Abnormally heavy precipitation events can lead to numerous hazards, including flooding, landslides, and avalanches. Their developments require a sufficient supply of moisture and some physical mechanism to produce condensation. Atmospheric rivers (ARs) defined as long and narrow corridors of strong horizontal moisture transport can provide such necessary conditions. The presence and strength of ARs are often described using the integrated water vapor (IWV) and the integrated vapor transport (IVT). However, the associated precipitation is not directly correlated with these two variables. It is the net convergence of moisture that determines the intensity of precipitation. The purpose of this study is to illustrate, in the context of AR analysis, how the converged vapor should be distributed between condensation and air moistening. A simple algorithm is proposed for estimating the heavy precipitation attributable to the IVT convergence. Bearing a strong resemblance to the Kuo-Anthes parameterization scheme for cumulus convection, the proposed algorithm calculates the large-scale primary condensation rate (PCR) as a proportion of the IVT convergence, with a reduction to account for the general moistening in the atmosphere. The amount of reduction is determined by the column relative humidity (CRH), which is defined as the ratio of IWV to its saturation counterpart. It is found that the PCR in an air column with CRH < 0.60 is negligibly small. Based on a one-year dataset from the Canadian global numerical weather prediction (NWP) model, the best cut-off value of CRH for the algorithm is 0.66. It is demonstrated that this diagnosable PCR compares well to the forecast precipitation rate given by the NWP model. Case studies are conducted to illustrate the usefulness of CRH and PCR as two complements to standard AR analysis and impact-based storm classification.

Recently, Anderson et al. (2012, https://doi.org/10.1126/science.1222978, 2017, https://doi. org/10.1073/pnas.1619318114) and Anderson and Clapp (2018, https://doi.org/10.1039/C7CP08331A) proposed that summertime convectively injected water vapor over North America could lead to stratospheric ozone depletion through halogenic catalytic reactions. Such ozone loss would reduce the ozone column and increase erythemal daily dose (EDD). Using 10 years of observations over the North American monsoon region from the Aura Ozone Monitoring Instrument, we find that the column ozone and EDD has a ~0.8–0.9 spatial correlation with lower stratospheric water vapor measured by the Aura Microwave Limb Sounder. We show that this correlation appears to be due to the elevation of the monsoonal tropopause and associated monsoonal convection. The increase in tropopause altitude reduces the ozone column and increases EDD. We see no apparent evidence of substantial heterogeneous chemical ozone loss in lower stratospheric ozone coincident with the stratospheric monsoonal water vapor enhancement.

Episodes of slow uplift and subsidence of the ground, called bradyseism, characterize the recent dynamics of the Campi Flegrei caldera (Italy). In the last decades two major bradyseismic crises occurred, in 1969/1972 and in 1982/1984, with a ground uplift of 1.70 m and 1.85 m, respectively. Thousands of earthquakes, with a maximum magnitude of 4.2, caused the partial evacuation of the town of Pozzuoli in October 1983. This was followed by about 20 years of overall subsidence, about 1 m in total, until 2005. After 2005 the Campi Flegrei caldera has been rising again, with a slower rate, and a total maximum vertical displacement in the central area of ca. 70 cm. The two signals of ground deformation and background seismicity have been found to share similar accelerating trends. The failure forecast method can provide a first assessment of failure time on present‐day unrest signals at Campi Flegrei caldera based on the monitoring data collected in [2011, 2020] and under the assumption to extrapolate such a trend into the future. In this study, we apply a probabilistic approach that enhances the well‐established method by incorporating stochastic perturbations in the linearized equations. The stochastic formulation enables the processing of decade‐long time windows of data, including the effects of variable dynamics that characterize the unrest. We provide temporal forecasts with uncertainty quantification, potentially indicative of eruption dates. The basis of the failure forecast method is a fundamental law for failing materials: ẇ-α ẅ = A, where ẇ is the rate of the precursor signal, and α, A are model parameters that we fit on the data. The solution when α >1 is a power law of exponent 1/(1 − α) diverging at time Tf , called failure time. In our case study, Tf is the time when the accelerating signals collected at Campi Flegrei would diverge if we extrapolate their trend. The interpretation of Tf as the onset of a volcanic eruption is speculative. It is important to note that future variations of monitoring data could either slow down the increase so far observed, or suddenly further increase it leading to shorter failure times than those here reported. Data from observations at all locations in the region were also aggregated to reinforce the computations of Tf reducing the impact of observation errors.

