependency rate from fossil sources of energy, the CO2 emissions and the volatile Ni-market international context, this model, if followed, will reinforce the societal cohesion and develop a sustainable economy diversification, while enhancing energy transition and a better ecological efficiency.

The distributions of mosquito vectors are expected to shift with rising temperatures due to climate change. But other global change patterns, like land cover change and human population growth, are simultaneously occurring. How will these changes interact to shift the future distributions of these vectors? Here, we analyzed how climate, land cover, and human population density regulate and predict habitat for two mosquito species, Aedes aegypti and Ae. albopictus, the primary vectors of dengue, Zika and chikungunya. We asked the following questions: How do environmental response curves derived from vector occurrence data compare to lab-derived responses? Based on these environmental response curves, which environmental drivers best predict the spatial distribution of each vector? Are environmental responses derived from large-scale (continental) occurrence data consistent at fine spatial scales? To answer these questions, we analyzed 6,317 Ae. aegypti occurrence records, 3,629 Ae. albopictus records, 10 satellite-derived environmental covariates, and two independent field surveys cover 134 sites. We found close agreement in the range of lab and environmental temperature responses, though the mean of observed temperatures was higher in the environment (31.0 °C for Ae. aegypti, 29.1 °C for Ae. albopictus) than lab predictions of the thermal optimum for transmission (29.1 °C for Ae. aegypti, 26.4 °C for Ae. albopictus). Using presence-only species distribution modeling approaches, we found that human population density was the best predictor for each vector’s spatial distribution (explaining 68.4% of model performance for Ae. aegypti, 48.7% for Ae. albopictus). These patterns were consistent in the field for presence/absence Ae. aegypti data (0.71 AUC, 0.80 recall), but failed to predict Ae. albopictus distributions in the sites we surveyed (0.53 AUC, 0.20 recall). In this session, we will explore these results and discuss the potential to predict and monitor Aedes habitat using satellite data.

Lightning and transient luminous events (TLEs) emit a short burst (~1 ms) of broadband electromagnetic waves, whose frequencies can range from a few Hz to the optical band, but the bulk of their energy is radiated as longwaves (<500 kHz). These longwave radio signals are named radio atmospherics, or colloquially sferics. Due to their low frequency, sferics can propagate in the Earth-ionosphere waveguide at global distances with relatively low attenuation (~3 dB per 1000 km). This allows a sparse network of longwave receiver stations, placed hundreds of kilometers apart, to geolocate lightning strikes at a global scale. Hardware performance of the receivers at these stations significantly impacts the data quality and determines the detection efficiency and location accuracy of the lightning detection network. In this work, we present a low-frequency remote sensing instrument for lightning geolocation in the form of an ultra-sensitive broadband electric field receiver. It is capable of detecting extremely weak sferics, enabled by its ideal sensitivity of 1 nV/(m√Hz), or 0.003 fT/√Hz. We present this receiver’s antenna-amplifier co-design and the design considerations to achieve this low sensitivity. We then report its performance characteristics, validated both theoretically and empirically. Finally, we present some of the novel applications of this device in the scope of lightning geolocation and remote sensing.

The magnetosphere of the Earth presents a large scale plasma physics laboratory in which the complex interacting plasma phenomena are involved: global convecting plasma dynamics, wave–particle interactions in the bow shock and transmitted shock waves/impulses and magnetic field reconnection in the plasma current sheets. The NASA magnetospheric multiscale mission (MMS) provides unique observations of the thin structures and wave–particles interactions at the shock-like impulses while the spacecrafts were located at the dawn terminator (the time is 2016-03-07 20:00:00 UTC). It was assumed that these impulses may be created by the interaction between the background flow and plasma clouds. It was also assumed that those clouds were produced by either flux-transfer events or by coalescence/reconnection processes at the magnetopause current layer or by the mirror instabilities inside the low latitude boundary layer. 3-D hybrid kinetic code with separate description of the background and cloud ions was used for interpretation of the observed impulse structures. In this report we will discuss the effects of particle heating and acceleration inside the foreshock of the shock-like impulses, effects of the ion and electron non-Maxwellian velocity distributions, and particle finite gyroradius, and triggering the electromagnetic instability.

