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427 records · Page 24

Highlights of TOMS Version 9 Total Ozone Algorithm

The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side benefit of this algorithm is that it is considerably simpler than the present algorithm that uses a database of 1512 profiles to retrieve total ozone. These profiles are tedious to construct and modify. Though conceptually similar to the SBUV V8 algorithm that was developed about a decade ago, the SBUV and TOMS V9 algorithms differ in detail. The TOMS algorithm uses 3 wavelengths to retrieve the profile while the SBUV algorithm uses 6-9 wavelengths, so TOMS provides less profile information. However both algorithms have comparable total ozone information and TOMS V9 can be easily adapted to use additional wavelengths from instruments like GOME, OMI and OMPS to provide better profile information at smaller SZAs. The other significant difference between the two algorithms is that while the SBUV algorithm has been optimized for deriving monthly zonal means by making an appropriate choice of the a priori error covariance matrix, the TOMS algorithm has been optimized for tracking short-term variability using month and latitude dependent covariance matrices.

Bhartia, Pawan↗

Survival of Snow in the Melting Layer: Relative Humidity Influence

This study quantifies how far snow can fall into the melting layer (ML) before all snow has melted by examining a combination of in-situ observations from aircraft measurements in Lagrangian spiral descents from above through the ML and descents and ascents into the ML, as well as an extensive database of NOAA surface observer reports during the past 50 years. The airborne data contain information on the particle phase (solid, mixed, or liquid), population size distributions and shapes, along with temperature, relative humidity, and vertical velocity. A wide range of temperatures and ambient relative humidities are used for both the airborne and ground-based data. It is shown that an ice bulb temperature of 0°C, together with the air temperature and pressure (altitude), are good first order predictors of the highest temperature snowflakes can survive in the melting layer before completely melting. Particle size is also important, as is whether the particles are graupel or hail. If the relative humidity is too low, the particles will sublimate completely as they fall into the melting layer. Snow as warm as +7°C is observed from aircraft measurements and surface observations. Snow pellets survive to even warmer temperatures. Relationships are developed to represent the primary findings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Optical constants of solid methane

Methane is the most abundant simple organic molecule in the outer solar system bodies. In addition to being a gaseous constituent of the atmospheres of the Jovian planets and Titan, it is present in the solid form as a constituent of icy surfaces such as those of Triton and Pluto, and as cloud condensate in the atmospheres of Titan, Uranus, and Neptune. It is expected in the liquid form as a constituent of the ocean of Titan. Cometary ices also contain solid methane. The optical constants for both solid and liquid phases of CH4 for a wide temperature range are needed for radiative transfer calculations, for studies of reflection from surfaces, and for modeling of emission in the far infrared and microwave regions. The astronomically important visual to near infrared measurements of solid methane optical constants are conspicuously absent from the literature. Preliminary results are presented on the optical constants of solid methane for the 0.4 to 2.6 micrometer region. Deposition onto a substrate at 10 K produces glassy (semi-amorphous) material. Annealing this material at approximately 33 K for approximately 1 hour results in a crystalline material as seen by sharper, more structured bands and negligible background extinction due to scattering. The constant k is reported for both the amorphous and the crystalline (annealed) states. Typical values (at absorption maxima) are in the .001 to .0001 range. Below lambda = 1.1 micrometers the bands are too weak to be detected by transmission through the films less than or equal to 215 micrometers in thickness, employed in the studies to date. Using previously measured values of the real part of the refractive index, n, of liquid methane at 110 K, n is computed for solid methane using the Lorentz-Lorenz relationship. Work is in progress to extend the measurements of optical constants n and k for liquid and solid to both shorter and longer wavelengths, eventually providing a complete optical constants database for condensed CH4.

Khare, Bishun N.↗

Reaction studies of neutral atomic C with H{sub 3}{sup +} using a merged-beams apparatus

