Artykuły w czasopismach na temat „Weather states”
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1
Craft, Erik D. "Private Weather Organizations and the Founding of the United States Weather Bureau". Journal of Economic History 59, nr 4 (grudzień 1999): 1063–71. http://dx.doi.org/10.1017/s0022050700024141.
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Goodman, Christopher J., i Jennifer D. Small Griswold. "Meteorological Impacts on Commercial Aviation Delays and Cancellations in the Continental United States". Journal of Applied Meteorology and Climatology 58, nr 3 (marzec 2019): 479–94. http://dx.doi.org/10.1175/jamc-d-17-0277.1.
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AbstractWeather creates numerous operational and safety hazards within the National Airspace System (NAS). In 2014, extreme weather events attributed 4.3% to the total number of delay minutes recorded by the Bureau of Transportation Statistics. When factoring weather’s impact on the NAS delays and aircraft arriving late delays, weather was responsible for 32.6% of the total number of delay minutes recorded. Hourly surface meteorological aviation routine weather reports (METARs) at major airports can be used to provide valuable insight into the likely causes of weather delays at individual airports. When combined with the Federal Aviation Administration’s (FAA’s) Operations Network (OPSNET) delay data, METARs can be used to identify the major causes of delays and to create delay climatologies for a specific airport. Also, patterns for delays and cancellations for the study period of 2003–15 can be identified for the individual airports included in this study. These patterns can be useful for operators and airport planners to optimize performance in the future.
3
Monmonier, Mark. "Telegraphy, iconography, and the weather map: Cartographic weather reports by the United States Weather Bureau, 1870–1935". Imago Mundi 40, nr 1 (styczeń 1988): 15–31. http://dx.doi.org/10.1080/03085698808592636.
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Simmering, Jacob E., Linnea A. Polgreen, Douglas B. Hornick, Daniel K. Sewell i Philip M. Polgreen. "Weather-Dependent Risk for Legionnaires’ Disease, United States". Emerging Infectious Diseases 23, nr 11 (listopad 2017): 1843–51. http://dx.doi.org/10.3201/eid2311.170137.
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Maddox, Robert A., Jian Zhang, Jonathan J. Gourley i Kenneth W. Howard. "Weather Radar Coverage over the Contiguous United States". Weather and Forecasting 17, nr 4 (sierpień 2002): 927–34. http://dx.doi.org/10.1175/1520-0434(2002)017<0927:wrcotc>2.0.co;2.
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LeComte, Doug. "Weather of 1990: Highlights in the United States…". Weatherwise 44, nr 1 (luty 1991): 8–12. http://dx.doi.org/10.1080/00431672.1991.9927150.
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Changnon, Stanley A., i Geoffrey J. D. Hewings. "Losses from Weather Extremes in the United States". Natural Hazards Review 2, nr 3 (sierpień 2001): 113–23. http://dx.doi.org/10.1061/(asce)1527-6988(2001)2:3(113).
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Le Comte, Douglas. "United States Weather Highlights 2006: The Temperature Rises". Weatherwise 60, nr 2 (styczeń 2007): 26–33. http://dx.doi.org/10.3200/wewi.60.2.26-33.
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Lee, Dongmin, Lazaros Oreopoulos, George J. Huffman, William B. Rossow i In-Sik Kang. "The Precipitation Characteristics of ISCCP Tropical Weather States". Journal of Climate 26, nr 3 (1.02.2013): 772–88. http://dx.doi.org/10.1175/jcli-d-11-00718.1.
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Abstract The authors examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35°S–35°N) for a 10-yr period. The main precipitation dataset used is the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis operational product 3B42 dataset, but Global Precipitation Climatology Project daily data are also used for comparison. It is found that the most convectively active ISCCP weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropics; yet, even this weather state appears to not precipitate about half the time, although this may be to some extent an artifact of detection and spatiotemporal matching limitations of the precipitation dataset. WS1 exhibits a modest annual cycle of the domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states appear to be stronger when occurring before or after WS1. The precipitation rates of the various weather states are different between ocean and land, with WS1 producing higher daytime rates on average over ocean than land, likely because of the larger size and more persistent nature of oceanic WS1s. The results of this study, in addition to advancing the understanding of tropical hydrology, can serve as higher-order diagnostics for evaluating the realism of tropical precipitation distributions in large-scale models.
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Roller, Christopher D., Jian-Hua Qian, Laurie Agel, Mathew Barlow i Vincent Moron. "Winter Weather Regimes in the Northeast United States". Journal of Climate 29, nr 8 (12.04.2016): 2963–80. http://dx.doi.org/10.1175/jcli-d-15-0274.1.
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Abstract The method of k-means cluster analysis is applied to U.S. wintertime daily 850-hPa winds across the Northeast. The resulting weather patterns are analyzed in terms of duration, station, gridded precipitation, storm tracks, and climate teleconnections. Five distinct weather patterns are identified. Weather type (WT) 1 is characterized by a ridge over the western Atlantic and positive precipitation anomalies as far north as the Great Lakes; WT2, by a trough along the eastern United States and positive precipitation anomalies into southern New England; WT3, by a trough over the western Atlantic and negative precipitation anomalies along much of the U.S. East Coast; WT4, by a trough east of Newfoundland and negative precipitation anomalies along parts of the U.S. East Coast; and WT5, by a broad, shallow trough over southeastern Canada and negative precipitation anomalies over the entire U.S. East Coast. WT5 and WT1 are the most persistent, while WT2 typically progresses quickly to WT3 and then to WT4. Based on mean station precipitation in the northeastern United States, most precipitation occurs in WT2 and WT3, with the least in WT1 and WT4. Extreme precipitation occurs most frequently in WT2. Storm tracks show that WT2 and WT3 are associated with coastal storms, while WT2 is also associated with Great Lakes storms. Teleconnections are linked with a change in WT frequency by more than a factor of 2 in several cases: for the North Atlantic Oscillation (NAO) in WT1 and WT4 and for the Pacific–North American (PNA) pattern in WT1 and WT3.
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Rossow, William B., Yuanchong Zhang i George Tselioudis. "Atmospheric Diabatic Heating in Different Weather States and the General Circulation". Journal of Climate 29, nr 3 (29.01.2016): 1059–65. http://dx.doi.org/10.1175/jcli-d-15-0760.1.
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Abstract Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space–time scales, comprising relatively infrequent, strong heating events by “stormy” weather and more nearly continuous, weak cooling by “fair” weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space–time scales might be used to establish useful “feedback like” relationships between cloud processes and the large-scale circulation.
