ERDDAP is a data server developed at NOAA Southwest Fisheries Science Center that allows users to easily access and download subsets of gridded and tabular data. At the Scientific Data Integration Group at NOAA’s Pacific Marine Environmental Laboratory we have focused on ERDDAP as the primary mechanism by which we serve all of our tabular data. Besides offering data access in a variety of useful formats, ERDDAP takes care of normalizing the data structure so that all tabular data sets have a simple row and column structure. Additionally, time values are normalized to have a consistent units across all data sets on the server. The simplified tabular nature of the discrete data in ERDDAP lends itself nicely to use with the Google Visualization API (Google Charts). Charts is an API which renders nearly all of the graphics in the browser client. The basis of all charts is the Google Charts DataTable which is exactly analogous to a TableDap table in ERDDAP. Charts are interactive, visually pleasing, free and easy to use and so connecting ERDDAP data to Google Charts is a natural fit. Even though ERDDAP has many output formats including several different JSON renderings, none fit exactly into the specified Charts data types. Initially, as a result, it was necessary to create custom code (either in the client or on a server between the client and the ERDDAP server) to manipulate the ERDDAP data stream to match the Charts API requirements. However, since Charts has a well-documented specification for a JSON representation of the required data type and because ERDDAP is an open source project, it was possible to extend ERDDAP to support the Charts DataTable as a new data type. Using this new data type, it’s possible to instantiate a Charts DataTable object directly from the ERDDAP URL using a simple Ajax call in the client which downloads the JSON DataTable representation. Because the newly added data type is now native to ERDDAP, it is possible to use default constraint syntax and ERDDAP RESTful services (using the ERDDAP user interface if desired) to build the URL for the exact data subset which is to be visualized by the desired google chart. In this presentation, we’ll explain what we’ve done to add the JSON data type to ERDDAP and provide many examples of client-side rendering of earth science and engineering data using Google Charts directly from ERDDAP URLs.

The western region of Bay of Bengal (BoB) is of high importance because of its variability in Western Boundary Current (WBC) pattern, numerous eddy genesis and biogeochemical activities. The WBC is northward in pre–Indian Summer Monsoon (ISM) season and southward in post–ISM season with the presence of anticyclonic and cyclonic gyres respectively. During ISM, the western BoB is dominated by various cyclonic and anticyclonic eddies with discontinuous WBC. The seasonally reversing wind pattern also favors the variation in the circulation pattern of the bay. The mechanism of eddy genesis in the western BoB and their characteristics specially during ISM, when the WBC is discontinuous, is not studied well. Our study uses the Regional Ocean Modeling System (ROMS) to investigate the role of coastal Kelvin wave, which originated from the equatorial wave guide, and local wind on the mesoscale eddies in the western BoB. To better understand the forcing mechanism involved, river influx and modified wind fields are incorporated in the experiments. The simulated Kelvin wave propagation is consistent with the satellite altimetry observations. Two upwelling and two downwelling Coastal Kelvin Wave (CKW) signals are identified. First upwelling signal (UCKW1) exists from January to April whereas the second signal (UCKW2) appears in September. Two downwelling signals are seen from May to August (DCKW1) and October to December (DCKW2), respectively. Depth of 20°C isotherm (D20) shows good correlation with the remote forcing signals as well as surface wind variability. The CKW signals during pre– and post–ISM (UCKW1 and DCKW2 respectively) are dominant. The reversing weaker signals (DCKW1 and UCKW2) contribute to the WBC discontinuity during ISM. Reduction in wind fields results in weak WBC during pre– and post–ISM. Increase in wind field results in strengthening of the weaker CKW modes rather than strengthening the WBC. Average surface eddy kinetic energy along with eddy intensity, radius and lifetime are sensitive to the change in wind field. The eddies are seen to propagate clockwise (anticlockwise) in general due to decrease (increase) in wind field. The study indicates that the CKWs and the local wind have significant impact on seasonally reversing WBC, eddy genesis and their characteristics in the western BoB.

