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The monitoring of water colour parameters can provide an important diagnostic tool for the assessment of aquatic ecosystem condition. Remote sensing has long been used to effectively monitor chlorophyll concentrations in open ocean systems; however, operational monitoring in coastal and estuarine areas has been limited because of the inherent complexities of coastal systems, and the coarse spectral and spatial resolutions of available satellite systems. Data were collected using the National Aeronautics and Space Administration (NASA) Advanced Visible-Infrared Imaging Spectrometer (AVIRIS) flown at an altitude of approximately 20 000 m to provide hyperspectral imagery and simulate both MEdium Resolution Imaging Spectrometer (MERIS) and Moderate Resolution Imaging Spectrometer (MODIS) data. AVIRIS data were atmospherically corrected using a radiative transfer modelling approach and analysed using band ratio and linear regression models. Regression analysis was performed with simultaneous field measurements data in the Neuse River Estuary (NRE) and Pamlico Sound on 15 May 2002. Chlorophyll a (Chl a) concentrations were optimally estimated using AVIRIS bands (9.5 nm) centred at 673.6 and 692.7 nm, resulting in a coefficient of determination (R 2) of 0.98. Concentrations of Chromophoric Dissolved Organic Matter (CDOM), Total Suspended Solids (TSS) and Fixed Suspended Solids (FSS) were also estimated, resulting in coefficients of determination of R 2 = 0.90, 0.59 and 0.64, respectively. Ratios of AVIRIS bands centred at or near those corresponding to the MERIS and MODIS sensors indicated that relatively good satellite-based estimates could potentially be derived for water colour constituents at a spatial resolution of 300 and 500 m, respectively. [ABSTRACT FROM AUTHOR]

A comparison of the statistics of daily precipitation over the conterminous United States is carried out using gridded station data and three generations of reanalysis products in use at the National Centers for Environmental Prediction (NCEP). The reanalysis products are the NCEP–NCAR reanalysis (Kalnay et al.), the NCEP–Department of Energy (DOE) reanalysis (Kanamitsu et al.), and the NCEP Climate Forecast System (CFS) reanalysis (Saha et al.). Several simple measures are used to characterize relationships between the observations and the reanalysis products, including bias, precipitation probability, variance, and correlation. Seasonality is accounted for by examining these measures for four nonoverlapping seasons, using daily data in each case. Relationships between daily precipitation and El Niño–Southern Oscillation (ENSO) phase are also considered. It is shown that the CFS reanalysis represents a clear improvement over the earlier reanalysis products, though significant biases remain. Comparisons of the error patterns in the reanalysis products provide a suitable basis for confident conversion of the Climate Prediction Center (CPC) operational monitoring and prediction products to the new generation of analyses based on CFS. [ABSTRACT FROM AUTHOR]

Introduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a significant challenge due to the ephemeral nature of defoliation events. Using the 2016 gypsy moth (Lymantria dispar) outbreak in Southern New England as a case study, we present a new approach for near-real-time defoliation monitoring using synthetic images produced from Landsat time series. By comparing predicted and observed images, we assessed changes in vegetation condition multiple times over the course of an outbreak. Initial measures can be made as imagery becomes available, and season-integrated products provide a wall-to-wall assessment of potential defoliation at 30 m resolution. Qualitative and quantitative comparisons suggest our Landsat Time Series (LTS) products improve identification of defoliation events relative to existing products and provide a repeatable metric of change in condition. Our synthetic-image approach is an important step toward using the full temporal potential of the Landsat archive for operational monitoring of forest health over large extents, and provides an important new tool for understanding spatial and temporal dynamics of insect defoliators. [ABSTRACT FROM AUTHOR]

The Minerals Management Service (MMS) International Activities and Marine Minerals Division is charged with management of Federal Outer Continental Shelf (OCS) sand and gravel resources that would be used for beach nourishment to repair storm damage and protect against sea-level rise. To reduce environmental damage associated with long-term and large-scale use of these resources, a project was funded by MMS to design a comprehensive physical and biological monitoring program for sand-mining activities. An initial task of this project was performance of a literature review to determine where information gaps existed regarding the effects of sand mining and which physical processes and biological resources should be the focus of monitoring. Based upon the literature review and a conference with other investigators, the monitoring program was designed to include the following elements: benthic communities and their trophic relationships to fishes, marine mammals and wildlife (operational monitoring), sediment sampling and analysis, wave monitoring and modeling, bathymetric and substrate surveys, and shoreline monitoring and modeling. Protocols were developed for these elements to ensure consistency of methods among studies. The two primary physical impacts of concern are changes to the sea bed resulting in changes to the erosion and sedimentation processes along the shore and changes to the sea bed that would have a direct and significant impact on the biological environment. The most important biological impacts from dredging to be monitored in this program are changes in benthic secondary production and trophic transfer to fishes. [ABSTRACT FROM AUTHOR]

The rising severity and frequency of wildfires in recent years in the United States have raised numerous concerns regarding the improvement in wildfire emergency response management and decision-making systems, which require operational high temporal and spatial resolution monitoring capabilities. Satellites are one of the tools that can be used for wildfire monitoring. However, none of the currently available satellite systems provide both high temporal and spatial resolution. For example, GOES-17 geostationary satellite fire products have high temporal (1–5 min) but low spatial resolution (≥2 km), and VIIRS polar orbiter satellite fire products have low temporal (~12 h) but high spatial resolution (375 m). This work aims to leverage currently available satellite data sources, such as GOES and VIIRS, along with deep learning (DL) advances to achieve an operational high-resolution, both spatially and temporarily, wildfire monitoring tool. Specifically, this study considers the problem of increasing the spatial resolution of high temporal but low spatial resolution GOES-17 data products using low temporal but high spatial resolution VIIRS data products. The main idea is using an Autoencoder DL model to learn how to map GOES-17 geostationary low spatial resolution satellite images to VIIRS polar orbiter high spatial resolution satellite images. In this context, several loss functions and DL architectures are implemented and tested to predict both the fire area and the corresponding brightness temperature. These models are trained and tested on wildfire sites from 2019 to 2021 in the western U.S. The results indicate that DL models can improve the spatial resolution of GOES-17 images, leading to images that mimic the spatial resolution of VIIRS images. Combined with GOES-17 higher temporal resolution, the DL model can provide high-resolution near-real-time wildfire monitoring capability as well as semi-continuous wildfire progression maps. [ABSTRACT FROM AUTHOR]