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

Despite recent advances in sensors, hydro-meteorological data remain scarce in urban watersheds. In the current, reactive approach to stormwater management, whether or not an urban flood event is documented, as well as where and how it actually occurred, is highly dependent on the level of monitoring. Even though there are many methods for observing flooding extent and predicting flooding vulnerability, issues with data availability and accuracy persist at the local level. Urban watersheds are spatially and temporally complex and flash floods, while of particular interest and importance to both hydrologists and communities, are hard to characterize, given that they are rare, spatially localized, short-lived, and often occur in locations without formal monitoring. On the other hand, identifying vulnerable areas in a large city using hydraulic/hydrological modeling would be very difficult, either because models have parameters that need to be calibrated against mostly non-existent data (in the case of conceptual models), or else we do not know all of the actual physical processes at work, or how to quantify them (in the case of physically-based models). Community-based monitoring activities can support the characterization of urban watersheds, as well as stormwater management, because they provide valuable spatial and temporal knowledge about the behavior of water flow and other related issues at a local level. An urban watershed study was conducted to demonstrate the value of community-based observations for understanding and characterizing urban pluvial flash flooding, by addressing the following questions: (i) How can communities feasibly monitor their local watershed using low-cost, straightforward approaches? (ii) How can local knowledge help us to better define and characterize urban pluvial flooding vulnerability? (iii) Are community-based data reliable and meaningful to urban watershed management and the decision-making process? To pursue these questions, participatory research was applied in a low-resourced community in the City of Paternò, in Sicily, Italy. We collected as unbiased as possible information about flash flooding events through 300 surveys. The locally-gathered data were compared to the results of advanced hydrodynamic models on smaller scales.

During the Arctic summer season, snow atop the sea ice melts and pools into low-lying areas on the surface. These melt ponds reduce surface albedo and increase solar absorption in the Arctic Ocean. Throughout the summer, melt ponds grow, drain, and connect, through a complex drainage system. Current melt pond schemes in sea ice models, such as the level-ice scheme in the Los Alamos Sea Ice Model (CICE), rely on a linear relationship between pond depth and fraction to predict the evolution of pond growth as the snow and sea ice melt. Although the inclusion of melt ponds in models has been shown to improve forecasts of end-of-summer sea ice extent, observations of melt pond depth and fraction guiding these models are from SHEBA, a spatially-limited field campaign which occurred over 20 years ago. Until recently, melt ponds characteristics have been difficult to resolve from spaceborne platforms due to their small size (10s - 100s m in diameter), and indistinguishable radiometric similarity to open water. Here we show that new, high-resolution laser altimetry measurements from ICESat-2 (IS2), combined with coincident high-resolution satellite imagery, provides a three-dimensional view of the melting sea ice cover. IS2, launched in September 2018, has now observed two summer melt seasons in the Arctic. IS2 operates at 532 nm, a wavelength that penetrates low turbidity water, and can therefore be used to capture the bathymetry of shallow water features. Building on previous work, we demonstrate IS2’s ability to detect and measure melt ponds on multiyear sea ice. We validate the existence of melt ponds with high resolution (10 m) visible imagery from the Sentinel-2 (S2) MultiSpectral Instrument. We apply the “density dimension algorithm – bifurcate” (DDA-bifurcate), an auto-adaptive algorithm utilizing data aggregation with the ability to track two surfaces, as well as a second algorithm that tracks melt pond surface and bottom, to derive melt pond depth for dozens of melt ponds in 2019 and 2020. Applying a sea ice surface classification algorithm to S2 imagery, we are able to determine melt pond fraction. We compare our findings of coincident melt pond fraction and depth with the melt pond parameterization used in the level-ice scheme in CICE. We discuss our results in the context of the existing literature on pond depth and volume.

