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Lunar and Planetary Science XXXV: Undergraduate Education and Research Programs, Facilities, and Information Access

The titles in this section include: 1) GRIDVIEW: Recent Improvements in Research and Education Software for Exploring Mars Topography; 2) Software and Hardware Upgrades for the University of North Dakota Asteroid and Comet Internet Telescope (ACIT); 3) Web-based Program for Calculating Effects of an Earth Impact; 4) On-Line Education, Web- and Virtual-Classes in an Urban University: A Preliminary Overview; 5) Modelling Planetary Material's Structures: From Quasicrystalline Microstructure to Crystallographic Materials by Use of Mathematica; 6) How We Used NASA Lunar Set in Planetary and Material Science Studies: Textural and Cooling Sequences in Sections of Lava Column from a Thin and a Thick Lava-Flow, from the Moon and Mars with Terrestrial Analogue and Chondrule Textural Comparisons; 7) Classroom Teaching of Space Technology and Simulations by the Husar Rover Model; 8) New Experiments (In Meteorology, Aerosols, Soil Moisture and Ice) on the New Hunveyor Educational Planetary Landers of Universities and Colleges in Hungary; 9) Teaching Planetary GIS by Constructing Its Model for the Test Terrain of the Hunveyor and Husar; 10) Undergraduate Students: An Untapped Resource for Planetary Researchers; 11) Analog Sites in Field Work of Petrology: Rock Assembly Delivered to a Plain by Floods on Earth and Mars; 12) RELAB (Reflectance Experiment Laboratory): A NASA Multiuser Spectroscopy Facility; 13) Full Text Searching and Customization in the NASA ADS Abstract Service.

Source record↗

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Variability↗

Influence of regional anthropogenic changes over Nile region on the climate system during the late Holocene (~2500 years before present)

The societal impacts of climate change during the late Holocene leads to regional anthropogenic changes over the Nile region floodplain and could have acted in tandem with natural factors like major volcanic eruptions on the regional climate system to magnify the local climatic impacts. This study aims to explore and investigate the sensitivity of climatic changes to the regional anthropogenic changes due to various factors over the Nile river floodplains during the late-Holocene (2.5K years before present). The GISS ModelE Earth system model will be used to simulate the various scenarios of regional increasing/decreasing river fraction, changes in vegetation type and cover, along with changes in land surface type against the no-changes scenario in absence of volcanic eruptions. The spatial coverage of the Nile river basin is estimated using the GIS shapefile based on elevation data from Shuttle Radar Topography Mission (SRTM) at 3 Arc-seconds (approx. 90-meter) horizontal resolution. The extent of flooding in the model grid (2.0°x2.5° in latitude and longitude) is estimated using the existing high-resolution (0.125°x0.125°) gridded topographic elevation information and mapped over the Nile river floodplains. This study also focuses on evaluating the NASA GISS ModelE for resolving the climate feedbacks and response on climate system due to anthropogenic changes and volcanic eruptions. It is also aimed to analyze and quantify the impact of various anthropogenic factors over the African monsoon system and rainfall over the region, which feeds the Nile River.

Anthropogenic changes↗

The derivation of a sub-canopy digital terrain model of a flooded forest using synthetic aperture radar

Synthetic aperture radar data from the Shuttle Imaging Radar-B Mission were combined with the tide surface information to create a digital terrain model for a 70-km by 40-km section of the Mouths of the Ganges forests in southern Bangladesh. The dominance of the interaction phenomenon (canopy to surface or surface to canopy reflection) in flooded forests was exploited to create sub-canopy flood boundary maps for two different tide times. The boundary maps were digitally combined in x, y, z space with tide elevation models created from tide gauge data gridding the survey site and used as input to interpolation routines to create a terrain model. The end product represents a significant step in our ability to characterize the topography and hydrology of wetland ecosystems. The model derived here can be used for simulating tidal flow and nutrient transport from the forest to the marine habitat.

Imhoff, Marc Lee↗

Powered By ERAD [Slides]

Energy Resilience Analysis for Distribution Power System (ERAD) is a free, open-source Python toolkit for estimating the energy and service impacts of hazards like earthquakes and flooding. It uses a graph-based approach to capture high resolution connectivity among the grid, critical services, and customers and rapidly compute household level metrics and aggregated statistics across large distribution systems. It uses asset fragility curves that relate hazard severity to survival probability for power system equipment including cables, transformers, substations, etc. The tool is designed to be modular and extensible, allowing it to interface with third-party hazard simulators and integrate into broader resilience analysis workflows. ERAD enables researchers, students, communities, distribution utilities, and other stakeholders to understand hazard impacts and evaluate the effectiveness of different programs to improve energy resilience. The webinar was hosted by NLR researcher Aadil Latif.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗

Bias Correction of Hydrologic Projections Strongly Impacts Inferred Climate Vulnerabilities in Institutionally Complex Water Systems

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes.

