States Weather Research Articles

Воздействие космической погоды на наземные технологические системы

This review, offered for the first time in the Russian scientific literature, is devoted to various aspects of the problem of the space weather impact on ground-based technological systems. Particular attention is paid to hazards to operation of power transmission lines, railway automation, and pipelines caused by geomagnetically induced currents (GIC) during geomagnetic disturbances. The review provides information on the main characteristics of geomagnetic field variability, on rapid field variations during various space weather mani-festations. The fundamentals of modeling geoelectric field disturbances based on magnetotelluric sounding algorithms are presented. The approaches to the assessment of possible extreme values of GIC are considered. Information about economic effects of space weather and GIC is collected. The current state and prospects of space weather forecasting, risk assessment for technological systems from GIC impact are discussed. While in space geophysics various models for predicting the intensity of magnetic storms and their related geomagnetic disturbances from observations of the interplanetary medium are being actively developed, these models cannot be directly used to predict the intensity and position of GIC since the description of the geomagnetic field variability requires the development of additional models. Revealing the fine structure of fast geomagnetic variations during storms and substorms and their induced GIC bursts appeared to be important not only from a practical point of view, but also for the development of fundamentals of near-Earth space dynamics. Unlike highly specialized papers on geophysical aspects of geomagnetic variations and engineering aspects of the GIC impact on operation of industrial transformers, the review is designed for a wider scientific and technical audience without sacrificing the scientific level of presentation. In other words, the geophysical part of the review is written for engineers, and the engineering part is written for geophysicists. Despite the evident applied orientation of the studies under consideration, they are not limited to purely engineering application of space geophysics results to the calculation of possible risks for technological systems, but also pose a number of fundamental scientific problems.

Space weather impact on ground-based technological systems

This review, offered for the first time in the Russian scientific literature, is devoted to various aspects of the problem of the space weather impact on ground-based technological systems. Particular attention is paid to hazards to operation of power transmission lines, railway automation, and pipelines caused by geomagnetically induced currents (GIC) during geomagnetic disturbances. The review provides information on the main characteristics of geomagnetic field variability, on rapid field variations during various space weather mani-festations. The fundamentals of modeling geoelectric field disturbances based on magnetotelluric sounding algorithms are presented. The approaches to the assessment of possible extreme values of GIC are considered. Information about economic effects of space weather and GIC is collected. The current state and prospects of space weather forecasting, risk assessment for technological systems from GIC impact are discussed. While in space geophysics various models for predicting the intensity of magnetic storms and their related geomagnetic disturbances from observations of the interplanetary medium are being actively developed, these models cannot be directly used to predict the intensity and position of GIC since the description of the geomagnetic field variability requires the development of additional models. Revealing the fine structure of fast geomagnetic variations during storms and substorms and their induced GIC bursts appeared to be important not only from a practical point of view, but also for the development of fundamentals of near-Earth space dynamics. Unlike highly specialized papers on geophysical aspects of geomagnetic variations and engineering aspects of the GIC impact on operation of industrial transformers, the review is designed for a wider scientific and technical audience without sacrificing the scientific level of presentation. In other words, the geophysical part of the review is written for engineers, and the engineering part is written for geophysicists. Despite the evident applied orientation of the studies under consideration, they are not limited to purely engineering application of space geophysics results to the calculation of possible risks for technological systems, but also pose a number of fundamental scientific problems.

A Forecaster’s Story: Robert H. Johns

The stages in the life of a severe storms forecaster, Robert H. Johns, are reconstructed from information in a series of interviews. The traditional interview format, question-and-answer mode, has been converted to a first-person narrative that leads to a more-continuous train of thought.
 The storyline begins by describing Johns’ entrainment into meteorology as a youngster. By virtue of his contact and conversations with farmers in rural Indiana, he became interested in weather’s impact on the farmers and their crop yields. Early stimulation also came from a challenging weather project in the 6th grade and reading of George Stewart’s novel Storm. From these experiences, Bob Johns decided to pursue a science career in service to society. This service took the form of work as a weather forecaster for the United States Weather Bureau (USWB)/National Weather Service (NWS).
 The arduous path to severe storms forecaster is traced by highlighting his youthful experiences, his academic training, and the stepwise progression from student trainee to lead forecaster at the Severe Local Storms (SELS) unit of the USWB/NWS.

