Quantifying the effects of freeze-thaw transitions and snowpack melt on land surface albedo and energy exchange over Alaska and Western Canada

Variations in land surface albedo and snow-cover strongly impact the global biosphere, particularly through the snow-albedo feedback on climate. The seasonal freeze-thaw (FT) transition is coupled with snowpack melt dynamics and strongly impacts surface water mobility and the energy budget in the northern (≥45°N) arctic and boreal region (ABR). However, understanding of the regional variation in snowmelt and its effect on the surface energy budget are limited due to sparse in situ measurements of these processes and environmental constraints on effective monitoring within the ABR. In this study, we combined synergistic observations from overlapping satellite optical-infrared and microwave sensor records to quantify the regional patterns and seasonal progression in wet snow conditions during the spring snowmelt and autumn snow accumulation periods across Alaska and western Canada. The integrated satellite record included daily landscape FT status from AMSR microwave brightness temperature retrievals; and snow-cover extent, black sky albedo and net shortwave solar radiation (R snet) derived from MODIS and AVHRR observations. The integrated satellite records were analyzed with in situ surface air temperature and humidity observations from regional weather stations over a two-year study period (2015–2016) overlapping with the NASA ABoVE (Arctic Boreal Vulnerability Experiment). Our results show a large (79%) mean decline in land surface albedo between dry snow and snow-free conditions during the spring (March–June) and autumn (August–November) transition periods. Onset of diurnal thawing and refreezing of the surface snow layer and associated wet snow conditions in spring contributed to an approximate 25% decrease in snow cover albedo that extended over a seven to 21 week snowpack depletion period. The lower wet snow albedo enhances R snet by approximately 74% (9–10 MJ m−2 d−1) relative to dry snow conditions, reinforcing snowmelt and surface warming, and contributing to growing season onset and activation of biological and hydrological processes in the ABR. These results contribute to better understanding of snow albedo feedbacks to Arctic amplification, and the representation of these processes in global Earth system models

Rain-on-snow events in Alaska, their frequency and distribution from satellite observations

Wet snow and the icing events that frequently follow wintertime rain-on-snow (ROS) affect high latitude ecosystems at multiple spatial and temporal scales, including hydrology, carbon cycle, wildlife, and human development. However, the distribution of ROS events and their response to climatic changes are uncertain. In this study, we quantified ROS spatiotemporal variability across Alaska during the cold season (November to March) and clarified the influence of precipitation and temperature variations on these patterns. A satellite-based daily ROS geospatial classification was derived for the region by combining remote sensing information from overlapping MODIS and AMSR sensor records. The ROS record extended over the recent satellite record (water years 2003–2011 and 2013–2016) and was derived at a daily time step and 6 km grid, benefiting from finer (500 m) resolution MODIS snow cover observations and coarser (12.5 km) AMSR microwave brightness temperature-based freeze–thaw retrievals. The classification showed favorable ROS detection accuracy (75%–100%) against in situ climate observations across Alaska. Pixel-wise correlation analysis was used to clarify relationships between the ROS patterns and underlying physiography and climatic influences. Our findings indicate that cold season ROS events are most common during autumn and spring months along the maritime Bering Sea coast and boreal interior regions, but are infrequent on the colder arctic North Slope. The frequency and extent of ROS events coincided with warm temperature anomalies (p \u3c 0.1), but showed a generally weaker relationship with precipitation. The weaker precipitation relationship was attributed to several factors, including large uncertainty in cold season precipitation measurements, and the important contribution of humidity and turbulent energy transfer in driving snowmelt and icing events independent of rainfall. Our results suggest that as high latitude temperatures increase, wet snow and ROS events will also increase in frequency and extent, particularly in the southwestern and interior regions of Alaska

Snow Phenology and Hydrologic Timing in the Yukon River Basin, AK, USA

The Yukon River basin encompasses over 832,000 km2 of boreal Arctic Alaska and northwest Canada, providing a major transportation corridor and multiple natural resources to regional communities. The river seasonal hydrology is defined by a long winter frozen season and a snowmelt-driven spring flood pulse. Capabilities for accurate monitoring and forecasting of the annual spring freshet and river ice breakup (RIB) in the Yukon and other northern rivers is limited, but critical for understanding hydrologic processes related to snow, and for assessing flood-related risks to regional communities. We developed a regional snow phenology record using satellite passive microwave remote sensing to elucidate interactions between the timing of upland snowmelt and the downstream spring flood pulse and RIB in the Yukon. The seasonal snow metrics included annual Main Melt Onset Date (MMOD), Snowoff (SO) and Snowmelt Duration (SMD) derived from multifrequency (18.7 and 36.5 GHz) daily brightness temperatures and a physically-based Gradient Ratio Polarization (GRP) retrieval algorithm. The resulting snow phenology record extends over a 29-year period (1988–2016) with 6.25 km grid resolution. The MMOD retrievals showed good agreement with similar snow metrics derived from in situ weather station measurements of snowpack water equivalence (r = 0.48, bias = −3.63 days) and surface air temperatures (r = 0.69, bias = 1 day). The MMOD and SO impact on the spring freshet was investigated by comparing areal quantiles of the remotely sensed snow metrics with measured streamflow quantiles over selected sub-basins. The SO 50% quantile showed the strongest (p \u3c 0.1) correspondence with the measured spring flood pulse at Stevens Village (r = 0.71) and Pilot (r = 0.63) river gaging stations, representing two major Yukon sub-basins. MMOD quantiles indicating 20% and 50% of a catchment under active snowmelt corresponded favorably with downstream RIB (r = 0.61) from 19 river observation stations spanning a range of Yukon sub-basins; these results also revealed a 14–27 day lag between MMOD and subsequent RIB. Together, the satellite based MMOD and SO metrics show potential value for regional monitoring and forecasting of the spring flood pulse and RIB timing in the Yukon and other boreal Arctic basins