Increased flash drought awareness in recent years has motivated the development of numerous indicators for monitoring, early warning, and assessment. The flash drought indicators can act as a complementary set of tools by which to inform flash drought response and management. However, the limitations of each indicator much be measured and communicated between research and practitioners to ensure effectiveness. The limitations of any flash drought indicator are better understood and overcome through assessment of indicator sensitivity and consistency; however, such assessment cannot assume any single indicator properly represents the flash drought "truth." To better understand the current state of flash drought monitoring, this study presents an intercomparison of nine, widely used flash drought indicators. The indicators represent perspectives and processes that are known to drive flash drought, including evapotranspiration and evaporative demand, precipitation, and soil moisture. We find no single flash drought indicator consistently outperforms all others across the contiguous United States. We do find the evaporative demand- and evapotranspiration-driven indicators tend to lead precipitation- and soil moisture-based indicators in flash drought onset, but also tend to produce more flash drought events collectively. Overall, the regional and definition-specific variability in results supports the argument for a multi-indicator approach for flash drought monitoring, as advocated by recent studies. Furthermore, flash drought research-especially evaluation of historical and potential future changes in flash drought characteristics-should test multiple indicators, datasets, and methods for representing flash drought, and ideally employ a multi-indicator analysis framework over use of a single indicator from which to infer all flash drought information. SIGNIFICANCE STATEMENT: Rapid onset or "flash" drought has been an increasing concern globally, with quickly intensifying impacts to agriculture, ecosystems, and water resources. Many tools and indicators have been developed to monitor and provide early warning for flash drought, ideally resulting in more time for effective mitigation and reduced impacts. However, there remains no widely accepted single method for defining, monitoring, and measuring flash drought, which means most indicators that are developed are compared with other individual indicators or conditions and impacts in one or two flash drought events. In this study, we measure the state of flash drought monitoring through an intercomparison of nine, widely used flash drought indicators that represent different aspects of flash drought. We find that no single flash drought indicator outperformed all others and suggest that a comprehensive flash drought monitor should leverage multiple, complementary indicators, datasets, and methods. Furthermore, we suggest flash drought research-especially that which reflects on historical or projected changes in flash drought characteristics-should seek multiple indicators, datasets, and methods for analyses, thereby reducing the potentially confounding effects of sensitivity to a single indicator. [ABSTRACT FROM AUTHOR]

Describes the facilities, operating procedures and performance of the reservoir release improvements on several Tennessee Valley Authority (TVA) dams. Background of the release improvement program; Information on dissolved oxygen concentration; Types of performance and operational monitoring.

Infrastructure plays a pivotal role in a nation's economic stability, security, and long-term sustainability. For decades, United States infrastructure has been rated as inadequate and the resources required for its restoration continue to grow. Despite the transformative potential of Building Information Modeling (BIM) coupled with digital technologies in revolutionizing the building industry, its widespread adoption within infrastructure projects remains limited. This study explores the application of BIM and emerging technologies in transportation projects' lifecycle, identifies research gaps, and discusses the use of technology to address current infrastructure challenges. Employing a systematic review approach, this research synthesizes BIM application studies based on well-defined criteria. The synthesis of the literature underscores the comprehensive integration of BIM throughout the lifecycle of transportation assets, catalyzed by collaborative, information-driven processes. However, challenges pertaining to interoperability, role delineation, standards enforcement, and cost persist. This study advocates for a deeper exploration of the synergy between BIM, digital technologies, and infrastructure, envisioning an enriched transportation lifecycle in the future. [ABSTRACT FROM AUTHOR]

By influencing soil organic carbon (SOC), cover crops play a key role in shaping soil health and hence the system's long‐term sustainability. However, the magnitude by which cover crops impacts SOC depends on multiple factors, including soil type, climate, crop rotation, tillage type, cover crop growth, and years under management. To elucidate how these multiple factors influence the relative impact of cover crops on SOC, we conducted a meta‐analysis on the impacts of cover crops within rotations that included corn (Zea mays L.) on SOC accumulation. Information on climatic conditions, soil characteristics, management, and cover crop performance was extracted, resulting in 198 paired comparisons from 61 peer‐reviewed studies. Over the course of each study, cover crops on average increased SOC by 7.3% (95% CI, 4.9%–9.6%). Furthermore, the impact of cover crop–induced increases in percent change SOC was evaluated across soil textures, cover crop types, crop rotations, biomass amounts, cover crop durations, tillage practices, and climatic zones. Our results suggest that current cover crop–based corn production systems are sequestering 5.5 million Mg of SOC per year in the United States and have the potential to sequester 175 million Mg SOC per year globally. These findings can be used to improve carbon footprint calculations and develop science‐based policy recommendations. Taken altogether, cover cropping is a promising strategy to sequester atmospheric C and hence make corn production systems more resilient to changing climates. Core Ideas: In the 61 studies that contained cover crops, the average SOC increase over each project was 7.3%.The amount of SOC stored was influenced by crop rotation, cover crop type and biomass, soil texture, and climate.Average cover crops increased SOC storage in the surface 30 cm was 0.88 Mg SOC (ha × per year).Globally, cover crop–based corn production systems have the potential to sequester 175 million Mg SOC per year. [ABSTRACT FROM AUTHOR]

