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Journal articles on the topic 'Fine weather'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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1

Toth, Zoltan, Steve Albers, and Yuanfu Xie. "Analysis of Fine-Scale Weather Phenomena." Bulletin of the American Meteorological Society 93, no. 3 (March 1, 2012): ES35—ES38. http://dx.doi.org/10.1175/bams-d-11-00148.1.

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2

Fernández-Caldas, Enrique. "In the Summertime When the Weather Is Fine." International Archives of Allergy and Immunology 161, no. 2 (2013): 97–98. http://dx.doi.org/10.1159/000345993.

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3

KAWAHARA, Yoshihisa, Noriyuki IKEDA, and Kenichiro KASHIWAGI. "Heat and Moisture Transfer in Tokyo under Fine Weather." ENVIRONMENTAL SYSTEMS RESEARCH 25 (1997): 469–74. http://dx.doi.org/10.2208/proer1988.25.469.

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4

Duval, Tim P., and J. M. Waddington. "Landscape and weather controls on fine-scale calcareous fen hydrodynamics." Hydrology Research 43, no. 6 (January 27, 2012): 780–97. http://dx.doi.org/10.2166/nh.2011.127.

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Calcareous fens are species-rich peatlands thought to form at discrete alkaline groundwater discharge points. Here the spatial and temporal variability in the peat pore-water hydrodynamics at a fine (plot) scale of three calcareous fens in southern Ontario was investigated over three growing seasons to evaluate the sensitivity of these wetlands to weather fluctuation and landscape position. Only a small area of the fens demonstrated patterns of groundwater upwelling, and positive vertical hydraulic gradients (VHG) were low, peaking at 0.1. Local decreases in saturated hydraulic conductivity generated areas of pore-water over-pressuring in the peat profile through much of the fens. Several areas were subjected to large negative VHG (max = −0.2), causing sustained groundwater recharge. In this study the strength of the connection to the principal source area of water (alkaline stream) determined the pattern and variability of calcareous fen peat hydrodynamics amongst three growing seasons differing markedly in precipitation. The range of pore-water hydrodynamics evident in this study provides evidence for the processes controlling the sensitivity of calcareous fens to climate and land-use change. A conceptual model linking calcareous fen landscape position to weather- and climate-induced hydrodynamic variability is presented to guide management of these biodiverse ecosystems.

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5

Elkins, Norman. "A POSSIBLE RELATIONSHIP BETWEEN FINE-WEATHER INVERSIONS AND FEEDING SWIFTS." Weather 45, no. 7 (July 1990): 262–65. http://dx.doi.org/10.1002/j.1477-8696.1990.tb05636.x.

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6

Neumann, J. "Forecasts of Fine Weather in the Literature of Classical Antiquity." Bulletin of the American Meteorological Society 70, no. 1 (January 1989): 46–49. http://dx.doi.org/10.1175/1520-0477-70.1.46.

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7

Lovas, Róbert, Péter Kardos, András Zénó Gyöngyösi, and Zsolt Bottyán. "Weather model fine-tuning with software container-based simulation platform." Időjárás 123, no. 2 (2019): 165–81. http://dx.doi.org/10.28974/idojaras.2019.2.3.

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8

Hobiger, Thomas, Seiichi Shimada, Shingo Shimizu, Ryuichi Ichikawa, Yasuhiro Koyama, and Tetsuro Kondo. "Improving GPS positioning estimates during extreme weather situations by the help of fine-mesh numerical weather models." Journal of Atmospheric and Solar-Terrestrial Physics 72, no. 2-3 (February 2010): 262–70. http://dx.doi.org/10.1016/j.jastp.2009.11.018.

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9

Wodrich, J. V., T. Winkler, B. Leaf, S. F. Clark, and B. Youker. "WET WEATHER IMPACTS ON INFLUENT FINE SCREENING SYSTEM DESIGN AND OPERATION." Proceedings of the Water Environment Federation 2005, no. 11 (January 1, 2005): 4395–411. http://dx.doi.org/10.2175/193864705783866649.

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10

Jiang, Zhihong, Yuguo Ding, Chunyu Zheng, and Weilin Chen. "An improved, downscaled, fine model for simulation of daily weather states." Advances in Atmospheric Sciences 28, no. 6 (October 18, 2011): 1357–66. http://dx.doi.org/10.1007/s00376-011-0086-8.

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11

Lin, Szu-Yin, Chi-Chun Chiang, Jung-Bin Li, Zih-Siang Hung, and Kuo-Ming Chao. "Dynamic fine-tuning stacked auto-encoder neural network for weather forecast." Future Generation Computer Systems 89 (December 2018): 446–54. http://dx.doi.org/10.1016/j.future.2018.06.052.

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12

Kranstauber, Bart, Willem Bouten, Hidde Leijnse, Berend-Christiaan Wijers, Liesbeth Verlinden, Judy Shamoun-Baranes, and Adriaan M. Dokter. "High-Resolution Spatial Distribution of Bird Movements Estimated from a Weather Radar Network." Remote Sensing 12, no. 4 (February 14, 2020): 635. http://dx.doi.org/10.3390/rs12040635.

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Weather radars provide detailed information on aerial movements of organisms. However, interpreting fine-scale radar imagery remains challenging because of changes in aerial sampling altitude with distance from the radar. Fine-scale radar imagery has primarily been used to assess mass exodus at sunset to study stopover habitat associations. Here, we present a method that enables a more intuitive integration of information across elevation scans projected in a two-dimensional spatial image of fine-scale radar reflectivity. We applied this method on nights of intense bird migration to demonstrate how the spatial distribution of migrants can be explored at finer spatial scales and across multiple radars during the higher flying en-route phase of migration. The resulting reflectivity maps enable explorative analysis of factors influencing their regional and fine-scale distribution. We illustrate the method’s application by generating time-series of composites of up to 20 radars, achieving a nearly complete spatial coverage of a large part of Northwest Europe. These visualizations are highly useful in interpreting regional-scale migration patterns and provide detailed information on bird movements in the landscape and aerial environment.

