Groundwater depletion in Central Wisconsin, due in part to agricultural high-capacity wells, has sparked an interest in precision irrigation to reduce groundwater pumping without a significant reduction in yield. A key challenge for bridging precision irrigation research and application is how best to monitor water stress in real-time. Aerial and satellite imagery are potential solutions. Drawbacks of these methods include cost, spatiotemporal resolution, and cloud interference, especially in humid regions. Recent advancements in remotely piloted aircrafts (RPAs) have made frequent, low-flying imagery collection more economical and feasible than ever before. We partnered with the Wisconsin Potato and Vegetable Grower Association to generate high-resolution maps of crop water stress using remotely sensed thermal and multi-spectral RPA imagery. Data were collected at a commercially irrigated potato field in the Central Sands region of Wisconsin from June to August 2019. Missions were flown weekly using a quadcopter RPA system instrumented with a newly released, combined multispectral/thermal camera developed for agricultural applications. Each mission included flights at 30, 60, and 90 m above ground level to assess tradeoffs between resolution, area, and flight time. We used biophysical data from an eddy covariance system installed within the flight domain to validate crop water stress maps generated from the remotely sensed RPA data. Ground measurements of surface temperature and soil moisture were collected throughout the domain within fifteen minutes of each mission. Ongoing results will be used to develop best practices for integrating RPAs into precision irrigation programs.

The Wang-Sheeley-Arge (WSA) model estimates the solar wind speed and interplanetary magnetic field polarity at any point in the inner heliosphere using global photospheric magnetic field maps as input. WSA employs the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models to determine the Sun’s global coronal magnetic field configuration. The PFSS and SCS models are connected through two radial parameters, the source surface and interface radii, which specify the overlap region between the inner SCS and outer PFSS model. Though both radii are adjustable within the WSA model, they have typically been fixed to 2.5 R sol. Our work highlights how the solar wind predictions improve when the radii are allowed to vary over time. Data assimilation using particle filtering (sequential Monte Carlo) is used to infer the optimal values over a fixed time window. The Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model generates an ensemble of photospheric maps that are used to drive WSA. When the solar wind model predictions and satellite observations are used in a newly-developed quality-of- agreement metric, sets of metric values are generated. These metric values are assumed to roughly correspond to the probability of the two key model radii. The highest metric value implies the optimal radii. Data assimilation entails additional choices relating to input realization and timeframe, with implications for variation in the solar wind over time. We present this work in its theoretical context and with practical applications for prediction accuracy.

NASA’s 2021 STV Incubation Study Report lists vertical (horizontal, geolocation) accuracy as an associated SATM product parameter for all (most) identified Science and Application Knowledge Gaps. The presented generalized Polynomial Chaos Expansion (gPCE) based method has wide ranging applicability to improve positioning, geolocation uncertainty estimates for all STV disciplines, but is presented for the bathymetric lidar use case, due to added complexity introduced by wave structure, roughness, and entry angle. Most LiDARs, though precise, are vulnerable to position, pointing errors as deviations from the expected principal axis lead to projection errors on target. While fidelity of location/pointing solutions can be high, determination of uncertainty remains relatively basic. Currently, the standard approach is the calculation of the Total Propagated Uncertainty (TPU), which is often plagued by simplifying approximations and ignored covariances. Additionally, uncertainty sources are often exclusively modeled as Gaussian, inaccurately capturing some variable distributions. Prominently, wave behavior is better described by Gamma distributions (which are supported under gPCE). This research addresses specific knowledge gaps in bathy-LiDAR measurement uncertainty through a more complete description of total aggregated uncertainties, from system level to geolocation, by applying a gPCE uncertainty quantification approach. gPCE intrinsically accounts for covariance between variables to determine the uncertainty in a measurement, without manually constructing a covariance matrix, through a surrogate model of system response. Determining point-wise positioning uncertainty using gPCE is less computationally expensive than Monte Carlo methods and more tractable for most dimensionalities of interest (roughly from 3 to 20+). The method also does not rely on simplifying assumptions used in typical TPU methods. Additionally, a key attribute of this approach is that global sensitivity analysis (GSA), after obtaining gPCE coefficients, is trivial and nearly costless to compute. Furthermore, GSA of system configurations/uncertainty is a powerful tool to design and develop LiDAR systems with the measurement requirements integrated into the design solution.