An experimental study on characteristics of impact compression of freeze–thawed granite samples under four different states considering moisture content and temperature difference

The mechanics of rock masses in cold regions have attracted the attention of researchers from all over the world, and the concern here is that the mechanical properties of rock masses are inevitably weakened under freeze–thaw cycles. In this paper, first, granite samples were subjected to different freeze–thaw cycles, and then treated in four different states, such as saturated and frozen states, saturated and normal temperature states, dry and frozen states, as well as dry and normal temperature states. The impact compression test was carried out using the Split Hopkinson Pressure Bar (SHPB) device. Results show that the impact strength of granite samples deteriorates with the increase of freeze–thaw cycles in the same state; for samples in different states, although the number of freeze–thaw cycles is equal, the degree of deterioration of the impact strength is different. For freeze–thawed granite samples in the same state, the dynamic elastic modulus decreases with the increase of freeze–thaw cycles, and its degree of decrease is different for different states. Under the same freeze–thaw cycles, the deterioration of mechanical properties of granite samples is different in four different weather states; for example, the dynamic elastic modulus from large to small is generally as follows: saturated and frozen states, saturated and normal temperature states, dry and frozen states, as well as dry and normal temperature states. Finally, the freeze–thaw influence factor is proposed to describe the damage of granite samples. All in all, it can be concluded that water and low temperature strengthen the influence of freeze–thaw cycles on the dynamic mechanical properties of granite.

Mesoscale Structure in the Solar Wind

Structures in the solar wind result from two basic mechanisms: structures injected or imposed directly by the Sun, and structures formed through processing en route as the solar wind advects outward and fills the heliosphere. On the largest scales, solar structures directly impose heliospheric structures, such as coronal holes imposing high speed streams of solar wind. Transient solar processes can inject large-scale structure directly into the heliosphere as well, such as coronal mass ejections. At the smallest, kinetic scales, the solar wind plasma continually evolves, converting energy into heat, and all structure at these scales is formed en route. “Mesoscale” structures, with scales at 1 AU in the approximate spatial range of 5–10,000 Mm and temporal range of 10 s–7 h, lie in the orders of magnitude gap between the two size-scale extremes. Structures of this size regime are created through both mechanisms. Competition between the imposed and injected structures with turbulent and other evolution leads to complex structuring and dynamics. The goal is to understand this interplay and to determine which type of mesoscale structures dominate the solar wind under which conditions. However, the mesoscale regime is also the region of observation space that is grossly under-sampled. The sparse in situ measurements that currently exist are only able to measure individual instances of discrete structures, and are not capable of following their evolution or spatial extent. Remote imaging has captured global and large scale features and their evolution, but does not yet have the sensitivity to measure most mesoscale structures and their evolution. Similarly, simulations cannot model the global system while simultaneously resolving kinetic effects. It is important to understand the source and evolution of solar wind mesoscale structures because they contain information on how the Sun forms the solar wind, and constrains the physics of turbulent processes. Mesoscale structures also comprise the ground state of space weather, continually buffeting planetary magnetospheres. In this paper we describe the current understanding of the formation and evolution mechanisms of mesoscale structures in the solar wind, their characteristics, implications, and future steps for research progress on this topic.

Stability assessment of obliquely-bedded rock cuts using multi-prong procedures – case study

The stability of vertical cuts in rocky strata, associated with the provision of the transportation infrastructure through a mountainous terrain, is always a challenge for the geotechnical engineers. The problem becomes further complex if the cuts are parallel or near parallel to the bedding planes. Such a scenario results in all sorts of slope instability scenarios, including planar, wedge, rockfall, and toppling failure. A linear project was planned to pass through the mountainous stretches of western Saudi Arabia. The rock slopes exposed at the site after the excavations constitute igneous origin Granite/Granodiorite rock present in a moderately to highly weathered state and consist of two sets of discontinuities; one running almost parallel to slope faces and another nearly orthogonal to the major set of discontinuities. Based on the orientation of the discontinuities along the cuts on both the sides of the excavation, there is a high probability of all types of slope failures, including planar, wedge, toppling, or boulder/rockfall. This paper presents details of geologic field mapping, field and laboratory testing, and the software analysis of several modes of the possible slope failure modes. The study was carried out considering all the potential triggering factors, including rainfall, under both static and dynamic/seismic conditions. The paper also discusses the slope failure prevention measures recommended based on the interpretation of the field and laboratory data, software analysis, and the construction sequence.