Drought monitoring and forecasting systems are used in the United States (U.S.) to inform drought management decisions. Drought forecasting efforts have often been conducted and evaluated at coarse spatial resolutions (i.e., >10‐km), which miss key local drought information at higher resolutions. Addressing the importance of forecasting drought at high resolutions, this study develops statistical models to evaluate 1‐ to 3‐month lead time predictability of meteorological and agricultural summer drought across the western U.S. at a 4‐km resolution. Our high‐resolution drought predictions have statistically significant skill (p ≤ 0.05) across 70%–100% of the western U.S., varying by evaluation metric and lead time. 1‐ to 3‐month lead time drought forecasts accurately represent monitored summer drought spatial patterns during major drought events, the interannual variability of drought area from 1982 to 2020 (r = 0.84–0.93), and drought trends (r = 0.94–0.97). 71% of western U.S summer drought area interannual variability can be explained by cold‐season (November–February) climate conditions alone allowing skillful 3‐month lead time predictions. Pre‐summer drought conditions (represented by drought indices) are the most important predictors for summer drought. Thus, the statistical models developed in this study heavily rely on the autocorrelation of chosen agricultural and meteorological drought indices which estimate land surface moisture memory. Indeed, prediction skill strongly correlates with persistence of drought conditions (r ≥ 0.73). This study is intended to support future development of operational drought early warning systems that inform drought management. Plain Language Summary: Droughts are complex and devastating natural disasters with severe implications in the western U.S. for energy production, agricultural yields, and wildfires, particularly during summer months. Drought monitoring and forecasting systems are used in the U.S. to inform drought management decisions. However, existing products and analyses are typically performed at coarse spatial resolutions (>10‐km). Because summer drought is spatially variable at finer resolutions than current drought monitoring and forecasting systems, it is valuable to develop seasonal drought forecasting systems at higher spatial resolutions. In this study we present a novel statistical modeling framework to forecast summer drought conditions at a high resolution (4‐km) at 1‐ to 3‐month lead times across the western U.S. Our models provide skillful predictions of drought across most of the western U.S., but there is degraded skill in areas where drought tends to be less persistent. Future research can expand on our work by predicting drought at finer temporal resolutions while maintaining the high spatial resolution used in this study's methodology. This research is intended to support development of future operational drought early warning systems that provide high spatial resolution forecasts. Key Points: Statistical models accurately predict summer meteorological and agricultural drought at 1‐, 2‐, and 3‐month lead times at a 4‐km resolutionMost of the interannual variability in summer drought area can be explained by preceding cold‐season climate conditionsStatistical models rely heavily on the autocorrelation of drought indices in drought forecasts [ABSTRACT FROM AUTHOR]

Abstract: Tamarix leaf beetles (Diorhabda carinulata) have been widely released on western U.S. rivers to control introduced shrubs in the genus Tamarix. Part of the motivation to control Tamarix is to salvage water for human use. Information is needed on the impact of beetles on Tamarix seasonal leaf production and subsequent water use over wide areas and multiple cycles of annual defoliation. Here we combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on Tamarix evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6–8week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ET was estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, results were variable among sites, ranging from no apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394mmyr−1 by Landsat and 314mmyr−1 by MODIS estimates (20–25% of potential ET), further constraining the amount of water that could be salvaged. Beetle–Tamarix interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent to which Tamarix populations will be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocam image, the low temporal resolution of Landsat, and the low spatial resolution of MODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols. [Copyright &y& Elsevier]

Effectively managing take of wildlife resulting from human activities poses a major challenge for applied conservation. Demographic data essential to decisions regarding take are often expensive to collect and are either not available or based on limited studies for many species. Therefore, modeling approaches that efficiently integrate available information are important to improving the scientific basis for sustainable take thresholds. We used the prescribed take level (PTL) framework to estimate allowable take for bald eagles (Haliaeetus leucocephalus) in the conterminous United States. We developed an integrated population model (IPM) that incorporates multiple sources of information and then use the model output as the scientific basis for components of the PTL framework. Our IPM is structured to identify key parameters needed for the PTL and to quantify uncertainties in those parameters at the scale at which the United States Fish and Wildlife Service manages take. Our IPM indicated that mean survival of birds >1 year old was high and precise (0.91, 95% CI = 0.90–0.92), whereas mean survival of first‐year eagles was lower and more variable (0.69, 95% CI = 0.62–0.78). We assumed that density dependence influenced recruitment by affecting the probability of breeding, which was highly imprecise and estimated to have declined from approximately 0.988 (95% CI = 0.985–0.993) to 0.66 (95% CI = 0.34–0.99) between 1994 and 2018. We sampled values from the posterior distributions of the IPM for use in the PTL and estimated that allowable take (e.g., permitted take for energy development, incidental collisions with human made structures, or removal of nests for development) ranged from approximately 12,000 to 20,000 individual eagles depending on risk tolerance and form of density dependence at the scale of the conterminous United States excluding the Southwest. Model‐based thresholds for allowable take can be inaccurate if the assumptions of the underlying framework are not met, if the influence of permitted take is under‐estimated, or if undetected population declines occur from other sources. Continued monitoring and use of the IPM and PTL frameworks to identify key uncertainties in bald eagle population dynamics and management of allowable take can mitigate this potential bias, especially where improved information could reduce the risk of permitting non‐sustainable take. [ABSTRACT FROM AUTHOR]

Solar monitoring is a method in which solar interferences, recorded during operational scanning of a radar, are used to monitor antenna pointing, identify signal processor issues, track receiver chain stability, and check the balance between horizontal and vertical polarization receive channels. The method is used by EUMETNET to monitor more than 100 radars in 20 European countries and it has been adopted by many national weather services across the world. NEXRAD is a network of 160 similar S-band weather radars (WSR-88Ds), which makes it most suitable for assessing the capability of the solar monitoring method on a continental scale. The NEXRAD level-II data contain radial-by-radial noise power estimates. An increase in this estimate is observed when the antenna points close to the sun. Our decoding software extracts these noise power estimates for the horizontal and vertical receive channels (converted to solar flux units) and other relevant metadata, including azimuth, elevation, observation time, and radar location. Here we present results of analyzing one year of solar monitoring data generated by 142 radars from the contiguous United States. We show monitoring results, geographical maps, and statistical outcomes on antenna pointing, solar fluxes, and differential reflectivity biases. We also assess the quality of the radars by defining a figure of merit, which is calculated from the solar monitoring results. The results demonstrate that the solar method provides great benefit for routine monitoring and harmonization of national and transnational operational radar networks. [ABSTRACT FROM AUTHOR]