Keyvan Malek↗

Experimental Investigation of Polymer Induced Fouling of Heater Tubes in the First-ever Polymer Flood Pilot on Alaska North Slope

Polymer flooding has been validated in the lab and by successful applications in other countries, such as Canada and China, to be an effective EOR technique for heavy oil reservoirs. Currently, polymer flooding is being pilot tested for the first time in the Schrader Bluff viscous oil reservoir at Milne Point field on Alaska North Slope (ANS). One of the major concerns of the operator is the impact of polymer on the oil production system after polymer breakthrough, especially the polymer induced fouling issues in the heat exchanger. This study investigates the propensity of polymer fouling on the heater tubes as a function of different variables, with the ultimate goal of determining safe and efficient operating conditions. A unique experimental set-up was indigenously designed and developed to simulate the fouling process on the heating tube. The influence of heating tube skin temperature, tube material, and polymer concentration on fouling tendency was investigated. Under each test condition, the test was run five times with the same tube, and in each run, the freshly prepared synthetic brine and polymer solution were heated from 77°F to 122°F to mimic field operating conditions. The heating time and fouling amount were recorded for each run. The morphology and composition of the deposit samples were analyzed by environmental scanning electron microscopy (ESEM) and X-ray diffraction (XRD), respectively. It has been found that, in general, the presence of polymer in produced fluids would aggravate the fouling issues on both carbon steel and stainless steel surfaces at all tested skin temperatures (165°F, 250 °F and 350°F), but only higher skin temperatures of 250°F and 350°F could cause polymer induced fouling issues on the copper tube surface and the fouling tendency increased with polymer concentration. At the lower skin temperatures of 165°F, no polymer-induced fouling was identified on the copper tube. A critical temperature that is related to the cloud point of the polymer solution was believed to exist, below which polymer induced fouling would not occur and only mineral scale deposited, but above which the polymer would obviously aggravate the fouling issue. The heating efficiency of the tube would be reduced gradually as more fouling material accumulates on its surface. The ESEM results indicate that if polymer precipitated and deposited on the surface, it would bond to the mineral crystals to form a stronger three- dimensional network structure, and that is why the polymer induced fouling was tougher and more difficult to be removed from the tube surface. The XRD analysis results confirm that the presence of polymer in the fluids can enhance the mineral scale propensity. Overall, the study results have provided practical guidance to the field operator for the ongoing polymer flooding pilot test on ANS. This study may also prove to be valuable for other chemical EOR projects around the world.

Alaska North Slope↗

Near-global summer circulation response to the spring surface temperature anomaly in Tibetan Plateau –– the GEWEX/LS4P first phase experiment

Subseasonal to seasonal (S2S) prediction of droughts and floods is one of the major challenges of weather and climate prediction. Recent studies suggest that the springtime land surface temperature/subsurface temperature (LST/SUBT) over the Tibetan Plateau (TP) can be a new source of S2S predictability. The project “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P)” was initiated to study the impact of springtime LST/SUBT anomalies over high mountain areas on summertime precipitation predictions. The present work explores the simulated global scale response of the atmospheric circulation to the springtime TP land surface cooling by 16 current state-of-the-art Earth System Models (ESMs) participating in the LS4P Phase I (LS4P-I) experiment. The LS4P-I results show, for the first time, that springtime TP surface anomalies can modulate a persistent quasi-barotropic Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train from the TP via the northeast Asia and Bering Strait to the western part of the North America, along with the springtime westerly jet from TP across the whole North Pacific basin. The TRC wave train modulated by the TP thermal anomaly play a critical role on the early summer surface air temperature and precipitation anomalies in the regions along the wave train, especially over the northwest North America and the southern Great Plains. The participant models that fail in capturing the TRC wave train greatly under-predict climate anomalies in reference to observations and the successful models. These results suggest that the TP LST/SUBT anomaly via the TRC wave train is the first order source of the S2S variability in the regions mentioned. Furthermore, the TP surface temperature anomaly can influence the Southern Hemispheric circulation by generating cross-equator wave trains. However, the simulated propagation pathways from the TP into the Southern Hemisphere show large inter-model differences. More dynamical understanding of the TRC wave train as well as its cross-equator propagation into the Southern Hemisphere will be explored in the newly launched LS4P phase II experiment.