We have investigated the chemistry of C+H{sub 3}{sup +} forming CH{sup +}, CH{sub 2}{sup +}, and CH{sub 3}{sup +}. These reactions are believed to be some of the key gas-phase astrochemical processes initiating the formation of organic molecules in molecular clouds. For this work, we have constructed a novel merged fast-beams apparatus which overlaps a beam of molecular ions onto a beam of ground-term neutral atoms. Here, we describe the apparatus in detail and present cross section data for forming CH{sup +} and CH{sub 2}{sup +} at relative energies from ≈9 meV to ≈20 and 3 eV, respectively. Measurements were performed for statistically populated C ({sup 3}P{sub J}) in the ground term reacting with hot H{sub 3}{sup +} (at an internal temperature of ∼2550 K). Using these data, we have derived rate coefficients for translational temperatures from ≈72 K to ∼2.3×10{sup 5} and 3.4×10{sup 4} K, respectively. For the formation of CH{sub 3}{sup +}, we are only able to place an upper limit on the rate coefficient. Our results for CH{sup +} and CH{sub 2}{sup +} are in good agreement with the mass-scaled results from a previous ion trap study of C + D{sub 3}{sup +}, at a translational temperature of ∼1000 K. That work also used statistically populated C ({sup 3}P{sub J}) but internally cold D{sub 3}{sup +} (∼77 K). The good agreement between the two experiments implies that the internal excitation of the H{sub 3}{sup +} is not significant so long as the reaction proceeds adiabatically. At 300 K, the C fine-structure levels are predicted to be essentially statistically populated, enabling us to compare our translational temperature results to thermal equilibrium calculations. At this temperature, our rate coefficient for forming CH{sup +} lies a factor of ≈2.9 below the Langevin rate coefficient currently given in astrochemical databases, and a factor of ∼1.8−3.3 below the published classical trajectory studies using quantum mechanical potential energy surfaces. Our results for CH{sub 2}{sup +} formation at 300 K are a factor of ≈26.7 above these semi-classical results. Astrochemical databases do not currently include this channel. We also present a method for converting our translational temperature results to thermal rate coefficients for temperatures below ∼300 K. The results indicated that CH{sub 2}{sup +} formation dominates over that of CH{sup +} at temperatures ≲50 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Web-based visual data exploration for improved radiological source detection

Radiation detection can provide a reliable means of detecting radiological material. Such capabilities can help to prevent nuclear and/or radiological attacks, but reliable detection in uncontrolled surroundings requires algorithms that account for environmental background radiation. The Berkeley Data Cloud (BDC) facilitates the development of such methods by providing a framework to capture, store, analyze, and share data sets. In the era of big data, both the size and variety of data make it difficult to explore and find data sets of interest and manage the data. Thus, in the context of big data, visualization is critical for checking data consistency and validity, identifying gaps in data coverage, searching for data relevant to an analyst's use cases, and choosing input parameters for analysis. Downloading the data and exploring it on an analyst's desktop using traditional tools are no longer feasible due to the size of the data. This study describes the design and implementation of a visualization system that addresses the problems associated with data exploration within the context of the BDC. Finally, the visualization system is based on a JavaScript front end communicating via REST with a back end web server.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the ease of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. As a result, this bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Mesoscale Convective Systems in Climate Simulations: Methodological Development and Results from MPAS-CAM over the U.S.

In this study, a process-oriented approach is developed to evaluate warm-season mesoscale convective system (MCS) precipitation and their favorable large-scale meteorological patterns (FLSMPs) over the U.S. This approach features a novel observation-driven MCS-tracking algorithm using infrared brightness temperature and precipitation feature at 12, 25 and 50 km resolution and metrics to evaluate the model large-scale environment favorable for MCS initiation. The tracking algorithm successfully reproduces the observed MCS statistics from a reference 4-km radar MCS database. To demonstrate the utility of the new methodologies in evaluating MCS in climate simulations with mesoscale resolution, the process-oriented approach is applied to two climate simulations produced by the Variable-Resolution Model for Prediction Across Scales coupled to the Community Atmosphere Model physics, with refined horizontal grid spacing at 50 km and 25 km over North America. With the tracking algorithm applied to simulations and observations at equivalent resolutions, the simulated number of MCS and associated precipitation amount, frequency and intensity are found to be consistently underestimated in the Central U.S., particularly from May to August. The simulated MCS precipitation shows little diurnal variation and lasts too long, while MCS precipitation area is too large and intensity is too weak. The model is able to simulate four types of observed FLSMP associated with frontal systems and low-level jets (LLJ) in spring, but the frequencies are underestimated because of low-level dry bias and weaker LLJ. Precipitation simulated under different FLSMPs peak during daytime, in contrast to the observed nocturnal peak. Implications of these findings for future model development and diagnostics are discussed.

54 ENVIRONMENTAL SCIENCES↗

Observational Search for Cometary Aging Processes

The scientific objectives of this study were (i) to search for physical differences in the behavior of the dynamically new comets (those which are entering the solar system for the first time from the Oort cloud) and the periodic comets, and (ii) to interpret these differences, if any, in terms of the physical and chemical nature of the comets and the evolutionary histories of the two comet groups. Because outer solar system comets may be direct remnants of the planetary formation processes, it is clear that the understanding of both the physical characteristics of these bodies at the edge of the planet forming zone and of their activity at large heliocentric distances, r, will ultimately provide constraints on the planetary formation process both in our Solar System and in extra-solar planetary systems. A combination of new solar system models which suggest that the protoplanetary disk was relatively massive and as a consequence comets could form at large distances from the sun (e.g. from the Uranus-Neptune region to the vicinity of the Kuiper belt), observations of activity in comets at large r, and laboratory experiments on low temperature volatile condensation, are dramatically changing our understanding of the chemical'and physical conditions in the early solar nebula. In order to understand the physical processes driving the apparent large r activity, and to address the question of possible physical and chemical differences between periodic, non-periodic and Oort comets, the PI has been undertaking a long-term study of the behavior of a significant sample of these comets (approximately 50) over a wide range of r to watch the development, disappearance and changing morphology of the dust coma. The ultimate goal is to search for systematic physical differences between the comet classes by modelling the coma growth in terms of volatile-driven activity. The systematic observations for this have been ongoing since 1986, and have been obtained over the course of approximately 300 nights using the telescopes on Mauna Kea, Kitt Peak, Cerro Tololo, the European Southern Observatory, and several other large aperture facilities. A greater than 2 TB database of broad band comet images has been obtained which follows the systematic development and fading of the cometary coma for the comets in the database. The results to date, indicate that there is a substantial difference in the brightness and the amount of dust as a function of r between the two comet classes. In addition to this major finding, the program has been responsible for several exciting discoveries, including: the P/Halley outburst at r = 14.3 AU, the discovery of Chiron's coma and modelling and observations of the gravitationally bound component, observational evidence that activity continues out beyond r = 17 AU for many dynamically new comets

