Spatial and temporal patterns in Arctic river ice breakup revealed by automated ice detection from MODIS imagery

The annual spring breakup of river ice has important consequences for northern ecosystems and significant economic implications for Arctic industry and transportation. River ice breakup research is restricted by the sparse distribution of hydrological stations in the Arctic, where limited available data suggests a trend towards earlier ice breakup. The specific climatic mechanisms driving this trend, however, are complex and can vary both regionally and within river systems. Consequently, understanding the response of river ice processes to a warming Arctic requires simultaneous examination of spatial and temporal patterns in breakup timing. In this paper, we describe an automated algorithm for river ice breakup detection using MODIS satellite imagery that enables identification of spatial and temporal breakup patterns at large scales. We examine breakup timing on the Mackenzie, Lena, Ob' and Yenisey rivers for the period 2000-2014. By dividing the rivers into 10 km segments and classifying each river pixel in each segment as snow/ice, mixed ice/water or open water based on MODIS reflectance, we determine breakup dates with a mean uncertainty of ±. 1.3 days. All statistically significant temporal trends are negative, indicating an overall shift towards earlier breakup. Considerable variability in the statistical significance and magnitude of trends along each river suggests that different climatic and physiographic drivers are impacting spatial patterns in breakup. Trends detected on the lower Mackenzie corroborate recent studies indicating weakening ice resistance and earlier breakup timing near the Mackenzie Delta. In Siberia, the increased magnitude of trends upstream and strong correlation between breakup initiation and whole-river breakup patterns suggest that earlier onset of upstream discharge may play the dominant role in determining breakup timing. Exploratory analysis demonstrates that MODIS imagery may also be used to differentiate thermal and mechanical breakup events

Global Characterization of Inland Water Reservoirs Using ICESat-2 Altimetry and Climate Reanalysis

Accurate, transparent knowledge of global reservoir levels is a prerequisite for effective management of water resources. However, no complete database exists because gauge data are not globally available and the current generation of satellite radar altimeters resolves only the world's largest reservoirs. Here, we investigate water level changes in global reservoirs using ICESat-2, National Aeronautics and Space Administration (NASA)'s new satellite laser altimetry mission. In just the first 12 months of the mission, we find that ICESat-2 accurately (±14.1 cm) retrieved water level changes for 3,712 global reservoirs having surface areas ranging from <1 to >10,000 km2. From this new global data set, we identify distinct regional patterns in reservoir level change that can be attributed to both water availability and management strategy. Our findings demonstrate that ICESat-2 will form a crucial component of any global reservoir level inventory and enable new insight into how reservoir management responds to climatic variability and increasing human demand

Arctic-Boreal Lake Dynamics Revealed Using CubeSat Imagery

Fine-scale, subseasonal fluctuations in Arctic-Boreal surface water reflect regional water balance and modulate trace gas emissions to the atmosphere but have eluded detection using traditional satellite remote sensing. We use high-resolution (~3–5 m), high-frequency CubeSat sensors to measure near-daily changes in lake surface area through an object-based tracking method that incorporates machine learning to overcome notable limitations of CubeSat imagery. From ~76,000 images we obtain >2.2 million individual observations of changing surface areas for 85,358 lakes in Northern Canada and Alaska between 1 May and 1 October 2017. We find broad-scale lake area declines across diverse climatic, hydrologic, and physiographic terrains. Localized exceptions reveal lowland flooding and aquatic vegetation phenology cycles. Cumulative small shoreline changes of abundant lakes on the Canadian Shield exceed total inundation variations of better-studied lowland environments, revealing a surprisingly dynamic landscape with respect to subseasonal variations in surface water extent and trace gas emissions

To think or to do: the impact of assessment and locomotion orientation on the Michelangelo phenomenon

This work examines how individual differences in assessment and locomotion shape goal pursuits in ongoing relationships. The Michelangelo phenomenon describes the role that close partners play in affirming versus disaffirming one another's pursuit of the ideal self. Using data from a longitudinal study of ideal goal pursuits among newly committed couples, we examined whether the action orientation that characterizes locomotion creates an optimal environment in which to give and receive affirmation, whereas the evaluative orientation that characterizes assessment creates a suboptimal environment for giving and receiving affirmation. Consistent with hypotheses, locomotion is positively associated with partner affirmation, movement toward the ideal self, and couple wellbeing, whereas parallel associations with assessment are negative. We also explore the behavioral mechanisms that may account for such associations