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Norin, Lars, Abhay Devasthale i Tristan S. L'Ecuyer. "The sensitivity of snowfall to weather states over Sweden". Atmospheric Measurement Techniques 10, nr 9 (5.09.2017): 3249–63. http://dx.doi.org/10.5194/amt-10-3249-2017.
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Abstract. For a high-latitude country like Sweden snowfall is an important contributor to the regional water cycle. Furthermore, snowfall impacts surface properties, affects atmospheric thermodynamics, has implications for traffic and logistics management, disaster preparedness, and also impacts climate through changes in surface albedo and turbulent heat fluxes. For Sweden it has been shown that large-scale atmospheric circulation patterns, or weather states, are important for precipitation variability. Although the link between atmospheric circulation patterns and precipitation has been investigated for rainfall there are no studies focused on the sensitivity of snowfall to weather states over Sweden.In this work we investigate the response of snowfall to eight selected weather states. These weather states consist of four dominant wind directions together with cyclonic and anticyclonic circulation patterns and enhanced positive and negative phases of the North Atlantic Oscillation. The presented analysis is based on multiple data sources, such as ground-based radar measurements, satellite observations, spatially interpolated in situ observations, and reanalysis data. The data from these sources converge to underline the sensitivity of falling snow over Sweden to the different weather states.In this paper we examine both average snowfall intensities and snowfall accumulations associated with the different weather states. It is shown that, even though the heaviest snowfall intensities occur during conditions with winds from the south-west, the largest contribution to snowfall accumulation arrives with winds from the south-east. Large differences in snowfall due to variations in the North Atlantic Oscillation are shown as well as a strong effect of cyclonic and anticyclonic circulation patterns. Satellite observations are used to reveal the vertical structures of snowfall during the different weather states.
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Carlson, Susan A., Geoffrey P. Whitfield, Ryan T. Davis, Erin L. Peterson, Janet E. Fulton i David Berrigan. "Associations between Perceptions and Measures of Weather and Walking, United States—2015". International Journal of Environmental Research and Public Health 18, nr 16 (9.08.2021): 8398. http://dx.doi.org/10.3390/ijerph18168398.
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Introduction: Weather can be a barrier to walking. Understanding how perceptions of weather as a barrier and measured temperature are associated with walking can inform monitoring and promotion strategies. The objective of this study is to examine the association between perceptions of weather as a barrier to walking and measured weather with the volume of leisure and transportation walking. Methods: The 2015 National Health Interview Survey (NHIS) assessed participation in and volume of walking (transportation, leisure) in the past week and frequency of reporting weather as a barrier to walking. Data were collected over the entire year. In 2019, we merged month-specific temperature data from the PRISM climate group with individual NHIS records. We examined associations using logistic (participation) and linear regression models (volume). Results: Participation in walking increased as frequency of reporting weather as a barrier to walking decreased, from ‘almost always’ (transportation: 23%, leisure: 42%) to ‘a little of the time’ (transportation: 40%, leisure: 67%). Among adults reporting walking, walking volume increased as frequency of reporting weather as a barrier decreased from ‘almost always’ (transportation: 51 min/week, leisure: 64 min/week) to ‘never’ (transportation: 69 min/week, leisure: 98 min/week). Month-specific temperature was significantly associated with leisure walking with lower participation at the lowest and highest temperature quintiles, although the strength of the association differed by frequency of reporting weather as a barrier. Conclusions: In general, prevalence and volume of leisure and transportation walking decreased as the perception of weather as a barrier increased. Low and high temperature conditions were also associated with leisure walking participation, particularly among adults with increased perceptions of weather as a barrier. Our findings highlight the importance of including strategies to help adults overcome perceived and actual weather-related barriers in walking promotion efforts.
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Morimoto, Hiroshi. "Use of Hidden Markov Models to Identify Background States Behind Risks of Cerebral Infarction and Ischemic Heart Disease". Journal of Mathematics Research 9, nr 1 (2.01.2017): 24. http://dx.doi.org/10.5539/jmr.v9n1p24.
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Cold exposure is often said to trigger the incidence of cerebral infarctions and ischemic heart disease. This association between weather and human health has attracted considerable interest, and has been explored using standard statistical techniques such as regression models. Meteorological factors, such as temperature, are controlled by background systems, notably weather patterns. Therefore, it is reasonable to posit that the incidence of diseases is similarly influenced by a background system. The aim of this paper was to identify and construct these respective background systems. Possible background states or "hidden states", behind the incidence of diseases were derived using the EM and Viterbi algorithms with in the framework of hidden Markov models (HMM). A self-organizing map (SOM) enabled identification of weather patterns, considered as background states behind meteorological factors. These background states were then compared, and the hidden states behind the incidence of diseases were identified by six weather patterns. This finding indicates new evidence of the links between weather and human health, shedding light on the association between changes in the weather and the onset of disease.
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Kalkstein, Laurence S., i Kathleen M. Valimont. "An Evaluation of Winter Weather Severity in the United States Using the Weather Stress Index". Bulletin of the American Meteorological Society 68, nr 12 (grudzień 1987): 1535–40. http://dx.doi.org/10.1175/1520-0477(1987)068<1535:aeowws>2.0.co;2.
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Changnon, Stanley A. "Geographical Distribution of Weather Catastrophes in the United States". Physical Geography 31, nr 1 (styczeń 2010): 29–39. http://dx.doi.org/10.2747/0272-3646.31.1.29.
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JANCIN, BRUCE. "Eczema Risk Higher in States With Cool, Dry Weather". Pediatric News 46, nr 7 (lipiec 2012): 6. http://dx.doi.org/10.1016/s0031-398x(12)70161-3.
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Wuebbles, Donald J., Kenneth Kunkel, Michael Wehner i Zachary Zobel. "Severe Weather in United States Under a Changing Climate". Eos, Transactions American Geophysical Union 95, nr 18 (6.05.2014): 149–50. http://dx.doi.org/10.1002/2014eo180001.
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Fiebrich, Christopher A. "History of surface weather observations in the United States". Earth-Science Reviews 93, nr 3-4 (kwiecień 2009): 77–84. http://dx.doi.org/10.1016/j.earscirev.2009.01.001.
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DeWalle, David R., Anthony R. Buda i Ann Fisher. "Extreme Weather and Forest Management in the Mid-Atlantic Region of the United States". Northern Journal of Applied Forestry 20, nr 2 (1.06.2003): 61–70. http://dx.doi.org/10.1093/njaf/20.2.61.