Obesity is a chronic disease that poses serious health and societal burdens. Although guidelines exist for obesity management in primary care, evaluating the success of obesity treatment programs is hampered by lack of established, robust quality measures. This study aimed to develop, and test for feasibility, measures for operational tracking, quality performance, and patient-centered care in the context of a national collaborative to develop a model for obesity management in the US primary care setting. The authors developed and evaluated 7 measures used to track the care of patients with overweight or obesity (n = 226,727 at baseline) receiving care within 10 health care organizations (HCOs). Measure categories included: (1) operational tracking (obesity/overweight prevalence and prevalence of obesity-related complications); (2) quality performance (obesity diagnosis, change in weight over time, anti-obesity medication prescriptions, and assessment of obesity-related complications); and (3) patient-centered care (patient-reported outcomes). Measures were tested for feasibility, variability across HCOs, ability to detect differences over time, and value to the HCOs. All measures were feasible to collect, provided value to the participating HCOs, and demonstrated variation and ability to detect differences over time (eg, rates of documented diagnosis of obesity classes 1, 2, and 3 increased from 29%, 46%, and 66%, respectively, at baseline to 35%, 53%, and 71% at study end). This study confirmed the feasibility and perceived value of 7 operational, performance, and patient-centered measures collected in primary care practices in 10 HCOs over an 18-month period. [ABSTRACT FROM AUTHOR]

Growing demands for temporally specific information on land surface change are fueling a new generation of maps and statistics that can contribute to understanding geographic and temporal patterns of change across large regions, provide input into a wide range of environmental modeling studies, clarify the drivers of change, and provide more timely information for land managers. To meet these needs, the U.S. Geological Survey has implemented a capability to monitor land surface change called the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative. This paper describes the methodological foundations and lessons learned during development and testing of the LCMAP approach. Testing and evaluation of a suite of 10 annual land cover and land surface change data sets over six diverse study areas across the United States revealed good agreement with other published maps (overall agreement ranged from 73% to 87%) as well as several challenges that needed to be addressed to meet the goals of robust, repeatable, and geographically consistent monitoring results from the Continuous Change Detection and Classification (CCDC) algorithm. First, the high spatial and temporal variability of observational frequency led to differences in the number of changes identified, so CCDC was modified such that change detection is dependent on observational frequency. Second, the CCDC classification methodology was modified to improve its ability to characterize gradual land surface changes. Third, modifications were made to the classification element of CCDC to improve the representativeness of training data, which necessitated replacing the random forest algorithm with a boosted decision tree. Following these modifications, assessment of prototype Version 1 LCMAP results showed improvements in overall agreement (ranging from 85% to 90%). • We developed a robust capability for operational monitoring of land surface change. • Landsat ARD and Continuous Change Detection and Classification are foundational. • Landsat's rich time series has substantial variability in observation frequency. • The algorithm was modified reducing variability in results between scene centers and overlap zones. • Classification was modified to improve training data representativeness and reduce artifacts. [ABSTRACT FROM AUTHOR]

In recent years, researchers of different communities have increased their efforts in formalizing a set of measurements regularly collected for analysing changes in Drivers, States, Impacts and Responses of a given discipline. In some cases, different actors have converged in a minimum set of Essential Variables (EVs), such as for Climate, Biodiversity or Oceans. The definition of such EVs is an ongoing evolution and in extension (e.g. EVs for water) although some communities have not even started (e.g. agriculture and energy). This paper characterizes the Earth Observation (EO) networks and creates a graph representation of their relations. Secondly, this graph is enriched with the EVs produced by each network creating a knowledge base. Finally, an effort has been done to identify links between EVs and Sustainable Development Goals (SDG) indicators in a way that they indirectly connect the EO. An analysis to detect gaps in EO variables due to a lack of observational networks is performed. Several suggestions for improving SDG indicators framework by considering EVs are exposed, as well as proposing new necessary EVs and suggesting new EO based indicators. The complete graph is available in the ENEON website (). [ABSTRACT FROM AUTHOR]

The US offshore wind industry is maturing with several projects in various stages of development. These projects require site wind and environmental data before and during operation. Conventional techniques such as fixed‐bottom meteorological towers present economical and permitting challenges for the US. Floating Light Detection and Ranging (LiDAR) buoys offer significant advantages including reduced costs, less permitting, and reusability. This paper presents the validation of the first floating LiDAR buoy in Northeast US waters. The buoy, named DeepCLiDAR, includes a LiDAR, ecological monitoring sensors, and metocean sensors. A three‐phase LiDAR validation plan was executed, and its results are presented. The objective of the validation plan was to verify the accuracy of measurements made by the LiDAR buoy in wave environments against an unmoving reference wind measurement. Due to a lack of reference met masts, the use of a LiDAR on land as a baseline reference was implemented for validation. Comparison to a reference LiDAR instead of a traditional meteorological tower was a unique approach required in the Northeast US waters due to the absence of a reference fixed‐bottom meteorological tower in the region at the time of this study. The testing included a comparison of wind speed measurements made by the buoy deployed 15 km offshore from the mainland and a land‐based reference LiDAR located on a nearby island. This paper presents the methodology and results of this program, which indicate favorable agreement. This was the first such validation program in the Northeast USA which is now seeing rapid development of offshore wind. [ABSTRACT FROM AUTHOR]

As drought involves diverse natural and human‐made processes in hydrologic cycles, it is necessary to track a process‐specific variable for efficient drought risk management. In this study, we employed a state‐of‐the‐art formulation of the generalized complementary relationship (GCR) to estimate terrestrial evapotranspiration (ET). The GCR ET estimates were used to assess historical droughts over the contiguous United States (CONUS) in relation to long‐term natural fluctuations. Results showed that the GCR provided strong performance in reproducing water balance ET estimates and correlations to the El Niño–Southern Oscillation, when compared to observation‐driven estimates and land surface models. For 1982‐2011, the GCR yielded better performance than land surface models even with estimated radiation inputs and no wind speed variations. The Standardized Evapotranspiration Deficit Index (SEDI) based on the GCR provided a consistent drought assessment with precipitation‐based drought identification and remotely sensed vegetation conditions. The SEDI seems to capture the heat wave‐driven flash drought together with water deficit‐driven droughts. In the CONUS, the La Niña‐like conditions were likely to trigger extensive vegetation droughts with extreme severity. This study found the three long‐term environmental factors that affect the general trend of ET deficits over the CONUS, which are the Atlantic Multidecadal Oscillation, the mean air temperature, and the Pacific Decadal Oscillation. Especially, the Atlantic Oscillation seems to be the most significant predictor that could explain the long‐term variation of vegetation droughts over the CONUS. This study highlights that the GCR‐based SEDI could be useful for monitoring and assessment of drought risks at a continental scale. Key Points: The generalized complementary principle showed strong performance in estimating evapotranspiration over the contiguous United StatesDroughts identified by evapotranspiration deficits agreed with remote sensing vegetation conditions and historical recordsFluctuations of sea surface temperatures explain principal components of evapotranspiration deficits significantly [ABSTRACT FROM AUTHOR]