Mount St. Helens, Washington State, USA, is characterized by a 2 x 3.5 km horseshoe-shaped and north-facing crater and hosts one of the last expanding glaciers in the Cascade Volcanic Arc, Crater Glacier. First observed in 2012, a new and extensive system of glaciovolcanic caves has developed around the 2004-2008 Lava Dome inside the Crater Glacier. Field studies have documented the cave characteristics via photography and tacheometric survey methods repeated from 2014-2019. Climatologic measurements reveal that sub-glacial fumarole activity leads to large-scale cave complexes, sometimes several hundred meters long. These allowed comparisons of passage extent and volume to be made and gave us a unique opportunity to observe their genesis over time. Ten distinct caves have been discovered in a circumferential pattern surrounding the 2004-2008 Lava Dome. The caves comprise a combined length of 2,232.3 m, the three most significant ones reaching more than 400 m each. Changes in the output of individual fumaroles which have melted the passages have also contributed to the appearance and disappearance of subglacial rooms and marginal dendritic passages which typically orient to entrances along the rock/ice interface. Over time the caves have demonstrated significant morphological changes. Multiple caves demonstrated increases in length and volume over the study period, along with changes to internal morphology. Caves located on the east and west arm of the glacier are additionally influenced by glacier movement and a fast flow rate which contribute much to morphology changes. Resurveys of cave passages over multiple years have revealed the dynamic nature of the systems, which are not necessarily in balance with the geothermal heat release. We expect that the overall growth of the cave systems will continue as long as an equilibrium of snow accumulation and ablation is reached or changes in volcanic activity occur. The newly formed glaciovolcanic cave systems on Mount St. Helens offer a rare view into the internal workings of a glacier and can lead to a better understanding of how glaciers and active volcanoes interact.

Cloud tomography (CT) is a promising approach in passive remote sensing using space-based imaging sensors like MISR and MODIS. In contrast with current cloud property retrievals in the VNIR-SWIR, which are grounded in 1D radiative transfer (RT), CT embraces the 3D nature of convective clouds. Forster et al. (2020) defined the “veiled core” (VC) of such clouds as the optically deep region where detailed 3D structure of the cloud has little impact on the multi-angle/multi-spectral images as long as average VC extinction and any significant cloud-scale gradient are preserved. Quantitatively, the difference between radiance fields escaping clouds remains commensurate with sensor noise when said clouds differ only in the small-scale distribution of extinction inside their VC. An important corollary for the large and ill-posed CT inverse problem is that the only unknowns of interest for the whole VC are its mean and any cloud-scale vertical trend in the extinction coefficient. Another ramification for CT algorithms under development is that the forward 3D RT model driving the inversion may be vastly simplified in the VC to gain efficiency. We explore that possibility here, assuming radiative diffusion as the simplified RT for the VC. We also describe the relevant RT physics that unfold in the VC and in the outer shell (OS) where detailed spatial structure does matter for image formation. This includes control by the VC of the cloud-scale contrast between brightnesses of illuminated and shaded boundaries, as well as the gradual blurring of spatial structure via directional diffusion with increasing optical distance into the OS. “Transport” space is the merger of 3D (or 1D) physical space and 2D direction space. Cloud image formation involves radiative diffusion processes (i.e., random walks) in both of these spaces, depending on what transport regime prevails. Fortunately for the future of computed CT and of passive cloud remote sensing in general, there is a clear spatial separation: asymptotic limit of radiative diffusion in the VC, standard RT in the OS. A hybrid forward model for CT will make use of this fact. Reference: Forster, L., Davis, A. B., Diner, D. J., & Mayer, B. (2021). Toward Cloud Tomography from Space Using MISR and MODIS: Locating the “Veiled Core” in Opaque Convective Clouds, Journal of the Atmospheric Sciences, 78(1), 155-166.

Public health communication strategies, including entertainment-education, can effectively change human behavior, improving health outcomes from climate change. Tools from social psychology, including social modeling and building self and collective efficacy, can help us to create a new model for current, culturally-relevant stories that can help communities adapt to climate change. As an example we will share key learnings from Rhythm and Glue, an applied television prototype, based on research from an NSF Advancing Informal STEM Learning submission. Best practices for climate communication include adaptations of entertainment-education techniques for culturally grounded representations of climate engagement positive outliers. As science communication progresses in adapting social psychology and sociology practices for climate communication, we would like to share how this prototype applies the methods and suggests some new directions that further adapt the practices to account for limited resources and media fragmentation challenges. While this work focuses on climate, it has broad implications for future science communication practices.