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Abstract Projected climate change could have major effects on forest management because of the potential for increased frequency, duration, and/or severity of extreme weather events. We surveyed public and private forestland management groups in the Mid-Atlantic region of the United States to better understand current interactions between extreme weather events and forest land management and to help predict future impacts. Our questionnaire addressed the importance and types of problems created by extreme weather events, the coping strategies employed to mitigate problems, and the overall economic effects of extreme weather. Responses were received from 322 forest managers/users (54% response rate) primarily representing state natural resources agencies, forestry consulting firms, large industrial forestry companies and smaller logging companies. Overall, respondents rated the impacts of extreme weather on their operations as low to modest; however, over 20% experienced “major” effects because of extreme weather over the past 10 yr. The highest rated impacts were: (1) reduced access to forestland because of flooding, deep snow, or wind- and ice-damaged trees; (2) increased costs for road and facility maintenance, and (3) direct damage to trees by wind, snow, or ice and subsequent effects on timber supplies and market prices. Mitigation strategies most commonly mentioned were switching of silvicultural systems and changing site preparation and planting schemes, but most respondents had not altered their management due to extreme weather. When asked about effects of a hypothetical 25% increase in severe weather, the most common mitigation strategy was increased investment in new equipment and facilities. Short-term economic impacts of severe weather varied between “supply increasing” conditions associated with increased tree damage and salvage operations and “supply decreasing” conditions related to reduced access to forest land. Increased severe weather due to climate change can be expected to have small to modest effects on forest management and users overall, but areas subjected to hurricanes and ice storms within the Mid-Atlantic region appear to be more sensitive to impacts of severe weather. North. J. Appl. For. 20(2):61–70.
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Krocak, Makenzie J., i Harold E. Brooks. "An Analysis of Subdaily Severe Thunderstorm Probabilities for the United States". Weather and Forecasting 35, nr 1 (13.01.2020): 107–12. http://dx.doi.org/10.1175/waf-d-19-0145.1.
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Abstract One of the challenges of providing probabilistic information on a multitude of spatiotemporal scales is ensuring that information is both accurate and useful to decision-makers. Focusing on larger spatiotemporal scales (i.e., from convective outlook to weather watch scales), historical severe weather reports are analyzed to begin to understand the spatiotemporal scales that hazardous weather events are contained within. Reports from the Storm Prediction Center’s report archive are placed onto grids of differing spatial scales and then split into 24-h convective outlook days (1200–1200 UTC). These grids are then analyzed temporally to assess over what fraction of the day a single location would generally experience severe weather events. Different combinations of temporal and spatial scales are tested to determine how the reference class (or the choice of what scales to use) alters the probabilities of severe weather events. Results indicate that at any given point in the United States on any given day, more than 95% of the daily reports within 40 km of the point occur in a 4-h period. Therefore, the SPC 24-h convective outlook probabilities can be interpreted as 4-h convective outlook probabilities without a significant change in meaning. Additionally, probabilities and threat periods are analyzed at each location and different times of year. These results indicate little variability in the duration of severe weather events, which allows for a consistent definition of an “event” for all locations in the continental United States.
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Gensini, Vittorio A., i Thomas L. Mote. "Estimations of Hazardous Convective Weather in the United States Using Dynamical Downscaling". Journal of Climate 27, nr 17 (28.08.2014): 6581–89. http://dx.doi.org/10.1175/jcli-d-13-00777.1.
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Abstract High-resolution (4 km; hourly) regional climate modeling is utilized to resolve March–May hazardous convective weather east of the U.S. Continental Divide for a historical climate period (1980–90). A hazardous convective weather model proxy is used to depict occurrences of tornadoes, damaging thunderstorm wind gusts, and large hail at hourly intervals during the period of record. Through dynamical downscaling, the regional climate model does an admirable job of replicating the seasonal spatial shifts of hazardous convective weather occurrence during the months examined. Additionally, the interannual variability and diurnal progression of observed severe weather reports closely mimic cycles produced by the regional model. While this methodology has been tested in previous research, this is the first study to use coarse-resolution global climate model data to force a high-resolution regional model with continuous seasonal integration in the United States for purposes of resolving severe convection. Overall, it is recommended that dynamical downscaling play an integral role in measuring climatological distributions of severe weather, both in historical and future climates.
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Horel, John D., Robert Ziel, Chris Galli, Judith Pechmann i Xia Dong. "An evaluation of fire danger and behaviour indices in the Great Lakes Region calculated from station and gridded weather information". International Journal of Wildland Fire 23, nr 2 (2014): 202. http://dx.doi.org/10.1071/wf12186.
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A web-based set of tools has been developed to integrate weather, fire danger and fire behaviour information for the Great Lakes region of the United States. Weather parameters obtained from selected observational networks are combined with operational high-resolution gridded analyses and forecast products from the United States National Weather Service. Fuel moisture codes and fire behaviour indices in the Fire Weather Index subsystem of the Canadian Forest Fire Danger Rating System are computed from these sources for current and forecast conditions. Applications of this Great Lakes Fire and Fuels System are demonstrated for the 2012 fire season. Fuel moisture codes and fire behaviour indices computed from gridded analyses differ from those derived from observations in a manner similar to the analysis errors typical for the underlying weather parameters. Indices that are particularly sensitive to seasonally accumulating precipitation, such as the Drought Code, exhibit the largest differences. The gridded analyses and forecasts provide considerable additional information for fire weather professionals to evaluate weather and fuel state in the region. The potential utility of these gridded analyses and forecasts throughout the continental United States is highlighted.
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Saunders, Michelle E., Kevin D. Ash i Jennifer M. Collins. "Usefulness of the United States National Weather Service Radar Display as Rated by Website Users". Weather, Climate, and Society 10, nr 4 (20.08.2018): 673–91. http://dx.doi.org/10.1175/wcas-d-17-0108.1.
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Abstract Weather radar is now widely viewed by the general public in the United States via television, computers/tablets, and smartphones. Anyone can consult near-real-time maps and animations of weather radar data when weather conditions are a factor. However, the usefulness of weather radar data for each user depends on a complex interaction of factors. There have been few studies providing conceptual arguments and empirical data to better understand what the most important factors are and to comprehend patterns of public weather radar use across the United States. The first part of this research provides a basic conceptual framework for research investigating the usefulness of weather radar displays as a source of weather information and as a decision aid. The second part aims to uncover several factors that influence the perceived usefulness rating of the National Weather Service (NWS) website’s weather radar display at both national and regional levels using variables gathered from the 2014 NWS customer satisfaction survey alongside relevant geographic and climatological variables. Data analyses include spatial clustering and ordinal regression utilized within a generalized linear model methodology. Overall, respondents who are more familiar with the NWS and their products, as well as those who indicate they are more likely to take action based on information provided by the NWS, are more likely to find the NWS radar display useful. Geographically, the NWS radar display is most useful to persons residing in the southern United States. Lightning is the most important hazard associated with higher radar usefulness ratings.
