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Atmospheric Motion Vectors (AMVs) calculated by six different institutions (Brazil Center for Weather Prediction and Climate Studies/CPTEC/INPE, European Organization for the Exploitation of Meteorological Satellites/EUMETSAT, Japan Meteorological Agency/JMA, Korea Meteorological Administration/KMA, Unites States National Oceanic and Atmospheric Administration/NOAA, and the Satellite Application Facility on Support to Nowcasting and Very short range forecasting/NWCSAF) with JMA’s Himawari-8 satellite data and other common input data are here compared. The comparison is based on two different AMV input datasets, calculated with two different image triplets for 21 July 2016, and the use of a prescribed and a specific configuration. The main results of the study are summarized as follows: (1) the differences in the AMV datasets depend very much on the ‘AMV height assignment’ used and much less on the use of a prescribed or specific configuration; (2) the use of the ‘Common Quality Indicator (CQI)’ has a quantified skill in filtering collocated AMVs for an improved statistical agreement between centers; (3) Among the six AMV operational algorithms verified by this AMV Intercomparison, JMA AMV algorithm has the best overall performance considering all validation metrics, mainly due to its new height assignment method: ‘Optimal estimation method considering the observed infrared radiances, the vertical profile of the Numerical Weather Prediction wind, and the estimated brightness temperature using a radiative transfer model’.

Satellite data are underutilized in many branches of operational oceanography. Users outside of the satellite community often encounter difficulty in discovering the types of satellite measurements that are available, and determining which satellite products are best for operational activities. In addition, the large choice of satellite data providers, each with their own data access protocols and formats, can make data access challenging. The mission of the NOAA CoastWatch Program is to make ocean satellite data easier to access and to apply to operational uses. As part of this mission, the West Coast Node of CoastWatch developed the NOAA Ocean Satellite Course, which introduces scientists and resource managers to ocean satellite products, and provides them tools to facilitate data access when using common analysis software. These tools leverage the data services provided by ERDDAP, a data distribution system designed to make data access easier via a graphical user interface and via machine-to-machine connections. The course has been offered annually since 2006 and has been attended by over 350 participants. Results of post-course surveys are analyzed to measure course effectiveness. The lessons learned from conducting these courses include using the preferred software of the course participants, providing easy access to datasets that are appropriate (fit for purpose) for operation applications, developing tools that address common tasks of the target audience, and minimizing the financial barriers to attend the course.

The climate normal, that is, the latest three full-decade average, of Arctic sea ice parameters is useful for baselining the sea ice state. A baseline ice state on both regional and local scales is important for monitoring how the current regional and local states depart from their normal to understand the vulnerability of marine and sea ice-based ecosystems to the changing climate conditions. Combined with up-to-date observations and reliable projections, normals are essential to business strategic planning, climate adaptation and risk mitigation. In this paper, monthly and annual climate normals of sea ice parameters (concentration, area, and extent) of the whole Arctic Ocean and 15 regional divisions are derived for the period of 1981−2010 using monthly satellite sea ice concentration estimates from a climate data record (CDR) produced by NOAA and the National Snow and Ice Data Center (NSIDC). Basic descriptions and characteristics of the normals are provided. Empirical Orthogonal Function (EOF) analysis has been utilized to describe spatial modes of sea ice concentration variability and how the corresponding principal components change over time. To provide users with basic information on data product accuracy and uncertainty, the climate normal values of Arctic sea ice extents (SIE) are compared with that of other products, including a product from NSIDC and two products from the Copernicus Climate Change Service (C3S). The SIE differences between different products are in the range of 2.3−4.5% of the CDR SIE mean. Additionally, data uncertainty estimates are represented by using the range (the difference between the maximum and minimum), standard deviation, 10th and 90th percentiles, and the first, second, and third quartile distribution of all monthly values, a distinct feature of these sea ice normal products.

