scholarly journals Weather Factors Associated with Extremely Large Fires and Fire Growth Days

2021 ◽  
pp. 1-53
Author(s):  
Brian E. Potter ◽  
Daniel McEvoy
Keyword(s):  
Wind Speed ◽  
Growth Response ◽  
Health Management ◽  
Fire Growth ◽  
Weather Factors ◽  
Evaporative Demand ◽  
Fire Weather Index ◽  
Near Surface ◽  
Daily Weather ◽  
Large Fires

Abstract“Megafires” are of scientific interest and concern for fire management, public safety planning, and smoke-related public health management. There is a need to predict them on time scales from days to decades. Understanding is limited, however, of the role of daily weather in determining their extreme size. This study examines differences in the daily weather during these and other, smaller fires, and in the two sets of fires’ responses to daily weather and antecedent atmospheric dryness. Twenty fires of unusual size (over 36 400 ha), were each paired with a nearby large fire (10 100 to 30 300 ha). Antecedent dryness and daily near-surface weather were compared for each set of fires. Growth response to daily weather was also examined for differences between the two sets of fires. Antecedent dryness measured as the Evaporative Demand Drought Index was greater for most of the fires of unusual size than it was for smaller fires. There were small differences in daily weather, with those differences indicating weather less conducive to fire growth for the unusually large fires than the smaller fires. Growth response was similar for the two sets of fires when weather properties were between 40th and 60th percentiles for each fire pair, but the unusually large fires’ growth was observably greater than the smaller fires’ growth for weather properties between the 80th to 100th percentiles. Response differences were greatest for wind speed, and for the Fosberg Fire Weather Index and variants of the Hot-Dry-Windy Index, which combine wind speed with atmospheric moisture.

scholarly journals Homogenization and Assessment of Observed Near-Surface Wind Speed Trends over Spain and Portugal, 1961–2011*

2014 ◽  
Vol 27 (10) ◽  
pp. 3692-3712 ◽  
Author(s):  
Cesar Azorin-Molina ◽  
Sergio M. Vicente-Serrano ◽  
Tim R. McVicar ◽  
Sonia Jerez ◽  
Arturo Sanchez-Lorenzo ◽  
...  
Keyword(s):  
Wind Speed ◽  
Mesoscale Model ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
State University ◽  
Evaporative Demand ◽  
Near Surface ◽  
Fifth Generation ◽  
Simulated Series ◽  
Increasing Trends

Abstract Near-surface wind speed trends recorded at 67 land-based stations across Spain and Portugal for 1961–2011, also focusing on the 1979–2008 subperiod, were analyzed. Wind speed series were subjected to quality control, reconstruction, and homogenization using a novel procedure that incorporated the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)-simulated series as reference. The resultant series show a slight downward trend for both 1961–2011 (−0.016 m s−1 decade−1) and 1979–2008 (−0.010 m s−1 decade−1). However, differences between seasons with declining values in winter and spring, and increasing trends in summer and autumn, were observed. Even though wind stilling affected 77.8% of the stations in winter and 66.7% in spring, only roughly 40% of the declining trends were statistically significant at the p < 0.10 level. On the contrary, increasing trends appeared in 51.9% of the stations in summer and 57.4% in autumn, with also around 40% of the positive trends statistically significant at the p < 0.10 level. In this article, the authors also investigated (i) the possible impact of three atmospheric indices on the observed trends and (ii) the role played by the urbanization growth in the observed decline. An accurate homogenization and assessment of the long-term trends of wind speed is crucial for many fields such as wind energy (e.g., power generation) and agriculture–hydrology (e.g., evaporative demand).