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Thomas, M. A., i A. Devasthale. "Sensitivity of free tropospheric carbon monoxide to atmospheric weather states and their persistency: an observational assessment over the Nordic countries". Atmospheric Chemistry and Physics Discussions 14, nr 7 (4.04.2014): 9249–74. http://dx.doi.org/10.5194/acpd-14-9249-2014.
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Abstract. Among various factors that influence the long-range transport of pollutants in the free troposphere (FT), the prevailing atmospheric weather states probably play the most important role in governing characteristics and efficacy of such transport. The weather states, such as a particular wind pattern, cyclonic or anticyclonic conditions etc, and their degree of persistency determine the spatio-temporal distribution and the final fate of the pollutants. This is especially true in the case of Nordic countries, where baroclinic disturbances and associated weather fronts primarily regulate local meteorology, in contrast to the lower latitudes where convective paradigm plays similar important role. Furthermore, the long-range transport of pollutants in the FT has significant contribution to the total column burden over the Nordic countries. However, there is insufficient knowledge on the large-scale co-variability of pollutants in the FT and atmospheric weather states based solely on observational data over this region. The present study attempts to quantify and understand this statistical co-variability while providing relevant meteorological background. To that end, we select eight weather states that predominantly occur over the Nordic countries and three periods of their persistency (3 days, 5 days, and 7 days), thus providing in total 24 cases to investigate sensitivity of free tropospheric carbon monoxide, an ideal tracer for studying pollutant transport, to these selected weather states. The eight states include four dominant wind directions (namely, NW, NE, SE and SW), cyclonic and anticyclonic conditions, and the enhanced positive and negative phases of the North Atlantic Oscillation (NAO). For our sensitivity analysis, we use recently released Version 6 retrievals of CO at 500 hPa from the Atmospheric Infrared Sounder (AIRS) onboard Aqua satellite covering 11 yr period from September 2002 through August 2013 and winds from the ECMWF's ERA-Interim project to classify weather states for the same 11 yr period. We show that, among the various weather states studied here, southeasterly winds lead to highest observed CO anomalies (up to +8%) over the Nordic countries while transporting pollution from the central and eastern parts of Europe. The second (up to +4%) and third highest (up to +2.5%) CO anomalies are observed when winds are northwesterly (facilitating inter-continental transport from polluted North American regions) and during the enhanced positive phase of the NAO respectively. Higher than normal CO anomalies are observed during anticyclonic conditions (up to +1%) compared to cyclonic conditions. The cleanest conditions are observed when winds are northeasterly and during the enhanced negative phases of the NAO, when relatively clean Arctic air masses are transported over the Nordic regions in the both cases. In case of nearly all weather states, the CO anomalies consistently continue to increase or decrease as the degree of persistency of a weather state is increased. The results of this sensitivity study further provide an observational basis for the process-oriented evaluation of chemistry transport models, especially with regard to the representation of large-scale coupling of chemistry and local weather states and its role in the long-range transport of pollutants in such models.
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Thomas, M. A., i A. Devasthale. "Sensitivity of free tropospheric carbon monoxide to atmospheric weather states and their persistency: an observational assessment over the Nordic countries". Atmospheric Chemistry and Physics 14, nr 21 (3.11.2014): 11545–55. http://dx.doi.org/10.5194/acp-14-11545-2014.
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Abstract. Among various factors that influence the long-range transport of pollutants in the free troposphere (FT), the prevailing atmospheric weather states probably play the most important role in governing characteristics and efficacy of such transport. The weather states, such as a particular wind pattern, cyclonic or anticyclonic conditions, and their degree of persistency determine the spatio-temporal distribution and the final fate of the pollutants. This is especially true in the case of Nordic countries, where baroclinic disturbances and associated weather fronts primarily regulate local meteorology, in contrast to the lower latitudes where a convective paradigm plays a similarly important role. Furthermore, the long-range transport of pollutants in the FT has significant contribution to the total column burden over the Nordic countries. However, there is insufficient knowledge on the large-scale co-variability of pollutants in the FT and atmospheric weather states based solely on observational data over this region. The present study attempts to quantify and understand this statistical co-variability while providing relevant meteorological background. To that end, we select eight weather states that predominantly occur over the Nordic countries and three periods of their persistency (3 days, 5 days, and 7 days), thus providing in total 24 cases to investigate sensitivity of free tropospheric carbon monoxide, an ideal tracer for studying pollutant transport, to these selected weather states. The eight states include four dominant wind directions (namely, NW, NE, SE and SW), cyclonic and anticyclonic conditions, and the enhanced positive and negative phases of the North Atlantic Oscillation (NAO). For our sensitivity analysis, we use recently released Version 6 retrievals of CO at 500 hPa from the Atmospheric Infrared Sounder (AIRS) onboard Aqua satellite covering the 11-year period from September 2002 through August 2013 and winds from the ECMWF's ERA-Interim project to classify weather states for the same 11-year period. We show that, among the various weather states studied here, southeasterly winds lead to highest observed CO anomalies (up to +8%) over the Nordic countries while transporting pollution from the central and eastern parts of Europe. The second (up to +4%) and third highest (up to +2.5%) CO anomalies are observed when winds are northwesterly (facilitating inter-continental transport from polluted North American regions) and during the enhanced positive phase of the NAO respectively. Higher than normal CO anomalies are observed during anticyclonic conditions (up to +1%) compared to cyclonic conditions. The cleanest conditions are observed when winds are northeasterly and during the enhanced negative phases of the NAO, when relatively clean Arctic air masses are transported over the Nordic regions in the both cases. In the case of nearly all weather states, the CO anomalies consistently continue to increase or decrease as the degree of persistency of a weather state is increased. The results of this sensitivity study further provide an observational basis for the process-oriented evaluation of chemistry transport models, especially with regard to the representation of large-scale coupling of chemistry and local weather states and its role in the long-range transport of pollutants in such models.
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Lazo, Jeffrey K., Megan Lawson, Peter H. Larsen i Donald M. Waldman. "U.S. Economic Sensitivity to Weather Variability". Bulletin of the American Meteorological Society 92, nr 6 (1.06.2011): 709–20. http://dx.doi.org/10.1175/2011bams2928.1.
