scholarly journals Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast

2021 ◽  
Vol 170 ◽  
pp. 595-612
Author(s):  
Gabriel García-Medina ◽  
Zhaoqing Yang ◽  
Wei-Cheng Wu ◽  
Taiping Wang
Keyword(s):  
High Resolution ◽  
The U.S

https://fisheries.org/doi/9781934874301-ch19

2012 ◽  
Keyword(s):  
Ecosystem Services ◽  
High Resolution ◽  
Fisheries Management ◽  
Human Activities ◽  
Gulf Of Maine ◽  
Energy Development ◽  
Benthic Habitat ◽  
Important Species ◽  
Seafloor Mapping ◽  
The U.S

<i>Abstract</i> .—The Gulf of Maine’s seafloor provides a wide array of valuable ecosystem services, including provision of habitat for commercially and ecologically important mammals, seabirds, fish, and invertebrates. Implementing ecosystem-based management will require improved information about the habitats of economically and ecologically important species and the impacts of different human activities, such as fish harvesting, offshore energy development, and shipping, to balance these competing needs. Currently, there is limited high resolution seabed substrate information in the Gulf of Maine, especially in the U.S. portion, because of the high cost of multi-beam echo sounder surveys. Moreover, this lack of coverage limits the ability of managers to use seafloor substrate information in ecosystem management activities, such as fisheries management, that require more holistic coverage of the bioregion. Therefore, the potential need for seafloor mapping in this region is enormous given the value of accurate seafloor information to managers in charge of minimizing impacts to and sustaining the ecosystem services provided by benthic habitat in the Gulf of Maine.

A High-Resolution Regional Wave Resource Characterization for the U.S. West Coast

2020 ◽  
Author(s):  
Taiping Wang ◽  
Zhaoqing Yang ◽  
Fadia Marion Ticona Rollano ◽  
Wei-Cheng Wu ◽  
Gabriel García-Medina
Keyword(s):  
High Resolution ◽  
West Coast ◽  
The U.S

scholarly journals Market-Driven Corn Monocropping in the U.S. Midwest

2019 ◽  
Vol 48 (02) ◽  
pp. 274-296 ◽  
Author(s):  
Haoying Wang ◽  
Ariel Ortiz-Bobea
Keyword(s):  
Environmental Policy ◽  
High Resolution ◽  
Land Cover ◽  
Crop Rotation ◽  
Aggregate Data ◽  
Market Returns ◽  
Land Cover Data ◽  
Price Shock ◽  
Market Driven ◽  
The U.S

This study examines the market drivers of corn monocropping in the U.S. Midwest by empirically analyzing crop rotation responses to market fluctuation from 2005 to 2014 and the price shock induced by the recent biofuel mandate. We find that the expected market returns for crops have a significant impact on farmers' decisions about monocropping. We also find that corn monocropping is loosely associated with the presence of nearby ethanol plants. This study illustrates the emerging use of high-resolution land cover data to tackle critical agribusiness and agro-environmental policy questions that remain elusive with aggregate data.

scholarly journals Impact of Anthropogenic Climate Change on United States Major Hurricane Landfall Frequency

2019 ◽  
Vol 7 (5) ◽  
pp. 135 ◽  
Author(s):  
Emma L. Levin ◽  
Hiroyuki Murakami
Keyword(s):  
Climate Change ◽  
United States ◽  
High Resolution ◽  
The United States ◽  
Anthropogenic Climate Change ◽  
Buffer System ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Long Duration ◽  
Major Hurricane ◽  
The U.S

Although anthropogenic climate change has contributed to warmer ocean temperatures that are seemingly more favorable for Atlantic hurricane development, no major hurricanes made landfall in the United States between 2006 and 2016. The U.S., therefore, experienced a major hurricane landfall drought during those years. Using the high-resolution Geophysical Fluid Dynamics Laboratory 25 km grid High-Resolution Forecast-Oriented Low Ocean Resolution (HiFLOR) global climate model, the present study shows that increases in anthropogenic forcing, due to increases in greenhouse gasses, are associated with fewer long-duration major hurricane landfall droughts in the U.S., which implies an increase in major hurricane landfall frequency. We create six different fixed-distance ‘buffers’ that artificially circle the United States coastline in 100 km radial increments and can compensate for the bias in hurricane landfall calculations with six-hourly datasets. Major hurricane landfall frequencies are computed by applying the buffer zones to the six-hourly observed and simulated storm track datasets, which are then compared with the observed recorded major hurricane frequencies. We found that the major hurricane landfall frequencies generated with the 200 km buffer using the six-hourly observed best-track dataset are most correlated with the observed recorded major hurricane landfall frequencies. Using HiFLOR with an implemented buffer system, we found less frequent projections of long-duration major hurricane landfall drought events in controlled scenarios with greater anthropogenic global warming, which is independent on the radius of the coastal buffer. These results indicate an increase in U.S. major hurricane landfall frequencies with an increase in anthropogenic warming, which could pose a substantial threat to coastal communities in the U.S.