Meech, Karen J.↗

AstroBiology Explorer Mission Concepts (ABE/ASPIRE)

The AstroBiology Explorer (ABE) and the Astrobiology Space InfraRed Explorer (ASPIRE) Mission Concepts are two missions designed to address the questions (1) Where do we come from? and (2) Are we alone? as outlined in NASA s Origins Program using infrared spectroscopy to explore the identity, abundance, and distribution of molecules of astrobiological importance throughout the Universe. The ABE mission s observational program is focused on six tasks to: (1) Investigate the evolution of ice and organics in dense clouds and star formation regions, and the young stellar/planetary systems that form in them; (2) Measure the evolution of complex organic molecules in stellar outflows; (3) Study the organic composition of a wide variety of solar system objects including asteroids, comets, and the planets and their satellites; (4) Identify organic compounds in the diffuse interstellar medium and determine their distribution , abundance, and change with environment; (5) Detect and identify organic compounds in other galaxies and determine their dependence on galactic type; and (6) Measure deuterium enrichments in interstellar organics and use them as tracers of chemical processes. The ASPIRE mission s observational program expands upon ABE's core mission and adds tasks that (7) Address the role of silicates in interstellar organic chemistry; and (8) Use different resolution spectra to assess the relative roles and abundances of gas- and solid-state materials. ABE (ASPIRE) achieves these goals using a highly sensitive, cryogenically-cooled telescope in an Earth drift-away heliocentric orbit, armed with a suite of infrared spectrometers that cover the 2.5-20(40) micron spectral region at moderate spectral resolution (R>2000). ASPIRE's spectrometer complement also includes a high-resolution (R>25,000) module over the 4-8 micron spectral region. Both missions target lists are chosen to observe a statistically significant sample of a large number of objects of varied types in support of the tasks outline above. The ABE and ASPIRE mission lifetimes are designed to be 14 months and 3 years, respectively, both with significant cryogen and propellant lifetime margins to support an extended observing campaign. The ABE/ASPIRE mission concepts and their supporting Science Teams are led by Principal Investigator Dr. Scott Sandford of NASA s Ames Research Center, with industry partner Ball Aerospace Technologies Ltd., and managed by Jet Propulsion Laboratory. The ABE/ASPIRE Science Operations will be carried out at NASA s Ames Research Center, and the ABE/ASPIRE database will be archived at Caltech/IPAC.

Sandford, Scott↗

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A. Liever↗

Critical Load Exceedances for North America and Europe using an Ensemble of Models and an Investigation of Causes for Environmental Impact Estimate Variability: An AQMEII4 Study

Exceedances of critical loads for deposition of sulphur (S) and nitrogen (N) to different ecosystems were estimated using European and North American ensembles of air quality models, under Phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4), to identify where risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and Europe 0.125° resolution domains, which were then used to calculate critical load exceedances. New, targeted deposition diagnostics implemented in AQMEII4 allowed an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. New datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2 % to 6.1 %; aquatic ecosystems: 21.2 % to 11.4 %). All models agreed in the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5 % to 75.8 %). The exceedances for herbaceous community richness also decreased between 2010 and 2016, from 13.9 % to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in both predictions of total N deposition and the change in N deposition, and hence in the predicted eutrophication exceedances between the two years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48 % to 4.32 % from 2009 to 2010) while eutrophication exceedance increased slightly (60.2 % to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the two years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulphur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to observed wet deposition of sulphate, nitrate and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases, and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulphate, nitrate and ammonium deposition fluxes between models was linked to the use of updated particle dry deposition parameterizations in some models. However, recent literature and further development of some of the models within the ensemble suggests these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulphur and nitrogen deposition prediction variability was linked to SO 2 and HNO 3 dry deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest and the smallest magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH 3 performance may underestimate the extent of NH 3 emissions fluxes from forested areas. Based on these results, an increased process-research focus is therefore recommended for the following model processes and on observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry deposition, cuticle and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH 3 bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH 3 emissions sources should be included in regional chemical transport models. The choice of land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.

critical loads↗