In this study, we present and validate a new numerical solver in OpenFOAM®-v1706 called “ibmPorFoam” that is developed modifying IHFOAM (Higuera et al., 2014) with Immersed Boundary Method. IHFOAM is previously developed modifying interFoam solver of OpenFOAM® to solve flow properties in porous media. IHFOAM solves Volume Averaged Reynolds Averaged Navier-Stokes Equations, captures the free surface using Volume of Fluid method, and is capable of generating and absorbing waves. Immersed boundary method implemented in this study is based on body force approach given by Liu (2013). ibmPorFoam is validated in two parts by using k-ε model as the turbulence closure. In the first part, a porous dam-break experiment (Lin, 1998) is studied as a 2D case study. Free surface measurements inside and outside the porous medium are compared with the numerical results. In the second part, 3D numerical simulations are carried out to determine flow properties around a rigid, impervious box based on the experimental setup of Kleefsman et al. (2005). Numerical results are compared with the experimental results at wave gauges along the channel and pressure gauges located on the box. Both experimental cases are also simulated using IHFOAM to observe the differences in the numerical solvers. It is seen that the results of numerical simulations conducted with ibmPorFoam are in fairly well-agreement with both experimental results and numerical results from IHFOAM. Acknowledgement: Support from TUBITAK, Turkey (Project No: 217M722) is acknowledged. References Higuera, Lara, Losada (2014a), 3D Interaction of Waves and Porous Coastal Structures using OpenFOAM®, Coastal Eng., 83, 43-258. Kleefsman, Fekken, Veldman (2005), A Volume-of-Fluid Based Simulation for Wave Impact Problems, J. Comp. Physics, 206, 363-393. Lin (1998), Numerical Modeling of Breaking Waves, PhD Thesis, Cornell University. Liu, X. (2013), Realistic Flow Simulations around and inside Porous Scour Protection, in proceedings of 2013 IAHR Congress, 1–8.

Carbon-capture and sequestration (CCS) in geologic reservoirs is one strategy for reducing anthropogenic CO2 emissions from large-scale point-source emitters. Recent developments have shown that basalt reservoirs are highly effective for permanent mineral trapping on the basis of CO2-water-rock interactions, which result in the formation of carbonate minerals. However, the injection of super-critical CO2 into the subsurface causes a disturbance in the pressure, temperature, and chemical systems within the target reservoir. How the ambient conditions change in response to a CO2 injection ultimately affects the transport and fate of the injected CO2. Understanding the behavior and transport of CO2 within a geologic reservoir is a difficult problem that is only exacerbated by heterogeneities within the reservoir, for example, permeability can be highly heterogeneous and exhibits significant control on the movement of CO2. The non-isothermal effects that accompany a CO2 injection are also affected by heterogeneous reservoir properties. These non-isothermal effects can lead to significant changes in temperature in both the reservoir water and rock, which can also affect the injectivity and movement of the CO2. This study is focused on gaining a better understanding of the non-isothermal effects of a CO2 injection and how the changes in temperature will affect the movement and reactivity of the CO2, as well as investigate the efficacy of using temperature as a proxy for CO2 breakthrough in the subsurface. iTOUGH2 eco2n is utilized to simulate CO2 injections into a 1D radially symmetric domain over a range of permeabilities, porosities, and salinities. Preliminary results indicate that for a modest CO2 injection rate of 31,500 metric tons/year the exothermic dissolution of CO2 can cause a temperature increase of up to 3.6oC at the edges of the CO2 plume and the Joule-Thomson effect can cause a decrease in temperature up to 10oC near the injection well. Additionally, results from this study indicate that the thermal effects of a CO2 injection, namely the heat of dissolution associated with a large-scale CO2 injection may be an effective MMV strategy for monitoring CO2 breakthrough.