We will present signal processing techniques based on shape analysis of the time-frequency signatures of chorus elements in the Van Allen Radiation Belts. Specifically, we will employ the Radon transform and the Distance Transform, which are well-known for isolating local shapes and patterns in the image processing literature, to achieve automated detection of the spectral morphology of chorus elements. In particular, we will introduce “shrink-wrapping” techniques that quantify the salient features defining the microstructure of chorus elements. We will present preliminary results based on case studies of the EMFISIS data from the Van Allen Radiation Belts mission.

The Unified Access Framework (UAF) project of the NOAA Global Earth Observation - Integrated Data Environment (GEO-IDE) in an on-going effort to provide access to NOAA-wide data in a way that is FAIR and meets PARR requirements. The first priority of UAF is to copy success. We recognize: data that follows the Climate and Forecast netCDF convention is readily used by working scientists; THREDDS Data Servers and ERDDAP servers are a popular ways to serve such data; these servers can be interrogated by software to determine that the data follows the conventions and the servers can be federated. To make the collection we construct a master “raw” catalog of candidate data set from THREDDS servers around NOAA and other organizations. The raw catalog is examined by custom software to eliminate large data collections which are not aggregated in time and organize the results into a “clean” catalog. The catalog is then examined by ERDDAP to provide ERDDAP GridDAP access and to verify that the data sources follow the CF convention. The gridded data sets are merged into a collection of TableDAP (netCDF Discrete Sampling Geometry) data sources. Currently the UAF ERDDAP server is home to 10,712 data sets. After the UAF ERDDAP server has examined the data collection, a Live Access Server (LAS) is configured to offer data analysis and visualization access to all the data sets. The final piece of the puzzle is to make the data FAIR and to achieve PARR compliance. This requires some tools that have been adapted and developed for this purpose. We resurrected the ncISO tool which can examine the contents of CF netCDF data sources and create ISO metadata and score the data according the the Unidata Attribute Convention for Data Discovery. We can help the centers hosting the data meet their PARR requirements by properly integrating the resulting metadata from ncISO into NOAA’s central data catalog. We have recently updated the templates which are used to generate the metadata to insure they are meeting the latest ISO and ADDC specifications. Work is underway at NOAA and Unidata to integrate the ncISO code back into the GitHub repository for the THREDDS Data Server. This will bring together two disparate ncISO implementations. UAF is a few people working a few hours a month to maintain and large and useful data collection and in this talk we’ll tell you how we do it.

The formation mechanisms of cirrus clouds in the tropics (24S–24N) are investigated using the monthly data in 2007–2015 from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and the fifth generation reanalysis product (ERA5) of the European Centre for Medium-Range Weather Forecasts. The data show that the relative humidity with respect to ice (RHi) in cloudy air samples is larger than in cloud-free air samples. Based on the contributions of the specific humidity (SH) and temperature anomalies to the RHi anomalies in cloudy air samples relative to cloud-free air samples, we obtain two categories of clouds: moisture-driven (MD) cirrus, and temperature-driven (TD) cirrus. MD cirrus are formed predominantly by positive SH anomalies, while TD cirrus are formed predominantly by negative temperature anomalies. Since moisture must be brought up to the upper troposphere and tropopause layer by convection, all positive SH anomalies and therefore all MD cirrus are driven by convection. TD cirrus are classified into two sub-categories: those that experience positive SH anomalies and are therefore influenced by convection, and those that experience negative SH anomalies and are therefore not influenced by convection. Averaged over all altitudes of the tropical atmosphere, there are four to five times more convective cirrus (including MD and TD-convective cirrus) than non-convective ones. The level of maximum convective cirrus occurrence is at 11–12 km, coincided with the level of maximum temperature lapse rate and convective outflow. Non-convective cirrus obtain their maximum frequency of occurrence at 16.3 km, which is just below the cold point tropopause at 16.8 km. The seasonal cycle of convective cirrus is consistent with that of tropical convection, while the seasonal cycle of non-convective cirrus is consistent with that of the cold point tropopause. There are two maxima in the frequency of occurrence of convective cirrus, one at 8–12 S in the austral summer, and the other at 8–12 N in the boreal summer. In contrast, non-convective cirrus occur most frequently near the equator in the boreal winter.