An overview of the standards program of the Acoustical Society of America (ASA) is presented. The American National Standards Institute (ANSI) accreditation and the U.S. voluntary consensus process are described. The structure of the ASA standards organization is explained and the roles of each standards committee are outlined. The standards development process from new work item proposal through final approval is detailed. The relationship between national and international standards bodies is also discussed. Examples of the practical benefits of acoustical standards for both participating organizations and end users are given. Information about how to participate in the standards process is also provided. [ABSTRACT FROM AUTHOR]

In 2012, the USA Corn Belt, an intensive agricultural region of the USA, was hit by a widespread severe drought, affecting states such as Illinois, Iowa, Nebraska, and Indiana. In this study, time series (2000–2012) of Moderate Resolution Imaging Spectroradiometer (MODIS) measurements were investigated to assess the 2012 drought conditions during the corn-growing season. Seven MODIS indices generated based on eight day MODIS reflectance and land surface temperature (LST) products were examined with standardized precipitation index (SPI) and Palmer-Zacross the Corn Belt to evaluate the relative performance of each MODIS index to detect agricultural drought. The normalized difference infrared index (NDII6) anomaly shows the highest correlation coefficient (r) with SPI at three time scales and correlates best with Palmer-Z, which suggests good sensitivity of the NDII6 anomaly to precipitation and moisture deficiency in agricultural areas. The temporal and spatial features of drought provided by MODIS indices were compared with maps of the USA Drought Monitor (USDM), the current advanced tool for drought monitoring. The rapid intensification of drought across the Corn Belt in 2012 summer captured by MODIS index anomalies agreed with the changes of USDM maps quite well, especially in August and September when extreme drought occurred. Through comparison with the USDM drought map, the NDII6 anomaly demonstrated an advantage in monitoring drought condition over irrigated land and showed the potential to advance fine-scale agricultural drought monitoring by providing more detailed spatial characterization. [ABSTRACT FROM PUBLISHER]

The Monitoring Trends in Burn Severity project is a comprehensive fire atlas for the United States that includes perimeters and severity data for all fires greater than a particular size (~400 ha in the western US, and ~200 ha in the eastern US). Although the database was derived for management purposes, the scientific community has expressed interest in its research capacity. As with any derived data, it is critical to understand inherent limitations to maximise the utility of the dataset without compromising the inferences. The classified severity product in particular is of limited use to research due to a lack of both consistency in developing class thresholds and empirical relationships with ecological metrics. Here we review the products available and their development process, and characterise and quantify the limitations of the classified burn severity data product based on the use of highly variable and subjective classification thresholds. We suggest a framework for overcoming these limitations by developing a more robust classified product that will support ecological management and applications. This framework utilises field data to develop consistent, ecologically based thresholds that incorporate existing ecoregion classifications from LANDFIRE or other fire management frameworks already widely integrated into planning efforts. The Monitoring Trends in Burn Severity project produced a national atlas of burn severity for science and management applications in the US. However, the classified data product has considerable limitations that inhibit broader utility, which could be overcome through a national re-classification effort that ties the product to LANDFIRE. [ABSTRACT FROM AUTHOR]

Shifting to renewable energy is an important global challenge, and there are many technologies available to help reduce carbon dioxide emissions. Seawater air conditioning (SWAC) is a renewable ocean thermal energy technology that will soon be implemented in Honolulu, Hawaii, on the island of Oahu. The SWAC system will operate by using cool water from 500 m depth in a heat exchange system and then will release this nutrient-rich water back into the ocean at a shallower depth of 100-140 m. The introduction of a plume of warmed (but still relatively cool) deep seawater has unknown impacts on the tropical marine environment. Possible impacts include increases in primary production, changes in water chemistry and turbidity, and changes in the local food web. We used moored instruments and shipboard profiling to describe oceanographic parameters at the future SWAC effluent site. Parameters varied with the M2 internal tide, and denser water was correlated with higher nitrate, lower oxygen, and lower chlorophyll a (correlation coefficients 0.55, -0.58, and -0.75, respectively). The nitrate concentrations in the plume will be >30.0 µmol kg-1, while ambient concentrations range from <2.0-9.8 µmol kg-1. Irradiance levels at the effluent depth are sufficient to support net photosynthesis, and the effluent's location in the pycnocline could lead to rapid horizontal advection of the plume and expansion of the spatial scale of impacts. These baseline data provide an understanding of pre-impact conditions at the future SWAC site and will enable a more accurate environmental assessment. A comprehensive and well-resolved environmental monitoring effort during SWAC operation will be necessary to quantify and understand these impacts. [ABSTRACT FROM AUTHOR]

Scientific and clinical activities undertaken by public health agencies may be misconstrued as medical research. Most discussions of regulatory and legal oversight of medical research focus on activities involving either patients in clinical practice or volunteers in clinical trials. These discussions often exclude similar activities that constitute or support core functions of public health practice. As a result, public health agencies and practitioners may be held to inappropriate regulatory standards regarding research. Through the lens of the Departments of Defense and Veterans Affairs, and using several case studies from these departments, we offer a framework for the adjudication of activities common to research and public health practice that could assist public health practitioners, research oversight authorities, and scientific journals in determining whether such activities require regulatory review and approval as research. [ABSTRACT FROM AUTHOR]

The article reports on the Russian government's plan to upgrade material protection, control, and accounting (MPC&A) systems at the country's nuclear facilities. It is said that this program is a crucial component of Russian-U.S. cooperation in the area of nuclear threat reduction. The program is implemented under a separate MPC&A agreement between Russia and the U.S.