Improved observations of ice hydrometeors can lead to better weather predictions and understanding of the hydrological cycle. Global coverage is best achieved by satellites, using active and passive microwave remote sensing due to the inherent penetration capability and sensitivity to the snow and ice cloud particles which scatter and absorb the radiation. Snow and cirrus cloud particles are to a large degree composed of aggregates. While it is known that the shape of these aggregates influence microwave measurements to various degrees, it is currently not fully clear to what extent certain particle features are of importance. For example, of what importance is the shape of individual crystals in the aggregates? This work is an attempt at improving our knowledge on the impact of ice aggregate microphysics on microwave and sub-millimetre scattering properties from a modelling point of view. A large amount of aggregates (roughly 4000) where modelled through several semi-physical stochastic simulations. The aggregates are composed of hexagonal ice crystals of varying axis ratio, ranging from 1/15 (plates) to 15 (columns), and assumed to be oriented in the horizontal plane. Single scattering properties of over 1000 aggregates were then assessed for zenith/nadir observations, using the discrete dipole approximation (DDA) at three typical radar bands (13.4, 35.6, 94.1 GHz) and three passive microwave frequencies (183.3, 325.15 and 664 GHz). An analysis on the sensitivity of these scattering data to various aggregate parameters is presented. In general, extinction was found to be less sensitive to shape than back-scattering at investigated at frequencies. Extinction at 664 GHz in particular was found to be shape insensitive; promising for the sake of the Ice Cloud Imager (ICI) on the upcoming Metop-SG satellite. In contrast, evaluation of triple frequency signatures showed relatively high shape sensitivity; of relevance to future multi-frequency radars.

The resonant charge exchange coupling between H+, H, O+ and O is a major driver of H+ and O+ transport between the plasmasphere and topside ionosphere. In this work, we present a new technique to derive model-independent neutral atomic hydrogen density, [H], based on parametric solution of the proton continuity equation including charge-exchange-driven transport. Estimation of [H] using the proton continuity equation incorporates atomic oxygen density [O] derived from the inversion of 135.6 nm OI emission measured by TIMED/GUVI and coincident ionospheric parameter measurements from the Arecibo incoherent scatter radar. Furthermore, by solving both the H+ and O+ continuity equations simultaneously, this work also quantifies the field-aligned vertical transport of protons between the plasmasphere and ionosphere and its effect on maintenance of the nightside and dayside ionospheric composition. Case studies during geomagnetically quiet intervals show that the transport of protons from the plasmasphere during nighttime is sufficient for the maintenance of the observed ionospheric O+ composition through reverse charge-exchange with O. Resulting O+ can diffuse upward or downward away from the source, which leads to observed counter-streaming of H+ and O+. Higher O+ densities on the dayside result in the charge-exchange production of H+, which acts as a source of protons to the plasmasphere. In summary, this work provides an unprecedented, model-independent quantification of diurnal conservation of plasmaspheric protons and its effect on ionospheric variability during quiet-times.

The ongoing collision, convergence and northward underthrusting of the Indian plate beneath the Eurasian plate resulted in large lateral variations in crustal thickness and composition beneath the Himalaya.The Kumaon Himalaya lies in the central part of the Himalayan orogeny and provides unique opportunity to study typical characteristics of the underlying crustal structure of the Himalayan fold-thrust-belt system. In the present study, crustal thickness and Poisson’s ratios were estimated at 13 broadband seismological stations established in a profile along the Kali river valley, Kumaon (Central) Himalaya. The seismological profile extends from the Indo-Gangetic plain (IGP) in the south to the Higher Himalaya in the north, passing through the Sub and Lesser Himalaya. The Receiver Function (RF) method has been adopted to investigate the crustal structure beneath the profile. Time domain iterative deconvolution method has been adopted for RF computation. The H-k stacking method has been adopted to analyze the RFs for obtaining average crustal thickness and Poisson’s ratio (s) of the crust beneath each station. The study reveals that the crustal thickness beneath the IGP is ~38 km which gradually increases up to ~41 km at the northernmost station located in the Higher Himalaya. The value of s varies within the range 0.23 – 0.28. Low values of s are observed in the Sub-Himalaya and outer Lesser Himalaya suggesting more of a felsic composition of crust in the region. Significantly high value of s (~0.28) is observed in the Dharchula region. Such high Poisson’s ratio cannot be explained by the presence of solely dry crustal rocks. Presence of mid-crustal fluid/partial melts beneath the region can be the possible cause of high Poisson’s ratio. The recent seismicity suggests a large number of micro-to-moderate magnitude earthquakes forming a cluster at shallow down to mid-crustal depths beneath the Dharchula region. Presence of fluids influences the rheological property and controls the mechanical and shear strength of crustal rocks producing the cluster of seismicity observed beneath the Dharchula region. Keywords: Receiver function, Crustal Thickness, Poisson’s Ratio, Kumaon Himalaya.