In water-limited environments, quantifying the timing and frequency of erratic rainfall recharge events and its climate forcing is of critical importance for groundwater resource management. In temperate semi-arid New South Wales, SE Australia (precipitation: 615 mm/year, pan evaporation: 1679 mm/year), since 2010 we have been using a limestone cave situated at 20 m below land surface, and just above the water table, as a vadose zone observatory of potential recharge approximated by drip rate observations. Complimented since 2018 by a soil moisture probe network and using the VarKarst karst-specialized recharge model, we investigate the climatic, hydrological and karst geological controls on recharge dynamics. We observe nineteen recharge events (07.2010 to 01.2021). They cluster into two periods (1) seven events between 08.2010 and 12.2010 during a La Niña (enhanced spring rainfall is typical in eastern Australia) and (2) seven events between 06.2016 and 10.2016 associated with a negative Indian Ocean Dipole (which is associated with wet winters and springs in southern Australia). Comparison with antecedent rainfall indicates a minimum of 40 mm rainfall over 14-days is required for recharge in winter, and >120 mm rainfall over 14-days in summer. We will use the karst recharge model to simulate the observed recharge events and to quantify the threshold behavior of the soil and vadose zone above the cave. Two recharge events have occurred since the establishment of the soil moisture network (03.05.2020, 29.07.2020). For those, we can analyze the influence of antecedent soil storage on the initiation of recharge and use this understanding for an evaluation of the simulated internal fluxes and storages of karst recharge model. Providing realistic results of both recharge and soil moisture observations, the model can be used as tool to predict the impact of past and future climate changes on groundwater renewal.

We present here a set of tools to curate, analyze, visualize and disseminate datasets, as well as communicate scientific findings, through easy-to-use web interfaces. PRISM uses the IRI Data Library (DL) to aggregate data from climate, agriculture, hydrology, ecology, finance, power outage and space weather domains of science, as well as the datasets resulting from their interdisciplinary research. These datasets vary in their spatial and temporal (and other) representations that the DL allows however to consistently represent in a multi-dimensional data framework. Proper curation facilitates interoperability and dissemination via other tools. We thus use popular python libraries (e.g. xarray, numpy, pandas) to query, manipulate and visualize the data and then build web applications to facilitate their exploration. The content and the interface of those applications, which we call Maprooms, are co-developed with the PRISM scientists in order to design the most relevant way to communicate their results.

Coastal interfaces blend processes dominated by upland region hydrology and ocean hydrodynamics (tides, winds, waves, baroclinic fluctuations, among others). These areas tend to be vulnerable to flooding, a matter of concern considering that around 40% of the world’s population lives within 100 km of the ocean. Specifically, The US East and Gulf of Mexico Coasts are heavily affected by extratropical storms every year with catastrophic consequences. Models that integrate the dynamics of both oceans and river networks are needed in order to better improve flood forecast systems in coastal areas. Due to their spatial and temporal scale differences, traditional models solve river and ocean hydrodynamics independently. As a first step toward unifying coastal interface modeling, we designed an ADCIRC-based model that uses unstructured, highly variable-sized triangular meshes that can accurately represent both ocean basins and inland river networks. This meshing technique allows for incorporating features that control the dynamics of the nearshore area, such as barrier islands, jetties, and dredged channels. We analyze how mesh design impacts water level estimations in the deep ocean as well as inland rivers. Accuracy in the deep ocean is sensitive primarily to bathymetry in areas with high energy dissipation, whereas water level prediction within river networks depends on both bathymetry and resolution. While a minimum resolution in the order of a hundred meters is enough to accurately predict water level for most rivers with tidal influence, smaller tributaries require resolutions down to tens of meters. Future research will use these findings to build precipitation and rainfall-runoff into the model for a more comprehensive understanding of the coastal interface hydrodynamics.