Constitutive model of structural alteration and swelling behavior for Old Alluvium

We describe a constitutive model for the compression and swelling behavior of Old Alluvium, a material with a complex microstructure characterized by Fe-oxides cementation and silt-sized aggregates of swelling clay minerals. Compression loading of this material breaks down the aggregate structure, altering the mineralogy, particle fracture properties, and physicochemical properties. We use cation exchange capacity as a measurable proxy to represent the microstructural evolution that can be linked to changes in compressibility with consolidation stress. At load reversal, the value of cation exchange capacity affects the microscale swelling pressures associated with osmotic repulsion between platelets of expansive nontronite. The micro- and macro-scale stiffnesses are linked through a parameter that relates the disjoining pressure to the macroscopic swelling pressure, and an interaction function. By relating macroscopic strains to microscale osmotic repulsion between expansive clay platelets, the proposed model builds directly on the physicochemical characteristics of the material and achieves a more consistent physical basis for describing the unloading response than prior formulations. We illustrate how the model can provide a framework for interpreting how engineering properties vary vertically with the state of weathering in the Old Alluvium soil profile. This approach should find broader application for other piedmont, transported, residual soils.

Satellite soil moisture data assimilation impacts on modeling weather variables and ozone in the southeastern US – Part 1: An overview

Abstract. This study evaluates the impact of satellite soil moisture (SM) data assimilation (DA) on regional weather and ozone (O3) modeling over the southeastern US during the summer. Satellite SM data are assimilated into the Noah land surface model using an ensemble Kalman filter approach within National Aeronautics and Space Administration's Land Information System framework, which is semicoupled with the Weather Research and Forecasting model with online Chemistry (WRF-Chem; standard version 3.9.1.1). The DA impacts on the model performance of SM, weather states, and energy fluxes show strong spatiotemporal variability. Dense vegetation and water use from human activities unaccounted for in the modeling system are among the factors impacting the effectiveness of the DA. The daytime surface O3 responses to the DA can largely be explained by the temperature-driven changes in biogenic emissions of volatile organic compounds and soil nitric oxide, chemical reaction rates, and dry deposition velocities. On a near-biweekly timescale, the DA modified the mean daytime and daily maximum 8 h average surface O3 by up to 2–3 ppbv, with the maximum impacts occurring in areas where daytime surface air temperature most strongly (i.e., by ∼2 K) responded to the DA. The DA impacted WRF-Chem upper tropospheric O3 (e.g., for its daytime-mean, by up to 1–1.5 ppbv) partially via altering the transport of O3 and its precursors from other places as well as in situ chemical production of O3 from lightning and other emissions. Case studies during airborne field campaigns suggest that the DA improved the model treatment of convective transport and/or lightning production. In the cases that the DA improved the modeled SM, weather fields, and some O3-related processes, its influences on the model's O3 performance at various altitudes are not always as desirable. This is in part due to the uncertainty in the model's key chemical inputs, such as anthropogenic emissions, and the model representation of stratosphere–troposphere exchanges. This can also be attributable to shortcomings in model parameterizations (e.g., chemical mechanism, natural emission, photolysis and deposition schemes), including those related to representing water availability impacts. This study also shows that the WRF-Chem upper tropospheric O3 response to the DA has comparable magnitudes with its response to the estimated US anthropogenic emission changes within 2 years. As reductions in anthropogenic emissions in North America would benefit the mitigation of O3 pollution in its downwind regions, this analysis highlights the important role of SM in quantifying air pollutants' source–receptor relationships between the US and its downwind areas. It also emphasizes that using up-to-date anthropogenic emissions is necessary for accurately assessing the DA impacts on the model performance of O3 and other pollutants over a broad region. This work will be followed by a Noah-Multiparameterization (with dynamic vegetation)-based study over the southeastern US, in which selected processes including photosynthesis and O3 dry deposition will be the foci.

Cloud, Aerosol, and Radiative Properties Over the Western North Atlantic Ocean.