Accurate kinematic models are fundamental to enhance our knowledge of the seismic cycle as well as to improve surface ground motion prediction. However, the solution of the ill-posed kinematic inverse problem is non-unique (e.g., Cohee & Beroza, 1994; Wald & Heaton, 1994; Cotton & Campillo, 1995 and Minson et al., 2013) and, according to current acquisition systems surrounding active faults, this problem is highly underdetermined, in spite of its rather simple formulation as a linear inverse problem. Non-linear formulations of the problem, based on model reduction strategies, alleviate the underdetermination of the problem. However, non-linear formulations imply drastic assumptions on the rupture history and they complicate the use of linear algebra tools to assess the uncertainties of results. Regardless of the assumed inverse formulation, the incorporation of physical constrains and prior information into the inverse problem is necessary to provide more robust and plausible solutions. In this work (Sanchez-Reyes et al. 2018), we present a new hierarchical linear time domain kinematic source inversion method able to assimilate data traces through evolutive time windows. This progressive approach, both on the data and model spaces, does require mild assumptions based on prior knowledge or preconditioning strategies on the slip rate local gradient estimations. Contrary to similar approaches (Fan et al., 2014), this strategy benefits from the sparsity and causality of the seismic rupture while still ensuring the positivity of the solution. While standard regularization terms are used for stabilizing the inversion, strategies based on parameter reduction leading to a non-linear relationship between the source history and the observed seismograms are avoided. Rise time, rupture velocity and other attributes can be extracted later on from the slip-rate inversion we perform. . Satisfactory results are obtained on synthetic benchmarks proposed by the Source Inversion Validation project (Mai et al. 2016) and for the 2016 M$_w$7.0 Kumamoto mainshock. Our specific formulation combined with simple prior information, as well as numerical results obtained so far, yields interesting perspectives for a quasi-real-time implementation and to ease the uncertainty quantification of such ill-conditioned problem.

The Bureau of Reclamation serves water to 31 million people and 20 percent of irrigators in the western United States. Reclamation generates large amounts of data and information describing reservoir operations, hydropower generation, environmental compliance, invasive mussels, infrastructure, and other aspects of Reclamation’s mission activities. Much of these data are currently accessed on a program-specific basis via legacy information management & technology (IMT) systems, often without modern features such as machine-readable data formats and web-services. The Department of the Interior’s Open Water Data Initiative addresses these issues, and Reclamation is striving to improve its data-publishing efforts, making its data more easily found, accessed, and applied to support public and private sector activities. This presentation provides an overview of two IMT systems that Reclamation has developed under OWDI: the Reclamation Water Information System (RWIS, water.usbr.gov) and the Reclamation Information Sharing Environment (RISE). RWIS was developed first as a pilot, demonstrating how multiple programs’ water data could be combined into a modernized data-publishing system. It provides free access to reservoir and water time series data from Reclamation’s five regions, includes map and query interfaces for data discovery and access, and web-services for automated retrieval. Based on the success of the RWIS pilot, Reclamation has more recently focused on developing RISE, which will envelop RWIS and feature a much larger collection of Reclamation data, including water quality as it pertains to Reclamation water management activities, invasive mussels, hydropower, and infrastructure, and more. RISE will also serve a mix of data types, going beyond RWIS’ scope of time series data to also include geospatial and documents data. This presentation summarizes RISE development approach, architecture and previews the upcoming release in Winter 2019.