The Rolling Deck to Repository (R2R; www.rvdata.us) program is entering its second decade of managing underway data from US-operated academic research vessels to ensure preservation of, and access to, these national oceanographic research assets. Reflecting on the move from decentralized data submission by chief scientists to an operational centralized facility has brought insights that may inform other communities with distributed networks of data acquisition providers with diverse practices and resources. 4,000 cruises and 100+TB of data later, here are lessons R2R has learned. - Managing data via a central aggregating system where both curation and domain data expertise can be optimally leveraged promotes more complete and efficient data preservation. - Identifying key organizing elements for the data, and implementing persistent identifiers and metadata for those elements, facilitates management and usability. R2R developed authoritative DOIs and standard metadata for cruises to organize R2R data for discoverability and access, and facilitate reciprocal linking to related data in external repositories. When data submissions from diverse providers are heterogeneous, standardizing data at ingest supports data aggregation and synthesis that promote broad data re-use. - Providing tools and expertise to assist with standardization, such as recommended data structures and best practice guidance for data acquisition, reduces heterogenoeus practices over time even when compliance is voluntary. - Developing organized and persistent communication mechanisms with all main stakeholders is central to success. R2R has annual community-level meetings, as well as more frequent individual interactions, with vessel operators/technicians, the NOAA National Centers for Environmental Information staff, and oceanographic research scientists. These communications have been critical to informing high level priorities, overall approaches, and specific technical details and decisions.

The zone of interaction between the Cocos (CO), Caribbean (CA) and North America (NA) plates in Guatemala is defined by the sub-parallel Motagua and Polochic strike-slip faults, a series of north-south-trending extensional grabens immediately south of the Motagua Fault, the Middle America trench, and faults within the Middle America volcanic arc. Historical earthquakes associated with these faults include the destructive 1976 Mw 7.5 earthquake along the Motagua fault and the 2012 Mw 7.5 Champerico thrust earthquake. The latest published GPS-based present-day kinematic model of the region shows that about two-thirds of the strain accumulation from the NA/CA relative motion concentrates on the Motagua fault and one third across the Polochic fault, suggesting that slip varies with time as a result of mechanical interactions within the Motagua-Polochic fault system. As part of the efforts to quantify the present-day kinematics and slip behavior of these faults, we use interferometric synthetic aperture radar (InSAR) to measure the strain rates across faults in Guatemala and to constrain slip partitioning among them. We processed L-band ALOS-1 images spanning from 2006 to 2011, and C-band Sentinel-1 images spanning from 2015 to 2019, from ascending and descending tracks covering the Polochic and Motagua faults, the Ipala and Guatemala City grabens, and part of the volcanic arc to the south. We are using the New Small temporal and spatial baselines (NSBAS) workflow to compute the interferograms, make tropospheric and ionospheric corrections, and perform time-series analysis. We present the first InSAR-based maps of interseismic velocity for this region, which will contribute to the refinement of interseismic locking estimates across the Motagua-Polochic fault system, the subduction zone, and other nearby faults.