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To estimate the economic effects of weather variability in the United States, the authors define and measure weather sensitivity as the variability in economic output that is attributable to weather variability, accounting for changes in technology and changes in levels of economic inputs (i.e., capital, labor, and energy). Using 24 yr of economic data and weather observations, quantitative models of the relationship between state-level sectoral economic output and weather variability are developed for the 11 nongovernmental sectors of the U.S. economy; temperature and precipitation measures were used as proxies for all weather impacts. All 11 sectors are found to have statistically significant sensitivity to weather variability. Economic inputs were then constant and economic output was estimated in the 11 estimated sector models, varying the weather inputs only using 70 yr of historic weather observations. It was found that U.S. economic output varies by up to $485 billion yr−1 of 2008 gross domestic product, about 3.4%, owing to weather variability. U.S. states that are more sensitive to weather variability are identified and sectors are ranked by their degree of weather sensitivity. This work illustrates a valid approach to measuring the economic impact of weather variability, gives baseline information and methods for more detailed studies of the sensitivity of each sector to weather variability, and lays the groundwork for assessing the value of current or improved weather forecast information given the economic impacts of weather variability.
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Landolt, Scott D., Joshua S. Lave, Darcy Jacobson, Andrew Gaydos, Stephanie DiVito i Daniel Porter. "The Impacts of Automation on Present Weather–Type Observing Capabilities across the Conterminous United States". Journal of Applied Meteorology and Climatology 58, nr 12 (grudzień 2019): 2699–715. http://dx.doi.org/10.1175/jamc-d-19-0170.1.
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AbstractIn the 1990s, the National Weather Service and the Federal Aviation Administration began deploying the Automated Surface Observing Systems (ASOS). These systems provided the capability to report real-time weather observations, including some types of present weather, as frequently as once every minute. Over 900 of these ASOS stations were installed across the United States, replacing most of the human observers. Despite the benefits offered, many issues were noted, including the inability to discern and report certain precipitation types, particularly drizzle, freezing drizzle, and ice pellets. These and other issues resulted in human observers being retained at roughly 130 ASOS airport locations around the country where high-quality weather observations are essential because of air traffic volume or other factors. The human observers at these locations work in conjunction with the ASOS, manually augmenting the automated weather observations when the ASOS provides erroneous data or when an ASOS observation is missing. To assess the impact of automation on present weather observations, the differences in present weather reports for two decades will be highlighted: 1979–88 (when only human observers reported the present weather observations) and 2005–14 (after the full ASOS network became operational). Comparisons between the decades will be further analyzed to determine the differences at the ASOS locations at which human observers were retained in the later decade, as well as the ASOS locations at which no humans were retained. Both the positive and negative impacts of automation, with an emphasis on aviation impacts, are presented.
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Stewart, Alan E., Jeffrey K. Lazo, Rebecca E. Morss i Julie L. Demuth. "The Relationship of Weather Salience with the Perceptions and Uses of Weather Information in a Nationwide Sample of the United States". Weather, Climate, and Society 4, nr 3 (30.05.2012): 172–89. http://dx.doi.org/10.1175/wcas-d-11-00033.1.
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Abstract The authors used data from a sample of 1465 adults living in the United States to perform a confirmatory factor analysis on the Weather Salience Questionnaire (WxSQ), a 29-item instrument designed to measure the ways in which weather is psychologically significant for people. The original measurement model of the WxSQ was confirmed in the present sample. Additional work also was performed to create a WxSQ short form consisting of seven items. The authors then examined the relationship of weather salience with the respondents’ climate zones of residence and several other weather-related attitudes and behaviors that were assessed in the national sample. People residing in continental and temperate climates expressed significantly more weather salience than those living in dry climates. Further, weather salience was significantly and positively related to the following: 1) the frequency with which people sought weather information and forecasts, 2) the frequency of seeking weather information during the day, 3) the frequency of using forecasts to plan daily activities, 4) seeking weather information for wider geographic areas, and 5) the use of precipitation and temperature forecasts. Weather salience also was significantly and positively related to the confidence people expressed about National Weather Service forecasts and to the perceived importance of these forecasts. The results imply that peoples’ level of weather salience, at least in part, affects their uses of weather information and their confidence in it. These results support the validity of the WxSQ and also reveal some of the psychological bases of people’s perceptions and uses of weather information.
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Fukutome, S., C. Prim i C. Schär. "The role of soil states in medium-range weather predictability". Nonlinear Processes in Geophysics 8, nr 6 (31.12.2001): 373–86. http://dx.doi.org/10.5194/npg-8-373-2001.
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Abstract. Current day operational ensemble weather prediction systems generally rely upon perturbed atmospheric initial states, thereby neglecting the eventual effect on the atmospheric evolution that uncertainties in initial soil temperature and moisture fields could bring about during the summer months. The purpose of this study is to examine the role of the soil states in medium-range weather predictability. A limited area weather prediction model is used with the atmosphere/ land-surface system in coupled or uncoupled mode. It covers Europe and part of the north Atlantic, and is driven by prescribed sea-surface temperatures over the sea, and by atmospheric reanalyses at its lateral boundaries. A series of 3 member ensembles of summer simulations are used to assess the predictability of a reference simulation assumed to be perfect. In a first step, two ensembles are simulated: the first with the atmosphere coupled to the land-surface model, the second in the uncoupled mode with perfect soil conditions prescribed every 6 hours. Subsequent experiments are combinations thereof, in which the uncoupled and coupled modes alternate in the course of a simulation. The results show that there are "stable" and "unstable" periods in the weather evolution under consideration. During the stable periods, the predictability (measured in terms of ensemble spread at 500 hPa) of the coupled and uncoupled dynamical systems is almost identical; prescribing the perfect soil conditions has a negligible impact upon the atmospheric predictability. In contrast, the predictability during an unstable phase is found to be remarkably improved in the uncoupled ensembles. This effect results from guiding the atmospheric phase-space trajectory along its perfect evolution. It persists even when switching back from the uncoupled to the coupled mode prior to the onset of the unstable phase, a result that underlines the importance of soil moisture and temperature in data assimilation systems.
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Serafin, Robert J., i James W. Wilson. "Operational Weather Radar in the United States: Progress and Opportunity". Bulletin of the American Meteorological Society 81, nr 3 (marzec 2000): 501–18. http://dx.doi.org/10.1175/1520-0477(2000)081<0501:owritu>2.3.co;2.
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Mahmood, Rezaul, Ryan Boyles, Kevin Brinson, Christopher Fiebrich, Stuart Foster, Ken Hubbard, David Robinson, Jeff Andresen i Dan Leathers. "Mesonets: Mesoscale Weather and Climate Observations for the United States". Bulletin of the American Meteorological Society 98, nr 7 (1.07.2017): 1349–61. http://dx.doi.org/10.1175/bams-d-15-00258.1.