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13

Webb, Stephen L., Kenneth L. Gee, Bronson K. Strickland, Stephen Demarais, and Randy W. DeYoung. "Measuring Fine-Scale White-Tailed Deer Movements and Environmental Influences Using GPS Collars." International Journal of Ecology 2010 (2010): 1–12. http://dx.doi.org/10.1155/2010/459610.

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Few studies have documented fine-scale movements of ungulate species, including white-tailed deer(Odocoileus virginianus), despite the advent of global positioning system (GPS) technology incorporated into tracking devices. We collected fine-scale temporal location estimates (i.e., 15 min/relocation attempt) from 17 female and 15 male white-tailed deer over 7 years and 3 seasons in Oklahoma, USA. Our objectives were to document fine-scale movements of females and males and determine effects of reproductive phase, moon phase, and short-term weather patterns on movements. Female and male movements were primarily crepuscular. Male total daily movements were 20% greater during rut () than postrut (). Female daily movements were greatest during postparturition (), followed by parturition (), and preparturition (). We found moon phase had no effect on daily, nocturnal, and diurnal deer movements and fine-scale temporal weather conditions had an inconsistent influence on deer movement patterns within season. Our data suggest that hourly and daily variation in weather events have minimal impact on movements of white-tailed deer in southern latitudes. Instead, routine crepuscular movements, presumed to maximize thermoregulation and minimize predation risk, appear to be the most important factors influencing movements.

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14

Barker, Collin, Sam Cipkar, Tyler Lavigne, Cameron Watson, and Maher Azzouz. "Real-Time Nuisance Fault Detection in Photovoltaic Generation Systems Using a Fine Tree Classifier." Sustainability 13, no. 4 (February 19, 2021): 2235. http://dx.doi.org/10.3390/su13042235.

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Nuisance faults are caused by weather events, which result in solar farms being disconnected from the electricity grid. This results in long stretches of downtime for troubleshooting as data are mined manually for possible fault causes, and consequently, cost thousands of dollars in lost revenue and maintenance. This paper proposes a novel fault detection technique to identify nuisance faults in solar farms. To initialize the design process, a weather model and solar farm model are designed to generate both training and testing data. Through an iterative design process, a fine tree model with a classification accuracy of 96.7% is developed. The proposed model is successfully implemented and tested in real-time through a server and web interface. The testbed is capable of streaming in data from a separate source, which emulates a supervisory control and data acquisition (SCADA) or weather station, then classifies the data in real-time and displays the output on another computer (which imitates an operator control room).

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15

Imbard, M., R. Juvanon du Vachat, A. Joly, Y. Durand, A. Craplet J. F. Geleyn, J. F. Geleyn, J. M. Audoin, N. Marie, and J. M. Pairin. "The PERIDOT Fine-Mesh Numerical Weather Prediction System Description, Evaluation and Experiments." Journal of the Meteorological Society of Japan. Ser. II 64A (1986): 455–65. http://dx.doi.org/10.2151/jmsj1965.64a.0_455.

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16

Hekimoğlu, Mert Hakan, Burak Kazaz, and Scott Webster. "Wine Analytics: Fine Wine Pricing and Selection Under Weather and Market Uncertainty." Manufacturing & Service Operations Management 19, no. 2 (May 2017): 202–15. http://dx.doi.org/10.1287/msom.2016.0602.

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17

Lee, Sang Hyuk, Jong Won Lee, Ki Soo Park, Soo Hyung Lee, and Hee Mun Park. "Statistical Analysis of Characteristics of Fine Particulate Matter Concentrations Considering Weather Conditions." International Journal of Highway Engineering 22, no. 5 (October 30, 2020): 37–45. http://dx.doi.org/10.7855/ijhe.2020.22.5.037.

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18

Ching, J., R. Rotunno, M. LeMone, A. Martilli, B. Kosovic, P. A. Jimenez, and J. Dudhia. "Convectively Induced Secondary Circulations in Fine-Grid Mesoscale Numerical Weather Prediction Models." Monthly Weather Review 142, no. 9 (September 2014): 3284–302. http://dx.doi.org/10.1175/mwr-d-13-00318.1.

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Mesoscale numerical weather prediction models using fine-grid [O(1) km] meshes for weather forecasting, environmental assessment, and other applications capture aspects of larger-than-grid-mesh size, convectively induced secondary circulations (CISCs) such as cells and rolls that occur in the convective planetary boundary layer (PBL). However, 1-km grid spacing is too large for the simulation of the interaction of CISCs with smaller-scale turbulence. The existence of CISCs also violates the neglect of horizontal gradients of turbulent quantities in current PBL schemes. Both aspects—poorly resolved CISCs and a violation of the assumptions behind PBL schemes—are examples of what occurs in Wyngaard’s “terra incognita,” where horizontal grid spacing is comparable to the scale of the simulated motions. Thus, model CISCs (M-CISCs) cannot be simulated reliably. This paper describes how the superadiabatic layer in the lower convective PBL together with increased horizontal resolution allow the critical Rayleigh number to be exceeded and thus allow generation of M-CISCs like those in nature; and how the M-CISCs eventually neutralize the virtual temperature stratification, lowering the Rayleigh number and stopping their growth. Two options for removing M-CISCs while retaining their fluxes are 1) introducing nonlocal closure schemes for more effective removal of heat from the surface and 2) restricting the effective Rayleigh number to remain subcritical. It is demonstrated that CISCs are correctly handled by large-eddy simulation (LES) and thus may provide a way to improve representation of them or their effects. For some applications, it may suffice to allow M-CISCs to develop, but account for their shortcomings during interpretation.