Over the last century, relative sea level has risen by more than 1 ft in Annapolis, Maryland. The rise in sea level has resulted in frequent flooding in the City of Annapolis. According to National Oceanic and Atmospheric Administration (NOAA), Annapolis has experienced a 925% increase in flooding days over the past 50 years. This flooding is directly affecting roadway transportation in Annapolis in terms of traffic disruptions, which may result in disconnected mobility among communities, road accidents and travel time delays, just to name a few. This study proposes a general modeling framework to identify roadway segments that are most likely to be flooded and by what depth, due to relative sea level rise and employs the model in the coastal area of Annapolis. To do this, roadway and bridge elevations extracted from LiDAR DEM and DSM respectively, were compared with the annual exceedance probability tide levels provided by NOAA. Roadway segment elevations below the selected tide levels (1%, 10%, and 99%) are considered to be inundated by 100-year, 10-year and 1-year sea level respectively. Results suggest that, out of 36 roadways (excluding local roads) examined, one minor arterial roadway segment may be flooded by a depth ranging from 0.075 inches to 7.22 inches, at a 99% tide level of 2.17 ft (0.66 m). Three minor arterial and one major collector roadway segments may be flooded by a depth ranging from 0.1 inches to 27.3 inches (2.27 ft), at a 10% tide level of 3.84 ft (1.17 m). Three minor arterial, four major collector, and two minor collector roadway segments may be flooded by a depth ranging from 0.002 inches to 52 inches (4.4 ft) at a 1% tide level of 5.97 ft (1.82 m). For the city’s transportation network to become more resilient against sea-level rise, these roadway segments should be prioritized for future capital investment in response to seal level rise.

Eastern Africa contains a well-preserved pedogenic carbonate record, useful for contextualizing the paleoenvironment associated with key fossil and archeological evidence. One significant paleoanthropological discovery from the Turkana Basin in Kenya was Nariokotome Boy, one of the most complete examples of Homo erectus discovered to date. This site is directly associated with a paleo-Vertisol and the Natoo tuff, enabling stratigraphic correlation into outcrop records. Leveraging this opportunity, we analyzed stable isotopes of pedogenic carbonates (n=74) to study the paleoenvironmental conditions in the Turkana Basin for three time slices between 1.9 and 1.2 Ma. We interpret that the narrow range of δ18O values implies the presence of one main water source throughout the time interval. Variation in δ13C, with a standard deviation of 1.5‰ and range of 6.9‰, can thus be considered a function of landscape heterogeneity rather than changing water source. Woody cover estimates from the paleosols within this study interval suggest this area was a wooded grassland despite a significant first-order paleoenvironmental change from a marginal lacustrine environment to a fluvially-dominated one. While our record cannot resolve variability on a millennial scale, the lack of significant long term trends in percent woody cover suggest that Nariokotome Boy and other hominin communities inhabited a paleoenvironment which was relatively stable in terms of vegetation composition despite a major lacustrine regression.

A system capable of reliably detecting catastrophic landslides and centimeter movement in land mass could save lives and offers landowners valuable information about gradual changes in soil displacement on their land. With precise acceleration and relative positioning data collected from an accelerometer and a set of GPS receivers, a system can be designed to detect subtle changes in sensor position due to land movement. With the rapid production of new microprocessors and greater memory storage capabilities the limits of microcontroller systems are continually expanding. The Slide Sentinel project offers landowners a low-cost alternative to commercial equipment consisting of a network of remote low power sensors that detect fast linear slides and eventually lower soil movements such as creep. Long range low-power (LoRa) radio connections on these sensor nodes wirelessly transmit three-dimensional acceleration, Real Time Kinematic (RTK) GPS coordinates, and sudden shift alerts to a common base station where they are exported to an online spreadsheet to be processed remotely.

Human-mediated climate change over the past century has made significant impacts on global ecosystems and biodiversity including accelerating redistribution of the geographic ranges of species. In mountainous regions, the transition zone from continuous closed-canopy subalpine forests to treeless alpine tundra areas at higher elevations is commonly referred to as ‘Alpine Treeline Ecotone’ (ATE). Globally, warming climate is expected to drive the ATE upslope, which could lead to negative impacts on local biodiversity and modify ecosystem function. However, existing studies rely primarily on field-based data which are difficult and time consuming to collect. In this research, we define three critical characteristics of the ATE including 1) an abrupt spatial shift in vegetative activity as elevation varies, 2) reduction in vegetative activity as elevation increases, and 3) vegetative activity is at an intermediate level. Using the geospatial tools provided by Google Earth Engine, we construct an index (ATEI) to identify areas with the three ATE features based on the image gradients of vegetative activity and elevation datasets. Based on the ATEI and Google Earth imagery in 115 Landsat pixels, we establish a Logistic regression model to estimate the probability of whether or not a sampled pixel is located within the ATE. The prediction accuracy is approximately 80%. Furthermore, the ATEI-estimated ATE elevation is strongly correlated (r = 0.96) with a set of field-based data at 20 sampling sites from across the region. Based on the average annual ATEIs from 2009 to 2011, we estimate the average ATE elevation for each mountain range in the western U.S. The result varies from 1,183 m to 3,584 m. The detection metric developed in this study facilitates monitoring the geographic location and potential shifts of ATEs as well as the general impact of climate change in mountainous regions during recent decades. We also expect this approach to be useful in monitoring other ecosystem boundaries.