Airborne observations of arctic-boreal water surface elevations from AirSWOT Ka-Band InSAR and LVIS LiDAR

AirSWOT is an experimental airborne Ka-band radar interferometer developed by NASA-JPL as a validation instrument for the forthcoming NASA Surface Water and Ocean Topography (SWOT) satellite mission. In 2017, AirSWOT was deployed as part of the NASA Arctic Boreal Vulnerability Experiment (ABoVE) to map surface water elevations across Alaska and western Canada. The result is the most extensive known collection of near-nadir airborne Ka-band interferometric synthetic aperture radar (InSAR) data and derivative high-resolution (3.6 m pixel) digital elevation models to produce water surface elevation (WSE) maps. This research provides a synoptic assessment of the 2017 AirSWOT ABoVE dataset to quantify regional WSE errors relative to coincident in situ field surveys and LiDAR data acquired from the NASA Land, Vegetation, and Ice Sensor (LVIS) airborne platform. Results show that AirSWOT WSE data can penetrate cloud cover and have nearly twice the swath-width of LVIS as flown for ABoVE (3.2 km vs. 1.8 km nominal swath-width). Despite noise and biases, spatially averaged AirSWOT WSEs can be used to estimate sub-seasonal hydrologic variability, as confirmed with field GPS surveys and in situ pressure transducers. This analysis informs AirSWOT ABoVE data users of known sources of measurement error in the WSEs as influenced by radar parameters including incidence angle, magnitude, coherence, and elevation uncertainty. The analysis also provides recommended best practices for extracting information from the dataset by using filters for these four parameters. Improvements to data handing would significantly increase the accuracy and spatial coverage of future AirSWOT WSE data collections, aiding scientific surface water studies, and improving the platform’s capability as an airborne validation instrument for SWOT

AirSWOT InSAR Mapping of Surface Water Elevations and Hydraulic Gradients Across the Yukon Flats Basin, Alaska

AirSWOT, an experimental airborne Ka-band interferometric synthetic aperture radar, was developed for hydrologic research and validation of the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission (to be launched in 2021). AirSWOT and SWOT aim to improve understanding of surface water processes by mapping water surface elevation (WSE) and water surface slope (WSS) in rivers, lakes, and wetlands. However, the utility of AirSWOT for these purposes remains largely unexamined. We present the first investigation of AirSWOT WSE and WSS surveys over complex, low-relief, wetland-river hydrologic environments, including (1) a field-validated assessment of AirSWOT WSE and WSS precisions for lakes and rivers in the Yukon Flats Basin, an Arctic-Boreal wetland complex in eastern interior Alaska; (2) improved scientific understanding of surface water flow gradients and the influence of subsurface permafrost; and (3) recommendations for improving AirSWOT precisions in future scientific and SWOT validation campaigns. AirSWOT quantifies WSE with an RMSE of 8 and 15 cm in 1 and 0.0625 km2 river reaches, respectively, and 21 cm in lakes. This indicates good utility for studying hydrologic flux, WSS, geomorphic processes, and coupled surface/subsurface hydrology in permafrost environments. This also suggests that AirSWOT supplies sufficient precision for validating SWOT WSE and WSS over rivers, but not lakes. However, improvements in sensor calibration and flight experiment design may improve precisions in future deployments as may modifications to data processing. We conclude that AirSWOT is a useful tool for bridging the gap between field observations and forthcoming global SWOT satellite products

A high-resolution airborne color-infrared camera water mask for the NASA ABoVE campaign