The aquaculture industry relies on federal investments to stimulate aquaculture research and development (R&D). We conducted this study to track federal spending for aquaculture using a large database of 2957 US federal research grants awarded from 1990 to 2015. During that period, 1.04 billion US dollars ( USD) were spent on aquaculture research, with 919 million USD from federal agencies and 123 million USD in matching funds. By comparison, over the same time frame, the US Department of Agriculture's R&D spending was 41 billion USD. Federal grant funding for aquaculture had a 37-fold return on investment since 2000. Microalgae, oysters, salmon and trout, catfish, and shrimp received the most grant support, and the most common topics/disciplines were aquaculture production sciences, aquatic animal health and disease, genetics and breeding, and nutrition. Our findings can be used to identify research gaps and inform federal policy, grant making, and budget allocation. [ABSTRACT FROM AUTHOR]

This paper discusses the radiometric calibration of millimeter sounder radiometers, on polar orbiter satellites in the NASA Global Precipitation Mission (GPM) constellation; and presents radiometric bias results. Because the Tropical Rainfall Measurement Mission (TRMM) operated for over 17 years, it is important to combine the TRMM and the GPM precipitation datasets to produce a climate data record for global climate change studies. In the last decade of TRMM's operation, sounder radiometers were introduced into the TRMM constellation, which included: Advanced Microwave Sounding Unit-B sensors flown on NOAA weather satellites and the microwave humidity sounders sensors flown on NOAA and meteorological operational satellite program satellites. These sensors have provided an invaluable dataset of radiance measurements with full earth coverage, which has been used in precipitation measurements, weather prediction, and climate studies. [ABSTRACT FROM PUBLISHER]

Exposure assessment for nano-objects, and their aggregates and agglomerates (NOAA), has evolved from explorative research toward more comprehensive exposure assessment, providing data to further develop currently used conservative control banding (CB) tools for risk assessment. This study aims to provide an overview of current knowledge on emission potential of NOAA across the occupational life cycle stages by a systematic review and subsequently use the results in a data analysis. Relevant parameters that influence emission were collected from peer-reviewed literature with a focus on the four source domains (SD) in the source-receptor conceptual framework for NOAA. To make the reviewed exposure data comparable, we applied an approach to normalize for workplace circumstances and measurement location, resulting in comparable “surrogate” emission levels. Finally, descriptive statistics were performed. During the synthesis of nanoparticles (SD1), mechanical reduction and gas phase synthesis resulted in the highest emission compared to wet chemistry and chemical vapor condensation. For the handling and transfer of bulk manufactured nanomaterial powders (SD2) the emission could be differentiated for five activity classes: (1) harvesting; (2) dumping; (3); mixing; (4) cleaning of a reactor; and (5) transferring. Additionally, SD2 was subdivided by the handled amount with cleaning further subdivided by energy level. Harvesting and dumping resulted in the highest emissions. Regarding processes with liquids (SD3b), it was possible to distinguish emissions for spraying (propellant gas, (high) pressure and pump), sonication and brushing/rolling. The highest emissions observed in SD3b were for propellant gas spraying and pressure spraying. The highest emissions for the handling of nano-articles (SD4) were found to nano-sized particles (including NOAA) for grinding. This study provides a valuable overview of emission assessments performed in the workplace during the occupational handling of NOAA. Analyses were made per source domain to derive emission levels which can be used for models to quantitatively predict the exposure. [ABSTRACT FROM PUBLISHER]