Loops under Strategies ... Continued

While there are many approaches for automatically proving termination of term rewrite systems, up to now there exist only few techniques to disprove their termination automatically. Almost all of these techniques try to find loops, where the existence of a loop implies non-termination of the rewrite system. However, most programming languages use specific evaluation strategies, whereas loop detection techniques usually do not take strategies into account. So even if a rewrite system has a loop, it may still be terminating under certain strategies. Therefore, our goal is to develop decision procedures which can determine whether a given loop is also a loop under the respective evaluation strategy. In earlier work, such procedures were presented for the strategies of innermost, outermost, and context-sensitive evaluation. In the current paper, we build upon this work and develop such decision procedures for important strategies like leftmost-innermost, leftmost-outermost, (max-)parallel-innermost, (max-)parallel-outermost, and forbidden patterns (which generalize innermost, outermost, and context-sensitive strategies). In this way, we obtain the first approach to disprove termination under these strategies automatically.Comment: In Proceedings IWS 2010, arXiv:1012.533

Synergistic Catalysis in Heterobimetallic Complexes for Homogeneous Carbon Dioxide Hydrogenation

Two heterobimetallic Mo,M’ complexes (M’ = IrIII, RhIII) were synthesized and fully characterized. Their catalytic activity in homogeneous carbon dioxide hydrogenation to formate was studied. A pronounced synergistic effect between the two metals was found, most notably between Mo and Ir, leading to a fourfold increase in activity compared with a binary mixture of the two monometallic counterparts. This synergism can be attributed to spatial proximity of the two metals rather than electronic interactions. To further understand the nature of this interaction, the mechanism of the CO2 hydrogenation to formate by a monometallic IrIII catalyst was studied using computational and spectroscopic methods. The resting state of the reaction was found to be the metal-base adduct, whereas the rate-determining step is the inner-sphere hydride transfer to CO2. Based on these findings, the synergism in the heterobimetallic complex is beneficial in this key step, most likely by further activating the CO2

Geometry of River Networks II: Distributions of Component Size and Number

The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length-scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.Comment: 16 pages, 13 figures, 4 tables, Revtex4, submitted to PR

Integrating snow science and wildlife ecology in Arctic-boreal North America

Snow covers Arctic and boreal regions (ABRs) for approximately 9 months of the year, thus snowscapes dominate the form and function of tundra and boreal ecosystems. In recent decades, Arctic warming has changed the snowcover\u27s spatial extent and distribution, as well as its seasonal timing and duration, while also altering the physical characteristics of the snowpack. Understanding the little studied effects of changing snowscapes on its wildlife communities is critical. The goal of this paper is to demonstrate the urgent need for, and suggest an approach for developing, an improved suite of temporally evolving, spatially distributed snow products to help understand how dynamics in snowscape properties impact wildlife, with a specific focus on Alaska and northwestern Canada. Via consideration of existing knowledge of wildlife-snow interactions, currently available snow products for focus region, and results of three case studies, we conclude that improving snow science in the ABR will be best achieved by focusing efforts on developing data-model fusion approaches to produce fit-for-purpose snow products that include, but are not limited to, wildlife ecology. The relative wealth of coordinated in situ measurements, airborne and satellite remote sensing data, and modeling tools being collected and developed as part of NASA\u27s Arctic Boreal Vulnerability Experiment and SnowEx campaigns, for example, provide a data rich environment for developing and testing new remote sensing algorithms and retrievals of snowscape properties

Unified View of Scaling Laws for River Networks

Scaling laws that describe the structure of river networks are shown to follow from three simple assumptions. These assumptions are: (1) river networks are structurally self-similar, (2) single channels are self-affine, and (3) overland flow into channels occurs over a characteristic distance (drainage density is uniform). We obtain a complete set of scaling relations connecting the exponents of these scaling laws and find that only two of these exponents are independent. We further demonstrate that the two predominant descriptions of network structure (Tokunaga's law and Horton's laws) are equivalent in the case of landscapes with uniform drainage density. The results are tested with data from both real landscapes and a special class of random networks.Comment: 14 pages, 9 figures, 4 tables (converted to Revtex4, PRE ref added

Tyrosine-Phosphorylated Caveolin-1 Blocks Bacterial Uptake by Inducing Vav2-RhoA-Mediated Cytoskeletal Rearrangements

During the early stages of infection, Neisseria gonorrhoeae triggers a phosphotyrosine-dependent Cav1-Vav2-RhoA signaling cascade that promotes the pathogen's extracellular state