scholarly journals Quantifying the Changing Nature of the Winter Season Precipitation Phase from 1849 to 2017 in Downtown Toronto (Canada)

Atmosphere ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 867
Author(s):  
Micah J. Hewer ◽  
William A. Gough
Keyword(s):  
Time Series ◽  
Winter Season ◽  
Total Precipitation ◽  
Weather Station ◽  
Urban Center ◽  
Downtown Area ◽  
Significant Rate ◽  
Phase Index ◽  
Time Period ◽  
Precipitation Phase

One hundred and sixty–nine years of weather station data were analyzed to quantify the changing nature of the winter season precipitation phase in the downtown area of Toronto (Canada). The precipitation variables examined were rainfall, snowfall water equivalent, total precipitation, rain days, snow days, and precipitation days. From these precipitation variables, three precipitation phase metrics were constructed for further analysis: the fraction of total precipitation that fell as snow, the fraction of precipitation days that recorded snow, and finally, the precipitation phase index (PPI) derived from comparing the rainfall to the snowfall water equivalent. Snowfall and snow days were decreasing at the most significant rate over this time period, and although rain days were increasing, total precipitation and precipitation days were also decreasing at a statistically significant rate. All three precipitation phase metrics suggest that winters are becoming less snowy in Toronto’s urban center. We also looked at trends and changes in average winter season temperatures to explore correlations between warming temperatures and changes in the winter season precipitation phase. Of the three precipitation phase metrics considered, the ratio of snow days to precipitation days recorded the strongest time series trend and the strongest correlation with warming temperatures.

scholarly journals Complexity traits and synchrony of cryptocurrencies price dynamics

2021 ◽  
Author(s):  
Davide Provenzano ◽  
Rodolfo Baggio
Keyword(s):  
Time Series ◽  
Complex Network ◽  
Complex Structures ◽  
Slope Parameter ◽  
Exponential Distributions ◽  
Horizontal Visibility ◽  
Time Period ◽  
Before And After ◽  
Visibility Algorithm ◽  
Similar Complex

AbstractIn this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three cryptocurrencies, Bitcoin, Ethereum, and Litecoin, over the period September 1,2015–March 31, 2020. Time series were first mapped into a complex network by the horizontal visibility algorithm in order to revel the structure of their temporal characters and dynamics. Then, the synchrony of the time series was investigated to determine the possibility that the cryptocurrencies under study co-bubble simultaneously. Findings reveal similar complex structures for the three virtual currencies in terms of number and internal composition of communities. To the aim of our analysis, such result proves that price and volume dynamics of the cryptocurrencies were characterized by cyclical patterns of similar wavelength and amplitude over the time period considered. Yet, the value of the slope parameter associated with the exponential distributions fitted to the data suggests a higher stability and predictability for Bitcoin and Litecoin than for Ethereum. The study of synchrony between the time series investigated displayed a different degree of synchronization between the three cryptocurrencies before and after a collapse event. These results could be of interest for investors who might prefer to switch from one cryptocurrency to another to exploit the potential opportunities of profit generated by the dynamics of price and volumes in the market of virtual currencies.

scholarly journals Exploring the Variation Trend of Urban Expansion, Land Surface Temperature, and Ecological Quality and Their Interrelationships in Guangzhou, China, from 1987 to 2019

2021 ◽  
Vol 13 (5) ◽  
pp. 1019
Author(s):  
Jianhui Xu ◽  
Yi Zhao ◽  
Caige Sun ◽  
Hanbin Liang ◽  
Ji Yang ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Impervious Surface ◽  
Ecological Quality ◽  
Urban Center ◽  
Urban Centers ◽  
Rapid Urbanization

This study explored the model of urban impervious surface (IS) density, land surface temperature (LST), and comprehensive ecological evaluation index (CEEI) from urban centers to suburbs. The interrelationships between these parameters in Guangzhou from 1987 to 2019 were analyzed using time-series Landsat-5 TM (Thematic Mapper), Landsat-8 OLI (Operational Land Imager), and TIRS (Thermal Infrared Sensor) images. The urban IS densities were calculated in concentric rings using time-series IS fractions, which were used to construct an inverse S-shaped urban IS density function to depict changes in urban form and the spatio-temporal dynamics of urban expansion from the urban center to the suburbs. The results indicated that Guangzhou experienced expansive urban growth, with the patterns of urban spatial structure changing from a single-center to a multi-center structure over the past 32 years. Next, the normalized LST and CEEI in each concentric ring were calculated, and their variation trends from the urban center to the suburbs were modeled using linear and nonlinear functions, respectively. The results showed that the normalized LST had a gradual decreasing trend from the urban center to the suburbs, while the CEEI showed a significant increasing trend. During the 32-year rapid urban development, the normalized LST difference between the urban center and suburbs increased gradually with time, and the CEEI significantly decreased. This indicated that rapid urbanization significantly expanded the impervious surface areas in Guangzhou, leading to an increase in the LST difference between urban centers and suburbs and a deterioration in ecological quality. Finally, the potential interrelationships among urban IS density, normalized LST, and CEEI were also explored using different models. This study revealed that rapid urbanization has produced geographical convergence between several ISs, which may increase the risk of the urban heat island effect and degradation of ecological quality.