Most of the conventional models require rainfall data for realistic modeling results, and where ground data is scarce, remotely sensed data plays a vital role. For monitoring, hydrological models require near real-time observations to allow for effective planning and forecasting. However, monitoring rainfall in mountainous region is difficult because of inaccessibility and sparse gauge density. However, the accurateness of these satellite estimates over different spatial and temporal scales is unknown. The study intended at carrying out a comparative analysis of satellite rainfall estimates as a substitution for ground-based rainfall observations in the Swat Catchment. Limited availability of temporally continuous available data records in Pakistan has been a problem and has effected the reliability of modeling results. As well as, data is not freely available and cost is the biggest hindrance to its usage. So, remotely sensed data plays a vital role both in terms of timely availability and its free of charge. For this region, only two remotely sensed gridded data products are freely available, i.e., NOAA RFE CA and TRMM RT. Respective two products have been analyzed by various verification statistics. RFE CA proves better probability of detection, false alarm ratio, threat score, and equitable threat score than TRMM RT. The outcome of this comparative study concludes that for hydrological modeling purposes, RFE CA data is the best choice in this region. The annual bias for RFE CA and TRMM RT is 14% (over-estimation) and 18% (under-estimation) over the years having coefficient of determination with the ground-based data of 0.87 and 0.76, respectively, on annual basis. The result shows the suitability of RFE CA for effective monthly rainfall-runoff modeling in Swat Catchment, Khyber Pakhtunkhawa, Pakistan. [ABSTRACT FROM AUTHOR]

Chemical compatibility is a key consideration throughout the chemical industry wherever two or more chemicals have the potential to mix, either inadvertently or by design. One of the most comprehensive tools available for determining chemical compatibility, the NOAA Chemical Reactivity Worksheet (CRW), has gained significant traction since the release of the third version (CRW3) in 2012. In 3 years, this free software has been downloaded >200,000 times and has become the chemical compatibility tool of choice at many organizations. As a result of an ongoing partnership between the National Oceanic and Atmospheric Administration (NOAA), The Dow Chemical Company, The Center for Chemical Process Safety (CCPS), Materials Technology Institute (MTI) and other industrial/academic/government volunteers, a fourth version of the CRW (CRW4) has been developed. The expanded capabilities of this new version include a materials of construction section, improved import/exporting/data sharing capabilities, additional reactive groups to aid in determining compatibility decisions, several user interface enhancements, along with the correction of minor issues found in the CRW3. This article will describe past development, the new features included in the CRW4, followed by a brief discussion of future development plans for the software tool. Such developments should solidify this tool's position as the gold standard within the chemical industry for determining chemical hazards. © 2016 American Institute of Chemical Engineers Process Saf Prog 36: 24-29, 2017 [ABSTRACT FROM AUTHOR]

Background: Nano-specific inhalation exposure models could potentially be effective tools to assess and control worker exposure to nano-objects, and their aggregates and agglomerates (NOAA). However, due to the lack of reliable and consistent collected NOAA exposure data, the scientific basis for validation of the existing NOAA exposure models is missing or limited. The main objective of this study was to gain more insight into the effect of various determinants underlying the potential on the concentration of airborne NOAA close to the source with the purpose of providing a scientific basis for existing and future exposure inhalation models. Method: Four experimental studies were conducted to investigate the effect of 11 determinants of emission on the concentration airborne NOAA close to the source during dumping of ~100% nanopowders. Determinants under study were: nanomaterial, particle size, dump mass, height, rate, ventilation rate, mixing speed, containment, particle surface coating, moisture content of the powder, and receiving surface. The experiments were conducted in an experimental room (19.5 m³) with well-controlled environmental and ventilation conditions. Particle number concentration and size distribution were measured using real-time measurement devices. Results: Dumping of nanopowders resulted in a higher number concentration and larger particles than dumping their reference microsized powder (P < 0.05). Statistically significant more and larger particles were also found during dumping of SiO2 nanopowder compared to TiO2/Al2O3 nanopowders. Particle surface coating did not affect the number concentration but on average larger particles were found during dumping of coated nanopowders. An increase of the powder's moisture content resulted in less and smaller particles in the air. Furthermore, the results indicate that particle number concentration increases with increasing dump height, rate, and mass and decreases when ventilation is turned on. Discussion: These results give an indication of the direction and magnitude of the effect of the studied determinants on concentrations close to the source and provide a scientific basis for (further) development of existing and future NOAA inhalation exposure models. [ABSTRACT FROM AUTHOR]