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Abstract Mesoscale in situ meteorological observations are essential for better understanding and forecasting the weather and climate and to aid in decision-making by a myriad of stakeholder communities. They include, for example, state environmental and emergency management agencies, the commercial sector, media, agriculture, and the general public. Over the last three decades, a number of mesoscale weather and climate observation networks have become operational. These networks are known as mesonets. Most are operated by universities and receive different levels of funding. It is important to communicate the current status and critical roles the mesonets play. Most mesonets collect standard meteorological data and in many cases ancillary near-surface data within both soil and water bodies. Observations are made by a relatively spatially dense array of stations, mostly at subhourly time scales. Data are relayed via various means of communication to mesonet offices, with derived products typically distributed in tabular, graph, and map formats in near–real time via the World Wide Web. Observed data and detailed metadata are also carefully archived. To ensure the highest-quality data, mesonets conduct regular testing and calibration of instruments and field technicians make site visits based on “maintenance tickets” and prescheduled frequencies. Most mesonets have developed close partnerships with a variety of local, state, and federal-level entities. The overall goal is to continue to maintain these networks for high-quality meteorological and climatological data collection, distribution, and decision-support tool development for the public good, education, and research.
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Le Comte, Douglas. "Wet & Windy: The United States Weather Highlights For 2004". Weatherwise 58, nr 2 (marzec 2005): 30–37. http://dx.doi.org/10.3200/wewi.58.2.30-37.
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Le Comte, Douglas. "The United States Weather Highlights of 2005: A Stormy Year". Weatherwise 59, nr 2 (styczeń 2006): 30–37. http://dx.doi.org/10.3200/wewi.59.2.30-37.
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Fultz, Andrew J., i Walker S. Ashley. "Fatal weather-related general aviation accidents in the United States". Physical Geography 37, nr 5 (25.07.2016): 291–312. http://dx.doi.org/10.1080/02723646.2016.1211854.
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Rapp, Claire, Emily Rabung, Robyn Wilson i Eric Toman. "Wildfire decision support tools: an exploratory study of use in the United States". International Journal of Wildland Fire 29, nr 7 (2020): 581. http://dx.doi.org/10.1071/wf19131.
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In the United States, many decision support tools exist to provide fire managers with weather and fire behaviour information to inform and facilitate risk-based decision-making. Relatively little is known about how managers use these tools in the field and when and how they may serve to influence decisions. To address this gap, we conducted exploratory interviews with 27 wildfire management and fire weather professionals across the United States. Results reveal that barriers to the use of decision support tools are structural and social. Specifically, fire weather and behaviour models may not generate reliable output and managers may not use the information they provide, but technical specialists on incident management teams (IMTs) play an active role in trying to overcome these barriers through their technical expertise and their relationships with other members of the IMT. Although researchers suggest tools such as the Wildland Fire Decision Support System (WFDSS) inform broad, strategic decision-making for line officers and IMTs, our results suggest fire weather and behaviour models are also important for communication and strategic or tactical planning within the IMT, especially for operations. We find that ultimately, managers may make use of fire weather and behaviour models, but they do not dictate decisions.
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Poterjoy, Jonathan, Ghassan J. Alaka i Henry R. Winterbottom. "The Irreplaceable Utility of Sequential Data Assimilation for Numerical Weather Prediction System Development: Lessons Learned from an Experimental HWRF System". Weather and Forecasting 36, nr 2 (kwiecień 2021): 661–77. http://dx.doi.org/10.1175/waf-d-20-0204.1.
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AbstractLimited-area numerical weather prediction models currently run operationally in the United States and follow a “partially cycled” schedule, where sequential data assimilation is periodically interrupted by replacing model states with solutions interpolated from a global model. While this strategy helps overcome several practical challenges associated with real-time regional forecasting, it is no substitute for a robust sequential data assimilation approach for research-to-operations purposes. Partial cycling can mask systematic errors in weather models, data assimilation systems, and data preprocessing techniques, since it introduces information from a different prediction system. It also adds extra heuristics to the model initialization steps outside the general Bayesian filtering framework from which data assimilation methods are derived. This study uses a research-oriented modeling system, which is self-contained in the operational Hurricane Weather Research and Forecasting (HWRF) Model package, to illustrate why next-generation modeling systems should prioritize sequential data assimilation at early stages of development. This framework permits the rigorous examination of all model system components—in a manner that has never been done for the HWRF Model. Examples presented in this manuscript show how sequential data assimilation capabilities can accelerate model advancements and increase academic involvement in operational forecasting systems at a time when the United States is developing a new hurricane forecasting system.
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Phan, Minh D., Burrell E. Montz, Scott Curtis i Thomas M. Rickenbach. "Weather on the Go: An Assessment of Smartphone Mobile Weather Application Use among College Students". Bulletin of the American Meteorological Society 99, nr 11 (listopad 2018): 2245–57. http://dx.doi.org/10.1175/bams-d-18-0020.1.
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AbstractMillions of people in the United States regularly acquire information from weather forecasts for a wide variety of reasons. The rapid growth in mobile device technology has created a convenient means for people to retrieve this data, and in recent years, mobile weather applications (MWAs) have quickly gained popularity. Research on weather sources, however, has been unable to sufficiently capture the importance of this form of information gathering. As use of these apps continues to grow, it is important to gain insight on the usefulness of MWAs to consumers. To better examine MWA preferences and behaviors relating to acquired weather information, a survey of 308 undergraduate students from three different universities throughout the southeast United States was undertaken. Analyses of the survey showed that smartphone MWAs are the primary weather forecast source among college students. Additionally, MWA users tend to seek short-term forecast information, like the hourly forecast, from their apps. Results also provide insight into daily MWA use by college students as well as perceptions of and preferential choices for specific MWA features and designs. The information gathered from this study will allow other researchers to better evaluate and understand the changing landscape of weather information acquisition and how this relates to the uses, perceptions, and values people garner from forecasts. Organizations that provide weather forecasts have an ever-growing arsenal of resources to disseminate information, making research of this topic extremely valuable for future development of weather communication technology.
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Turvey, Calum G., i Michael Norton. "An Internet-Based Tool for Weather Risk Management". Agricultural and Resource Economics Review 37, nr 1 (kwiecień 2008): 63–78. http://dx.doi.org/10.1017/s106828050000215x.
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This paper introduces a web-based computer program designed to evaluate weather risk management and weather insurance in the United States. The paper outlines the economics of weather risk in terms of agricultural production and household well-being; defines weather risk in terms of intensity, duration, and frequency; and illustrates the computer program use by comparing heat and precipitation risks at Ardmore, Oklahoma, and Ithaca, New York.