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19

Beaver, Scott, Ahmet Palazoglu, Angadh Singh, Su-Tzai Soong, and Saffet Tanrikulu. "Identification of weather patterns impacting 24-h average fine particulate matter pollution." Atmospheric Environment 44, no. 14 (May 2010): 1761–71. http://dx.doi.org/10.1016/j.atmosenv.2010.02.001.

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20

Anderson, Hal E. "Moisture diffusivity and response time in fine forest fuels." Canadian Journal of Forest Research 20, no. 3 (March 1, 1990): 315–25. http://dx.doi.org/10.1139/x90-046.

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Fine forest fuels, such as grasses, hardwood leaves, and conifer needles, vary greatly in response times and mean moisture diffusion coefficients when exposed to desorption and adsorption conditions. Results are reported for tests made with recently dead and weathered dead fine forest fuels and small woody samples. Test conditions were 26.7 °C (80°F) with changes in relative humidity from 90 to 20% and back, in an environmental chamber. Moisture diffusivities of fine forest fuels were found to be smaller than diffusivities of woody samples. The diffusivities of the foliage and grass fuels tested ranged from near 1.0 × 10−10 to 1.0 × 10−8 cm2/s, whereas the woody fuels ranged from 1.5 × 10−7 to3.0 × 10−5 cm2/s. Weathered fine fuels had faster response times and higher diffusivities than recently cast materials. Adsorption response times were longer and diffusivities lower than for fuels in desorption. Response times of various recently dead fine fuels ranged from 0.2 to 37 h and weathered fuels from 0.5 to 10 h. Therefore, specific fuel types need to be tested to assign more precise response times. Under the drying conditions of 26.7 °C and 20% relative humidity, fine forest fuels had lower diffusivities and longer response times than anticipated in the United States National Fire Danger Rating System. As a result, predicted fire danger during or after a weather change may be overestimated because fuels are responding more slowly than anticipated. Equations are presented for making first estimates of response time and (or) diffusivity if certain physical properties are known: surface area-to-volume ratio, packing ratio, and bed depth.

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21

Bonnardot, Valérie, Victoria Anne Carey, Malika Madelin, Sylvie Cautenet, Zelmari Coetzee, and Hervé Quénol. "Spatial variability of night temperatures at a fine scale over the Stellenbosch wine district, South Africa." OENO One 46, no. 1 (March 31, 2012): 1. http://dx.doi.org/10.20870/oeno-one.2012.46.1.1504.

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<p style="text-align: justify;"><strong>Aim</strong>: To improve knowledge of spatial climatic variability in viticultural region at fine scale</p><p style="text-align: justify;"><strong>Methods and results</strong>: Night temperatures recorded at 40 data loggers that were located in the vineyards of the Stellenbosch Wine of Origin District were monitored during different weather conditions during the 2009 grape ripening period (January-March). The daily maximum difference in minimum temperature between the coolest and warmest sites was, on average, 3.2 °C for the three-month period while it reached a difference of 14 °C under radiative conditions (a difference of 1 °C to 2 °C per km and 3 °C per 100 m elevation approximately). Numerical simulations of night temperatures, using a mesoscale atmospheric model, were performed for two weather events over this period. Night temperature fields at 200m resolution were generated, taking large scale weather conditions into account. Data from 16 automatic weather stations were used for validation. Temperature data from the data loggers that were located in the vineyards were used to produce maps of spatial distribution of the daily minimum temperature at a 90m scale by means of multicriteria statistical modelling, which concomitantly took environmental factors into account. Locations with optimum thermal conditions for color and flavor development and maintenance were identified based on average values for the three-month period and for specific weather conditions.</p><p style="text-align: justify;"><strong>Conclusion</strong>: The range of minimum temperatures varied as a function of geographical factors and synoptic weather conditions, which resulted in significant differences in night-time thermal conditions over the wine district, with possible implications for grape metabolism. The great spatial variability within short distances emphasized the difficulty of validating outputs of atmospheric modelling with accuracy. The study showed the importance and relevance of increasing resolution to refine studies on climate spatial variability and to perform climate modelling based on distinguished weather types.</p><p style="text-align: justify;"><strong>Significance and impact of the study</strong>: In the context of climate change, it is crucial to improve knowledge of current climatic conditions at fine scale during periods of grapevine growth and berry ripening in order to have a baseline from which to work when discussing and considering future local adaptations to accommodate to a warmer environnement.</p>

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22

Lai, Li-Wei. "Extreme fine particulate matter events in Taiwan Island related to synoptic weather patterns." Theoretical and Applied Climatology 144, no. 1-2 (February 19, 2021): 593–609. http://dx.doi.org/10.1007/s00704-021-03549-5.

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23

Loken, Eric D., Adam J. Clark, Ming Xue, and Fanyou Kong. "Comparison of Next-Day Probabilistic Severe Weather Forecasts from Coarse- and Fine-Resolution CAMs and a Convection-Allowing Ensemble." Weather and Forecasting 32, no. 4 (July 3, 2017): 1403–21. http://dx.doi.org/10.1175/waf-d-16-0200.1.