scholarly journals LO22: Improving the pain experience for children with limb injury: a city-wide quality improvement collaborative

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S14-S14
Author(s):  
J. Thull-Freedman ◽  
T. Williamson ◽  
E. Pols ◽  
A. McFetridge ◽  
S. Libbey ◽  
...  
Keyword(s):  
Time Series ◽  
Quality Improvement ◽  
Time Series Analysis ◽  
Median Time ◽  
Interrupted Time Series ◽  
Interrupted Time Series Analysis ◽  
Process Measures ◽  
Limb Injury ◽  
Time Period ◽  
Limb Injuries

Introduction: Undertreated pain is known to cause short and long-term harm in children. Limb injuries are a common painful condition in emergency department (ED) patients, accounting for 12% of ED visits by children. Our city has one pediatric ED in a freestanding children’s hospital and 3 general ED’s that treat both adults and children. 68% of pediatric limb injuries in our city are treated in the pediatric ED and 32% are treated in a general ED. A quality improvement (QI) initiative was developed at the children’s hospital ED in April 2015 focusing on “Commitment to Comfort.” After achieving aims at the childrens hospital, a QI collaborative was formed among the pediatric ED and the 3 general ED’s to 1) improve the proportion of children citywide receiving analgesia for limb injuries from 27% to 40% and 2) reduce the median time to analgesia from 37 minutes to 15 minutes, during the time period of April-September, 2016. Methods: Data were obtained from computerized order entry records for children 0-17.99 years visiting any participating ED with a chief complaint of limb injury. Project teams from each site met monthly to discuss aims, develop key driver diagrams, plan tests of change, and share learnings. Implementation strategies were based on the Model for Improvement with PDSA cycles. Patient and family consultation was obtained. Process measures included the proportion of children treated with analgesic medication and time to analgesia; balancing measures were duration of triage and length of stay for limb injury and all patients. Site-specific run charts were used to detect special cause variation. Data from all sites were combined at study end to measure city-wide impact using 2 and interrupted time series analysis. Results: During the 3.5-year time period studied (April 1, 2014-September 30, 2017), there were 45,567 visits to the participating ED’s by children 0-17.99 years with limb injury. All visits were included in analysis. Special cause was detected in run charts of all process measures. Interrupted time series analysis comparing the year prior to implementation at the childrens hospital in April 2015 to the year following completion of implementation at the 3 general hospitals in October 2016 demonstrated that the proportion of patients with limb injury receiving analgesia increased from 27% to 40% (p<0.01), and the median time from arrival to analgesia decreased from 37 to 11 minutes (p<0.01). Balancing measure analysis is in progress. Conclusion: This multisite initiative emphasizing “Commitment to Comfort” was successful in improving pain outcomes for all children with limb injuries seen in city-wide ED’s, and was sustained for one year following implementation. A QI collaborative can be an effective method for spreading improvement. The project team is now spreading the Commitment to Comfort initiative to over 30 rural and regional EDs throughout the province through establishment of a provincial QI collaborative.

scholarly journals Time Series Seasonal Analysis Based on Fuzzy Transforms

2017 ◽  
Author(s):  
Ferdinando Di Martino ◽  
Salvatore Sessa
Keyword(s):  
Time Series ◽  
Seasonal Forecasting ◽  
Weather Station ◽  
Fuzzy Transform ◽  
Italian Region ◽  
Mean Temperature ◽  
Forecasting Method ◽  
Seasonal Analysis ◽  
The Universe ◽  
Universe Of Discourse

We define a new seasonal forecasting method based on fuzzy transforms. We use the best interpolating polynomial for extracting the trend of the time series and generate the inverse fuzzy transform on each seasonal subset of the universe of discourse for predicting the value of a an assigned output. Like first example, we use the daily weather dataset of the municipality of Naples (Italy) starting from data collected from 2003 till to 2015 making predictions on the following outputs: mean temperature, max temperature and min temperature, all considered daily. Like second example, we use the daily mean temperature measured at the weather station &ldquo;Chiavari Caperana&rdquo; in the Liguria Italian Region. We compare the results with our method, the average seasonal variation, ARIMA and the usual fuzzy transforms concluding that the best results are obtained under our approach in both examples.