Recurrence Characteristics Analysis of Near-Surface Wind Speed Signal with Different Sampling Frequencies

2014 ◽  
Vol 599-601 ◽  
pp. 1605-1609 ◽  
Author(s):  
Ming Zeng ◽  
Zhan Xie Wu ◽  
Qing Hao Meng ◽  
Jing Hai Li ◽  
Shu Gen Ma
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Surface Wind Speed ◽  
Recurrence Plot ◽  
Sampling Frequency ◽  
Near Surface ◽  
Gas Leakage ◽  
Time Period ◽  
Characteristics Analysis ◽  
Quantification Analysis

The wind is the main factor to influence the propagation of gas in the atmosphere. Therefore, the wind signal obtained by anemometer will provide us valuable clues for searching gas leakage sources. In this paper, the Recurrence Plot (RP) and Recurrence Quantification Analysis (RQA) are applied to analyze the influence of recurrence characteristics of the wind speed time series under the condition of the same place, the same time period and with the sampling frequency of 1hz, 2hz, 4.2hz, 5hz, 8.3hz, 12.5hz and 16.7hz respectively. Research results show that when the sampling frequency is higher than 5hz, the trends of recurrence nature of different groups are basically unchanged. However, when the sampling frequency is set below 5hz, the original trend of recurrence nature is destroyed, because the recurrence characteristic curves obtained using different sampling frequencies appear cross or overlapping phenomena. The above results indicate that the anemometer will not be able to fully capture the detailed information in wind field when its sampling frequency is lower than 5hz. The recurrence characteristics analysis of the wind speed signals provides an important basis for the optimal selection of anemometer.

scholarly journals The ground-level ozone concentration is inversely correlated with the number of COVID-19 cases in Warsaw, Poland

2021 ◽  
Author(s):  
Oskar Wiśniewski ◽  
Wiesław Kozak ◽  
Maciej Wiśniewski
Keyword(s):  
Wind Speed ◽  
Ozone Concentration ◽  
Inverse Correlation ◽  
Ground Level ◽  
Viral Agent ◽  
The Novel ◽  
Weather Factors ◽  
Ground Level Ozone ◽  
The Many ◽  
The Impact

AbstractCOVID-19, which is a consequence of infection with the novel viral agent SARS-CoV-2, first identified in China (Hubei Province), has been declared a pandemic by the WHO. As of September 10, 2020, over 70,000 cases and over 2000 deaths have been recorded in Poland. Of the many factors contributing to the level of transmission of the virus, the weather appears to be significant. In this work, we analyze the impact of weather factors such as temperature, relative humidity, wind speed, and ground-level ozone concentration on the number of COVID-19 cases in Warsaw, Poland. The obtained results show an inverse correlation between ground-level ozone concentration and the daily number of COVID-19 cases.

scholarly journals Observed Boundary Layer Wind Structure and Balance in the Hurricane Core. Part I: Hurricane Georges

2006 ◽  
Vol 63 (9) ◽  
pp. 2169-2193 ◽  
Author(s):  
Jeffrey D. Kepert
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Tropical Cyclone ◽  
Radial Profile ◽  
Lower Altitude ◽  
Near Surface ◽  
Wind Structure ◽  
The Right ◽  
Tropical Cyclone Boundary Layer ◽  
Upper Boundary

Abstract The GPS dropsonde allows observations at unprecedentedly high horizontal and vertical resolution, and of very high accuracy, within the tropical cyclone boundary layer. These data are used to document the boundary layer wind field of the core of Hurricane Georges (1998) when it was close to its maximum intensity. The spatial variability of the boundary layer wind structure is found to agree very well with the theoretical predictions in the works of Kepert and Wang. In particular, the ratio of the near-surface wind speed to that above the boundary layer is found to increase inward toward the radius of maximum winds and to be larger to the left of the track than to the right, while the low-level wind maximum is both more marked and at lower altitude on the left of the storm track than on the right. However, the expected supergradient flow in the upper boundary layer is not found, with the winds being diagnosed as close to gradient balance. The tropical cyclone boundary layer model of Kepert and Wang is used to simulate the boundary layer flow in Hurricane Georges. The simulated wind profiles are in good agreement with the observations, and the asymmetries are well captured. In addition, it is found that the modeled flow in the upper boundary layer at the eyewall is barely supergradient, in contrast to previously studied cases. It is argued that this lack of supergradient flow is a consequence of the particular radial structure in Georges, which had a comparatively slow decrease of wind speed with radius outside the eyewall. This radial profile leads to a relatively weak gradient of inertial stability near the eyewall and a strong gradient at larger radii, and hence the tropical cyclone boundary layer dynamics described by Kepert and Wang can produce only marginally supergradient flow near the radius of maximum winds. The lack of supergradient flow, diagnosed from the observational analysis, is thus attributed to the large-scale structure of this particular storm. A companion paper presents a similar analysis for Hurricane Mitch (1998), with contrasting results.

