Passive microwave derived snowmelt timing: significance, spatial and temporal variability, and potential applications

Snow accumulation and melt are dynamic features of the cryosphere indicative of a changing climate. Spring melt and refreeze timing are of particular importance due to the influence on subsequent hydrological and ecological processes, including peak runoff and green-up. To investigate the spatial and temporal variability of melt timing across a sub-arctic region (the Yukon River Basin (YRB), Alaska/Canada) dominated by snow and lacking substantial ground instrumentation, passive microwave remote sensing was utilized to provide daily brightness temperatures (Tb) regardless of clouds and darkness. Algorithms to derive the timing of melt onset and the end of melt-refreeze, a critical transition period where the snowpack melts during the day and refreezes at night, were based on thresholds for Tb and diurnal amplitude variations (day and night difference). Tb data from the Special Sensor Microwave Imager (1988 to 2011) was used for analyzing YRB terrestrial snowmelt timing and for characterizing melt regime patterns for icefields in Alaska and Patagonia. Tb data from the Advanced Microwave Scanning Radiometer for EOS (2003 to 2010) was used for determining the occurrence of early melt events (before melt onset) associated with fog or rain on snow, for investigating the correlation between melt timing and forest fires, and for driving a flux-based snowmelt runoff model. From the SSM/I analysis: the melt-refreeze period lengthened for the majority of the YRB with later end of melt-refreeze and earlier melt onset; and positive Tb anomalies were found in recent years from glacier melt dynamics. From the AMSR-E analysis: early melt events throughout the YRB were most often associated with warm air intrusions and reflect a consistent spatial distribution; years and areas of earlier melt onset and refreeze had more forest fire occurrences suggesting melt timing\u27s effects extend to later seasons; and satellite derived melt timing served as an effective input for model simulation of discharge in remote, ungauged snow-dominated basins. The melt detection methodology and results present a new perspective on the changing cryosphere, provide an understanding of melt\u27s influence on other earth system processes, and develop a baseline from which to assess and evaluate future change. The temporal and spatial variability conveyed through the regional context of this research may be useful to communities in climate change adaptation planning

Risk Analysis in Setting Allowable Harvests: Annual Catch Limits under the Magnuson Stevens Reauthorization Act

Under the reauthorized Magnuson-Stevens Act (MSRA), US fisheries management councils must specify an annual catch limit (ACL) for each managed species and institute accountability measures (AMs) to ensure that actual harvest will not cause the stock to be overfished. While the details of implementation are still being developed, a set of Proposed Guidelines for performing ACL analysis has been developed. The purpose of this paper is to provide a preliminary assessment of these guidelines. The MSRA specifies two principles to be used as a framework for determining how Councils can comply with the ACL and AM measures. Both deal with uncertainty in the overall fisheries management process. The first is the separation between science and policy in setting the upper level on allowable harvests. The second is the requirement to take strong management actions to ensure that, given real world enforcement issues, the actual harvest in any year does not surpass the allowable harvest level. The procedure for applying the principles is quite complex and it goes beyond a strict interpretation of the written language in the law. However, it is consistent with current procedures and with commonly accepted principles in fisheries management policy. The Proposed Guidelines suggest that a distinction be made between scientific and implementation uncertainty. While the distinction may follow from the two principles, a preliminary look at the logical process of developing the required control rules for specifying Acceptable Biological Catch and Annual Catch Targets raises questions about the usefulness of this distinction in actual policy analysis

The Evaporative Stress Index as an indicator of agricultural drought in Brazil: An assessment based on crop yield impacts

To effectively meet growing food demands, the global agronomic community will require a better understanding of factors that are currently limiting crop yields and where production can be viably expanded with minimal environmental consequences. Remote sensing can inform these analyses, providing valuable spatiotemporal information about yield-limiting moisture conditions and crop response under current climate conditions. In this paper we study correlations for the period 2003-2013 between yield estimates for major crops grown in Brazil and the Evaporative Stress Index (ESI) - an indicator of agricultural drought that describes anomalies in the actual/reference evapotranspiration (ET) ratio, retrieved using remotely sensed inputs of land surface temperature (LST) and leaf area index (LAI). The strength and timing of peak ESI-yield correlations are compared with results using remotely sensed anomalies in water supply (rainfall from the Tropical Rainfall Mapping Mission; TRMM) and biomass accumulation (LAI from the Moderate Resolution Imaging Spectroradiometer; MODIS). Correlation patterns were generally similar between all indices, both spatially and temporally, with the strongest correlations found in the south and northeast where severe flash droughts have occurred over the past decade, and where yield variability was the highest. Peak correlations tended to occur during sensitive crop growth stages. At the state scale, the ESI provided higher yield correlations for most crops and regions in comparison with TRMM and LAI anomalies. Using finer scale yield estimates reported at the municipality level, ESI correlations with soybean yields peaked higher and earlier by 10 to 25 days in comparison to TRMM and LAI, respectively. In most states, TRMM peak correlations were marginally higher on average with municipality-level annual corn yield estimates, although these estimates do not distinguish between primary and late season harvests. A notable exception occurred in the northeastern state of Bahia, where the ESI better captured effects of rapid cycling of moisture conditions on corn yields during a series of flash drought events. The results demonstrate that for monitoring agricultural drought in Brazil, value is added by combining LAI with LST indicators within a physically based model of crop water use. Published by Elsevier Inc.Embrapa Visiting Scientist Program ; Labex US, an international scientific cooperation program - Brazilian Agricultural Research Corporation - Embrapa, ; United States Department of Agriculture (USDA