This study examines the atmospheric properties of weather states (WSs) derived from the International Satellite Cloud Climatology Project over the Western North Atlantic Ocean. In particular, radiation and aerosol data corresponding to two sites in the study domain, Pennsylvania State University and Bermuda, were examined to characterize the atmospheric properties of the various satellite-derived WSs. At both sites, the fair weather WS was most prevalent, followed by the cirrus WS. Differences in the seasonality of the various WSs were observed at the two sites. Fractional sky cover and effective shortwave cloud transmissivity derived from ground-based radiation measurements were able to capture differences among the satellite-derived WSs. Speciated aerosol optical thicknesses (AOT) from the Modern-Era Retrospective Analysis for Research and Applications, version 2 were used to investigate potential differences in aerosol properties among the WSs. The clear sky WS exhibited below-average seasonal values of AOT at both sites year-round, as well as relatively high rates of occurrence with low AOT events. In addition, the clear sky WS showed above-average contributions from dust and black carbon to the total AOT year-round. Finally, transitions between various WSs were examined under low, high, and midrange AOT conditions. The most common pathway was for the WSs to remain in the same state after a 3 h interval. Some WSs, such as mid latitude storms, deep convection, middle top, and shallow cumulus, were more prevalent as ending states under high AOT conditions. This work motivates examining differences in aerosol properties between WSs in other regions.

Geological influence on the index properties variability and shear strength probability density functions

Determining soil properties variability in geotechnical engineering is one of the most important tasks in reliability-based designs (RBDs). However, these analyses have been carried without taking into account the influence of the geological origin on the different aspects that alter the soil properties variability. Therefore, two types of geological formations are analysed: residual soils (stationary origin) and mudflows (dynamic origin). First, the index properties variability was evaluated for each geology, where mudflows are less variable in comparison with the residual soils. It was confirmed that the correlations of the effective friction angle should not be used for high-plasticity and fine-grained soils; however, the shape characteristics of the probability density functions (PDFs) of both effective and total parameters depend on the geological origin. The undrained compressive strength ( q u ) analyses show that geology influences the shape characteristics of the PDF and is directly proportional to the ( N 1 ) 60 PDF. From the results, mudflows have a q u PDF with a lognormal tendency, which is inferred to be due to the possible presence of rock fragments and randomness related to the soil's formation. However, the residual soils, under the same state of weathering, tend to have a normal q u PDF, possibly owing to the stationary origin of these soils. Supplementary material: Datasets are available at https://doi.org/10.6084/m9.figshare.c.5420240

Variations in the geomagnetic field that accompanied the 10 June 2021 solar eclipse

Urgency. At present, the existence of the geomagnetic effect of solar eclipses (SEs) is in question. The data presented in the literature are contradictory. Some researchers assert that the amplitude of the north-south component of the main geomagnetic field increases, while others that it decreases. The third group of researchers notes that this amplitude does not change at all, but instead the amplitude of the west-east component shows variations. In some cases, observations confirm the mechanism for the geomagnetic effect caused by disturbances in the Sq current system, while in other cases observations contradict with the mechanism. The difficulties that are encountered in observing the SE geomagnetic effect are caused by the fact that the magnetic field is subjected to the influence of many energy sources. The magnitude of the geomagnetic effect depends not only on the magnitude (phase) of the solar eclipse but also on the state of space weather, geographic coordinates of data acquisition, local time, season, etc. Therefore, the study of the geomagnetic effect from each new solar eclipse remains an urgent problem. The main feature of the 10 June 2021 Solar eclipse is its annularity. The maximum magnitude did not exceed 0.943, and the eclipse obscuration 89%. The aim of this work is to present the results of analysis of variations in the geomagnetic field that were recorded by the INTERMAGNET during the 10 June 2021 SE. Methods and Methodology. To analyze the effects in the main Earth’s magnetic field, the INTERMAGNET data have been utilized. The data have been analyzed from 15 magnetic observatories located between 77.47°-N and 48.17°-N latitude where the maximum phase varied from 0.943 to 0.124. The analysis was performed with 1-min temporal resolution providing a 0.1-nT resolution. To determine spectral content of the quasi-periodic variations, the systems spectral analysis has been used, which combines mutually complementary the short-time Fourier transform, the wavelet transform employing the Morlet wavelet as a basis function, and the Fourier transform in a sliding window with a width adjusted to be equal to a fixed number of harmonic periods. Results. An aperiodic geomagnetic effect of a solar eclipse has been detected and explained; it consists in a decrease by not greater than 30 nT in the level of the north-south component. The effect is explained by a variation in the ionospheric current density in the west-east direction as a result of a decrease in the electron density during the eclipse. A quasi-periodic geomagnetic effect of a solar eclipse has been revealed; it is explained by the generation of atmospheric gravity waves. The wave acts to modulate the ionospheric electric current, as well as to drag the electrons inducing additional quasi-periodic ionospheric current with a period equal to the wave period. The amplitude of the quasi-periodic variations was observed to be a few nanoteslas. The systems spectral analysis provided more precise values of periods of quasi-periodic variations in the geomagnetic field accompanying the solar eclipse, approximately 20 min and 35 min. Conclusions. The aperiodic and quasi-periodic geomagnetic effects are caused by the disturbance (generation) of the ionospheric current.