Spanning a period of more than 15 years, the Landsat Legacy Project Team researched, complied and published, in late 2017, Landsat's Enduring Legacy that describes the myriad of factors that surround the nearly half-century of monitoring the Earth's surface with Landsat. Born of technologies that evolved from the World War II, Landsat not only pioneered global land monitoring but, in the process, drove innovation in digital imaging technologies and encouraged development of global imagery archives. Access to this imagery led to early breakthroughs in natural resources assessments, particularly for agriculture, forestry, and geology. The technical and political aspects of the remote sensing revolution led by Landsat were not simple or straightforward. Early conflicts between civilian and defense satellite remote sensing users gave way to disagreements over whether the Landsat system should be a public service or a private enterprise. Only the combined engagement of civilian and defense organizations ultimately saved this pioneer satellite land monitoring program from termination. With the emergence of 21st century Earth system science research, coupled with greatly enhanced data computing, storage and transfer capabilities, the full value of the Landsat concept and its continuous, calibrated nearly half-century global archive has been recognized and embraced. The attempts to privatize Landsat had dramatic negative impacts on the collection, availability, and use of the data. These impacts should inform deliberations on the future of the Landsat program moving toward a Sustained Land Imaging program following Landsat 9. Discussion of Landsat's future continues, but its heritage will not be forgotten.

This study investigates how marine resource users are impacted by the offshore Block Island Wind Farm (BIWF). In the summer and fall of 2017, we conducted semi-structured interviews with recreational and commercial fishermen that use the area around the BIWF. We asked fishermen about their perceptions of changes in the ecology of the area during and after the offshore wind turbines were constructed, and how their behavior and use of the area changed in response to the construction and post-construction of the wind farm. We interviewed over 20 fishermen, mainly based out of Block Island or Point Judith, Narragansett. Analysis of the interview data suggests that some fishermen view the wind farm as a positive development for fishing in the area, while others have mixed feelings or dislike the project. Perceptions of changes in the BIWF area seem to vary within and among commercial and recreational fishermen. In addition, comparison of interview data with ecological data on fish and lobster in the BIWF area before, during and post-construction highlights areas of agreement and disagreement between perceived and observed changes. These results provide important information on how offshore wind farms in the Northeast are impacting marine resource users in terms of perceived and observed impacts. Open Access Paper: https://www.frontiersin.org/articles/10.3389/fmars.2018.00439/full

Vertical electrical sounding (VES) surveys were performed on the Chukchi Sea ice near Utqiagvik (ne’ Barrow), AK in March, 2018, using a capacitively coupled resistivity array. The purpose of this study was to determine the effectiveness of the VES method in determining the thickness of the sea ice and potentially the depth to the sea floor. The array was deployed in an atypical set-up, with the transmitter and a single receiver being moved incrementally further from a central point. The results of three trials from 2018 are presented, along with the re-analysis of data from two trials from March, 2016. The VES data were analyzed using “cumulative resistivity” plots, from which ice thicknesses were determined. Ice depths were measured by drilling through the ice at the central point of the array. The VES and drill thicknesses agree to within a few percent for the ≲1m-thick ice. The VES plots may also indicate differences in ice composition as it transitions from the solid uppermost ice down to seawater.