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Abstract Given increasing computing power, an important question is whether additional computational resources would be better spent reducing the horizontal grid spacing of a convection-allowing model (CAM) or adding members to form CAM ensembles. The present study investigates this question as it applies to CAM-derived next-day probabilistic severe weather forecasts created by using forecast updraft helicity as a severe weather proxy for 63 days of the 2010 and 2011 NOAA Hazardous Weather Testbed Spring Forecasting Experiments. Forecasts derived from three sets of Weather Research and Forecasting Model configurations are tested: a 1-km deterministic model, a 4-km deterministic model, and an 11-member, 4-km ensemble. Forecast quality is evaluated using relative operating characteristic (ROC) curves, attributes diagrams, and performance diagrams, and forecasts from five representative cases are analyzed to investigate their relative quality and value in a variety of situations. While no statistically significant differences exist between the 4- and 1-km deterministic forecasts in terms of area under ROC curves, the 4-km ensemble forecasts offer weakly significant improvements over the 4-km deterministic forecasts over the entire 63-day dataset. Further, the 4-km ensemble forecasts generally provide greater forecast quality relative to either of the deterministic forecasts on an individual day. Collectively, these results suggest that, for purposes of improving next-day CAM-derived probabilistic severe weather forecasts, additional computing resources may be better spent on adding members to form CAM ensembles than on reducing the horizontal grid spacing of a deterministic model below 4 km.

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Das, Someshwar, S. V. Singh, E. N. Rajagopal, and Robert Gall. "Mesoscale Modeling for Mountain Weather Forecasting Over the Himalayas." Bulletin of the American Meteorological Society 84, no. 9 (September 1, 2003): 1237–44. http://dx.doi.org/10.1175/bams-84-9-1237.

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Severe weather has a more calamitous effect in the mountainous region because the terrain is complex and the economy is poorly developed and fragile. Such weather systems occurring on a small spatiotemporal scale invite application of models with fine-grid resolution and observations from radars and satellites besides the conventional observations for forecasting and disaster mitigation.

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25

MICHALAKES, JOHN, and MANISH VACHHARAJANI. "GPU ACCELERATION OF NUMERICAL WEATHER PREDICTION." Parallel Processing Letters 18, no. 04 (December 2008): 531–48. http://dx.doi.org/10.1142/s0129626408003557.

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Weather and climate prediction software has enjoyed the benefits of exponentially increasing processor power for almost 50 years. Even with the advent of large-scale parallelism in weather models, much of the performance increase has come from increasing processor speed rather than increased parallelism. This free ride is nearly over. Recent results also indicate that simply increasing the use of large-scale parallelism will prove ineffective for many scenarios where strong scaling is required. We present an alternative method of scaling model performance by exploiting emerging architectures using the fine-grain parallelism once used in vector machines. The paper shows the promise of this approach by demonstrating a nearly 10 × speedup for a computationally intensive portion of the Weather Research and Forecast (WRF) model on a variety of NVIDIA Graphics Processing Units (GPU). This change alone speeds up the whole weather model by 1.23×.

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Liu, Wei, Yue Yang, and Longsheng Wei. "Weather Recognition of Street Scene Based on Sparse Deep Neural Networks." Journal of Advanced Computational Intelligence and Intelligent Informatics 21, no. 3 (May 19, 2017): 403–8. http://dx.doi.org/10.20965/jaciii.2017.p0403.

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Recognizing different weather conditions is a core component of many different applications of outdoor video analysis and computer vision. Street analysis performance, including detecting street objects, detecting road lines, recognizing street sign and etc., varies greatly with weather, so modeling based on weather recognition is the key resolution in this field. Features derived from intrinsic properties of different weather conditions contribute to successful classification. We first propose using deep learning features from convolutional neural networks (CNN) for fine recognition. In order to reduce the parameter redundancy in CNN, we used sparse decomposition to dramatically cut down the computation. Recognition results for databases show superior performance and indicate the effectiveness of extracted features.

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27

Ansley, RJ, DL Jones, TR Tunnell, BA Kramp, and PW Jacoby. "Honey Mesquite Canopy Responses to Single Winter Fires: Relation to Herbaceous Fuel, Weather and Fire Temperature." International Journal of Wildland Fire 8, no. 4 (1998): 241. http://dx.doi.org/10.1071/wf9980241.