Scattering of longwave radiation by cloud particles has been regarded unimportant and hence commonly neglected in global climate models. However, it has been demonstrated by recent studies that cloud longwave scattering plays an unignorable role in modulating the energy budget of the Earth System. Offline radiative transfer calculation showed that excluding cloud longwave scattering could overestimate outgoing longwave radiation and underestimate downward irradiance to the surface, and thus impose excessive cooling onto the atmosphere column. How this physical process interacts with other processes in the Arctic climate system, however, has not been thoroughly evaluated yet. Given the fact that the melting of ice and snow that cover the vast surface of the Arctic region is sensitive to energy budget, and such melting may trigger further feedback mechanisms, the neglection of cloud longwave scattering could bias the regional climate simulations to a considerable extent. We have incorporated cloud longwave scattering into the NCAR CESM and the DoE E3SM and this study analyzed the impact on the simulated polar climates in both earth system models. Cloud longwave scattering leads to a warmer surface air temperature in both models, especially over the wintertime. A detailed surface energy budget analysis is performed, for both the mean state and the temporal variability. Preliminary results suggest that the leading change is downward longwave flux and upward longwave flux, followed by the changes of turbulent heat flux. How the longwave scattering treatments can couple with cloud microphysics and precipitation physics to affect Arctic precipitation is further explored.

Atmospheric drag describes the main perturbing force of the atmosphere on the orbital trajectories of near-Earth orbiting satellites. The ability to accurately model atmospheric drag is critical for precise satellite orbit determination and collision avoidance. Assuming we know atmospheric winds and satellite velocity, area and mass, the primary sources of uncertainty in atmospheric drag include mass density of the space environment and the spacecraft drag coefficient, CD. Historically, much of the focus has been on physically or empirically estimating mass density, while CD is treated as a fitting parameter or fixed value. Presently, CD can be physically modeled through energy and momentum exchange processes between the atmospheric gas particles and the satellite surface. However, physical CD models rely on assumptions regarding the scattering and adsorption of atmospheric particles, and these responses are driven by atmospheric composition and temperature. Modifications to these assumptions can cause CD to change by up to ~40%. The nature and magnitude of these changes also depend on the shape of the spacecraft. We can check the consistency of the CD model assumptions by comparing densities derived from satellite drag measurements and computed CD values for satellites of different shapes orbiting in the same space environment. Since all of the satellites should see the same density, offsets in the derived densities should be attributable to inconsistencies in the CD model. Adjusting the CD model scattering assumptions can improve derived density consistency among the different satellites and inform the physics behind CD modeling. In turn, these efforts will help to reduce uncertainty in CD, leading to improved atmospheric drag estimates.

We use numerical solutions of the Richard’s Equations for 3D porous media to investigate the influence of agricultural subsurface drainage as a hydrologic process and its effect on the hydrologic regime of a watershed. Specifically, we determine the relation between subsurface seepage and subsurface storage in hillslopes with (drained) and without (undrained) subsurface drainage. Simulations are performed in Hydrus3D and the output is analyzed with MATLAB’s curve fitting tools, to create simple ordinary differential equations that represent the relationship between subsurface flow and subsurface storage for hillslopes of varying topographical gradients and shapes. We have determined an ‘activation point’ below which the seepage/storage relationship is roughly linear, and above which the drained and undrained simulations behave according to different nonlinear functional forms. Although the seepage/storage relationship of flat hillslopes have parametric consistencies independent of the hillslope gradient, the addition of curvature increases the complexity. In this work, we describe approximations to account for curved hillslopes. From our formulation, subsurface flow for varying hillslopes can be approximated using only the water storage and the topography of the hillslope. Reducing the system from partial differential equations (Hydrus) to ordinary differential equations improves scalability of the model. Simplified equations are used to study the consequences of large-scale changes in agricultural landscapes due to subsurface drainage.

A key to understanding the evolution of the Martian climate over its history is the study of how the Martian atmosphere escapes to space. Studying the near-Mars space environment allows us to better understand atmospheric escape processes. One of these important processes is ion escape, in which atmospheric particles that are primarily ionized by the solar radiation above the exobase region can escape from the planet. Various model results, as well as MAVEN observations, have shown several important channels for ion escape in the Martian plasma environment. One of these channels forms when pickup ions are accelerated away from the planet by a motional electric field, creating a “plume” of escape organized by the upstream solar wind electric field. Although plasma models have predicted the existence of this plume before, only recently have we been able to regularly identify it in observations. Relatively little work has been done on how modeling choices influence the morphology of the plume. Here we present a comparison of two BATS-R-US multi-fluid MHD simulations, each with different spatial resolution, run using input conditions taken from a single MAVEN orbit in which the plume signature was clearly identified. Our analysis primarily focuses on differences seen in the location and morphology of the ion plume. While the two simulations match well at low altitudes, location differences in the ion plume become clear at high altitudes. We also analyze the effect of different spatial resolution on the simulated ion escape rates. Detailed investigation of the plume region in these simulations has also provided us with a better understanding of the underlying physics that shape and act on the ion plume. We have analyzed and identified regions where the v x B force accelerates ions while the J x B force confines them. This in turn allows us to identify the location of the plume. This study highlights the importance of choices in spatial resolution when modeling features in the Martian magnetosphere.