EVALUATION OF CLOUDS, RADIATION, AND PRECIPITATION IN CMIP6 MODELS USING GLOBAL WEATHER STATES DERIVED FROM ISCCP-H CLOUD PROPERTY DATA

AbstractA clustering methodology is applied to cloud optical depth cloud top pressure (TAU-PC) histograms from the new, 1-degree resolution, ISCCP-H dataset, to derive an updated global Weather State (WS) dataset. Then, PC-TAU histograms from current-climate CMIP6 model simulations are assigned to the ISCCP-H WSs along with their concurrent radiation and precipitation properties, to evaluate model cloud, radiation, and precipitation properties in the context of the Weather States. The new ISCCP-H analysis produces WSs that are very similar to those previously found in the lower resolution ISCCP-D dataset. The main difference lies in the splitting of the ISCCP-D thin stratocumulus WS between the ISCCP-H shallow cumulus and stratocumulus WSs, which results in the reduction by one of the total WS number. The evaluation of the CMIP6 models against the ISCCP-H Weather States, shows that, in the ensemble mean, the models are producing an adequate representation of the frequency and geographical distribution of the WSs, with measurable improvements compared to the WSs derived for the CMIP5 ensemble. However, the frequency of shallow cumulus clouds continues to be underestimated, and, in some WSs the good agreement of the ensemble mean with observations comes from averaging models that significantly overpredict and underpredict the ISCCP-H WS frequency. In addition, significant biases exist in the internal cloud properties of the model WSs, such as the model underestimation of cloud fraction in middle-top clouds and secondarily in midlatitude storm and stratocumulus clouds, that result in an underestimation of cloud SW cooling in those regimes.

Incorporating weather forecasts into risk-based irrigation decision-making

ABSTRACT Irrigation decision-making is complex. It requires balancing multiple risks . We examined if incorporation of weather forecasts into irrigation decision-making improved environmental and economic outcomes on dairy farms in Canterbury, New Zealand. We focused on understanding how farmers can manage irrigation decision-making with uncertain weather forecasts, and the associated impacts on drainage, pasture growth and economics. Previous work had demonstrated that weather conditions were not used in irrigation decision-making as much as desirable and that weather forecast uncertainty was not explicitly considered. , We incorporated weather forecasts as a perfect forecast and the best available forecast. We used probability percentiles to incorporate forecast uncertainty into decision-making. The research hypothesis was that through utilising risk profiles of factors that influence environmental and economic outcomes of irrigation decisions, farmers could improve decison-makingwhen faced with uncertain future weather states. When weather forecasts were integrated into irrigation decision-making, there were environmental and economic benefits relative to a simple deficit-based irrigation decision rule. Based on a case study, we predicted 5% additional profit (approximately, $200 per hectare) may be possible when the best available forecasts was used relative to a simple deficit-based decision rule, and a further 1% profit if forecast uncertainty was considered.

Predicting Weather Forecasting State Based on Data Mining Classification Algorithms

Weather forecasting is the process of predicting the status of the atmosphere for certain regions or locations by utilizing recent technology. Thousands of years ago, humans tried to foretell the weather state in some civilizations by studying the science of stars and astronomy. Realizing the weather conditions has a direct impact on many fields, such as commercial, agricultural, airlines, etc. With the recent development in technology, especially in the DM and machine learning techniques, many researchers proposed weather forecasting prediction systems based on data mining classification techniques. In this paper, we utilized neural networks, Naïve Bayes, random forest, and K-nearest neighbor algorithms to build weather forecasting prediction models. These models classify the unseen data instances to multiple class rain, fog, partly-cloudy day, clear-day and cloudy. These model performance for each algorithm has been trained and tested using synoptic data from the Kaggle website. This dataset contains (1796) instances and (8) attributes in our possession. Comparing with other algorithms, the Random forest algorithm achieved the best performance accuracy of 89%. These results indicate the ability of data mining classification algorithms to present optimal tools to predict weather forecasting.