In this study, daily maps of snow cover distribution and sea ice extent produced by NOAA’s interactive multisensor snow and ice mapping system (IMS) were validated using in situ snow depth data from observing stations obtained from NOAA’s National Climatic Data Center (NCDC) for calendar years 2006 to 2010. IMS provides daily maps of snow and sea ice extent within the Northern Hemisphere using data from combination of geostationary and polar orbiting satellites in visible, infrared and microwave spectrums. Statistical correspondence between the IMS and in situ point measurements has been evaluated assuming that ground measurements are discrete and continuously distributed over a 4 km IMS snow cover maps. Advanced Very High Resolution Radiometer (AVHRR) land and snow classification data are supplemental datasets used in the further analysis of correspondence between the IMS product and in situ measurements. The comparison of IMS maps with in situ snow observations conducted over a period of four years has demonstrated a good correspondence of the data sets. The daily rate of agreement between the products mostly ranges between 80% and 90% during the Northern Hemisphere through the winter seasons when about a quarter to one third of the territory of continental US is covered with snow. Further, better agreement was observed for stations recording higher snow depth. The uncertainties in validation of IMS snow product with stationed NCDC data were discussed.

Land surface temperature (LST) is a significant parameter for many applications. Many studies have proposedvarious algorithms, such as the split-window method, for retrieving surface temperatures from two spectrallyadjacent thermal infrared bands of satellite data. Each algorithm is developed for a limited study area andapplication. In this paper, as part of developing an optimal split-window method in the southeast of Tehran province,Iran, four commonly applied algorithms to retrieve the LST from AVHRR were compared. This study was carriedout in a wheat farm site located in the Pakdasht Agricultural Region. Measurements of LST over the farm were madewith a manual infrared radiometer at the time of NOAA overpass for 18 days of May to June 2004. These days werecloud free over the study area. A total of 18 NOAA images were acquired for the days that LST measurements weremade. The temperatures derived by the different split-window algorithms were compared to ground truthmeasurements. The performance of the split window algorithms was checked with three statistical indices: root meansquare error (RMSE), mean bias error (MBE) and coefficient of determination (R2). The results showed that theUlivieri split-window algorithm produced the lowest value of RMSE and MBE (2.71 and 0.26 K, respectively) andits highest value of R2 (0.92) gave more accurate results than the other algorithms.

This research was conducted to understand monthly characteristic and variability of surface wind circulation over the Indian Ocean. The method used in this research was descriptive analysis. The data used was the monthly direction and velocity of surface wind obtained from the National Oceanic and Atmospheric Administration. The result showed that the monthly variability of surface wind circulation over the Indian Ocean is influenced by movement of the sun. The change in the variability of surfacewind circulation was more in the northern hemisphere, but vice versa surface wind circulation in the southern hemisphere was constant during the year. Generally, velocity of surface wind circulation was the greatest occurred in July and was the weakness occurred in April.

Two multispectral threshold techniques have been developed and tested for the automatic classification of AVHRR/NOAA and SEVIRI/Meteosat-10 data. They provide day-and-night detection and the assessment of cloud-cover parameters, as well as the discrimination of precipitation zones and severe weather phenomena. The validation of output information products, which has been performed with ground-based conventional meteorological observations and radar data, as well as with independent satellite-based estimates of cloud cover and precipitation parameters, confirms the feasibility of developed techniques and reasonable accuracy of output products. Therefore, the technique is concurrent to those implemented in current foreign satellite centers. [ABSTRACT FROM AUTHOR]

In a 1988 study, a generalized non-linear SST algorithm was derived from the radiative transfer equation. An empirical approximation to this algorithm provided the simplified NLSST algorithm for computing sea surface temperatures with satellite radiometer data. It has remained a favorite of the remote sensing community for the past 25 years. However, a 1998 study demonstrated that the functional form of the generalized non-linear algorithm, which is here designated the GNLSST, is very much data dependent. In this paper we explore the various functional forms that the GNLSST may take. Rather than using actual satellite data, we model the effects of atmospheric absorption by water vapor, under saturation conditions, on the satellite split-window temperature difference, ΔT, in the 11–13 μm infra-red spectral region. The parameters used in the GNLSST algorithm are adjusted to demonstrate the various forms that the GNLSST can take. One key finding is that the familiar algorithms used for measuring SST, such as the MCSST, the NLSST and the QSST are all special solutions to the more general GNLSST algorithm. Additionally, the GNLSST may take other forms, which are described graphically. The simplifying assumptions which yield the NLSST solution represent an approximation to reality when working with actual satellite data. It is demonstrated that minor modifications to the regression procedures, which are used to derive the NLSST with satellite split-window data, may reduce the temperature errors resulting from these approximations. Alternative forms of the GNLSST algorithm may be useful for users of regional split-window satellite data. [ABSTRACT FROM AUTHOR]