The ocean covers 70% of the surface of the planet, yet absorbs a remarkable 93% of the additional heat trapped by anthropogenic greenhouse gases due to its large size, the omnipresent stirring by wind, and the “high heat capacity” of water; yet the molecular basis for the high specific heat of water (CP) is not well known. It has long been established that specific heats are closely tied to molecular weight. Ironically, water has no fixed molecular weight: it exists as a bi-molecular fluid consisting of the singlet H2O form and an ensemble of hydrogen bonded forms in a temperature dependent equilibrium. We show that the mean molecular weight of water over the range 0-40°C is 82-79. The warming of water induces the breaking of hydrogen bonds (8.364 kJ/mol), increasing the population of the singlet H2O form at the expense of the hydrogen bonded forms. Although warming of sea water by 10°C yields only a 2% increase in free H2O, this accounts for some 36% of the energy consumed. Consequently, the high heat capacity of water, and water in sea water, is attributable (64%) to the large molecular weight of the hydrogen bonded forms, dominantly as the tetrahedral pentamer (H2O)5, and also (36%) to the energy required to break hydrogen bonds. The CP for pure water decreases with increased temperature due to the decrease in the ensemble molecular weight with warming, while the CP for sea water increases with increasing temperature due the work required to increase the translational energy of the large hydrated cations, which are dominantly Na(H2O)6 with a molecular weight of 131. Thus, it is the multiple forms of water and their hydrogen bonding that accounts for the high specific heat of both pure water and sea water.

It is difficult to teach for both understanding and application, and the climate crisis highlights this in profound ways. Even those who understand the extreme threats posed by anthropogenic climate change have been largely at a loss for how to generate a response to such threats at scale. What drives people, organizations and governments to actually act in the face of crisis? In at least several historical examples, the impetus for action includes being astounded and scared while also having reason for hope and the ability to display courage. These steps are infused with building visceral understanding of the problems’ magnitude. Examples that follow this pattern include US involvement in World War II, the Apollo Program, and the civil rights movement. “Where Does Gasoline Go?” and “Fire & Brimstone & Fort McMurray” are presentations that, when brought together apply this framework to climate change communication. Americans burn 391 million gallons of gasoline per day, each containing 5.5 pounds of carbon. To sequester that carbon by tree-planting requires the equivalent of growing a 2x4 for each gallon. If the US were to offset current emissions from gasoline (roughly a quarter of total US emissions) by planting trees, we’d need to grow 4.3 billion pounds of wood every day - more than 1.5 trillion pounds/year. When you fill your tank, count 2x4s as the gallons roll by, and mentally scale this up to every driver in the country. If one understands both scale and the basics of climate change, this is both astonishing and terrifying. We have faced terrifying situations before and we have emerged from them. Indeed, throughout human history, we have always lived in times characterized by the wonderful and horrible simultaneously. We have also always made apocalyptic prophecies that, at least at the global scale, have not come to pass. For the credible ones, people eventually acted and were able to meet the challenges (though sometimes at horrific costs). Recognizing that we have always been wrong in predicting global apocalypses and that when the situation becomes dire (as it is doing now) we have taken effective action is reason for hope. The process described here, through the story of a gallon of gasoline, couples clear science with powerful emotion. It closes with hope. And, it offers tools and a broader approach that can be widely replicated.