Optimizing FSO networks resilient to adverse weather conditions by means of enhanced uncertainty sets

This work deals with dimensioning of wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry an acceptable level of the demanded traffic in all weather states that can be foreseen in network operation. Such a model can be achieved using robust optimization techniques, and for that it is important to find a tractable way of characterizing possible link (capacity) degradation states corresponding to weather conditions not known in advance. In the paper we show how the set of link degradation states may be represented mathematically in a compact and tractable way to be exploited in optimization. To solve this task we will make use of a generalization of a combinatorial problem of finding a minimum hitting set to deduce a compact set approximating a given set of link degradation states, (called uncertainty set). Finally, we provide a mathematical model with respect to a general form of uncertainty sets and illustrate the effectiveness of our model by means of a numerical study.

Impacts of swat weather generator statistics from high-resolution datasets on monthly streamflow simulation over Peninsular Spain

Study regionPeninsular Spain. Study focusWeather data are the key drivers of hydrological modelling. However, available weather data can present gaps in data sequences and are often limited in their spatial coverage for use in such hydrological models as the Soil and Water Assessment Tool (SWAT). To overcome this limitation, SWAT includes a weather generator algorithm that can complete this data based on long-term weather statistics. This work presents a newly developed weather statistics dataset for Peninsular Spain (PSWG), calculated from national gridded datasets according to the SWAT model format. PSWG provides a higher resolution that stands as a compelling alternative to the statistics calculated from the Climate Forecast System Reanalysis (CFSR) that are available on the SWAT website. New hydrological insights for the regionThe dataset has been evaluated using PSWG and CFSR datasets for different data availability scenarios to reconstruct weather series in three watersheds with contrasting weather climates. Results underscore the superiority of the PSWG dataset in reconstructing missing data for hydrological simulations. This approach provides a strong alternative for SWAT applications in Peninsular Spain and the applied methodology can be replicated in other countries that dispose of high-resolution gridded rainfall and temperature datasets.

Evaluation and Comparison of Current Emulsification Algorithms and Their Uncertainty in Oil Spill Modeling Software

Oil spill risk assessments (OSRAs) do not currently distinguish between potentially more toxic, fresh crude oil and less toxic, highly-weathered residues which limits the understanding of the highest risk areas to prioritize mitigation measures and allocate response resources. Fate and trajectory models, used commonly for OSRA, have advanced significantly over the last five years now with enhanced ability to model chemical and physical parameters at greater resolution. Using this enhanced resolution, modelers may be able to provide some indication of the weathered state of the oil as input to the OSRA. In order to evaluate the degree of certainty in such a prediction, it is necessary to better understand the uncertainty in the modeled weathering processes that influence the toxicity of the oil. Emulsification plays a significant role in modeling of oil thickness (and therefore photo-modification), evaporation, and dissolution which are important modulators of oil toxicity. In this project, the emulsification algorithms of three currently available fate and trajectory models, ADIOS, OILMAP/SIMAP, and OSCAR, were evaluated to gain a better understanding of the degree of certainty in the modeled weathered state of oil. In this work, the basis of emulsification algorithms implemented in the models referenced above were identified, and it was found that each of these models incorporates emulsification differently. ADIOS2 relies on emulsification data gathered from mixing oil and water in a food processor. An updated version of ADIOS2 (ADIOS3) is based on a new formulation that is dependent on measured SARA components of the oil, but is still under construction and is not yet implemented. OILMAP/SIMAP use the algorithm presented in Mackay and Zagorski (1982). OSCAR uses a water uptake algorithm that was calibrated to in-house laboratory experiments. Further investigation into the development of each of these emulsification algorithms provided insight into the degree of uncertainty in these models and their input parameters, and what oil types may not be appropriately characterized by the implemented emulsification model. Additionally, the impact of that uncertainty on oil fate was investigated by evaluating the changes in the amount of emulsification when modifying user input parameters within realistic assumption ranges. The findings and comparison of the implementation of these emulsification algorithms and the sensitivity of the results to different inputs is presented here.