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Honey mesquite (Prosopis glandulosa Torr.) canopy responses to fire were measured following 20 single winter fires conducted in north Texas. Weather conditions during the fires, understory herbaceous fine fuel (fine fuel) amount and moisture content, fire temperature at 0 cm, 10-30 cm and 1-3 m above ground, and canopy responses were compared. Ten fires occurred on a site where fine fuel was a mixture of cool and warm season grasses (mixed site). The other 10 fires occurred on a site dominated by warm season grasses (warm site). When both sites were included in regressions, peak fire temperature at all heights was positively related to fine fuel amount. Fine fuel amount, fine fuel moisture content, air temperature (AT) and relative humidity (RH) affected fire temperature duration in seconds over 100°C (FTD100) at 1-3 m height, but not at ground level. Mesquite percent above-ground mortality (topkill) increased with increasing fine fuel amount, decreasing fuel moisture content, increasing AT, and decreasing RH. Percent foliage remaining on non-topkilled (NTK) trees was inversely related to fine fuel amount and AT, and positively related to fine fuel moisture content. Effect of fire on mesquite topkill and foliage remaining of NTK trees was strongly affected by RH at the warm site (r2 = 0.92 and 0.82, respectively), but not at the mixed site. This difference was due to RH affecting fuel moisture content (and subsequently fire behavior) to a greater degree at the warm than at the mixed site, because of the lower green tissue content in warm site grasses at the time of burning. Under adequate fine fuel amounts to carry a fire, mesquite canopy responses to fire (i.e., topkill vs, partial canopy defoliation) were largely determined by AT and RH conditions during the fire. This has implications if the management goal is to preserve the mesquite overstory for a savanna result instead of topkilling all trees. Two substudies were conducted during 3 of the fires. Substudy 1 determined mesquite response to fire in 2 plots with different understory herbaceous fuel loads (5,759 vs. 2,547 kg/ha) that were burned under under similar weather conditions. Mesquite topkill was 81% and 11% in the high and low fuel fires, respectively. Under similar weather conditions, fine fuel was an important factor in affecting mesquite responses to fire. However, as demonstrated in the main study, under a variety of weather conditions, AT and RH influenced mesquite response to fire as much or more than did fine fuel. Substudy 2 compared response of mesquite plants with abundant and dry subcanopy fine fuel (3252 kg/ha; fuel moisture 10.4%), or sparse and green subcanopy fuel (1155 kg/ha; fuel moisture 25.9%) to a high intensity fire. All trees were topkilled, including those with low subcanopy fuel, probably from convection heat generated from herbaceous fuel in interspaces between trees. In support of this conclusion, thermocouple data from all 20 fires indicated that canopy responses were more related to fire temperature at 1-3 m than at lower heights. This suggests that the topkill mechanism was due to convective heat within the canopy rather than a girdling effect of fire at stem bases.

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TSUJI, Koji, Masafumi FUJITA, WeonJae KIM, Satoshi MANAGAKI, Fumiyuki NAKAJIMA, and Hiroaki FURUMAI. "Diurnal Behavior of LAS in Domestic Wastewater from Residential District on Fine-Weather Day." Journal of Japan Society on Water Environment 30, no. 10 (2007): 579–83. http://dx.doi.org/10.2965/jswe.30.579.

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29

Richards, R. "Fine forecasts: encouraging the media to include ultraviolet radiation information in summertime weather forecasts." Health Education Research 19, no. 6 (December 1, 2004): 677–85. http://dx.doi.org/10.1093/her/cyg085.

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30

Tian, Qing, Mei Li, Scott Montgomery, Bo Fang, Chunfang Wang, Tian Xia, and Yang Cao. "Short-Term Associations of Fine Particulate Matter and Synoptic Weather Types with Cardiovascular Mortality: An Ecological Time-Series Study in Shanghai, China." International Journal of Environmental Research and Public Health 17, no. 3 (February 10, 2020): 1111. http://dx.doi.org/10.3390/ijerph17031111.

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Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.

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Tymstra, Cordy, Mike D. Flannigan, Owen B. Armitage, and Kimberley Logan. "Impact of climate change on area burned in Alberta's boreal forest." International Journal of Wildland Fire 16, no. 2 (2007): 153. http://dx.doi.org/10.1071/wf06084.

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Eight years of fire weather data from sixteen representative weather stations within the Boreal Forest Natural Region of Alberta were used to compile reference weather streams for low, moderate, high, very high and extreme Fire Weather Index (FWI) conditions. These reference weather streams were adjusted to create daily weather streams for input into Prometheus – the Canadian Wildland Fire Growth Model. Similar fire weather analyses were completed using Canadian Regional Climate Model (CRCM) output for northern Alberta (174 grid cells) to generate FWI class datasets (temperature, relative humidity, wind speed, Fine Fuel Moisture Code, Duff Moisture Code and Drought Code) for 1 ×, 2 × and 3 × CO2 scenarios. The relative differences between the CRCM scenario outputs were then used to adjust the reference weather streams for northern Alberta. Area burned was calculated for 21 fires, fire weather classes and climate change scenarios. The area burned estimates were weighted based on the historical frequency of area burned by FWI class, and then normalized to derive relative area burned estimates for each climate change scenario. The 2 × and 3 × CO2 scenarios resulted in a relative increase in area burned of 12.9 and 29.4% from the reference 1 × CO2 scenario.

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32

Brožková, R., M. Derková, M. Belluš, and A. Farda. "Atmospheric forcing by ALADIN/MFSTEP and MFSTEP oriented tunings." Ocean Science 2, no. 2 (September 1, 2006): 113–21. http://dx.doi.org/10.5194/os-2-113-2006.

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Abstract. ALADIN/MFSTEP is a configuration of the numerical weather prediction (NWP) model ALADIN run in a dedicated real-time mode for the purposes of the MFSTEP Project. A special attention was paid to the quality of atmospheric fluxes used for the forcing of fine-scale oceanographic models. This paper describes the novelties applied in ALADIN/MFSTEP initiated by the MFSTEP demands, leading also to improvements in general weather forecasting.

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Brožková, R., M. Derková, M. Belluš, and F. Farda. "Atmospheric forcing by ALADIN/MFSTEP and MFSTEP oriented tunings." Ocean Science Discussions 3, no. 3 (May 24, 2006): 319–42. http://dx.doi.org/10.5194/osd-3-319-2006.

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Abstract. ALADIN/MFSTEP is a configuration of the numerical weather prediction (NWP) model ALADIN run in a dedicated real-time mode for the purposes of the MFSTEP Project. A special attention was paid to the quality of atmospheric fluxes used for the forcing of fine-scale oceanographic models. This paper describes the novelties applied in ALADIN/MFSTEP initiated by the MFSTEP demands, leading also to improvements in general weather forecasting.

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CHOMÉ, F., and C. NICOLIS. "LIMITED AREA WEATHER PREDICTION MODELS VIEWED AS DYNAMICAL SYSTEMS." International Journal of Bifurcation and Chaos 09, no. 05 (May 1999): 831–42. http://dx.doi.org/10.1142/s0218127499000584.