Background: Control banding can be used as a first-tier assessment to control worker exposure to nano-objects and their aggregates and agglomerates (NOAA). In a second tier, more advanced modelling approaches are needed to produce quantitative exposure estimates. As currently no general quantitative nano-specific exposure models are available, this study evaluated the validity and applicability of using a generic exposure assessment model (the Advanced REACH Tool--ART) for occupational exposure to NOAA. Method: The predictive capability of ART for occupational exposure to NOAA was tested by calculating the relative bias and correlations (Pearson) between the model estimates and measured concentrations using a dataset of 102 NOAA exposure measurements collected during experimental and workplace exposure studies. Results: Moderate to (very) strong correlations between the ART estimates and measured concentrations were found. Estimates correlated better to measured concentration levels of dust (r = 0.76, P < 0.01) than liquid aerosols (r = 0.51, P = 0.19). However, ART overestimated the measured NOAA concentrations for both the experimental and field measurements (factor 2--127). Overestimation was highest at low concentrations and decreased with increasing concentration. Correlations seemed to be better when looking at the nanomaterials individually compared to combined scenarios, indicating that nanomaterial-specific characteristics are not well captured within the mechanistic model of the ART. Discussion: Although ART in its current state is not capable to estimate occupational exposure to NOAA, the strong correlations for the individual nanomaterials indicate that the ART (and potentially other generic exposure models) have the potential to be extended or adapted for exposure to NOAA. In the future, studies investigating the potential to estimate exposure to NOAA should incorporate more explicitly nanomaterial-specific characteristics in their models. [ABSTRACT FROM AUTHOR]

The European Landscape Convention encourages the inventory and characterization of landscapes for environmental management and planning actions. Among the range of data sources available for landscape classification, remote sensing has substantial applicability, although difficulties might arise when available data are not at the spatial resolution of operational interest. We evaluated the applicability of two remote sensing products informing on land cover (the categorical CORINE map at 30 m resolution and the continuous NDVI spectral index at 1 km resolution) in landscape classification across a range of spatial resolutions (30 m, 90 m, 180 m, 1 km), using the Cantabrian Mountains (NW Spain) as study case. Separate landscape classifications (using topography, urban influence and land cover as inputs) were accomplished, one per each land cover dataset and spatial resolution. Classification accuracy was estimated through confusion matrixes and uncertainty in terms of both membership probability and confusion indices. Regarding landscape classifications based on CORINE, both typology and number of landscape classes varied across spatial resolutions. Classification accuracy increased from 30 m (the original resolution of CORINE) to 90m, decreasing towards coarser resolutions. Uncertainty followed the opposite pattern. In the case of landscape classifications based on NDVI, the identified landscape patterns were geographically structured and showed little sensitivity to changes across spatial resolutions. Only the change from 1 km (the original resolution of NDVI) to 180 m improved classification accuracy. The value of confusion indices increased with resolution. We highlight the need for greater effort in selecting data sources at the suitable spatial resolution, matching regional peculiarities and minimizing error and uncertainty. [ABSTRACT FROM AUTHOR]