S-SOM v1.0: a structural self-organizing map algorithm for weather typing

Abstract. This study proposes a novel structural self-organizing map (S-SOM) algorithm for synoptic weather typing. A novel feature of the S-SOM compared with traditional SOMs is its ability to deal with input data with spatial or temporal structures. In detail, the search scheme for the best matching unit (BMU) in a S-SOM is built based on a structural similarity (S-SIM) index rather than by using the traditional Euclidean distance (ED). S-SIM enables the BMU search to consider the correlation in space between weather states, such as the locations of highs or lows, that is impossible when using ED. The S-SOM performance is evaluated by multiple demo simulations of clustering weather patterns over Japan using the ERA-Interim sea-level pressure data. The results show the S-SOM's superiority compared with a standard SOM with ED (or ED-SOM) in two respects: clustering quality based on silhouette analysis and topological preservation based on topological error. Better performance of S-SOM versus ED is consistent with results from different tests and node-size configurations. S-SOM performs better than a SOM using the Pearson correlation coefficient (or COR-SOM), though the difference is not as clear as it is compared to ED-SOM.

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast—Part 2: Circulation, Boundary Layer, and Clouds

AbstractThe Western North Atlantic Ocean (WNAO) is a complex land‐ocean‐atmosphere system that experiences a broad range of atmospheric phenomena, which in turn drive unique aerosol transport pathways, cloud morphologies, and boundary layer variability. This work, Part 2 of a 2‐part paper series, provides an overview of the atmospheric circulation, boundary layer variability, three‐dimensional cloud structure, and precipitation over the WNAO; the companion paper (Part 1) focused on chemical characterization of aerosols, gases, and wet deposition. Seasonal changes in atmospheric circulation and sea surface temperature explain a clear transition in cloud morphologies from small shallow cumulus clouds, convective clouds, and tropical storms in summer, to stratus/stratocumulus and multilayer cloud systems associated with winter storms. Synoptic variability in cloud fields is estimated using satellite‐based weather states, and the role of postfrontal conditions (cold‐air outbreaks) in the development of stratiform clouds is further analyzed. Precipitation is persistent over the ocean, with a regional peak over the Gulf Stream path, where offshore sea surface temperature gradients are large and surface fluxes reach a regional peak. Satellite data show a clear annual cycle in cloud droplet number concentration with maxima (minima) along the coast in winter (summer), suggesting a marked annual cycle in aerosol‐cloud interactions. Compared with satellite cloud retrievals, four climate models qualitatively reproduce the annual cycle in cloud cover and liquid water path, but with large discrepancies across models, especially in the extratropics. The paper concludes with a summary of outstanding issues and recommendations for future work.

Examining the role of wind in\xa0human illness due to pesticide drift in Washington state, 2000\u20132015

BackgroundPesticides play an important role in protecting the food supply and the public’s health from pests and diseases. By their nature, pesticides can be toxic to unintended target organisms. Changing winds contribute to pesticide drift— the off-target movement of pesticides—and can result in occupational and bystander illness.MethodsWe systematically linked historical weather data to documented pesticide drift illnesses. We used Washington State Department of Health data to identify 252 drift events that included 690 confirmed cases of illness from 2000 to 2015. To characterize wind speed and direction at the time of the events, we paired these data with meteorological data from a network of 171 state weather stations. We report descriptive statistics and the spatio-temporal extent of drift events and compare applicator-reported weather conditions to those from nearby meteorological stations.ResultsMost drift events occurred in tree fruit (151/252 = 60%). Ground spraying and aerial applications accounted for 68% and 23% of events, respectively; 69% of confirmed cases were workers, and 31% were bystanders. Confirmed cases were highest in 2014 (129) from 22 events. Complete applicator spray records were available for 57 drift events (23%). Average applicator-reported wind speeds were about 0.9 m •sec− 1 (2 mi •hr− 1) lower than corresponding speeds from the nearest weather station values.ConclusionsDrift events result from a complex array of factors in the agricultural setting. We used known spatio-temporal aspects of drift and historical weather data to characterize these events, but additional research is needed to put our findings into practice. Particularly critical for this analysis is more accurate and complete information about location, time, wind speed, and wind direction. Our findings can be incorporated into new training materials to improve the practice of pesticide application and for better documentation of spray drift events. A precision agriculture approach offers technological solutions that simplify the task of tracking pesticide spraying and weather conditions. Public health investigators will benefit from improved meteorological data and accurate application records. Growers, applicators, and surrounding communities will also benefit from the explanatory and predictive potential of wind ramping studies.