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Different strategies for building high-resolution models providing a more detailed description of a limited area of interest as for example, in regional weather forecasts are developed. They are subsequently compared, on the basis of the dynamical behavior generated by the corresponding models. The statistical properties of the relevant fields are analyzed, and predictability experiments are performed on statistical ensembles of close lying trajectories whose mean distance represents the uncertainty in the initial state of the system. The results show that a global, variable-mesh model performs much better than a limited area fine mesh one embedded into a coarser global model.

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Flannigan, MD, BM Wotton, and S. Ziga. "A Study on the Interpolation of Fire Danger Using Radar Precipitation Estimates." International Journal of Wildland Fire 8, no. 4 (1998): 217. http://dx.doi.org/10.1071/wf9980217.

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In Canada, many fire management agencies interpolate indexes of the Fire Weather Index System to estimate the fire danger between weather stations. Difficulties with interpolation arise because summer precipitation can be highly variable over short distances. This variability hinders the usefulness of interpolating precipitation, which is one of the inputs for the Fire Weather Index System. Precipitation estimates from the Canadian Atmospheric Environment Service radar at Upsala, Ontario, were used to determine if this will enable a more accurate measure of the fire danger over the region. Three methods of interpolation of the fire danger between weather stations were compared: first, the standard practice of interpolating fire weather indexes from weather stations to any specified location; second, interpolating the weather variables, temperature, relative humidity, wind speed and precipitation from the weather station to any specified site and then calculating the fire weather indexes; third, interpolating weather variables as in Method 2 above except using the precipitation estimate from the radar and then calculating the fire weather indexes for any specified site. Overall, results indicate that the standard procedure of interpolating the fire weather indexes performs better than the other two methods. However, there are indexes where the other methods perform best (e.g., the fine fuel moisture code is best determined by using the radar precipitation estimation method). Fire management agencies should continue to use the standard practice of interpolating fire weather indexes to estimate fire danger between weather stations. Factors influencing the performance of the radar estimated precipitation method of estimating fire danger are discussed along with potential application of precipitation radar for fire management purposes.

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He, Yongming, Lei He, Yuan Wang, Yu Xiao, Yingwu Chen, and Lining Xing. "Autonomous Mission Replanning Method for Imaging Satellites Considering Real-Time Weather Conditions." Journal of Computational and Theoretical Nanoscience 13, no. 10 (October 1, 2016): 6967–73. http://dx.doi.org/10.1166/jctn.2016.5654.

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During the observations made by imaging satellites, meteorological factors are likely to change frequently. The vagaries of weather conditions and significant effects on the actual observation results mean that there is an urgent need to apply more intelligence to satellite mission planning. Thus, this paper describes an autonomous replanning method for imaging satellites that considers the real-time weather conditions. Considering the characteristics of different input data, this method replans the low-yield task set and fine-tunes others to improve profitability. Moreover, the proposed method can heuristically select the appropriate adjustment rule to achieve autonomous satellite mission planning. A series of simulations with various task quantities and in different environments shows that the proposed method can respond effectively to real-time weather changes, and can steadily improve the total profits in a variety of weather conditions during Earth observation activities.

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Murase, Hiroshi, Masayuki Yoda, Goro Sawa, and Eiji Kaneko. "Residual DC Charge Leakage Mechanism of a Transmission Line under Fine and Dry Weather Conditions." IEEJ Transactions on Power and Energy 125, no. 10 (2005): 1000–1006. http://dx.doi.org/10.1541/ieejpes.125.1000.

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Owolagba, John, and Shahid Azam. "Effect of seasonal weather variations on the desiccation behavior of treated oil sand fine tailings." Environmental Earth Sciences 74, no. 2 (February 22, 2015): 1711–17. http://dx.doi.org/10.1007/s12665-015-4179-z.

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Murase, Hiroshi, Masayuki Yoda, Goro Sawa, and Eiji Kaneko. "Residual DC charge leakage mechanism of a transmission line under fine and dry weather conditions." Electrical Engineering in Japan 165, no. 2 (November 15, 2008): 45–52. http://dx.doi.org/10.1002/eej.20417.

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Anderson, Stuart A. J., and Wendy R. Anderson. "Predicting the elevated dead fine fuel moisture content in gorse (Ulex europaeus L.) shrub fuels." Canadian Journal of Forest Research 39, no. 12 (December 2009): 2355–68. http://dx.doi.org/10.1139/x09-142.

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Methods were developed to predict the moisture content of the elevated dead fine fuel layer in gorse ( Ulex europaeus L.) shrub fuels. This layer has been observed to be important for fire development and spread in these fuels. The accuracy of the Fine Fuel Moisture Code (FFMC) of the Canadian Fire Weather Index System to predict the moisture content of this layer was evaluated. An existing model was used to determine the response time and equilibrium moisture content from field data. This response time was incorporated into a bookkeeping model, combining the FFMC and this response time–equilibrium moisture content model. The FFMC poorly predicted the elevated dead fuel moisture content in gorse fuels, and attempts to improve its accuracy through regression modelling were unsuccessful. The response time of the elevated dead fine fuel layer was very fast (38–77 min) and has important implications for fire danger rating. The bookkeeping approach was the most promising method to predict elevated dead fuel moisture content. A limitation was the inability to model fuel-level meteorology. However, this model warrants further validation and extension to other shrub fuels and could be incorporated into existing fire danger rating systems that can utilize hourly weather data.