scholarly journals Snow density along the route traversed by the Japanese-Swedish Antarctic Expedition 2007/08

2012 ◽  
Vol 58 (209) ◽  
pp. 529-539 ◽  
Author(s):  
Shin Sugiyama ◽  
Hiroyuki Enomoto ◽  
Shuji Fujita ◽  
Kotaro Fukui ◽  
Fumio Nakazawa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Surface Wind ◽  
Coastal Region ◽  
Snow Density ◽  
Syowa Station ◽  
Near Surface ◽  
A Value ◽  
Surface Snow ◽  
The Mean ◽  
The Antarctic

AbstractDuring the Japanese-Swedish Antarctic traverse expedition of 2007/08, we measured the surface snow density at 46 locations along the 2800 km long route from Syowa station to Wasa station in East Antarctica. The mean snow density for the upper 1 (or 0.5) m layer varied from 333 to 439 kg m-3 over a region spanning an elevation range of 365-3800 ma.s.l. The density variations were associated with the elevation of the sampling sites; the density decreased as the elevation increased, moving from the coastal region inland. However, the density was relatively insensitive to the change in elevation along the ridge on the Antarctic plateau between Dome F and Kohnen stations. Because surface wind is weak in this region, irrespective of elevation, the wind speed was suggested to play a key role in the near-surface densification. The results of multiple regression performed on the density using meteorological variables were significantly improved by the inclusion of wind speed as a predictor. The regression analysis yielded a linear dependence between the density and the wind speed, with a coefficient of 13.5 kg m-3 (m s-1)-1. This relationship is nearly three times stronger than a value previously computed from a dataset available in Antarctica. Our data indicate that the wind speed is more important to estimates of the surface snow density in Antarctica than has been previously assumed.

scholarly journals Evaluation of the AMPS Boundary Layer Simulations on the Ross Ice Shelf, Antarctica, with Unmanned Aircraft Observations

2017 ◽  
Vol 56 (8) ◽  
pp. 2239-2258 ◽  
Author(s):  
Jonathan D. Wille ◽  
David H. Bromwich ◽  
John J. Cassano ◽  
Melissa A. Nigro ◽  
Marian E. Mateling ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Relative Humidity ◽  
High Wind ◽  
Ice Shelf ◽  
High Wind Speed ◽  
Near Surface ◽  
Ross Ice Shelf ◽  
Low Cloud ◽  
The Antarctic