Introduction: An increased production and use of carbon nanotubes (CNTs) is occurring worldwide. In parallel, a growing concern is emerging on the adverse effects the unintentional inhalation of CNTs can have on humans. There is currently a debate regarding which exposure metrics and measurement strategies are the most relevant to investigate workplace exposures to CNTs. This study investigated workplace CNT emissions using a combination of time-integrated filter sampling for scanning electron microscopy (SEM) and direct reading aerosol instruments (DRIs). Material and Methods: Field measurements were performed during small-scale manufacturing of multiwalled carbon nanotubes using the arc discharge technique. Measurements with highly time- and size-resolved DRI techniques were carried out both in the emission and background (far-field) zones. Novel classifications and counting criteria were set up for the SEM method. Three classes of CNT-containing particles were defined: type 1: particles with aspect ratio length:width >3:1 (fibrous particles); type 2: particles without fibre characteristics but with high CNT content; and type 3: particles with visible embedded CNTs. Results: Offline sampling using SEM showed emissions of CNT-containing particles in 5 out of 11 work tasks. The particles were classified into the three classes, of which type 1, fibrous CNT particles contributed 37%. The concentration of all CNT-containing particles and the occurrence of the particle classes varied strongly between work tasks. Based on the emission measurements, it was assessed that more than 85% of the exposure originated from open handling of CNT powder during the Sieving, mechanical work-up, and packaging work task. The DRI measurements provided complementary information, which combined with SEM provided information on: (i) the background adjusted emission concentration from each work task in different particle size ranges, (ii) identification of the key procedures in each work task that lead to emission peaks, (iii) identification of emission events that affect the background, thereby leading to far-field exposure risks for workers other than the operator of the work task, and (iv) the fraction of particles emitted from each source that contains CNTs. Conclusions: There is an urgent need for a standardized/harmonized method for electron microscopy (EM) analysis of CNTs. The SEM method developed in this study can form the basis for such a harmonized protocol for the counting of CNTs. The size-resolved DRI techniques are commonly not specific enough to selective analysis of CNT-containing particles and thus cannot yet replace offline time-integrated filter sampling followed by SEM. A combination of EM and DRI techniques offers the most complete characterization of workplace emissions of CNTs today. [ABSTRACT FROM AUTHOR]

Today, nanoparticles are used in many products. One of the most common nanoparticles is titanium dioxide (TiO 2 ). These particles generate reactive oxygen species (ROS) upon UV irradiation. Although nanoparticles are very useful in many products, there are concerns about their biological and ecological effects when released into the environment. Thus, it was assessed that the effect of TiO 2 nano-objects, and their aggregates and agglomerates greater than 100 nm (NOAA) on microbes under UV irradiation by using Escherichia coli and Saccharomyces cerevisiae . ROS generation was evaluated by adding TiO 2 nanoparticles and methylene blue to distilled water. We also assessed growth inhibition by adding TiO 2 nanoparticles and microbes in minimal agar medium. Moreover, microbial inactivation was assessed by adding TiO 2 nanoparticles and microbes to PBS. Upon UV irradiation, TiO 2 -NOAAs decomposed methylene blue and generated ROS. TiO 2 -NOAAs also decomposed methylene blue in minimal agar medium under UV irradiation; however, they did not inhibit microbial growth. Surprisingly, TiO 2 -NOAAs in the medium protect microbes from UV irradiation as colony formation was observed only near TiO 2 -NOAAs. In PBS, TiO 2 -NOAAs did not inactivate microbes but instead protected microbes from lethal UV irradiation. These results suggest that the amount of ROS generated by TiO 2 -NOAAs is not enough to inactivate microbes. In fact, our results suggest that TiO 2 -NOAAs may protect microbes from UV irradiations. [ABSTRACT FROM AUTHOR]