Interoperability between datasets in Heliophysics and Planetary archives is increasingly important to address complex science questions about space weather and planetary plasma environments. Yet for cross-disciplinary studies, data ingestion is often a tedious, time-consuming process. We have developed the Heliophysics Application Programmer’s Interface (HAPI), a standard specification that captures a lowest common denominator method for accessing time series data. HAPI offers the ability to request data from multiple sources using a single interface, coupled with the ability to get identically formatted data from each source. HAPI has been recognized as a standard by the Committee on Space Research (COSPAR) and has gained adoption at multiple institutions in the US, including Goddard Space Flight Center’s Coordinated Data Analysis Web (GSFC/CDAWeb), the Planetary Data System Planetary Plasma Interactions Node (PDS/PPI), and the Laboratory for Atmospheric and Space Physics (LASP) Interactive Solar Irradiance Data Center (LISIRD). European plasma data centers such as the French Plasma Physics Data Centre (CDPP) and European Space Astronomy Centre (ESAC) are also in the process of adopting HAPI. We present an overview of the HAPI specification and describe how data centers can add HAPI access to their content. We also present how scientists can plot or download HAPI data using Python or using existing analysis tools such as Autoplot (Faden, 2010) and Space Physics Environment Data Analysis Software (SPEDAS) (Angelopoulos, 2019). Faden, J.B., Weigel, R.S., Merka, J. et al. Autoplot: a browser for scientific data on the web. Earth Sci Inform 3, 41–49 (2010). https://doi.org/10.1007/s12145-010-0049-0 Angelopoulos V, Cruce P, Drozdov A, et al. The Space Physics Environment Data Analysis System (SPEDAS). Space Sci Rev. 2019;215(1):9. doi:10.1007/s11214-018-0576-4

The research data repository of the Environmental Data Initiative (EDI) is a signatory of the FAIR Data Principles. Building on over 30 years of data curation research and experience in the NSF-funded US Long-Term Ecological Research program (LTER), it provides mature functionalities, well established workflows, and support for ‘long-tail’ environmental data publication. High quality scientific metadata are enforced through automatic checks against community developed rules and the Ecological Metadata Language (EML) standard. Although the EDI repository is far along the continuum of making its data FAIR, representatives from EDI and the LTER Information Management community have recently been developing best practices for the edge cases in environmental data publishing. Here we discuss and seek feedback on how to best handle the publication of these ‘long-tail’ data when extensive additional data are available along with e.g., genomics data, physical specimens, or flux tower data. While these latter data are better handled in other discipline-specific repositories such as NCBI, iDigBio, and AmeriFlux, they are frequently associated with other data collected at the same time and location, or even from the same samples. This is particularly relevant across the LTER Network, where sites represent integrative research projects. Questions we address (and seek community input from) include: How to archive documents and images when they are data, e.g., field notebooks, or time-lapse photographs of plant phenology? How to deal with data from Unmanned Vehicle (e.g., drones and underwater gliders), acoustic data, or model outputs, which may be several terabytes in size? How should processing scripts or modeling code be associated with data? Overall, these best practices address issues of Findability and Accessibility of data as well as greater transparency of the research process.

Nutrient pollution is considered one of America’s most widespread, costly, and challenging environmental problems. Artificial Floating Islands (AFIs), a phytoremediation technology, has been proven as an efficient, environmental-friendly, and cost-effective strategy to address this issue. However, most previous studies of AFIs were done in controlled conditions at mesocosm experiments. In addition, limited information exists on the use of AFIs as a nutrient remediation/prevention strategy in Ohio. This study aims to fill these gaps. We are currently undertaking a combination of mesocosm and natural experiment to assess the nutrient-removal efficiency of AFI systems in the Milliron Research Wetlands (at the Ohio State University Mansfield campus), and establish a performance baseline for two native aquatic plant species, Carex comosa and Eleocharis palustris. In this study, 18 AFIs, 6 planted with Carex comosa, 6 with Eleocharis palustris, and 6 have no plants, were deployed in a section of the Milliron Research Wetlands. Physical and chemical parameters are being monitored bi-weekly. The AFI systems are constructed using PVC pipes to provide buoyance, EVA foam mats as platforms, and nylon nets to cover the system. Each AFI unit has nine luffa sponges, inserted in the foam mat, to hold aquatic plant seedlings, keep the moisture of roots, and enlarge the surface area for bacterial biofilm development. Since nutrient removal from the wetland is affected by numerous natural processes, a mesocosm experiment was set up to assist the quantification of nutrient removal due specifically to the presence of AFIs. The mesocosm experiment mimics the natural experiment at the wetland and contain 12 equal-size tanks containing water pumped directly from the wetland, 3 of which have AFIs with Carex comosa, 3 have Eleocharis palustris, 3 have no plants, and 3 contain just water from the wetland. Physical and chemical measurements (as well as sample collections) are performed weekly in the tanks. Water in the tanks are exchanged bi-weekly. Preliminary results show that the AFI systems quickly developed large root systems and extensive bacterial biofilms. The effects of the associations between plant biomass, biofilm development, and changing chemical and physical conditions will be investigated as the experiment progresses.