54 ENVIRONMENTAL SCIENCES↗

Volcanic Climate Warming through Radiative and Dynamical Feedbacks of SO2 Emissions

Volcanic flood basalt eruptions have been linked to or are contemporaneous with major climate disruptions, ocean anoxic events, and mass extinctions throughout at least the last 400M years of Earth’s history. Previous studies and recent history have shown that volcanically-driven climate cooling can occur through reflection of sunlight by H2SO4 aerosols, while longer-term climate warming can occur via CO2 emissions. We use the Goddard Earth Observing System Chemistry- Climate Model to simulate a four-year duration volcanic SO2 emission of the scale of the Wapshilla Ridge member of the Columbia River Basalt eruption. Brief cooling from H2SO4 aerosols is outweighed by dynamically and radiatively driven warming of the climate through a three orders of magnitude increase in stratospheric H2O vapor.

Scott D Guzewich↗

Volcanic Climate Warming through Radiative and Dynamical Feedbacks of SO2 Emissions

Volcanic flood basalt eruptions have been linked to or are contemporaneous with major climate disruptions, ocean anoxic events, and mass extinctions throughout at least the last 400M years of Earth’s history. Previous studies and recent history have shown that volcanically-driven climate cooling can occur through reflection of sunlight by H2SO4 aerosols, while longer-term climate warming can occur via CO2 emissions. We use the Goddard Earth Observing System Chemistry-Climate Model to simulate a four-year duration volcanic SO2 emission of the scale of the Wapshilla Ridge member of the Columbia River Basalt eruption. Brief cooling from H2SO4 aerosols is outweighed by dynamically and radiatively driven warming of the climate through a three orders of magnitude increase in stratospheric H2O vapor.

Scott D Guzewich↗

How does humidity data impact land surface modeling of hydrothermal regimes at a permafrost site in Utqia$\mathrm{\dot{g}}$vik, Alaska?

Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. Here, we found that higher values of RH (up to 40%) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30% maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physically-based predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling.

54 ENVIRONMENTAL SCIENCES↗

The Effects of Snow Depth Forcing on Southern Ocean Sea Ice Simulations

The spatial and temporal distribution of snow on sea ice is an important factor for sea ice and climate models. First, it acts as an efficient insulator between the ocean and the atmosphere, and second, snow is a source of fresh water for altering the already weak Southern Ocean stratification. For the Antarctic, where the ice thickness is relatively thin, snow can impact the ice thickness in two ways: a) As mentioned above snow on sea ice reduces the ocean-atmosphere heat flux and thus reduces freezing at the base of the ice flows; b) a heavy snow load can suppress the ice below sea level which causes flooding and, with subsequent freezing, a thickening of the sea ice (snow-to-ice conversion). In this paper, we compare different snow fall paramterizations (incl. the incorporation of satellite-derived snow depth) and study the effect on the sea ice using a sea ice model.

Powel, Dylan C.↗

Aerosol-Cloud-Precipitation Interactions over Indo-Gangetic Basin

About 60% of world population reside in Asia, in term of which sheer population density presents a major environmental stress. Economic expansion in this region is, in fact, accompanied by increases in bio-fuel burning, industrial pollution, and land cover and land use changes. With a growth rate of approx. 8%/yr for Indian economy, more than 600 million people from Lahore, Pakistan to Calcutta, India over the Indo-Gangetic Basin have particularly witnessed increased frequencies of floods and droughts as well as a dramatic increase in atmospheric loading of aerosols (i.e., anthropogenic and natural aerosol) in recent decades. This regional change (e.g., aerosol, cloud, precipitation, etc.) will constitute a vital part of the global change in the 21st century. Better understanding of the impacts of aerosols in affecting monsoon climate and water cycles is crucial in providing the physical basis to improve monsoon climate prediction and for disaster mitigation. Based on climate model simulations, absorbing aerosols (dust and black carbon) play a critical role in affecting interannual and intraseasonal variability of the Indian monsoon. An initiative on the integrated (aerosols, clouds, and precipitation) measurements approach over the Indo-Gangetic Basin will be discussed. An array of ground-based (e.g., AERONET, MPLNET, SMART-COMMIT, etc.) and satellite (e.g., Terra, A-Train, etc.) sensors will be utilized to acquire aerosol characteristics, sources/sinks, and transport processes during the pre-monsoon (April-May, aerosol forcing) season, and to obtain cloud and precipitation properties during the monsoon (May-June, water cycle response) season. Close collaboration with other international programs, such as ABC, CLIVAR, GEWEX, and CEOP in the region is anticipated.

Tsay, S.-C.↗

A Modeling Study of the Spring 2011 Extreme US Weather Activity

The spring of 2011 was characterized by record-breaking tornadic activity with substantial loss of life and destruction of property. While a waning La Nina and other atmospheric teleconnections have been implicated in the development of these extreme weather events, a quantitative assessment of their causes is still lacking. This study uses high resolution (1/4 lat/lon) GEOS-5 AGCM experiments to quantify the role of SSTs and soil moisture in the development of the extreme weather activity with a focus on April - the month of peak tornadic activity. The simulations, consisting of 22-member ensembles of three-month long simulations (initialized March 1st) reproduce the main features of the observed large-scale changes including the below-normal temperature and above-normal precipitation in the Central US, and the hot and dry conditions to the south. Various sensitivity experiments are conducted to separate the roles of the SST, soil moisture and the initial atmospheric conditions in the development and predictability of the atmospheric conditions (wind shear, moisture, etc.) favoring the severe weather activity and flooding.