AbstractAccurately predicting moisture and stability in the Antarctic planetary boundary layer (PBL) is essential for low-cloud forecasts, especially when Antarctic forecasters often use relative humidity as a proxy for cloud cover. These forecasters typically rely on the Antarctic Mesoscale Prediction System (AMPS) Polar Weather Research and Forecasting (Polar WRF) Model for high-resolution forecasts. To complement the PBL observations from the 30-m Alexander Tall Tower! (ATT) on the Ross Ice Shelf as discussed in a recent paper by Wille and coworkers, a field campaign was conducted at the ATT site from 13 to 26 January 2014 using Small Unmanned Meteorological Observer (SUMO) aerial systems to collect PBL data. The 3-km-resolution AMPS forecast output is combined with the global European Centre for Medium-Range Weather Forecasts interim reanalysis (ERAI), SUMO flights, and ATT data to describe atmospheric conditions on the Ross Ice Shelf. The SUMO comparison showed that AMPS had an average 2–3 m s−1 high wind speed bias from the near surface to 600 m, which led to excessive mechanical mixing and reduced stability in the PBL. As discussed in previous Polar WRF studies, the Mellor–Yamada–Janjić PBL scheme is likely responsible for the high wind speed bias. The SUMO comparison also showed a near-surface 10–15-percentage-point dry relative humidity bias in AMPS that increased to a 25–30-percentage-point deficit from 200 to 400 m above the surface. A large dry bias at these critical heights for aircraft operations implies poor AMPS low-cloud forecasts. The ERAI showed that the katabatic flow from the Transantarctic Mountains is unrealistically dry in AMPS.

scholarly journals Local Characteristics of the Nocturnal Boundary Layer in Response to External Pressure Forcing

2017 ◽  
Vol 56 (11) ◽  
pp. 3035-3047 ◽  
Author(s):  
Steven J. A. van der Linden ◽  
Peter Baas ◽  
J. Antoon van Hooft ◽  
Ivo G. S. van Hooijdonk ◽  
Fred C. Bosveld ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Stable Boundary Layer ◽  
Dynamical Behavior ◽  
Geostrophic Wind ◽  
External Pressure ◽  
Near Surface ◽  
Stable Boundary ◽  
Wind Speeds ◽  
Turbulent Characteristics

AbstractGeostrophic wind speed data, derived from pressure observations, are used in combination with tower measurements to investigate the nocturnal stable boundary layer at Cabauw, the Netherlands. Since the geostrophic wind speed is not directly influenced by local nocturnal stability, it may be regarded as an external forcing parameter of the nocturnal stable boundary layer. This is in contrast to local parameters such as in situ wind speed, the Monin–Obukhov stability parameter (z/L), or the local Richardson number. To characterize the stable boundary layer, ensemble averages of clear-sky nights with similar geostrophic wind speeds are formed. In this manner, the mean dynamical behavior of near-surface turbulent characteristics and composite profiles of wind and temperature are systematically investigated. The classification is found to result in a gradual ordering of the diagnosed variables in terms of the geostrophic wind speed. In an ensemble sense the transition from the weakly stable to very stable boundary layer is more gradual than expected. Interestingly, for very weak geostrophic winds, turbulent activity is found to be negligibly small while the resulting boundary cooling stays finite. Realistic numerical simulations for those cases should therefore have a comprehensive description of other thermodynamic processes such as soil heat conduction and radiative transfer.

scholarly journals Joint Modeling of Severe Dust Storm Events in Arid and Hyper Arid Regions Based on Copula Theory: A Case Study in the Yazd Province, Iran

Climate ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 64 ◽  
Author(s):  
Tayyebeh Mesbahzadeh ◽  
Maryam Mirakbari ◽  
Mohsen Mohseni Saravi ◽  
Farshad Soleimani Sardoo ◽  
Nir Y. Krakauer
Keyword(s):  
Wind Speed ◽  
Natural Disasters ◽  
Return Period ◽  
Vertical Velocity ◽  
Geopotential Height ◽  
Dust Storms ◽  
Maximum Wind Speed ◽  
Near Surface ◽  
Copula Theory ◽  
Maximum Wind