Observations from the LADEE, Apollo and Surveyor missions have provided evidence of an active lunar dust environment where dust is ejected from the surface into the exosphere by natural physical mechanisms (e.g., meteoroid impacts and possibly electrostatic lofting). Characterizing the spatial and temporal distribution of different exospheric dust populations, and how they are coupled to other components of the dynamic lunar environment, is important to understanding the surface evolution of the Moon. Additionally, anthropogenic dust ejected from the surface by human/robotic exploration activities can be a significant source of exospheric dust. Experience from the Apollo missions showed that dust has the potential to be hazardous as it can interfere with the operation of mechanical, thermal and optical systems. Therefore, it is vitally important to be able to monitor the dust environment to ensure mission safety for future exploration, especially in the Artemis era. An effective method for observing any dust populations in the lunar exosphere is to measure the intensity of sunlight scattered by the dust. This can reveal the dust abundance and spatial distribution, as well as constrain the average grain size by measuring the angular width of the forward scattering lobe. The largest uncertainties in such measurements lies in the grain scattering properties, namely: scattering coefficient, phase function shape and polarization. All of these become more important at larger scattering angles, where diffraction no longer dominates. Typically, the dust size distribution cannot be measured uniquely, and must be constrained by a set of forward simulations at multiple wavelengths and scattering angles. We present a precomputed grid of light scattering properties for irregularly shaped grains (Richard et al., 2011), which are a more realistic representation of lunar dust than the Mie models commonly employed. The grid spans UV to near-IR wavelengths and encompasses a wide range of grain size. Scattering from smaller grains is computed using the Discrete Dipole (DDA) method (DDSCAT) and at larger sizes using the Hapke-Equivalent Slab with Allen diffraction (this will soon be replaced by ray tracing with diffraction). Applications of this grid include observation interpretation and modelling of sunlight scattered by meteoroid impact plumes, lunar horizon glow, and exploration activities.

We measured during the MOSAiC field experiment the snow microstructure on sea-ice from early winter to the melt season, and continued measurements with the surface scattering layer. We could measure every week 1-2 full snow profiles between 0.1-0.3 m. We extracted, mostly in-situ, cores of 48-78 mm diameter and of about 0.1 m length, and scanned with 18-28 µm resolution. The goal of these measurements is to understand the formation and metamorphism of the snowpack in detail, and to derive detailed geometrical and physical properties from the samples. We will present first examples and and overview of characteristic snow profiles from leg 1 - 4, spanning the winter, spring and melt season.

Gas and vapour emissions from subglacial or subnivean volcanoes are capable of melting voids and passageways, here termed glaciovocanic caves and chimneys, in the overlying ice/snow. Glaciovolcanic caves (sub-horizontal) and chimneys (vertical) have been documented within a variety of volcanic regions around the world, with their formation sometimes preceding volcanic eruptions. Studying the formation and evolution of glaciovolcanic caves and chimneys and their relation to changes within the associated volcanic and glacial systems, therefore has potential to inform glaciovolcanic hazard assessments. In 2016, glaciovolcanic chimneys were discovered within Job Glacier in the Mt. Meager Volcancic Complex, British Columbia, Canada. The hypothesis that the chimneys formed as a result of glacier thinning, rather than due to an increase in volcanic activity, has yet to be tested. Here we seek to describe the morphology of these glaciovolcanic features, with respect to glaciological conditions and geothermal heat fluxes, using analytical models. By adapting existing analytical models of subglacial hydrological channels to account for the flow of geothermal gases instead of water, we derive the opening and closure rates for glaciovolcanic caves and chimneys. We use idealized glacier geometries and simplified descriptions of the energy transfer between the geothermal gases and the ice walls to facilitate our analysis. Steady-state geometries are found by balancing the melt opening, internal energy loss and the closure due to ice creep, and presented as functions of glacier thickness and geothermal heat flux. Our analytical results will be used to guide numerical simulations with more complex geometries and transient glaciovolcanic conditions. A better understanding of these complex interactions will facilitate more effective assessment of potential precursory signals of volcanic activity.