It is increasingly recognized that light-absorbing impurities deposited on a surface can reduce its albedo and lead to increased absorption of solar radiation. Natural dust can travel substantial distances in the Earth’s atmosphere from its original source. It affects all climatic zones from the tropics to the poles and it may have a regional or global impact on air quality and human health. In the Arctic, a rapid increase in temperature compared to the global change, known as Arctic Amplification, is closely linked to snow albedo feedback. Furthermore, recent studies detail an extreme climate change scenario in the history of our planet that lead to catastrophic cascading events and global mass extinction triggered by atmospheric soot injections. Therefore, knowledge of optical properties of dust particles is important for improved climate models and dust effect studies. Here we report detailed results of multi-angular polarized measurements of light scattered by volcanic sand particles obtained with the FIGIFIGO goniospectrometer (Peltoniemi et al. 2014). The design concept of this custom made instrument has a well designed user friendly interface, a high level of automation, and an excellent adaptability to a wide range of weather conditions during field measurements. The foreoptics is connected to an ASD FieldSpec Pro FR 350-2500 nm spectroradiometer by an optical fiber. A calcite Glan-Thompson prism is used as a polarizer, covering the full spectral range with better than 1% accuracy. The samples studied in this work were collected from the Mýrdalssandur area in Iceland (in March 2016) and from the Villarica area in Chile (in July 2019). Following established FGI practices in laboratory conditions samples are further divided into the following categories: (1) natural volcanic sand, (2) sieved volcanic sand (dust) where the size of the particles is less than 250 μm, including dry and wet sample condition, and (3) a fine-grained powder of milled volcanic sand measurable also as aerosol. The potential use of the results from our measurements are diverse, including their use as a ground truth reference for Earth Observation and remote sensing studies, estimating climate change over time, as well as measuring other ecological effects caused by changes in atmospheric composition or land cover.

Tree damage can provide insights into internal dynamic pressure changes of pyroclastic density currents (PDC). On 18 May 1980, Mount St. Helens erupted a laterally directed PDC that decimated ~600km2 of forest, referred to as the blowdown zone. The head of the current contained the peak dynamic pressure, which uprooted or broke off most trees and stripped them of vegetation; however, some partially stripped tree trunks were left standing. Tree damage was assessed using aerial photography taken one month after the eruption. The flow direction of the PDC was mapped from shadows of root balls of toppled trees and directions of fallen trees. Along given flow paths, the density of standing trees was measured by the number of shadows within 200m2 areas. Towards the northwest, the average tree density increased from 0.01 to 0.58 (± 0.19) trees/m2 with distance. Additionally, analysis identified 95 clusters of trees still standing in the blowdown zone, situated on the lee sides of hills or plateaus. Blurry, cylindrical shadows versus well-defined, cylindrical shadows distinguished standing trees with foliage in clusters from those without. Five variables were used to determine the heights of trees: ground slope and aspect, bearing and length of shadows, and the sun angle above the horizon. Trees stripped of foliage in patches have average heights of 16 ± 7m and occur where the PDC reached 66 ± 24% of its runout. Foliage patches have average heights of 12 ± 7m and occur where the PDC reached 91 ± 9% of its runout. Tree heights in the patches indicate a localized height the peak dynamic pressure must jump as it travels over hills and away from its source. Patches with foliage imply that the peak dynamic pressure has risen above the tops of the trees, whereas patches without foliage suggest that the peak dynamic pressure was still low enough to damage trees even though the current had jumped over topography. Outside of the patches, increasing tree density suggests that dynamic pressure waned with distance.

Mineral hazards are a common, yet often less-recognized group of features compared to other types of natural and man-made hazards. We define “mineral hazards” in part as minerals and elements that occur naturally in elevated, potentially harmful, concentrations in rocks, soils, and certain fluids. Also included are features from human activities related to extraction of mineral and energy resources. Along with its large human population, extensive development, and diverse natural environment, California is very complex geologically, thus it contains many areas of mineral hazards that make it appropriate for such a study. Although mineral hazards have been investigated over several decades by the California Geological Survey (CGS), no systematic statewide assessment had been accomplished until recently when, at the request of the California Department of Transportation (Caltrans), the CGS completed a preliminary assessment of potential mineral hazards over the entire state. This work focused on natural and man-made minerals-related features that might adversely affect construction, use, and maintenance of state and federal highways under Caltrans jurisdiction. The features evaluated include: 1) geologic units that may contain naturally-occurring asbestos (NOA), fibrous erionite, or elevated concentrations of regulated metals (Ag, Ba, Be, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Tl, V, Zn) and metalloids (As, Sb, Se); 2) faults, which can be sites of increased potential for certain types of mineralization; 3) mines and prospects, which can be sources of anomalous concentrations of metals and ore-processing chemicals; 4) oil and natural-gas seeps; 5) thermal springs and fumaroles; and 6) oil, natural-gas, and geothermal wells. The methods and products developed during the Caltrans study can be applied worldwide to many other uses besides highways where there are obligations to protect public health and safety and the environment. The products include maps that highlight types and locations of potential mineral hazards, digital data in GIS format, and accompanying reports that provide details and additional information. Although they do not indicate risk or probability, these products can be applied by users from many backgrounds as screening tools to assess potential for the presence of mineral hazards.