The airborne AirSWOT instrument suite, consisting of an interferometric Ka-band synthetic aperture radar and color-infrared (CIR) camera, was deployed to northern North America in July and August 2017 as part of the NASA Arctic-Boreal Vulnerability Experiment (ABoVE).We present validated, open (i.e., vegetation-free) surface water masks produced from high-resolution (1 m), co-registered AirSWOT CIR imagery using a semi-automated, object-based water classification. The imagery and resulting high-resolution water masks are available as open-access datasets and support interpretation of AirSWOT radar and other coincident ABoVE image products, including LVIS, UAVSAR, AIRMOSS, AVIRIS-NG, and CFIS. These synergies offer promising potential for multi-sensor analysis of Arctic-Boreal surface water bodies. In total, 3167 km2 of open surface water were mapped from 23,380 km2 of flight lines spanning 23 degrees of latitude and broad environmental gradients. Detected water body sizes range from 0.00004 km2 (40 m2) to 15 km2. Power-law extrapolations are commonly used to estimate the abundance of small lakes from coarser resolution imagery, and our mapped water bodies followed power-law distributions, but only for water bodies greater than 0.34 (±0.13) km2 in area. For water bodies exceeding this size threshold, the coefficients of power-law fits vary for different Arctic-Boreal physiographic terrains (wetland, prairie pothole, lowland river valley, thermokarst, and Canadian Shield). Thus, direct mapping using high-resolution imagery remains the most accurate way to estimate the abundance of small surface water bodies. We conclude that empirical scaling relationships, useful for estimating total trace gas exchange and aquatic habitats on Arctic-Boreal landscapes, are uniquely enabled by high-resolution AirSWOT-like mappings and automated detection methods such as those developed here

Muon Track Reconstruction and Data Selection Techniques in AMANDA

The Antarctic Muon And Neutrino Detector Array (AMANDA) is a high-energy neutrino telescope operating at the geographic South Pole. It is a lattice of photo-multiplier tubes buried deep in the polar ice between 1500m and 2000m. The primary goal of this detector is to discover astrophysical sources of high energy neutrinos. A high-energy muon neutrino coming through the earth from the Northern Hemisphere can be identified by the secondary muon moving upward through the detector. The muon tracks are reconstructed with a maximum likelihood method. It models the arrival times and amplitudes of Cherenkov photons registered by the photo-multipliers. This paper describes the different methods of reconstruction, which have been successfully implemented within AMANDA. Strategies for optimizing the reconstruction performance and rejecting background are presented. For a typical analysis procedure the direction of tracks are reconstructed with about 2 degree accuracy.Comment: 40 pages, 16 Postscript figures, uses elsart.st

Results from the Antarctic Muon and Neutrino Detector Array (AMANDA)

We show new results from both the older and newer incarnations of AMANDA (AMANDA-B10 and AMANDA-II, respectively). These results demonstrate that AMANDA is a functioning, multipurpose detector with significant physics and astrophysics reach. They include a new higher-statistics measurement of the atmospheric muon neutrino flux and preliminary results from searches for a variety of sources of ultrahigh energy neutrinos: generic point sources, gamma-ray bursters and diffuse sources producing muons in the detector, and diffuse sources producing electromagnetic or hadronic showers in or near the detector.Comment: Invited talk at the XXth International Conference on Neutrino Physics and Astrophysics (Neutrino 2002), Munich, Germany, May 25-30, 200

On the selection of AGN neutrino source candidates for a source stacking analysis with neutrino telescopes

The sensitivity of a search for sources of TeV neutrinos can be improved by grouping potential sources together into generic classes in a procedure that is known as source stacking. In this paper, we define catalogs of Active Galactic Nuclei (AGN) and use them to perform a source stacking analysis. The grouping of AGN into classes is done in two steps: first, AGN classes are defined, then, sources to be stacked are selected assuming that a potential neutrino flux is linearly correlated with the photon luminosity in a certain energy band (radio, IR, optical, keV, GeV, TeV). Lacking any secure detailed knowledge on neutrino production in AGN, this correlation is motivated by hadronic AGN models, as briefly reviewed in this paper. The source stacking search for neutrinos from generic AGN classes is illustrated using the data collected by the AMANDA-II high energy neutrino detector during the year 2000. No significant excess for any of the suggested groups was found.Comment: 43 pages, 12 figures, accepted by Astroparticle Physic