Bottom trawl fishing footprints on the world’s continental shelves

Publication history: Accepted - 23 August 2018; Published online - 8 October 2018.Bottom trawlers land around 19 million tons of fish and invertebrates annually, almost one-quarter of wild marine landings. The extent of bottom trawling footprint (seabed area trawled at least once in a specified region and time period) is often contested but poorly described. We quantify footprints using high-resolution satellite vessel monitoring system (VMS) and logbook data on 24 continental shelves and slopes to 1,000-m depth over at least 2 years. Trawling footprint varied markedly among regions: from <10% of seabed area in Australian and New Zealand waters, the Aleutian Islands, East Bering Sea, South Chile, and Gulf of Alaska to >50% in some European seas. Overall, 14% of the 7.8 million-km2 study area was trawled, and 86% was not trawled. Trawling activity was aggregated; the most intensively trawled areas accounting for 90% of activity comprised 77% of footprint on average. Regional swept area ratio (SAR; ratio of total swept area trawled annually to total area of region, a metric of trawling intensity) and footprint area were related, providing an approach to estimate regional trawling footprints when highresolution spatial data are unavailable. If SAR was ≤0.1, as in 8 of 24 regions, therewas >95% probability that >90%of seabed was not trawled. If SAR was 7.9, equal to the highest SAR recorded, there was >95% probability that >70% of seabed was trawled. Footprints were smaller and SAR was ≤0.25 in regions where fishing rates consistently met international sustainability benchmarks for fish stocks, implying collateral environmental benefits from sustainable fishing.Funding for meetings of the study group and salary support for R.O.A. were provided by the following: David and Lucile Packard Foundation; the Walton Family Foundation; the Alaska Seafood Cooperative; American Seafoods Group US; Blumar Seafoods Denmark; Clearwater Seafoods Inc.; Espersen Group; Glacier Fish Company LLC US; Gortons Seafood; Independent Fisheries Limited N.Z.; Nippon Suisan (USA), Inc.; Pesca Chile S.A.; Pacific Andes International Holdings, Ltd.; San Arawa, S.A.; Sanford Ltd. N.Z.; Sealord Group Ltd. N.Z.; South African Trawling Association; Trident Seafoods; and the Food and Agriculture Organisation of the United Nations. Additional funding to individual authors was provided by European Union Project BENTHIS EU-FP7 312088 (to A.D.R., O.R.E., F.B., N.T.H., L.B.-M., R.C., H.O.F., H.G., J.G.H., P.J., S.K., M.L., G.G.-M., N.P., P.E.P., T.R., A.S., B.V., and M.J.K.); the Instituto Português do Mar e da Atmosfera, Portugal (C.S.); the International Council for the Exploration of the Sea Science Fund (R.O.A. and K.M.H.); the Commonwealth Scientific and Industrial Research Organisation (C.R.P. and T.M.); the National Oceanic and Atmospheric Administration (R.A.M.); New Zealand Ministry for Primary Industries Projects BEN2012/01 and DAE2010/ 04D (to S.J.B. and R.F.); the Institute for Marine and Antarctic Studies, University of Tasmania and the Department of Primary Industries, Parks, Water and Environment, Tasmania, Australia (J.M.S.); and UK Department of Environment, Food and Rural Affairs Project MF1225 (to S.J.)