This overview describes those satellite time series that represent at least a 20-year-long record of land-surface observations. The focus is on the optical remote-sensing measurements to study and monitor land-surface characteristics at spatial resolutions from tens of metres to a few kilometres. The objective is to draw the attention of the science community to the longest time series of space observations of the Earth's characteristics available in the US data archives. We highlight the moderate resolution data record from Landsat – the longest record of land observations from space. The utility of Landsat data for time series analyses has increased tremendously during the past few years since the data became freely available. Our intention is to give as much information on the data availability as possible with references in peer-reviewed journals and current websites, where users can find further details on the features of the data sets described here. [ABSTRACT FROM AUTHOR]

Forest disturbances around the world have the potential to alter forest type and cover, with impacts on diversity, carbon storage, and landscape composition. These disturbances, especially fire, are common and often large, making ground investigation of forest recovery difficult. Remote sensing offers a means to monitor forest recovery in real time, over the entire landscape. Typically, recovery monitoring via remote sensing consists of measuring vegetation indices (e.g., NDVI) or index-derived metrics, with the assumption that recovery in NDVI (for example) is a meaningful measure of ecosystem recovery. This study tests that assumption using MODIS 16-day imagery from 2000 to 2010 in the area of the Colorado's Routt National Forest Hinman burn (2002) and seedling density counts taken in the same area. Results indicate that NDVI is rarely correlated with forest recovery, and is dominated by annual and perennial forb cover, although topography complicates analysis. Utility of NDVI as a means to delineate areas of recovery or non-recovery are in doubt, as bootstrapped analysis indicates distinguishing power only slightly better than random. NDVI in revegetation analyses should carefully consider the ecology and seasonal patterns of the system in question. [ABSTRACT FROM AUTHOR]

The Environmental Modeling Center (EMC) at the National Centers for Environmental Prediction (NCEP) and the University of Washington (UW) run parallel drought monitoring systems over the continental United States based on the North American Land Data Assimilation System (NLDAS). The NCEP system uses four land surface models (LSMs): Variable Infiltration Capacity (VIC), Noah, Mosaic, and Sacramento (SAC). The UW system uses VIC, SAC, Noah, and the Community Land Model (CLM). An assessment of differences in drought characteristics using both systems for the period 1979-2008 was performed. For soil moisture (SM) percentiles and runoff indices, differences are relatively small among different LSMs in the same system. However, the ensemble mean differences between the two systems are large over the western United States-in some cases exceeding 20% for SM and runoff percentile differences. These differences are most apparent after 2002 when the NCEP system transitioned to use the real-time North American Regional Reanalysis (NARR) and its precipitation gauge station data. (The UW system went into real-time operation in 2005.) Experiments were performed to address the sources of uncertainties. Comparison of simulations using the two systems with different model forcings indicates that the precipitation forcing differences are the primary source of the SM and runoff differences. While temperature, shortwave and longwave radiation, and wind speed forcing differences are also large after 2002, their contributions to SM and runoff differences are much smaller than precipitation. [ABSTRACT FROM AUTHOR]

The potential of CloudSat W-band radar for observing wintertime storms affecting the West Coast of North America is evaluated. Storms having high hydrological impact often result from landfalls of 'atmospheric rivers' ('ARs'), which are the narrow elongated regions of water vapor transport from the tropics. CloudSat measurements are used for retrievals of rain rate R and cloud ice water path (IWP) along the satellite ground track over ocean and land. These retrievals present quasi-instantaneous vertical cross sections of precipitating systems with high-resolution information about hydrometeors. This information is valuable in coastal areas with complex terrain where observations with existing instrumentation, including ground-based radars, are limited. CloudSat reflectivity enhancements [i.e., bright band (BB)] present a way to estimate freezing levels, indicating transitions between rainfall and snowfall. CloudSat estimates of these levels were validated using data from radiosonde soundings and compared to model and microwave sounder data. Comparisons of CloudSat retrievals of rain rates with estimates from ground-based radars in the areas where measurements from these radars were available indicated an agreement within retrieval uncertainties, which were around 50%%. The utility of CloudSat was illustrated for case studies of pronounced AR events at landfall and over ocean. Initial analysis of CloudSat crossings of ARs during the 2006/07 season were used for rainfall regime prevalence assessment. It indicated that stratiform rain, which often had BB features, warm rain, and mixed rain were observed with about 26%%, 24%%, and 50%% frequency. Stratiform regions generally had higher rain rates. Significant correlation (~0.72) between mean values of IWP and rain rate was observed for stratiform rainfall. [ABSTRACT FROM AUTHOR]

The article reports on prescription drug overdose as an epidemic in the U.S. According to data, the prevention of opioid overdose deaths should focus on strategies that target persons who seek care from multiple doctors and high-dosage medical users. The author adds that there are some promising strategies for addressing the high-risk groups including the use of prescription data with insurance restrictions to reduce the inappropriate use of opioids and to prevent doctor shopping.

Two remote-sensing optical algorithms for the retrieval of the water quality components (WQCs) in the Albemarle-Pamlico Estuarine System (APES) were developed and validated for chlorophyll a (Chl). Both algorithms were semi-empirical because they incorporated some elements of optical processes in the atmosphere, water, and air/water interface. One incorporated a very simple atmospheric correction and modified quasi-single-scattering approximation (QSSA) for estimating the spectral Gordon's parameter, and the second estimated WQCs directly from the top of atmosphere satellite radiance without atmospheric corrections. A modified version of the Global Meteorological Database for Solar Energy and Applied Meteorology (METEONORM) was used to estimate directional atmospheric transmittances. The study incorporated in situ Chl data from the Ferry-Based Monitoring (FerryMon) program collected in the Neuse River Estuary (n = 633) and Pamlico Sound (n = 362), along with Medium Resolution Imaging Spectrometer (MERIS) satellite imagery collected (2006-2009) across the APES; providing quasi-coinciding samples for Chl algorithm development and validation. Results indicated a coefficient of determination (R2) of 0.70 and mean-normalized root-mean-squares errors (NRMSE) of 52% in the Neuse River Estuary and R2 = 0.44 (NRMSE = 75 %) in the Pamlico Sound-without atmospheric corrections. The simple atmospheric correction tested provided on performance improvements. Algorithm performance demonstrated the potential for supporting long-term operational WQCs satellite monitoring in the APES. [ABSTRACT FROM AUTHOR]

The article discusses the enactment of certain laws related to national and commercial space programs in the U.S. It mentions that the enactment proposal is prepared by the Office of the Law Revision Counsel of the U.S. House of Representatives, which enacts the bill into the U.S. Code as a positive law. It notes that the bill is made with several revisions in response to the comments received.