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Handlos, Zachary J., i Larissa E. Back. "Estimating Vertical Motion Profile Shape within Tropical Weather States over the Oceans". Journal of Climate 27, nr 20 (7.10.2014): 7667–86. http://dx.doi.org/10.1175/jcli-d-13-00602.1.
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Abstract The vertical structure of tropical deep convection strongly influences interactions with larger-scale circulations and climate. This paper focuses on investigating this vertical structure and its relationship with mesoscale tropical weather states. The authors test the hypothesis that latent heating plus turbulent flux convergence varies (in space and time) in association with weather state type. The authors estimate mean-state vertical motion profile shape and latent heating plus turbulent flux convergence for six weather states defined using cloud-top pressure and optical depth properties from the International Satellite Cloud Climatology Project (ISCCP) dataset. Assuming two modes of vertical motion profile variability, these modes are statistically extracted from reanalysis data using a principal component analysis. Using these modes and the relationship between vertical motion, the dry static energy budget, and mass continuity, the authors estimate vertical motion profile shape. In these estimates, the authors use Global Precipitation Climatology Project (GPCP) [and Tropical Rainfall Measuring Mission (TRMM) 3B42] precipitation and Quick Scatterometer (QuikSCAT) surface convergence data in the ITCZ region from 2001 to 2006. Finally, these profile shapes are categorized by weather state type and spatiotemporally averaged to generate mean-state vertical motion profiles and latent heating plus turbulent flux convergence. The authors find that vertical motion profile shape varies by weather state. The isolated systems convective regime exhibits more “bottom heaviness” than the other convectively active regimes, with maximum upward vertical motion occurring in the lower troposphere rather than the middle to upper troposphere. The variability observed does not coincide with the conventional profile variability based on stratiform rain fraction.
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Shah, D. A., E. D. De Wolf, P. A. Paul i L. V. Madden. "Functional Data Analysis of Weather Variables Linked to Fusarium Head Blight Epidemics in the United States". Phytopathology® 109, nr 1 (styczeń 2019): 96–110. http://dx.doi.org/10.1094/phyto-11-17-0386-r.
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In past efforts, input weather variables for Fusarium head blight (FHB) prediction models in the United States were identified after following some version of the window-pane algorithm, which discretizes a continuous weather time series into fixed-length windows before searching for summary variables associated with FHB risk. Functional data analysis, on the other hand, reconstructs the assumed continuous process (represented by a series of recorded weather data) by using smoothing functions, and is an alternative way of working with time series data with respect to FHB risk. Our objective was to functionally model weather-based time series data linked to 865 observations of FHB (covering 16 states and 31 years in total), classified as epidemics (FHB disease index ≥ 10%) and nonepidemics (FHB disease index < 10%). Altogether, 94 different time series variables were modeled by penalized cubic B-splines for the smoothing function, from 120 days pre-anthesis to 20 days post-anthesis. Functional mean curves, standard deviations, and first derivatives were plotted for FHB epidemics relative to nonepidemics. Function-on-scalar regressions assessed the temporal trends of the magnitude and significance of the mean difference between functionally represented weather time series associated with FHB epidemics and nonepidemics. The mean functional weather-variable curve for epidemics started to deviate, in general, from that for nonepidemics as early as 40 days pre-anthesis for several weather variables. The greatest deviations were often near anthesis, the period of maximum susceptibility of wheat to FHB-causing fungi. The most consistent separations between the mean functional curves were seen with the daily averages of moisture-related variables (such as average relative humidity) and with variables summarizing the daily variation in temperature (as opposed to the daily mean). Functional data analysis was useful for extending our knowledge of relationships between weather variables and FHB epidemics.
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Ollinaho, Pirkka, Glenn D. Carver, Simon T. K. Lang, Lauri Tuppi, Madeleine Ekblom i Heikki Järvinen. "Ensemble prediction using a new dataset of ECMWF initial states – OpenEnsemble 1.0". Geoscientific Model Development 14, nr 4 (23.04.2021): 2143–60. http://dx.doi.org/10.5194/gmd-14-2143-2021.
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Abstract. Ensemble prediction is an indispensable tool in modern numerical weather prediction (NWP). Due to its complex data flow, global medium-range ensemble prediction has almost exclusively been carried out by operational weather agencies to date. Thus, it has been very hard for academia to contribute to this important branch of NWP research using realistic weather models. In order to open ensemble prediction research up to the wider research community, we have recreated all 50+1 operational IFS ensemble initial states for OpenIFS CY43R3. The dataset (OpenEnsemble 1.0) is available for use under a Creative Commons licence and is downloadable from an https server. The dataset covers 1 year (December 2016 to November 2017) twice daily. Downloads in three model resolutions (TL159, TL399, and TL639) are available to cover different research needs. An open-source workflow manager, called OpenEPS, is presented here and used to launch ensemble forecast experiments from the perturbed initial conditions. The deterministic and probabilistic forecast skill of OpenIFS (cycle 40R1) using this new set of initial states is comprehensively evaluated. In addition, we present a case study of Typhoon Damrey from year 2017 to illustrate the new potential of being able to run ensemble forecasts outside of major global weather forecasting centres.
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Glahn, Bob, Kathryn Gilbert, Rebecca Cosgrove, David P. Ruth i Kari Sheets. "The Gridding of MOS". Weather and Forecasting 24, nr 2 (1.04.2009): 520–29. http://dx.doi.org/10.1175/2008waf2007080.1.
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Abstract Model output statistics (MOS) guidance forecasts have been produced at stations and provided to National Weather Service forecasters and private entities for over three decades. As the numerical weather prediction models became more accurate, MOS followed that trend. Up until a few years ago, the MOS produced at observation locations met the basic need for guidance. With the advent of the Interactive Forecast Preparation System and the National Digital Forecast Database, gridded MOS forecasts became needed as guidance for forecasters. One method of providing such grids is to objectively analyze the MOS forecasts for points. A basic successive correction method has been extended to analyze MOS forecasts and surface weather variables. This method is being applied to MOS forecasts to provide guidance for producing grids of sensible weather elements such as temperature, clouds, and snow amount. Guidance forecasts have been implemented for the conterminous United States for most weather elements contained in routine weather forecasts. This paper describes the method applied to daytime maximum temperature over the conterminous United States and gives example results.
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Cross, Rachael N., i Daphne S. LaDue. "When Uncertainty is Certain: A Nuanced Trust between Emergency Managers and Forecast Information in the Southeastern United States". Weather, Climate, and Society 13, nr 1 (styczeń 2021): 137–46. http://dx.doi.org/10.1175/wcas-d-20-0017.1.