Delivering long-term, high quality environmental sensor data spanning the continent is a primary goal in the National Ecological Observatory Network’s (NEON) Instrumented Systems (IS) group. Some independent observations collected by NEON’s Observation System (OS) measure similar data at the same location and time as the in-situ sensors. Coinciding IS and OS measurements facilitate supplementary data quality assessments by vetting IS sensor data (e.g. aquatic pH probe) against corresponding OS data (e.g. water grab sample analyzed in a lab for pH). To assess whether IS data agree with OS measurements, we use uncertainty as a tool to understand data quality. The uncertainty between NEON IS and OS data follow analytical (e.g. summation in quadrature) or numerical (e.g. Monte Carlo) approaches depending on the complexity of the IS-OS comparison algorithms. NEON calculates the IS-OS uncertainties, and applies the expanded uncertainty as control limits for acceptable IS-OS data comparisons. IS-OS comparisons falling outside the uncertainty-based control limits help to (i) explore unaccounted uncertainty in the IS and OS data, and (ii) address issues in the data or sample collection process as ongoing continuous improvement strategies.

Understanding, predicting, and responding to a rapidly changing Arctic requires sustained observations that capture variability and transformative change of the Arctic systems with all its major components. A key challenge for researchers, Arctic communities, and others tasked with effective responses to such change is to achieve structured coordination of numerous individual observing activities and networks. These have different regional and thematic foci. Many are driven from the bottom-up by research interests, while others are mission-oriented operational networks. The Arctic Observing Summit (AOS) is an effort that seeks to help coordinate such disparate activities and support efforts such as the Sustaining Arctic Observing Networks (SAON) initiative. We report on progress as part of an AOS 2018 working group focused on implementation and optimization of sustained observations. Drawing on the Framework on Ocean Observations, our group identified effective approaches and barriers to integration of different observation requirements and activities/platforms into a coherent observing framework. Case studies for benthic communities, sea ice prediction, and permafrost highlighted the importance of allowing for independently driven activities to coalesce into a uniform framework. This in turn requires clearly defined requirements that ideally serve multiple societal benefits. Such clear definitions also aid private-public partnerships and the development of new observing system business models. Prerequisite to better coordination is a comprehensive, international assessment that describes the current set of systems, community-based networks, sensors, networks, and surveys that are used to observe the Arctic today. Pieces of such an endeavor are starting to emerge, and SAON may serve as a home for integrating and building upon these pieces. Essential to this goal is the development of a knowledge map that collates and connects observing resources to societal benefits, helps identify and prioritize essential variables, data management needs, and critical products and services. The AOS 2018 calls for the launch of an optimization and implementation team of experts that would conduct such an effort under the auspices of SAON. We explore different elements of such a team’s portfolio of tasks.

Reliability of future global warming projections depends on how well climate models reproduce the observed climate change over the twentieth century. In this regard, deviations of the model simulated climate change from observations, such as a recent “pause” in global warming, have received considerable attention. Such decadal mismatches between model simulated and observed climate trends are common throughout the twentieth century, and their causes are still poorly understood. Here we show that the discrepancies between the observed and simulated climate variability on decadal and longer time scale have a coherent structure suggestive of a pronounced global multidecadal oscillation. Surface temperature anomalies associated with this variability originate in the North Atlantic and spread out to the Pacific and Southern oceans and Antarctica, with Arctic following suit in about 25–35 years. While climate models exhibit various levels of decadal climate variability and some regional similarities to observations, noneof the model simulations considered match the observed signal in terms of its magnitude, spatial patterns and their sequential time development. These results highlight a substantial degree of uncertainty in our interpretation of the observed climate change using current generation of climate models.