Physical processes responsible for the abnormally wet condition in the Central Intermountain West (CIW) of the United States in June 2009 were investigated. It was illustrated that persistent rainy conditions over the CIW during June 2009 were associated with a pronounced circumglobal teleconnection pattern, which is characterized as a short Rossby wave train along the jet stream waveguide with a wave number 5 structure. The ascending motion and moisture flux convergence over the CIW associated with the cyclonic action center over the US West Coast in the teleconnection wave train could be essential for the persistent local rainfall during June 2009. Further analysis suggested that the June 2009 circulation pattern is consistent with a prevailing mode of the summer circumglobal teleconnection pattern. The findings in this study provide information for improved understanding of the early summer rainfall regime in the CIW. [ABSTRACT FROM AUTHOR]

In addition to retailing new vehicles, automotive manufacturers in the United States sell millions of vehicles through leasing and to fleet customers every year. The majority of these vehicles are returned to the automotive manufacturers at the end of the contracted term and must be "remarketed." In 2007, about 10 million used vehicles were sold at more than 400 auctions in the United States. Large consigners face decisions every day about when, where, and at what price to offer these vehicles, which has significant financial implications for their profitability. To address the challenges of the distribution process, Power Information Network (PIN), a division of J.D. Power and Associates, developed the PIN Optimal Distribution of Auction Vehicles System (ODAV), an automated decision optimization system that helps remarketers maximize profits through the most advantageous distribution of their auction vehicles. At the core of the system is a combination of three models that determine the distribution of the vehicles on a daily basis: a nearest neighbor linear regression model for short-term auction price forecasting; an autoregressive integrated moving average time-series analysis model for volume-price elasticity; and a genetic algorithm optimizer for vehicle distribution. Since its launch in 2003, PIN has been providing ODAV services on a daily basis, and to date, more than two million vehicles have been distributed through this system. In this paper, we will describe the PIN ODAV System, its implementation, and the business impact by using as an example the experience with our largest client, Chrysler Group LLC. [ABSTRACT FROM AUTHOR]

Satellite-derived normalized difference vegetation index (NDVI) data have been used extensively to detect and monitor vegetation conditions at regional and global levels. A combination of NDVI data sets derived from AVHRR and MODIS can be used to construct a long NDVI time series that may also be extended to VIIRS. Comparative analysis of NDVI data derived from AVHRR and MODIS is critical to understanding the data continuity through the time series. In this study, the AVHRR and MODIS 16-day composite NDVI products were compared using regression and agreement analysis methods. The analysis shows a high agreement between the AVHRR-NDVI and MODIS-NDVI observed from 2002 and 2003 for the conterminous United States, but the difference between the two data sets is appreciable. Twenty per cent of the total difference between the two data sets is due to systematic difference, with the remainder due to unsystematic difference. The systematic difference can be eliminated with a linear regression-based transformation between two data sets, and the unsystematic difference can be reduced partially by applying spatial filters to the data. We conclude that the continuity of NDVI time series from AVHRR to MODIS is satisfactory, but a linear transformation between the two sets is recommended. [ABSTRACT FROM AUTHOR]

The National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite Data and Information Service (NESDIS) operates a fleet of civilian, polar-orbiting, environmental satellites that provide users and researchers with a continuous suite of atmospheric and surface products on a global scale. The first advanced TIROS operational vertical sounder (ATOVS) radiometer configuration, onboard NOAA-15, was successfully launched into an early evening orbit on 13 May 1998. The ATOVS featured the new 13 channel advanced microwave sounding unit (AMSU) module A1, the 2 channel AMSU-A2 and 5 channel AMSU-B radiometers, which replaced the MSU and SSU, along with a similar HIRS and AVHRR instrument payload (Goodrun G., Kidwell, K.B. and Winston, W., 2000, NOAA-KLM users guide: September 2000 revision, Technical Document, National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, National Climatic Data Center) that had been operational since 1979. The ATOVS onboard NOAA-16 was successfully launched into an afternoon orbit on 21 September 2000, followed by NOAA-17 into a late evening orbit on 24 June 2002, creating the first ever three-satellite constellation of operational polar satellites (ATOVS). The following report summarizes the online and offline scientific processing systems, respectively, for deriving the NESDIS operational ATOVS sounding products and presents a series of results for the unique three-operational-satellite configuration of NOAA-15, 16 and 17. Results focus on the value of the derived products in the analyses of global and regional scale weather, including direct comparisons against collocated numerical weather prediction (NWP) forecast and radiosonde data. The report is prefaced by a brief history of satellite weather products and concludes with future plans to meet expanding user requirements. [ABSTRACT FROM AUTHOR]

This section offers news briefs on acoustical standards. The Acoustical Society of America has formed a new standards subcommittee on Animal Bioacoustics. Meetings of the National Standards Committees will be held in conjunction with the 156th meeting of the Acoustical Society of America in Miami, Florida. Meetings of the International Standards Committees is scheduled on May 26-30, 2008.

The article presents news briefs related to the area of acoustical standards in the U.S. and in other countries. The Acoustical Society of America (ASA) Standards has launched its new website containing general information about each Standards Committee and U.S. Technical Advisory Group. A calendar of national and international Standards Committee Meetings in 2007 is also presented.