The United States’ National Oceanic and Atmospheric Administration (NOAA) operates over one hundred observing systems and numerical models providing information and forecasts about the planetary environment from the bottom of the ocean to the surface of the Sun. Collected NOAA data constitute an irreplaceable resource that must be well-documented, discoverable, accessible, and preserved for future use. Good data management should therefore be part of NOAA's core business practices, and employees and leadership should be aware of their roles and responsibilities in this arena. NOAA has developed an Environmental Data Management (EDM) Framework document that discusses Principles, Governance, Resources, Standards, Architecture, Assessment, and the Data Lifecycle, and which also enumerates specific recommendations. The NOAA EDM Committee has issued Directives pertaining to data management planning, archiving, data access, metadata, and other topics. A Data Catalog has been established, and a project to assign persistent, citable identifiers to archival data is well underway. Numerous groups at NOAA are performing technical work related to data access, usability, and preservation. The purpose of this article is to describe these documents and activities in order to share our experiences and to provide guidance and encouragement for improved data management practices and processes at other organizations. [ABSTRACT FROM AUTHOR]

With the renewed interest in regional Tsunami Warning Systems and the potential tsunami threats throughout the Caribbean and West coast of the United States, the National Ocean Service (NOS), National Water Level Observation Network (NWLON) consisting of 175 primary stations, is well situated to play a role in the National Hazard Mitigation effort. In addition, information regarding local mean sea level trends and GPS derived geodetic datum relationships at numerous coastal locations is readily available for tsunami hazard assessment and mapping applications.Tsunami inundation maps and modeling are just two of the more important products which may be derived from NWLON data. In addition to the seven water level gauges that are hardwired into the West Coast and Alaska Tsunami Warning Center (WClATWC), NOS has a significant number of gauges with real-time satellite telemetry capabilities located along the Pacific Northwest coastline, the Gulf of Mexico and the Caribbean. These gauges, in concert with near shore buoy systems, have the potential for increasing the effectiveness of the existing tsunami warning system.The recent expansion of the Caribbean Sea Level Gauge Network through the NOS regional partnerships with Central American and Caribbean countries have opened an opportunity for a basin-wide tsunami warning network in a region which is ill prepared for a major tsunami event.

Background: Occupational exposure to manufactured nano-objects and their agglomerates, and aggregates (NOAA) has been described in several workplace air monitoring studies. However, data pooling for general conclusions and exposure estimates are hampered by limited exposure data across the occupational life cycle of NOAA and a lack in comparability between the methods of collecting and analysing the data. By applying a consistent method of collecting and analysing the workplace exposure data, this study aimed to provide information about the occupational NOAA exposure levels across various life cycle stages of NOAA in the Netherlands which can also be used for multi-purpose use. Methods: Personal/near field task-based exposure data was collected using a multi-source exposure assessment method collecting real time particle number concentration, particle size distribution (PSD), filter-based samples for morphological, and elemental analysis and detailed contextual information. A decision logic was followed allowing a consistent and objective way of analysing the exposure data. Results: In total, 46 measurement surveys were conducted at 15 companies covering 18 different exposure situations across various occupational life cycle stages of NOAA. Highest activity-effect levels were found during replacement of big bags (<1000-76 000 # cm−3), mixing/dumping of powders manually (<1000-52 000 # cm−3) and mechanically (<1000-100 000 # cm−3), and spraying of liquid (2000-800 000 # cm−3) showing a high variability between and within the various exposure situations. In general, a limited change in PSD was found during the activity compared to the background. Conclusions: This broad-scale exposure study gives a comprehensive overview of the NOAA exposure situations in the Netherlands and an indication of the levels of occupational exposure to NOAA across various life cycle of NOAA. The collected workplace exposure data and contextual information will serve as basis for future pooling of data and modelling of worker exposure. [ABSTRACT FROM AUTHOR]