Evolution of Protein Kinase R Antagonism in Primate Cytomegaloviruses

Thesis (Ph.D.)--University of Washington, 2016-11During millions of years of coevolution with their hosts, cytomegaloviruses (CMVs) have succeeded in adapting to overcome host-specific immune defenses, including the protein kinase R (PKR) pathway. Consequently, these adaptations may also contribute to the inability of CMVs to cross species barriers. Here, we provide evidence that the evolutionary arms race between the antiviral factor PKR and its CMV antagonist TRS1 has led to extensive differences in the species-specificity of primate CMV TRS1 proteins. Moreover, we identify a single residue in human PKR that when mutated to the amino acid present in Agm PKR (F489S) is sufficient to confer resistance to HCMVTRS1. Notably, this precise molecular determinant of PKR resistance has evolved under strong positive selection among primate PKR alleles and is positioned within the αG helix, which mediates the direct interaction of PKR with its substrate eIF2α. Remarkably, this same residue also impacts sensitivity to K3L, an eIF2α mimic encoded by poxviruses. Unlike K3L, TRS1 has no homology to eIF2α, suggesting that unrelated viral genes have convergently evolved to target this critical region of PKR. Despite its functional importance, the αG helix exhibits extraordinary plasticity, enabling adaptations that allow PKR to evade diverse viral antagonists while still maintaining its critical interaction with eIF2α

Recent ice cap snowmelt in Russian High Arctic and anti-correlation with late summer sea ice extent

Glacier surface melt dynamics throughout Novaya Zemlya (NovZ) and Severnaya Zemlya (SevZ) serve as a good indicator of ice mass ablation and regional climate change in the Russian High Arctic. Here we report trends of surface melt onset date (MOD) and total melt days (TMD) by combining multiple resolution-enhanced active and passive microwave satellite datasets and analyze the TMD correlations with local temperature and regional sea ice extent. The glacier surface snowpack on SevZ melted significantly earlier (−7.3 days/decade) from 1992 to 2012 and significantly longer (7.7 days/decade) from 1995 to 2011. NovZ experienced large interannual variability in MOD, but its annual mean TMD increased. The snowpack melt on NovZ is more sensitive to temperature fluctuations than SevZ in recent decades. After ruling out the regional temperature influence using partial correlation analysis, the TMD on both archipelagoes is statistically anti-correlated with regional late summer sea ice extent, linking land ice snowmelt dynamics to regional sea ice extent variations

Early snowmelt events: detection, distribution, and significance in a major sub-arctic watershed

High latitude drainage basins are experiencing higher average temperatures, earlier snowmelt onset in spring, and an increase in rain on snow (ROS) events in winter, trends that climate models project into the future. Snowmelt-dominated basins are most sensitive to winter temperature increases that influence the frequency of ROS events and the timing and duration of snowmelt, resulting in changes to spring runoff. Of specific interest in this study are early melt events that occur in late winter preceding melt onset in the spring. The study focuses on satellite determination and characterization of these early melt events using the Yukon River Basin (Canada/USA) as a test domain. The timing of these events was estimated using data from passive (Advanced Microwave Scanning Radiometer—EOS (AMSR-E)) and active (SeaWinds on Quick Scatterometer (QuikSCAT)) microwave remote sensors, employing detection algorithms for brightness temperature (AMSR-E) and radar backscatter (QuikSCAT). The satellite detected events were validated with ground station meteorological and hydrological data, and the spatial and temporal variability of the events across the entire river basin was characterized. Possible causative factors for the detected events, including ROS, fog, and positive air temperatures, were determined by comparing the timing of the events to parameters from SnowModel and National Centers for Environmental Prediction North American Regional Reanalysis (NARR) outputs, and weather station data. All melt events coincided with above freezing temperatures, while a limited number corresponded to ROS (determined from SnowModel and ground data) and a majority to fog occurrence (determined from NARR). The results underscore the significant influence that warm air intrusions have on melt in some areas and demonstrate the large temporal and spatial variability over years and regions. The study provides a method for melt detection and a baseline from which to assess future change.Lehigh University and NASA Headquarters under the NASA Earth and Space Science Fellowshi

Comparison of satellite-derived LAI and precipitation anomalies over Brazil with a thermal infrared-based Evaporative Stress Index for 2003–2013