River corridors, the spatial domains around rivers in which river water interacts with surrounding sediment and rock, are important components of watersheds. They comprise extremely complex ecosystems: heterogeneous at all spatial scales with strong temporal dynamics, coupled biological, geochemical, and hydrologic processes, and ubiquitous human impacts. We present several ways that our project, focused around the 75 km Hanford Reach of the Columbia River but with multiple connections to other systems, is addressing this challenge. These include 1) deployment of intensive, automated sensor networks supplemented by data from the Hanford Environmental Information System (HEIS) for hyporheic zone monitoring 2) data assimilation of these and other data into models using joint hydrologic and geophysical inversion, 3) integrating MASS2 model outputs and bathymetry data using machine learning to classify hydromorphologic features, 4) a community-based effort to develop broad understanding of organic carbon biogeochemistry and microbiomes in diverse river systems, and 5) use of multi-‘omics data to develop new biogeochemical reaction networks. These underpin the incorporation of process understanding and diverse data into high-resolution mechanistic models, and employment of those models to develop reduced-order models that can be applied at large scales while retaining the effects of local features and processes. In so doing we are contributing to reduction of uncertainties associated with major Earth system biogeochemical fluxes, thus improving predictions of environmental and human impacts on water quality and riverine ecosystems and supporting environmentally responsible management of linked energy-water systems.

Topographic maps represent a three-dimensional (3D) surface using a system of symbols in two-dimensions (2D). To facilitate students’ understanding of topographic maps, the Augmented Reality (AR) Sandbox reads the elevation of actual sand and projects the topographic map lines onto the surface of the sand. Although over 600 institutions have built AR Sandboxes to help people interpret topographic maps, classroom studies using the AR Sandbox have not found significant gains on topographic map assessments. The present study is a 2 by 2 design testing the affordances of the AR Sandbox in a laboratory setting. In the first level of the study, participants interacted with the AR sandbox (3D) or a regular computer monitor (2D) to give them feedback on five landforms they constructed in the sand. Participants initially constructed the landforms in the sand with the feedback off (i.e., sand without the overlaid projection or monitor). The feedback was then turned on and participants compared and contrasted their landform to the target topographic map. Participants were then asked to modify their landform with the feedback on (continuous), or the feedback was turned off (discrete) during modification. A mixed-ANOVA revealed significant gains on a modified version of the Topographic Map Assessment (TMA-B) from pre- to post-intervention (F(1, 74) = 80.34, p < .001). A significant interaction revealed that participants in the 2D condition had greater gains (M = 2.91, SD = 2.48) than those in the 3D (M = 1.64, SD = 2.07) condition (F(1, 74) = 6.38, p = .014), although both conditions had significant pre- to post-intervention improvement (2D: t(37) = 7.24, p < .001, d = 1.02; 3D: t(39) = 5.01, p < .001, d = 0.64). On average, the discrete feedback groups spent significantly less intervention time (M = 48.3, SD = 16.9) compared to the continuous groups (M = 58.2, SD = 18.1) (F(1, 76) = 6.20, p = .015). The findings suggest that the AR Sandbox does improve topographic map skill for individual students using our approach, and that the most efficient technique engages students in discrete episodes of feedback using the 2D computer monitor.

Water erosion triggers the spending of billions of dollars a year to Brazil, as well as social and environmental issues. One of the strategies to minimise soil erosion and to foster economic development is adopting techniques for the integration of agricultural systems. Nevertheless, studies on long-term experimental fields under integrated systems are scarce regarding the effect of the integrated crop, livestock, and forestry system on soil and water loss. As integrated agricultural systems are popularising, especially in the Brazilian Cerrado, it is key to understand their impacts on the erosive processes. As experimental data are fundamental to develop and assess mathematical models, the lack of such information halts the advance of technologies that support agricultural development. Here, we assess the influence of integrated crop, livestock, and forestry systems on interrill erosion. For that, we will run tests using a portable plot-scale (0.7 m2) rainfall simulator on Dystrophic Red Latosol using a rainfall intensity of 60 ± 5 mm h-1. We will study the following management systems: livestock loading in rotation Panicum Maximum cv. Mombaça pasture; continuous Brachiaria Decumbens pasture; soybean crop during summer and crop rotation during fall-winter; and integrated crop-livestock-forestry system alternating between a four-year Panicum Maximum cv. Massai pasture and a four-year soybean crop both associated with Eucalyptus production. The soil management systems have been established since 1993 to evaluate economic and agriculture efficiencies. Thereby, we look forward to providing not only economic advantages but also new reference values of soil erosion under integrated agricultural systems, helping to build resilience for food security. Our findings will also contribute to adequate land use, therefore, promoting soil and water conservation.