scholarly journals Analysis of the time series of waste water quality at the inflow of the wastewater treatment plant and transfer functions

2014 ◽  
Vol 62 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Ivan Nesmerak ◽  
Sarka D. Blazkova
Keyword(s):  
Time Series ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Transfer Functions ◽  
Treatment Plant ◽  
Total Precipitation ◽  
Periodic Components ◽  
The Relationship ◽  
Pollution Loads ◽  
Daily Total

Abstract Time series of the daily total precipitation, daily wastewater discharges and daily concentrations and pollution loads of BOD5, COD, SS, N-NH4, Ntot and Ptot were analyzed at the inflow to the wastewater treatment plant (WWTP) for a larger city in 2004-2009 (WWTP is loaded by pollution from 435,000 equivalent inhabitants). The time series of the outflow from a WWTP was also available for 2007. The time series of daily total precipitation, daily wastewater discharges, concentrations and pollution loads at the inflow and outflow from the WWTP were standardized year by year to exclude a long-term trend, and periodic components with a period of 7 days and 365 days (and potentially also 186.5 days) were excluded from the standardized series. However, these two operations eliminated only a small part of the variance; there was a substantial reduction in the variance only for ammonium nitrogen and total nitrogen at the inflow and outflow from a WWTP. The relationship between the inflow into a WWTP and the outflow from a WWTP for the concentrations and pollution loads was described by simple transfer functions (SISO models) and more complicated transfer functions (MISO models). A simple transfer function (SISO model) was employed to describe the relationship between the daily total precipitation and the wastewater discharge.

Summer

2019 ◽  
pp. 228-242
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Time Series ◽  
Detailed Analysis ◽  
Total Precipitation ◽  
Mean Temperature ◽  
The Mean ◽  
Weather Record ◽  
Extremes Of Temperature

Chapter 22 provides a detailed analysis of the long weather record at the Radcliffe Observatory, Oxford for summer. Averages and extremes of temperature, precipitation and sunshine are presented, with coverage relevant to the month or season including the incidence of snowfall, thunderstorms, gales and the like, illustrated by contemporary accounts and photography. Each chapter ends with a complete time series of the mean temperature, total precipitation and total sunshine for the month or season from the entire record, updated to 2018.

Spring

2019 ◽  
pp. 222-227
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Time Series ◽  
Detailed Analysis ◽  
Total Precipitation ◽  
Mean Temperature ◽  
The Mean ◽  
Weather Record ◽  
Extremes Of Temperature

Chapter 21 provides a detailed analysis of the long weather record at the Radcliffe Observatory, Oxford for spring. Averages and extremes of temperature, precipitation and sunshine are presented, with coverage relevant to the month or season including the incidence of snowfall, thunderstorms, gales and the like, illustrated by contemporary accounts and photography. Each chapter ends with a complete time series of the mean temperature, total precipitation and total sunshine for the month or season from the entire record, updated to 2018.

October

2019 ◽  
pp. 165-171
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Time Series ◽  
Detailed Analysis ◽  
Total Precipitation ◽  
Mean Temperature ◽  
The Mean ◽  
Weather Record ◽  
Extremes Of Temperature

Chapter 16 provides a detailed analysis of the long weather record at the Radcliffe Observatory, Oxford for October. Averages and extremes of temperature, precipitation and sunshine are presented, with coverage relevant to the month or season including the incidence of snowfall, thunderstorms, gales and the like, illustrated by contemporary accounts and photography. Each chapter ends with a complete time series of the mean temperature, total precipitation and total sunshine for the month or season from the entire record, updated to 2018.

June

2019 ◽  
pp. 123-131
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Time Series ◽  
Detailed Analysis ◽  
Total Precipitation ◽  
Mean Temperature ◽  
The Mean ◽  
Weather Record ◽  
Extremes Of Temperature

Chapter 12 provides a detailed analysis of the long weather record at the Radcliffe Observatory, Oxford for June. Averages and extremes of temperature, precipitation and sunshine are presented, with coverage relevant to the month or season including the incidence of snowfall, thunderstorms, gales and the like, illustrated by contemporary accounts and photography. Each chapter ends with a complete time series of the mean temperature, total precipitation and total sunshine for the month or season from the entire record, updated to 2018.

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