The Common Community Physics Package (CCPP): bridging the gap between research and operations to improve U.S. numerical weather prediction capabilities

2020 ◽  
Author(s):  
Dom Heinzeller ◽  
Grant Firl ◽  
Ligia Bernardet ◽  
Laurie Carson ◽  
Man Zhang ◽  
...  
Keyword(s):  
High Resolution ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Modeling Framework ◽  
Initial Development ◽  
Numerical Weather ◽  
Computational Performance ◽  
The Common ◽  
The U.S ◽  
Physical Parameterizations

&lt;p&gt;Improving numerical weather prediction systems depends critically on the ability to transition innovations from research to operations (R2O) and to provide feedback from operations to research (O2R). This R2O2R cycle, sometimes referred to as &quot;crossing the valley of death&quot;, has long been identified as a major challenge for the U.S. weather enterprise.&lt;/p&gt;&lt;p&gt;As part of a broader effort to bridge this gap and advance U.S. weather prediction capabilities, the Developmental Testbed Center (DTC) with staff at NOAA and NCAR has developed the Common Community Physics Package (CCPP) for application in NOAA's Unified Forecasting System (UFS). The CCPP consists of a library of physical parameterizations and a framework, which interfaces the physics with atmospheric models based on metadata information and standardized interfaces. The CCPP physics library contains physical parameterizations from the current operational U.S. global, mesoscale and high-resolution models, future implementation candidates, and additional physics from NOAA, NCAR and other organizations. The range of physics options in the CCPP physics library enables the application of the UFS - as well as every other model using the CCPP - across scales, from now-casting to seasonal and from high-resolution regional to global ensembles.&lt;/p&gt;&lt;p&gt;While the initial development of the CCPP was centered around the FV3 (Finite-Volume Cubed-Sphere) dynamical core of the UFS, its focus has since widened. The CCPP is also used by the DTC Single Column Model to support a hierarchical testing strategy, and by the next generation NEPTUNE (Navy Environmental Prediction sysTem Utilizing the Numa corE) model of the Naval Research Laboratory. Further, and most importantly, NOAA and NCAR recently signed an agreement to jointly develop the CCPP framework as a single, standardized way to interface physics with their models of the atmosphere (and other compartments of the Earth system). This places the CCPP in the heart of several of the U.S. flagship models and opens the door for bringing innovations from a large research community into operations.&lt;/p&gt;&lt;p&gt;In this contribution, we will present a brief overview of the concept of the CCPP, its technical design and the requirements for parameterizations to be considered as CCPP-compliant. We will describe the integration of CCPP in the UFS and touch upon the challenges in creating a flexible modeling framework while maintaining high computational performance. We will also provide information on how to obtain, use and contribute to the CCPP, as well as on the future development of the CCPP framework and upcoming additions to the CCPP physics library.&lt;/p&gt;

Deciphering Holocene sea-level history on the U.S. Gulf Coast: A high-resolution record from the Mississippi Delta

2004 ◽  
Vol 116 (7) ◽  
pp. 1026 ◽  
Author(s):  
Torbjörn E. Törnqvist ◽  
Juan L. González ◽  
Lee A. Newsom ◽  
Klaas van der Borg ◽  
Arie F.M. de Jong ◽  
...  
Keyword(s):  
High Resolution ◽  
Sea Level ◽  
Mississippi Delta ◽  
Gulf Coast ◽  
The U.S ◽  
Holocene Sea Level

Perspective on Advancing FDA Regulatory Monitoring for Mycotoxins in Foods using Liquid Chromatography and Mass Spectrometry (Review)

2016 ◽  
Vol 99 (4) ◽  
pp. 890-894 ◽  
Author(s):  
Kai Zhang ◽  
Jon W Wong ◽  
Alexander J Krynitsky ◽  
Mary W Trucksess
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Food Safety ◽  
High Resolution ◽  
Drug Administration ◽  
Matrix Effects ◽  
Tandem Ms ◽  
Mycotoxin Analysis ◽  
Lc Tandem Ms ◽  
The U.S