Understanding the falling velocity of cloud droplets and ice crystals in a nonuniform flow is fundamental to cloud physics and precipitation. In this study, the mean settling velocity of a hydrometeor falling into a non-stationary fluid is examined. To investigate the possible particle-fluid interaction, a homogeneous and isotropic turbulent flow fields is considered. The study covers a wide range of flow velocities and hydrometeor density and size. The results show initially reduction of hydrometeor settling velocity and then enhancement in strong turbulence. The mean settling velocity depends on a) mean flow and turbulent intensity i.e., standard deviation of flow and b) particle terminal velocity i.e., the shape and size of hydrometeor, its density, the dynamic viscosity and the density of the fluid, and the gravitational acceleration. The non-dimensional parameters that are important in characterization of hydrometeor settling velocities are estimated using dimensional analysis. These non-dimensional parameters are then used to formulate the mean settling velocity.

Team collaboration theories or the role that organizational design plays in promoting long-term research success are often secondary considerations within ambitious community-wide research initiatives. However, for research project managers or community managers called in to consult on the formation of new projects, research proposals, or collaborative partnerships, understanding and applying this body of knowledge in the early initiating or planning phases of new research can strongly promote innovative, collegial, and productive outcomes. In 2018, the Arctic Research Consortium of the U.S. undertook a strategic planning initiative to identify the strategic goals and objectives that will guide our research community support efforts over the next five years. As part of this effort, we determined ARCUS would be doing more to directly evaluate and understand the Arctic research community and its support needs. We also confirmed that we will be taking part in efforts to build out and new initiatives such as the Arctic System Science Collaboratory and UArctic Analytics Institute. As a first step toward achieving both of these objectives, ARCUS staff undertook an internal study to identify the common organizational design structures of current Arctic research programs and what recommendations we could make to improve on these designs within the new and emerging programs we support. Using document analysis and key informant interviews, we created a typology of the collaborative research program structures supported by ARCUS as well as other Arctic research programs funded through the National Science Foundation. The pros and cons of these support structures were then explored and evaluated through the lens of team collaboration and organizational design theories. Our findings highlight the important role that research project and community managers play in promoting collaborative institutional structures and cultures and that without intentional and without ongoing efforts to build and improve them, the productivity and longevity of research communities is likely to decline.

The Sample Analysis at Mars (SAM) instrument is a suite of instruments aboard the Mars Science Laboratory that landed on Mars in 2012. Recent measurements of SAM inlet cover actuator temperatures during the 2018 Mars Global Dust Storm have shown less extreme, more benign effects that are beneficial to mechanism performance. These in-situ measurements and models developed from the current study can guide development of actuators and mechanisms on future robotic and manned mission to Mars. Deck-mounted actuators saw drastic, factor of two reduction in diurnal temperature range from 70C to 35C. Maximum temperatures were reduced from +10C to -10C due lower daytime air temperature and attenuation of solar flux absorbed by the actuator body due to increased opacity. Minimum temperatures increased from -60C to -45C due to warmer night-time air temperatures and an enhanced downwelling atmospheric radiation at the surface also caused by dust in the air. Another demonstration of the effects of the dust storm on inlet cover actuator temperature is the linear relation of optical depth plotted against logarithmic diurnal temperature range. Air-fall dust deposition on the white rover deck during the dust storm is indicated by scatter on this linear trend. Other constantly-monitored SAM temperatures include sensors on a second actuator that also shows the effects discussed above and two sensors mounted internally to SAM with less pronounced effects. In this work we will present an overview of the dust storm effects superimposed on the seasonal variation of actuator and other SAM temperatures.