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AbstractWeather forecasting is not an exact science, and, in regions near the southern end of the Appalachian Mountains, the vastly different types of topography and frequency of rapidly forming storms can result in high uncertainty in severe weather forecasts. NOAA created its VORTEX-Southeast (SE) research program to tackle these unique challenges and integrate them with social science research to increase the survivability of southeastern U.S. weather. As part of VORTEX-SE, this study focused on the severe weather preparation and decision-making of emergency management and, in particular, how uncertainty in severe weather forecasts impacted the relationship between emergency managers (EMs) and weather providers. We conducted in-depth, critical incident background interviews with 35 emergency management personnel across 14 counties. An inductive, data-driven analysis approach revealed several factors contributing to an added layer of practical uncertainty beyond the meteorological forecast uncertainty that impacted and helped to explain the nature of trust in the EM–National Weather Service (NWS) relationship. No- or short-notice events, null events, gaps in information, and differences in perspectives when compared with weather forecasters have led emergency managers to modify their procedures in ways that position them to adapt quickly to unexpected changes in the forecast. The need to do so creates a complex, nuanced trust between these groups. This paper explains how EMs developed a nuanced trust of forecast information, how that trust is a recognition of the inherent uncertainty in severe weather forecasts, and how to strengthen the NWS–EM relationship.
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Driscoll, Dennis M. "A Survey of the Use of National Weather Service Forecasts by Television Weather Forecasters in the United States". Weather and Forecasting 1, nr 3 (grudzień 1986): 155–63. http://dx.doi.org/10.1175/1520-0434(1986)001<0155:asotuo>2.0.co;2.
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Jun, Tackseung, i Rajiv Sethi. "Extreme weather events and military conflict over seven centuries in ancient Korea". Proceedings of the National Academy of Sciences 118, nr 12 (15.03.2021): e2021976118. http://dx.doi.org/10.1073/pnas.2021976118.
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We explore the causal connection between weather and war by constructing and analyzing a dataset featuring extreme weather events and military conflicts involving a set of stable political entities that existed side by side over several centuries, namely, the three ancient kingdoms of the Korean Peninsula between 18 Before the Common Era and 660 Common Era. Conflicts are classified as desperate if a state experiencing the shock invades a neighbor and opportunistic if a state experiencing the shock is invaded by a neighbor. We find that weather-induced conflict was significant, but largely opportunistic rather than desperate. That is, states experiencing an adverse shock were more likely to be invaded, but not more likely to initiate attack. We also provide evidence that the channel through which weather shocks gave rise to opportunistic invasions was food insecurity, which weakened the power of states to repel attack. Since climate change is projected to give rise to an increased frequency of extreme weather events, these historical findings have contemporary relevance.
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Erickson, Michael J., Brian A. Colle i Joseph J. Charney. "Evaluation and Postprocessing of Ensemble Fire Weather Predictions over the Northeast United States". Journal of Applied Meteorology and Climatology 57, nr 5 (maj 2018): 1135–53. http://dx.doi.org/10.1175/jamc-d-17-0180.1.
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AbstractThe Short-Range Ensemble Forecast (SREF) system is verified and bias corrected for fire weather days (FWDs) defined as having an elevated probability of wildfire occurrence using a statistical Fire Weather Index (FWI) over a subdomain of the northeastern United States (NEUS) between 2007 and 2014. The SREF is compared to the Rapid Update Cycle and Rapid Refresh analyses for temperature, relative humidity, specific humidity, and the FWI. An additive bias correction is employed using the most recent previous 14 days [sequential bias correction (SBC)] and the most recent previous 14 FWDs [conditional bias correction (CBC)]. Synoptic weather regimes on FWDs are established using cluster analysis (CA) on North American Regional Reanalysis sea level pressure, 850-hPa temperature, 500-hPa temperature, and 500-hPa geopotential height. SREF severely underpredicts FWI (by two indices at FWI = 3) on FWDs, which is partially corrected using SBC and largely corrected with CBC. FWI underprediction is associated with a cool (ensemble mean error of −1.8 K) and wet near-surface model bias (ensemble mean error of 0.46 g kg−1) that decreases to near zero above 800 hPa. Although CBC improves reliability and Brier skill scores on FWDs, ensemble FWI values exhibit underdispersion. CA reveals three synoptic weather regimes on FWDs, with the largest cool and wet biases associated with a departing surface low pressure system. These results suggest the potential benefit of an operational analog bias correction on FWDs. Furthermore, CA may help elucidate model error during certain synoptic weather regimes.
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Yu, Lejiang, Shiyuan Zhong, Xindi Bian, Warren E. Heilman i Joseph J. Charney. "The Interannual Variability of the Haines Index over North America". Journal of Applied Meteorology and Climatology 52, nr 11 (listopad 2013): 2396–409. http://dx.doi.org/10.1175/jamc-d-13-068.1.
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AbstractThe Haines index (HI) is a fire-weather index that is widely used as an indicator of the potential for dry, low-static-stability air in the lower atmosphere to contribute to erratic fire behavior or large fire growth. This study examines the interannual variability of HI over North America and its relationship to indicators of large-scale circulation anomalies. The results show that the first three HI empirical orthogonal function modes are related respectively to El Niño–Southern Oscillation (ENSO), the Arctic Oscillation (AO), and the interdecadal sea surface temperature variation over the tropical Pacific Ocean. During the negative ENSO phase, an anomalous ridge (trough) is evident over the western (eastern) United States, with warm/dry weather and more days with high HI values in the western and southeastern United States. During the negative phase of the AO, an anomalous trough is found over the western United States, with wet/cool weather and fewer days with high HI, while an anomalous ridge occurs over the southern United States–northern Mexico, with an increase in the number of days with high HI. After the early 1990s, the subtropical high over the eastern Pacific Ocean and the Bermuda high were strengthened by a wave train that was excited over the tropical western Pacific Ocean and resulted in warm/dry conditions over the southwestern United States and western Mexico and wet weather in the southeastern United States. The above conditions are reversed during the positive phase of ENSO and AO and before the early 1990s.
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Rigden, Angela J., Guido D. Salvucci, Dara Entekhabi i Daniel J. Short Gianotti. "Partitioning Evapotranspiration Over the Continental United States Using Weather Station Data". Geophysical Research Letters 45, nr 18 (21.09.2018): 9605–13. http://dx.doi.org/10.1029/2018gl079121.
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Egan, Patrick J., i Megan Mullin. "Recent improvement and projected worsening of weather in the United States". Nature 532, nr 7599 (20.04.2016): 357–60. http://dx.doi.org/10.1038/nature17441.
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