The National Oceanic and Atmospheric Administration's (NOAA) mission is to monitor, assess, and predict an ever-changing environment that extends from the bottom of the ocean to the surface of the sun. The National Environmental Satellite, Data, and Information Service (NESDIS) operates a fleet of environmental satellites that provide observations and measurements critical for this assessment of the Earth-sun system, including data for real-time monitoring of severe weather events and for developing numerical prediction models and forecasts. NESDIS also archives the data collected so users can access historical satellite data on atmosphere, land, and oceans dating back to the 1970s and in situ data going back centuries in order to improve our understanding of Earth's climate system. Because the World Ocean is one of the most important drivers of weather and climate on the planet, NOAA satellites provide global data for operational products that affect Earth's ocean ecosystems, including coral bleaching alert areas, detecting harmful algal blooms, and monitoring sea ice. With its high-volume data centers, NESDIS provides access to the world's most comprehensive sources of marine environmental data and information. This paper provides a brief history of NOAA satellites and an overview of the satellites currently in operation. Then, it focuses on satellite data and products that come together to monitor Earth's oceans and provide support for tropical storm monitoring, El Niño Southern Oscillation research, and ocean ecosystem monitoring. The paper concludes with a look toward NOAA's next generation of satellites thatwill be launching in the coming years and their effect on ocean monitoring. [ABSTRACT FROM AUTHOR]

The National Ocean Service (NOS), a line office of the National Oceanic and Atmospheric Administration (NOAA), is the nation's ocean and coastal agency. Our activities span a broad range that includes charting our nation's coastline; defining the National Spatial Reference System; providing the national network of coastal tide and water level sensors; serving as the lead federal agency of the U.S. Integrated Ocean Observing System; administering the Coastal Zone Management Program; providing the scientific foundation and socioeconomic information to local, state, and regional decision makers to adapt to the impacts of coastal hazards and climate change; serving as the authoritative resource for science related to debris, oil, and chemical spills; managing marine sanctuaries; and supporting the management of estuarine research reserves, coral reefs, and marine protected areas. Today, our coasts and coastal communities face increasingly significant impacts of higher intensity coastal storms; changing sea levels and Great Lakes levels; increased coastal development; increased demand on natural resources and infrastructure; and increased demands on our marine transportation system. In response to these issues, NOS aligns its activities along three priorities: (1) supporting coastal resilience; (2) advancing coastal intelligence; and (3) promoting place-based conservation. NOS relies on coastal observations and data products to carry out our mission. Characteristics of future coastal observations include lower cost coupled with greater efficiency, diverse platforms, multiuse data collection, and crowdsourcing. Data products will need to be increasingly geographically tailored; result from a greater degree of coordination and integration; and result in greater data access. [ABSTRACT FROM AUTHOR]

Shipboard measurements from late 2006 made by the Danish Galathea 3 Expedition and satellite sea surface temperature images revealed a chain of cool and warm 'mushroom' dipole vortices that mixed warm, salty, oxygen-poor waters on and near the continental shelf of the Great Australian Bight (GAB) with cooler, fresher, oxygen-rich waters offshore. The alternating 'jets' flowing into the mushrooms were directed mainly northwards and southwards and differed in temperature by only 1.5°C; however, the salinity difference was as much as 0.5, and therefore quite large. The GAB waters were slightly denser than the cooler offshore waters. The field of dipoles evolved and distorted, but appeared to drift westwards at 5 km day-1 over two weeks, and one new mushroom carried GAB water southwards at 7 km day-1. Other features encountered between Cape Leeuwin and Tasmania included the Leeuwin Current, the South Australian Current, the Flinders Current and the waters of Bass Strait. In 2006 the third Danish 'Galathea' Expedition (the earlier expeditions were in 1845/47 and 1950/52) detected puzzling water property variations across the Great Australian Bight. Satellite temperature images linked the variations to alternating north-south jets connected to large mushroom-shaped features that mixed waters from the continental shelf and open ocean. The Bight is frequented by tuna, whales and other creatures and is being explored for oil and gas. [ABSTRACT FROM AUTHOR]

This article describes the processes involved for the location of the Volcano of Colima in a NOAA satellite image by subtraction between the band T3 and T4 to calculate the effective temperature of the hot point and locate the pixel containing the volcano, after converting the digital values to temperature. Once the pixel is detected, the image is transformed by different interpolation methods and incorporating a DTM (Digital Terrain Model) to check its subpixel location in a NOAA image. This study provides a better understanding of the area and more precise studies of volcanic risks, thus serving as a basis for further analysis applied to environmental studies. [ABSTRACT FROM AUTHOR]