scholarly journals Characteristics and trend of extreme temperature in Spatio-temporal context, South Xinjiang China.

2021 ◽  
Author(s):  
Ahmad Ali Khan ◽  
Yuanjie Zhao ◽  
Jamil Khan ◽  
Ghani Rahman ◽  
Muhammad Rafiq
Keyword(s):  
Time Series Data ◽  
Focal Point ◽  
Extreme Temperature ◽  
Climatic Conditions ◽  
Trend Detection ◽  
Series Data ◽  
Estimation Model ◽  
Upward Trend ◽  
Sen’S Slope ◽  
Increasing Trend

Abstract Evaluation of climate change study is vital for appropriate management of hydrological resources and future planning. South Xinjiang is comprising various sort of climatic conditions. The focal point of this study is to assess the dissemination and pattern of temperature for as far back as 39 years in south Xinjiang China. The time series data recorded as maximum, minimum and mean monthly temperature at different metrological stations. For trend detection Mann-Kendall tests and Sen's slope estimation model were applied for appropriate results. The statistical analysis of the study indicates a significant upward trend in three types mean max. min. and average temperature on seasonal & monthly scale. Change points find out in the four decades show an increasing trend of temperature. Results found from Sen's slope magnitudes vary from 0.010ºC to 0.070ºC in Tmax per annum. Further, Sen's slope from − 0.150ºC to 0.080ºC and − 0.080ºC to 0.060ºC every year for both Tmin and Tmean. So for the increasing trend in all temperature is a get way to a dangerous atmospheric devastation and environmental change. Seasonal evaluation of temperature (JJA) June, July and August detected upward trend of temperature while the rainfall occurring months (NDJF), November, December, January and February found significantly dry. The seasonal changeability of temperature is straightforwardly responsible for desertification in the area. The conclusion of the research study that southern Xinjiang facing severe dry conditions are essential to highlight this burning issue for further development and sustainability of water resources.

Temporal trends of the association between extreme temperatures and hospitalisations for schizophrenia in Hefei, China from 2005 to 2014

2021 ◽  
Vol 78 (5) ◽  
pp. 364-370
Author(s):  
Rubing Pan ◽  
Qizhi Wang ◽  
Weizhuo Yi ◽  
Qiannan Wei ◽  
Jian Cheng ◽  
...  
Keyword(s):  
Time Series Data ◽  
Temporal Trends ◽  
Extreme Temperature ◽  
Series Data ◽  
Extreme Temperatures ◽  
Distributed Lag ◽  
Increasing Trend ◽  
Related Hospitalisation ◽  
Extreme Cold ◽  
And Gender

ObjectiveWe aimed to examine the temporal trends of the association between extreme temperature and schizophrenia (SCZ) hospitalisations in Hefei, China.MethodsWe collected time-series data on SCZ hospitalisations for 10 years (2005–2014), with a total of 36 607 cases registered. We used quasi-Poisson regression and distributed lag non-linear model (DLNM) to assess the association between extreme temperature (cold and heat) and SCZ hospitalisations. A time-varying DLNM was then used to explore the temporal trends of the association between extreme temperature and SCZ hospitalisations in different periods. Subgroup analyses were conducted by age (0–39 and 40+ years) and gender, respectively.ResultsWe found that extreme cold and heat significantly increased the risk of SCZ hospitalisations (cold: 1st percentile of temperature 1.19 (95% CI 1.04 to 1.37) and 2.5th percentile of temperature 1.16 (95% CI 1.03 to 1.31); heat: 97.5th percentile of temperature 1.37 (95% CI 1.13 to 1.66) and 99th percentile of temperature 1.38 (95% CI 1.13 to 1.69)). We found a slightly decreasing trend in heat-related SCZ hospitalisations and a sharp increasing trend in cold effects from 2005 to 2014. However, the risk of heat-related hospitalisation has been rising since 2008. Stratified analyses showed that age and gender had different modification effects on temporal trends.ConclusionsThe findings highlight that as temperatures rise the body’s adaptability to high temperatures may be accompanied by more threats from extreme cold. The burden of cold-related SCZ hospitalisations may increase in the future.

scholarly journals Assessment of Trends and Variability of Rainfall and Temperature for the District of Mandi in Himachal Pradesh, India

2017 ◽  
Vol 25 (3) ◽  
pp. 15-22 ◽  
Author(s):  
John Mohd Wani ◽  
V. K. Sarda ◽  
Sanjay. K. Jain
Keyword(s):  
Time Series Data ◽  
Kendall Test ◽  
Himachal Pradesh ◽  
Annual Rainfall ◽  
Series Data ◽  
Maximum Temperature ◽  
Sen’S Slope ◽  
Annual Minimum Temperature ◽  
Increasing Trend ◽  
Mann Kendall Test