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Liu, Jane, and Siliang Cui. "Meteorological Influences on Seasonal Variation of Fine Particulate Matter in Cities over Southern Ontario, Canada." Advances in Meteorology 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/169476.

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This study examines meteorological impacts on seasonal variation of fine particulate matter (PM2.5) in southern Ontario, Canada. After analyzing PM2.5data at 12 cities in the region in 2006, we found that PM2.5concentrations were 30–40% higher in summer (7–15 μg/m3) than in winter (4–11 μg/m3). High PM2.5episodes occurred more frequently in warmer seasons. Analyses of surface meteorology, weather maps, and airflow trajectories suggest that these PM2.5episodes were often related to synoptic transport of pollutants from highly polluted areas in the United States. The southerly or southwesterly winds associated with midlatitude cyclones play an important role in such transport. A typical weather pattern favoring the transport is suggested. When it was hot, humid, and stagnant with southerly or southwesterly winds, the likelihood of high PM2.5occurrences was high. The Greater Golden Horseshoe and Southwestern Ontario regions had higher PM2.5(6–12 μg/m3annually) than the northern region (4–6 μg/m3), reflecting combined effects of meteorology, regional transport, and local emissions. In the future, PM2.5transport from the United States will likely increase in abundance because of possible prolonged accumulation at the pollution sources as the frequency of the midlatitude cyclones may reduce under climate change.

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Govett, Mark, Jim Rosinski, Jacques Middlecoff, Tom Henderson, Jin Lee, Alexander MacDonald, Ning Wang, Paul Madden, Julie Schramm, and Antonio Duarte. "Parallelization and Performance of the NIM Weather Model on CPU, GPU, and MIC Processors." Bulletin of the American Meteorological Society 98, no. 10 (October 1, 2017): 2201–13. http://dx.doi.org/10.1175/bams-d-15-00278.1.

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Abstract The design and performance of the Non-Hydrostatic Icosahedral Model (NIM) global weather prediction model is described. NIM is a dynamical core designed to run on central processing unit (CPU), graphics processing unit (GPU), and Many Integrated Core (MIC) processors. It demonstrates efficient parallel performance and scalability to tens of thousands of compute nodes and has been an effective way to make comparisons between traditional CPU and emerging fine-grain processors. The design of the NIM also serves as a useful guide in the fine-grain parallelization of the finite volume cubed (FV3) model recently chosen by the National Weather Service (NWS) to become its next operational global weather prediction model. This paper describes the code structure and parallelization of NIM using standards-compliant open multiprocessing (OpenMP) and open accelerator (OpenACC) directives. NIM uses the directives to support a single, performance-portable code that runs on CPU, GPU, and MIC systems. Performance results are compared for five generations of computer chips including the recently released Intel Knights Landing and NVIDIA Pascal chips. Single and multinode performance and scalability is also shown, along with a cost–benefit comparison based on vendor list prices.

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Park, Sun Kyoung. "Seasonal Variations of Fine Particulate Matter and Mortality Rate in Seoul, Korea with a Focus on the Short-Term Impact of Meteorological Extremes on Human Health." Atmosphere 12, no. 2 (January 25, 2021): 151. http://dx.doi.org/10.3390/atmos12020151.

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Rapid industrialization of Korea’s economy has brought with it environmental pollution that threatens human health. Among various other pollutants, ambient fine particulate matter known to endanger human health often exceeds air quality standards in Seoul, South Korea’s capital. The goal of this research is to find the impact of meteorological extremes and particle levels on human health. The analysis was conducted using hourly air pollutant concentrations, meteorological variables, and the daily mortality from cerebrovascular disease. Results show that the effect of fine particulate matter on mortality from cerebrovascular disease was more noticeable during meteorological extremes. The linkage between extreme weather conditions and mortality was more apparent in winter than in summer. Comprehensive studies of various causes of diseases should be continued to more accurately analyze the effects of fine particulate matter on human health and meteorological extremes, and to further minimize the public health impact of air pollution and meteorological conditions.

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Gebetsberger, Manuel, Jakob W. Messner, Georg J. Mayr, and Achim Zeileis. "Fine-Tuning Nonhomogeneous Regression for Probabilistic Precipitation Forecasts: Unanimous Predictions, Heavy Tails, and Link Functions." Monthly Weather Review 145, no. 11 (November 2017): 4693–708. http://dx.doi.org/10.1175/mwr-d-16-0388.1.

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Raw ensemble forecasts of precipitation amounts and their forecast uncertainty have large errors, especially in mountainous regions where the modeled topography in the numerical weather prediction model and real topography differ most. Therefore, statistical postprocessing is typically applied to obtain automatically corrected weather forecasts. This study applies the nonhomogenous regression framework as a state-of-the-art ensemble postprocessing technique to predict a full forecast distribution and improves its forecast performance with three statistical refinements. First of all, a novel split-type approach effectively accounts for unanimous zero precipitation predictions of the global ensemble model of the ECMWF. Additionally, the statistical model uses a censored logistic distribution to deal with the heavy tails of precipitation amounts. Finally, it is investigated which are the most suitable link functions for the optimization of regression coefficients for the scale parameter. These three refinements are tested for 10 stations in a small area of the European Alps for lead times from +24 to +144 h and accumulation periods of 24 and 6 h. Together, they improve probabilistic forecasts for precipitation amounts as well as the probability of precipitation events over the default postprocessing method. The improvements are largest for the shorter accumulation periods and shorter lead times, where the information of unanimous ensemble predictions is more important.