Schubert, S.↗

Comparing Proxy and Model Estimates of Hydroclimate Variability and Change over the Common Era

Water availability is fundamental to societies and ecosystems, but our understanding of variations in hydroclimate (including extreme events, flooding, and decadal periods of drought) is limited because of a paucity of modern instrumental observations that are distributed unevenly across the globe and only span parts of the 20th and 21st centuries. Such data coverage is insufficient for characterizing hydroclimate and its associated dynamics because of its multidecadal to centennial variability and highly regionalized spatial signature. High-resolution (seasonal to decadal) hydroclimatic proxies that span all or parts of the Common Era (CE) and paleoclimate simulations from climate models are therefore important tools for augmenting our understanding of hydroclimate variability. In particular, the comparison of the two sources of information is critical for addressing the uncertainties and limitations of both while enriching each of their interpretations. We review the principal proxy data available for hydroclimatic reconstructions over the CE and highlight the contemporary understanding of how these proxies are interpreted as hydroclimate indicators. We also review the available last-millennium simulations from fully coupled climate models and discuss several outstanding challenges associated with simulating hydroclimate variability and change over the CE. A specific review of simulated hydroclimatic changes forced by volcanic events is provided, as is a discussion of expected improvements in estimated radiative forcings, models, and their implementation in the future. Our review of hydroclimatic proxies and last-millennium model simulations is used as the basis for articulating a variety of considerations and best practices for how to perform proxy-model comparisons of CE hydroclimate. This discussion provides a framework for how best to evaluate hydroclimate variability and its associated dynamics using these comparisons and how they can better inform interpretations of both proxy data and model simulations.We subsequently explore means of using proxy-model comparisons to better constrain and characterize future hydroclimate risks. This is explored specifically in the context of several examples that demonstrate how proxy-model comparisons can be used to quantitatively constrain future hydroclimatic risks as estimated from climate model projections.

Common Era↗

Convection and lunar thermal history

The effects of solid interior convection on the thermal history of the moon are examined. Convective models of lunar evolution are calculated to demonstrate the influence of various viscosities, radioactive heat source distributions and initial temperature profiles and tested by means of a thermal history simulation code. Results indicate that solid convection does not necessarily produce a quasi-steady thermal balance between heat sources and surface losses. The state of the lithosphere is found to be sensitive to the efficiency of heat source redistribution, while that of the convecting interior depends primarily on rheology. Interior viscosities of 10 to the 21st to 10 to the 22nd cm/sec are obtained, along with a central temperature above 1100 C. It is suggested that mare flooding could have been the result of magma production by pressure release melting in the upwelling region of convection cells.

Cassen, P.↗

Planting miscanthus instead of row crops may increase the productivity and economic performance of farmed potholes

Abstract Climate change projections indicate that precipitation events in the central United States are expected to become more intense, more frequent in the spring, and less frequent in the summer. Such a precipitation shift could adversely impact crop yields, especially in subfield areas known as farmed potholes, which are highly susceptible to flooding and ponding, and crop death is more likely to occur, particularly early in the growing season. This suggests that planting alternative crops, such as more flood tolerant perennials, in these areas may be a more profitable option. Using observations of crop growth and yield along with ponding depth of a specific field and farmed pothole in the central United States, we developed a spatially explicit version of the agroecosystem model Agro‐IBIS to estimate water depth and crop yield. After evaluating the model, we conducted a case study for a specific farmed pothole with a range of future precipitation scenarios with Agro‐IBIS to simulate the effects of contemporary (2002–2016) and future precipitation on a conventional corn/soybean ( Zea mays L. and Glycine max Merr.) rotation and an alternative perennial miscanthus ( Miscanthus × giganteus Greef et Deu.) cropping system. The depth and frequency of ponding increased under most future precipitation scenarios. The corn/soybean rotation had greater total loss (i.e., no yield) on average (>30%) for all scenarios in comparison to miscanthus (<10%). Under one future precipitation scenario with increased spring precipitation, both the corn/soybean rotation and miscanthus simulations showed an increase in yield. A simple budget analysis indicated that it is more profitable to plant miscanthus instead of corn or soybeans where yields in farmed potholes are consistently poor. Our findings show that potholes can be individually modeled, and their influence on yield can be quantified for use in future management decisions dictated by change in climate.

54 ENVIRONMENTAL SCIENCES↗