In today's challenging business climate, a variety of constitutencies in the financial services industry are looking to professional standard setting organizations to establish and promote Best Practices in the marketplace. Such organizations, working with financial services companies and regulators, can accomplish a great deal to promote consumer trust. In addition, there are encouraging indications that the value of professional organizations is being recognized and, therefore, woven into the future regulatory and marketplace infrastructure. [ABSTRACT FROM AUTHOR]

Changes in the nature of humanitarian crises and in the ways that the international community responds to such crises demand a radically overhauled role for the United Nations system. At a time when the UN and its member states are pursuing reform of some of that institution's most fundamental peace and security functions, this paper suggests that reform, too, is required to meet humanitarian crises of the future. This paper proposes a new type of operational role for the UN, while at the same time arguing that the UN has to place itself in the vanguard of humanitarian assistance as ‘the standard-bearer’. The article draws many of its conclusions and recommendations from a recently completed study, requested by the Inter-Agency Standing Committee, concerning the effect for the UN system of changes in humanitarian financing. [ABSTRACT FROM AUTHOR]

Drought events across the United States since 1995 illustrate the country’s continuing vulnerability to drought. Officials are beginning to recognize the need for enhanced mitigation actions to reduce the increasing economic, environmental, and social impacts of droughts. One way to better understand a region’s drought vulnerability and identify the appropriate mitigation actions to take is to conduct a drought risk analysis. However, drought risk can be a confusing concept for many planners. For this reason, a simplified, flexible framework for conducting a drought risk analysis is presented. This framework is based on a combination of natural hazards theory and interactions with a variety of drought planners in the field, and is intended to be a practical, action-oriented model to assist drought planners on a variety of political and geographic scales. Several case studies are also discussed to demonstrate the application of such a model. [ABSTRACT FROM AUTHOR]

Carbon sequestration was estimated a northern mixed-grass prairie site and a sagebrush–steppe site in southeastern Wyoming using an approach that integrates remote sensing, CO2 flux measurements, and meteorological data. Net ecosystem exchange (NEE) of CO2 was measured using aircraft and ground flux techniques and was linearly related to absorbed photosynthetically active radiation (APAR). The slope of this relationship is the radiation use efficiency (ℇ = 0.51 g C/MJ APAR); there were no significant differences in the regression coefficients between the two sites. Furthermore, ecosystem chamber measurements of total respiration in 1998 and 1999 were used to develop a functional relationship with daily average temperature; the Q10 of the relationship was 2.2. Using the Advanced Very High Resolution radiometer. Normalized Difference Vegetation Index and meteorological data, annual gross primary production and respiration were calculated from 1995 to 1999 for the two sites. Overall, the sagebrush–steppe site was a net carbon sink, whereas the northern mixed-grass prairie site was in carbon balance. There was no significant relationship between NEE and APAR for a coniferous forest site, indicating this method for scaling up CO2 flux data may be only applicable to rangeland ecosystems. The combination of remote sensing with data from CO2 flux networks can be used to estimate carbon sequestration regionally in rangeland ecosystems. [ABSTRACT FROM AUTHOR]

There is increasing interest in accurate estimates of regional carbon fluxes, and identification of the causes of land/atmosphere/ocean exchange of carbon. Improved information will lead to better policies for managing greenhouse gas emissions and sequestration. The goals of this paper are to review the capability of ongoing operational inventory programs for estimating forest carbon stocks and stock changes, and to identify opportunities to improve forest carbon monitoring by enhancing these programs and supplementing them with new monitoring capability. Carbon in forest ecosystems and wood products cannot be measured directly. Ongoing forest monitoring programs provide a statistical basis for estimating carbon stocks and stock changes, based on data already collected, with a temporal resolution of about 5 years. Improvements in inventories will shorten the reporting cycle and add some variables that enhance the content with respect to carbon estimation, but it will take about a decade for full implementation. Meanwhile, there is an important role for remote sensing measurements, modeling, and imputation techniques to fill gaps in spatial coverage and content. Elements of the proposed North American Carbon Program, if implemented, will improve the estimates of forest ecosystem carbon. [ABSTRACT FROM AUTHOR]

The monitoring and analysis of drought have long suffered from the lack of an adequate definition of the phenomenon. As a result, drought indices have slowly evolved during the last two centuries from simplistic approaches based on some measure of rainfall deficiency, to more complex problem-specific models. Indices developed in the late nineteenth and early twentieth century included such measures as percent of normal precipitation over some interval, consecutive days with rain below a given threshold, formulae involving a combination of temperature and precipitation, and models factoring in precipitation deficits over consecutive days. The incorporation of evapotranspiration as a measure of water demand by Thornthwaite led to the landmark development in 1965 by Palmer of a water budget-based drought index that is still widely used. Drought indices developed since the 1960s include the Surface Water Supply Index, which supplements the Palmer Index by integrating snowpack, reservoir storage, streamflow, and precipitation at high elevations; the Keetch-Byram Drought Index, which is used by fire control managers; the Standardized Precipitation Index; and the Vegetation Condition Index, which utilizes global satellite observations of vegetation condition. These models continue to evolve as new data sources become available. The twentieth century concluded with the development of the Drought Monitor tool, which incorporates Palmer's index and several other (post Palmer) indices to provide a universal assessment of drought conditions across the entire United States. By putting the development of these drought indices into a historical perspective, this paper provides a better understanding of the complex Palmer Index and of the nature of measuring drought in general. [ABSTRACT FROM AUTHOR]

In the 1970s, tremendous progress was made in the physics of atmospheric finescale turbulence. In subsequent decades, effort in this field has languished. Although many scientific and technological problems associated with finescale turbulence are still unsolved, and although the need for the solution of some of them is now more urgent than three decades ago, the finescale turbulence community has never regained the strength and impact that it had in the 1970s. On 9–11 Aug 1999, a workshop on Atmospheric Turbulence at Meter– and Submeter Scales was held in Boulder, Colorado. Thirty–five invited participants with interests in this field discussed its past and future. Based on these discussions, this paper offers recommendations for three future canonical field experiments that would combine state–of–the–art methodologies to observe, simulate, and understand atmospheric finescale turbulence, in what sense it is relevant to remote sensing observations, and to what extent it affects the formation and evolution of clouds and precipitation. [ABSTRACT FROM AUTHOR]