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45

Amiro, B. D., K. A. Logan, B. M. Wotton, M. D. Flannigan, J. B. Todd, B. J. Stocks, and D. L. Martell. "Fire weather index system components for large fires in the Canadian boreal forest." International Journal of Wildland Fire 13, no. 4 (2004): 391. http://dx.doi.org/10.1071/wf03066.

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Canadian Fire Weather Index (FWI) System components and head fire intensities were calculated for fires greater than 2 km2 in size for the boreal and taiga ecozones of Canada from 1959 to 1999. The highest noon-hour values were analysed that occurred during the first 21 days of each of 9333 fires. Depending on ecozone, the means of the FWI System parameters ranged from: fine fuel moisture code (FFMC), 90 to 92 (82 to 96 for individual fires); duff moisture code (DMC), 38 to 78 (10 to 140 for individual fires); drought code (DC), 210 to 372 (50 to 600 for individual fires); and fire weather index, 20 to 33 (5 to 60 for individual fires). Fine fuel moisture code decreased, DMC had a mid-season peak, and DC increased through the fire season. Mean head fire intensities ranged from 10 to 28 MW m−1 in the boreal spruce fuel type, showing that most large fires exhibit crown fire behaviour. Intensities of individual fires can exceed 60 MW m−1. Most FWI System parameters did not show trends over the 41-year period because of large inter-annual variability. A changing climate is expected to create future weather conditions more conducive to fire throughout much of Canada but clear changes have not yet occurred.

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46

Lafont, M., L. Grapentine, Q. Rochfort, J. Marsalek, G. Tixier, and P. Breil. "Bioassessment of wet-weather pollution impacts on fine sediments in urban waters by benthic indices and the sediment quality triad." Water Science and Technology 56, no. 9 (November 1, 2007): 13–20. http://dx.doi.org/10.2166/wst.2007.737.

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Benthic invertebrate assessments can be used to gauge the impact of urban wet-weather flows in receiving waters. Experiences from Cemagref in France have shown that standardized benthic indices (e.g. Oligochaete Index of Sediment Bioindication - IOBS) can be used to reliably determine the ecological status of urban streams and can be incorporated into the new European Water Framework Directive. The Canadian studies on streams and stormwater ponds using chemical analyses, benthic toxicity testing and benthic invertebrate community structure (i.e. the sediment quality triad) comparisons have shown that toxicity was more likely to occur in ponds at sites with higher concentrations of heavy metals and heavier polycyclic aromatic hydrocarbons, and at greater water depths, where fine sediments from urban runoff accumulated. A more comprehensive evaluation of wet-weather flow impacts could be obtained by combining approaches from both countries.

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Yin Kaixin, 尹凯欣, 范承玉 Fan Chengyu, 王海涛 Wang Haitao, 乔春红 Qiao Chunhong, and 张鹏飞 Zhang Pengfei. "Research on aerosol extinction characteristics in haze and fine weather in southeast coastal area of China." High Power Laser and Particle Beams 27, no. 7 (2015): 71011. http://dx.doi.org/10.3788/hplpb20152707.71011.

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48

Vlahogianni, Eleni I., and Matthew G. Karlaftis. "Comparing traffic flow time-series under fine and adverse weather conditions using recurrence-based complexity measures." Nonlinear Dynamics 69, no. 4 (April 4, 2012): 1949–63. http://dx.doi.org/10.1007/s11071-012-0399-x.

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49

Wong, Wai-Kin, Cheong-Shing Lau, and Pak-Wai Chan. "Aviation Model: A Fine-Scale Numerical Weather Prediction System for Aviation Applications at the Hong Kong International Airport." Advances in Meteorology 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/532475.

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The Hong Kong Observatory (HKO) is planning to implement a fine-resolution Numerical Weather Prediction (NWP) model for supporting the aviation weather applications at the Hong Kong International Airport (HKIA). This new NWP model system, called Aviation Model (AVM), is configured at a horizontal grid spacing of 600 m and 200 m. It is based on the WRF-ARW (Advance Research WRF) model that can have sufficient computation efficiency in order to produce hourly updated forecasts up to 9 hours ahead on a future high performance computer system with theoretical peak performance of around 10 TFLOPS. AVM will be nested inside the operational mesoscale NWP model of HKO with horizontal resolution of 2 km. In this paper, initial numerical experiment results in forecast of windshear events due to seabreeze and terrain effect are discussed. The simulation of sea-breeze-related windshear is quite successful, and the headwind change observed from flight data could be reproduced in the model forecast. Some impacts of physical processes on generating the fine-scale wind circulation and development of significant convection are illustrated. The paper also discusses the limitations in the current model setup and proposes methods for the future development of AVM.

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Obembe, Oladipo S., Nathan P. Hendricks, and Jesse Tack. "Decreased wheat production in the USA from climate change driven by yield losses rather than crop abandonment." PLOS ONE 16, no. 6 (June 17, 2021): e0252067. http://dx.doi.org/10.1371/journal.pone.0252067.

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An increase in global average surface temperature over the 21st century will affect food production. There is still uncertainty if the source of the production losses caused by climate change could be driven either by lower yield or reduced area harvested. We use county-level production data on winter wheat coupled with fine-scale weather outcomes between 1981-2007 to examine the impact of climate change on winter wheat production in Kansas. We decompose the total impact of weather variables through both the yield and harvested acreage channels. We find that an insignificant portion—both in terms of magnitude and statistical significance—of the production losses are due to reduced harvested acres (i.e., crop abandonment). The proportion harvested only account for 14.88% and 21.71% of the total damages under RCPs 4.5 and 8.5 and neither effect is statistically significant. An implication of this result implies that studies that only examine climate impacts on harvested yields are not significantly underestimating the climate change impacts on production.

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