The Permian Basin has become the United States’ largest producer of oil over the past decade. Along with the rise in production, there has been an increase in the rate of low magnitude earthquakes, some of which have been associated with hydrocarbon extraction and wastewater injection. A detailed knowledge of changes to the subsurface can aid in understanding the causes of seismicity, and these changes can be inferred from InSAR surface deformation measurements. In this study, we show that both cm-level cumulative deformation, as well as mm-level coseismic deformation signals, are detectable in West Texas. In a region west of Mentone, TX, we reconstructed the subtle coseismic deformation signal on the order of ~5 mm associated with the recent M4.9 earthquake. Over ~100,000 km2 of the Permian Basin, we created annual cumulative LOS deformation maps, decomposing into vertical and eastward components where overlapping data are available. These maps contain numerous subsidence and uplift features near active production and disposal wells. The most important deformation signatures are linear streaks that extend tens of kilometers near Pecos, TX, where a cluster of increased seismic events was cataloged by TexNet. As validated by independent GPS data, our InSAR processing strategy achieved millimeter-level accuracy. A careful treatment of the InSAR tropospheric noise, which can be as large as 15 cm in West Texas, is required to detect surface deformation signals with such low signal-to-noise ratio. We developed an outlier removal technique based on robust statistics to detect the presence of strong, non-Gaussian noise. We compared the surface deformation solutions of multiple InSAR time series methods, and all of them produced more accurate and consistent deformation trends after removing outlier InSAR measurements. We are exploring a Bayesian generalization of SBAS velocity estimation by including probabilistic data rejection to determine which pixels should be excluded from the model fitting. This technique provides a full posterior distribution of the model parameters along with the best-fit surface velocity.

Habitable regions of Europa may include a subsurface ocean and transient liquid environments within its icy shell. Ocean-surface communication may occur on 1–2 million-year (My) timescales or even more rapidly in chaos regions. Any ice-entombed organisms could remain viable at near-surface depths (10–100 cm) over 1–10 ky. The proposed Europa Lander will target samples at depths >10 cm, potentially enabling recovery of viable organisms if sampling conditions are ideal. Any life there would likely represent a separate genesis event from Earth life. Life detection approaches should therefore not only target life as we know it (contamination, common physicochemistry), but also as we don’t know it, to lower the risk of false negatives. We propose to target prebiotic, ancient, or extant life using a novel fully-electronic single-molecule detection strategy. Now in early development (PICASSO), the Electronic Life-detection Instrument for Enceladus/Europa (ELIE) instrument will utilize quantum electron tunneling between nanogap electrodes to interrogate the electronic structure of single molecules. Nanogaps are formed by breaking a gold nanowire embedded on a silicon chip. Bending is then used to control the gap size in the sub-nanometer regime. A molecule can be identified by its characteristic conductance and interaction time as a function of gap size. This technology can detect and distinguish among amino acids, and detect RNA and DNA bases and short base sequences. The extrapolated limit of detection for single amino acids is ~200 ppt after 5 min of sampling (~1 pMol/g). Integrating upfront separation methods will enhance specificity and sensitivity. Our lab-bench prototype integrates a nanogap chip, low-noise amplifier, and a laptop for data processing. We target a ~1 kg flight instrument mass. ELIE will be able to measure two key biosignatures: the amino acid complexity distribution, and charged informational polymers, through to be universal for aqueous based life.

Cloud microphysics plays important role on the storm dynamics. To investigate the impact of advanced microphysics schemes, using single and double moment (WSM6/WDM6) schemes, numerical simulations are conducted for a severe convective system that formed over the Korean Peninsula. Spatial rainfall distribution and pattern correlation associated with the convective system are improved in WDM6. During developing stage of the system, the distribution of total hydrometeors is larger in WDM6 compared to WSM6. Along with mixing ratio of hydrometeors (cloud, rain, graupel, snow and ice),number concentration of cloud and rainwater are also predicted in WDM6. To understand the differences in vertical representation of cloud hydrometeors between the schemes, rain number concentration (Nr) from WSM6 is also computed using particle density to compare with Nr readily available in WDM6.Varied vertical distribution, and large differences in rain number concentration, rain particle mass are evident between the schemes. Inclusion of number concentration of rain and cloud, CCN along with mixing ratio of different hydrometers have improved the storm morphology in WDM6. Inorder to investigate the cloud-aerosol interactions, numerical simulation has been conducted using an increase in CCN(aerosol) in WDM6 which has shown an improved rainfall distribution with intense hydrometer distribution. The latent heating (LH) rates of different phase change processes (condensation, evaporation, freezing, melting, sublimation and deposition) are also computed using various transformation rate terms in the microphysics modules. It is inferred that the change in aerosol has increased the LH of evaporation and freezing and affected the warming and cooling processes, cloud vertical distribution and subsequent rainfall.