Natural disasters such as dust storms are random phenomena created by complicated mechanisms involving many parameters. In this study, we used copula theory for bivariate modeling of dust storms. Copula theory is a suitable method for multivariate modeling of natural disasters. We identified 40 severe dust storms, as defined by the World Meteorological Organization, during 1982–2017 in Yazd province, central Iran. We used parameters at two spatial vertical levels (near-surface and upper atmosphere) that included surface maximum wind speed, and geopotential height and vertical velocity at 500, 850, and 1000 hPa. We compared two bivariate models based on the pairs of maximum wind speed–geopotential height and maximum wind speed–vertical velocity. We determined the bivariate return period using Student t and Gaussian copulas, which were considered as the most suitable functions for these variables. The results obtained for maximum wind speed–geopotential height indicated that the maximum return period was consistent with the observed frequency of severe dust storms. The bivariate modeling of dust storms based on maximum wind speed and geopotential height better described the conditions of severe dust storms than modeling based on maximum wind speed and vertical velocity. The finding of this study can be useful to improve risk management and mitigate the impacts of severe dust storms.

scholarly journals Wind plants can impact long-term local atmospheric conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicola Bodini ◽  
Julie K. Lundquist ◽  
Patrick Moriarty
Keyword(s):  
Wind Speed ◽  
Urban Areas ◽  
Weather Prediction ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
Direct Observations ◽  
Stable Conditions ◽  
Weather And Climate ◽  
Central United States

AbstractLong-term weather and climate observatories can be affected by the changing environments in their vicinity, such as the growth of urban areas or changing vegetation. Wind plants can also impact local atmospheric conditions through their wakes, characterized by reduced wind speed and increased turbulence. We explore the extent to which the wind plants near an atmospheric measurement site in the central United States have affected their long-term measurements. Both direct observations and mesoscale numerical weather prediction simulations demonstrate how the wind plants induce a wind deficit aloft, especially in stable conditions, and a wind speed acceleration near the surface, which extend $$\sim 30$$ ∼ 30  km downwind of the wind plant. Turbulence kinetic energy is significantly enhanced within the wind plant wake in stable conditions, with near-surface observations seeing an increase of more than 30% a few kilometers downwind of the plants.

scholarly journals Time Series Analysis on Incidence of Pulmonary Tuberculosis With Weather Factors During 2004-2017 in Guangdong Province, China

2021 ◽  
Author(s):  
Tianyu Qin ◽  
Yu Hao ◽  
Juan He
Keyword(s):  
Wind Speed ◽  
Atmospheric Pressure ◽  
Guangdong Province ◽  
Maximum Temperature ◽  
Maximum Pressure ◽  
Weather Factors ◽  
Sarima Model ◽  
Extreme Wind ◽  
Wind Speed Maximum ◽  
Extreme Wind Speed

Abstract Background: Although the occurrence of some infectious diseases including TB was found to be associated with specific weather factors, few studies have incorporated weather factors into the model to predict the incidence of tuberculosis (TB). We aimed to establish an accurate forecasting model using TB data in Guangdong Province, incorporating local weather factors.Methods: Data of sixteen meteorological variables (2003-2016) and the TB incidence data (2004-2016) of Guangdong were collected. Seasonal autoregressive integrated moving average (SARIMA) model was constructed based on the data. SARIMA model with weather factors as explanatory variables (SARIMAX) was performed to fit and predict TB incidence in 2017. Results: Maximum temperature, maximum daily rainfall, minimum relative humidity, mean vapor pressure, extreme wind speed, maximum atmospheric pressure, mean atmospheric pressure and illumination duration were significantly associated with log(TB incidence). After fitting the SARIMAX model, maximum pressure at lag 6 (β= -0.007, P < 0.05, 95% confidence interval (CI): -0.011, -0.002, mean square error (MSE): 0.279) was negatively associated with log(TB incidence), while extreme wind speed at lag 5 (β=0.009, P < 0.05, 95% CI: 0.005, 0.013, MSE: 0.143) was positively associated. SARIMAX (1, 1, 1) (0, 1, 1)12 with extreme wind speed at lag 5 was the best predictive model with lower Akaike information criterion (AIC) and MSE. The predicted monthly TB incidence all fall within the confidence intervals using this model. Conclusions: Weather factors have different effects on TB incidence in Guangdong. Incorporating meteorological factors into the model increased the accuracy of prediction.

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