SummaryShortwave vegetation index (VI) and leaf area index (LAI) remote sensing products yield inconsistent depictions of biophysical response to drought and pluvial events that have occurred in Brazil over the past decade. Conflicting reports of severity of drought impacts on vegetation health and functioning have been attributed to cloud and aerosol contamination of shortwave reflectance composites, particularly over the rainforested regions of the Amazon basin which are subject to prolonged periods of cloud cover and episodes of intense biomass burning. This study compares timeseries of satellite-derived maps of LAI from the Moderate Resolution Imaging Spectroradiometer (MODIS) and precipitation from the Tropical Rainfall Mapping Mission (TRMM) with a diagnostic Evaporative Stress Index (ESI) retrieved using thermal infrared remote sensing over South America for the period 2003–2013. This period includes several severe droughts and floods that occurred both over the Amazon and over unforested savanna and agricultural areas in Brazil. Cross-correlations between absolute values and standardized anomalies in monthly LAI and precipitation composites as well as the actual-to-reference evapotranspiration (ET) ratio used in the ESI were computed for representative forested and agricultural regions. The correlation analyses reveal strong apparent anticorrelation between MODIS LAI and TRMM precipitation anomalies over the Amazon, but better coupling over regions vegetated with shorter grass and crop canopies. The ESI was more consistently correlated with precipitation patterns over both landcover types. Temporal comparisons between ESI and TRMM anomalies suggest longer moisture buffering timescales in the deeper rooted rainforest systems. Diagnostic thermal-based retrievals of ET and ET anomalies, such as used in the ESI, provide independent information on the impacts of extreme hydrologic events on vegetation health in comparison with VI and precipitation-based drought indicators, and used in concert may provide a more reliable evaluation of natural and managed ecosystem response to variable climate regimes

Monitoring daily evapotranspiration over two California vineyards using Landsat 8 in a multi-sensor data fusion approach

California\u27s Central Valley grows a significant fraction of grapes used for wine production in the United States. With increasing vineyard acreage, reduced water availability in much of California, and competing water use interests, it is critical to be able to monitor regional water use and evapotranspiration (ET) over large areas, but also in detail at individual field scales to improve water management within these viticulture production systems. This can be achieved by integrating remote sensing data from multiple satellite systems with different spatiotemporal characteristics. In this research, we evaluate the utility of a multi-scale system for monitoring ET as applied over two vineyard sites near Lodi, California during the 2013 growing season, leading into the drought in early 2014. The system employs a multi-sensor satellite data fusion methodology (STARFM: Spatial and Temporal Adaptive Reflective Fusion Model) combined with a multi-scale ET retrieval algorithm based on the Two- Source Energy Balance (TSEB) land-surface representation to compute daily ET at 30mresolution. In this system, TSEB is run using thermal band imagery from the Geostationary Environmental Operational Satellites (GOES; 4- km spatial resolution, hourly temporal sampling), the Moderate Resolution Imaging Spectroradiometer (MODIS) data (1 km resolution, daily acquisition) and the new Landsat 8 satellite (sharpened to 30m resolution, ~16 day acquisition). Estimates of daily ET generated in two neighboring fields of Pinot noir vines of different age agree with ground-based flux measurements acquired in-field during most of the 2013 season with relative mean absolute errors on the order of 19–23% (root mean square errors of approximately 1mmd−1), reducing to 14–20% at the weekly time step relevant for irrigation management (~5 mmwk−1). A model overestimation of ET in the early season was detected in the younger vineyard, perhaps relating to an inter-row grass cover crop. Spatial patterns of cumulative ET generally correspond to measured yield maps and indicate areas of variable crop moisture, soil condition, and yield within the vineyards that could require adaptive management. The results suggest that multi-sensor remote sensing observations provide a unique means for monitoring crop water use and soil moisture status at field-scales over extended growing regions, and may have value in supporting operational water management decisions in vineyards and other high value crops

Melt Patterns and Dynamics in Alaska and Patagonia Derived from Passive Microwave Brightness Temperatures

Glaciers and icefields are critical components of Earth’s cryosphere to study and monitor for understanding the effects of a changing climate. To provide a regional perspective of glacier melt dynamics for the past several decades, brightness temperatures (Tb) from the passive microwave sensor Special Sensor Microwave Imager (SSM/I) were used to characterize melt regime patterns over large glacierized areas in Alaska and Patagonia. The distinctness of the melt signal at 37V-GHz and the ability to acquire daily data regardless of clouds or darkness make the dataset ideal for studying melt dynamics in both hemispheres. A 24-year (1988–2011) time series of annual Tb histograms was constructed to (1) characterize and assess temporal and spatial trends in melt patterns, (2) determine years of anomalous Tb distribution, and (3) investigate potential contributing factors. Distance from coast and temperature were key factors influencing melt. Years of high percentage of positive Tb anomalies were associated with relatively higher stream discharge (e.g., Copper and Mendenhall Rivers, Alaska, USA and Rio Baker, Chile). The characterization of melt over broad spatial domains and a multi-decadal time period offers a more comprehensive picture of the changing cryosphere and provides a baseline from which to assess future change