Abstract The presence of mycotoxins (such as aflatoxins, deoxynivalenol, fumonisins, and patulin) is routinely monitored by the U.S. Food and Drug Administration (FDA) to ensure that their concentrations in food are below the levels requiring regulatory action or advisories. To improve the efficiency of mycotoxin analysis, the researchers at the FDA's Center for Food Safety and Applied Nutrition have been evaluating modern LC-MS technologies. Consequently, a variety of LC–tandem MS and LC–high-resolution MS methods have been developed, which simultaneously identify and quantitate multiple mycotoxins in foods and feeds. Although matrix effects (matrix-induced ion suppression or enhancement) associated with LC-MS-based mycotoxin analysis remain, this review discusses methods for managing these effects and proposes practical solutions for the future implementation of LC-MS-based multimycotoxin analysis.

scholarly journals State of the Science: Screening, Surveillance, and Epidemiology of HPV-Related Malignancies

2021 ◽  
pp. 1-12
Author(s):  
Rahel Ghebre ◽  
J. Michael Berry-Lawhorn ◽  
Gypsyamber D’Souza
Keyword(s):  
Cervical Cancer ◽  
Cancer Screening ◽  
High Resolution ◽  
Cervical Cancer Screening ◽  
Task Force ◽  
Hpv Vaccination ◽  
Cancer Society ◽  
Screening Guidelines ◽  
Cancer Precursors ◽  
The U.S

Oropharyngeal, cervical, vulvar, and anal cancers share a common risk factor of HPV infection. HPV vaccination is currently recommended at age 11 or 12 to prevent new HPV infections for all genders with catch-up vaccination recommened up to age 26. Despite the known effectiveness of HPV vaccination to prevent HPV-related cancer, there is continued low uptake in the United States; only 40% of eligible persons were vaccinated in 2018, though rates are 70% among teenagers. Current American Cancer Society cancer screening guidelines recommend cervical cancer screening, but do not have specific recommendations for screening for other HPV-related cancers. Oropharyngeal cancer precursors have yet to be identified, and there are currently no routine screening tests for oropharyngeal cancer recommended by the U.S. Preventive Services Task Force. The U.S. Preventive Services Task Force and American Cancer Society recommend cervical cancer screening for women at average risk up to age 65, and screening guidelines do not currently differ by HPV vaccination status. Primary HPV DNA testing was first approved for cervical cancer screening in 2016 and was shown to be superior for cervical cancer prevention. Vulvar and anal cancer precursors have been identified, but optimal screening remains unclear. Examination of the anal canal and perianus is best performed by trained clinicians using high-resolution anoscopy, and effectiveness of using high-resolution anoscopy to detect and treat anal high-grade squamous intraepithelial lesions to prevent cancer is actively being researched. Current multistep approaches to control HPV-related malignancies include HPV vaccination coupled with cervical cancer screening or surveillance for oropharyngeal, vulvar, and anal cancers.

A Comparison of the U.S. Climate Reference Network Precipitation Data to the Parameter-Elevation Regressions on Independent Slopes Model (PRISM)

2020 ◽  
Vol 21 (10) ◽  
pp. 2391-2400
Author(s):  
Michael S. Buban ◽  
Temple R. Lee ◽  
C. Bruce Baker
Keyword(s):  
United States ◽  
Soil Moisture ◽  
High Resolution ◽  
The United States ◽  
Reference Network ◽  
Socioeconomic Impacts ◽  
Surface Precipitation ◽  
Using Data ◽  
Elevation Model ◽  
The U.S

AbstractSince drought and excessive rainfall can have significant socioeconomic impacts, it is important to have accurate high-resolution gridded datasets that can help improve analysis and forecasting of these conditions. One such widely used dataset is the Parameter-Elevation Regressions on Independent Slopes Model (PRISM). PRISM uses a digital elevation model (DEM) to obtain gridded elevation analyses and then uses a regression analysis along with approximately 15 000 surface precipitation measurements to produce a 4-km resolution daily precipitation product over the conterminous United States. The U.S. Climate Reference Network (USCRN) consists of 114 stations that take highly accurate meteorological measurements across all regions of the United States. A comparison between the USCRN and PRISM was performed using data from 2006 to 2018. There were good comparisons between the two datasets across nearly all seasons and regions; most mean daily differences were <1 mm, with most absolute daily differences ~5 mm. The most general characteristics were for a net dry bias in the PRISM data in the Southwest and a net moist bias in the southern United States. Verifying the PRISM dataset provides us with confidence it can be used with estimates of evapotranspiration, high-resolution gridded soil properties, and vegetation datasets to produce a daily gridded soil moisture product for operational use in the analyses and prediction of drought and excessive soil moisture conditions.

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