Abstract Climate variability, particularly, that of the annual air temperature and precipitation, has received a great deal of attention worldwide. The magnitude of the variability of the factors changes according to the locations. The present study focuses on detecting the trends and variability in the annual temperature and rainfall for the district of Mandi in Himachal Pradesh, India. This study used annual and monsoon time series data for the time period 1981-2010 and modified the Mann-Kendall test and Sen's slope estimator in analyzing the problem. The results of the analysis indicate that the annual maximum temperature (TMX) and annual minimum temperature (TMN) for the period of 30 years have shown an increasing trend, whereas the monsoon’s maximum and minimum temperatures have shown a decreasing trend, although it is statistically not significant. The amount of annual rainfall does not show any significant trend, but the monsoonal rainfall has shown an increasing trend that is also statistically not significant. The resulting Mann-Kendall test statistic (Z) and Sen’s slope estimate (Q) of all the parameters studied indicate that changes are occurring in the magnitude and timing of the precipitation and temperature events at the Mandi station.

scholarly journals The impact of bank-specific and macroeconomic variables on profitability of Islamic rural bank in Indonesia

2019 ◽  
Vol 5 (3) ◽  
Author(s):  
Muhammad Sanusi
Keyword(s):  
Banking Sector ◽  
Time Series Data ◽  
Series Data ◽  
Estimation Model ◽  
Policy Makers ◽  
Vector Error Correction ◽  
Macroeconomic Variables ◽  
Vector Error ◽  
The Impact

This paper investigates the impact of bank-specific and macroeconomic variables on the profitability of Islamic rural bank (BPRS) in Indonesia. Using monthly time series data from January 2010 - December 2018. The estimation model used is a vector error correction model to analyze the long-term and short-term relationships between bank-specific and macroeconomic variables on the profitability of Islamic rural bank. The results showed that CAR and LnTA had a significant positive relationship, while NPF, BOPO and IPI had a negative and significant relationship to the profitability of Islamic rural banks. But FDR and Inflation variables are not significantly related to the profitability of Islamic rural bank. The results leave implications for policy makers, investors and banking sector managers. Based on evidence that bank profitability is more influenced by internal banks (as specific as banks), this research can help Islamic rural banks to help them understand which factors are important to be analyzed to obtain higher profitability.

scholarly journals Forecasting road traffic accident deaths in India using seasonal autoregressive integrated moving average model

2018 ◽  
Vol 5 (9) ◽  
pp. 3962
Author(s):  
Manikandan M. ◽  
Vishnu Prasad R. ◽  
Amit Kumar Mishra ◽  
Rajesh Kumar Konduru ◽  
Newtonraj A.
Keyword(s):  
Traffic Accidents ◽  
Time Series Data ◽  
Road Traffic ◽  
Moving Average ◽  
Arima Model ◽  
World Health ◽  
Series Data ◽  
Road Traffic Accidents ◽  
Increasing Trend ◽  
Health Organization

Background: As per World Health Organization (WHO) report 1.24 million people die each year as a result of road traffic accidents (RTA) globally. A vast majority of 20-50 million people suffer from non-fatal injuries, many of them ultimately end in disability. Forecasting RTA deaths could help in planning the intervention at the right time in an effective way.Methods: An attempt was made to forecast the RTA deaths in India with seasonal auto regressive integrated moving average (SARIMA) model. ARIMA model is one of the common methods which are used for forecasting variables as the method is very easy and requires only long time series data. The method of selection of appropriate ARIMA model has been explained in detail. Month wise RTA deaths for previous years data was collected from Govt. of India website. Data for 12 years (2001 to 2012) was extracted and appropriate ARIMA model was selected. Using the validated ARIMA model the RTA deaths are forecasted for 8 years (2013-2020).Results: The appropriate SARIMA (1,0,0) (2,1,0) 12 model was selected based on minimal AIC and BIC values. The forecasted RTA deaths show increasing trend overtime.Conclusions: There is an increasing trend in the forecasted numbers of road traffic accidental deaths and it also shows seasonality of RTA deaths with more number of accidents during the month of April and May in every years. It is recommended that the policy makers and transport authority should pay more attention to road traffic accidents and plan some effective intervention to reduce the burden of RTA deaths.

scholarly journals Trend Analysis of Meteorological Variables: Rainfall and Temperature

2021 ◽  
Vol 7 (11) ◽  
pp. 1868-1879
Author(s):  
Jada El Kasri ◽  
Abdelaziz Lahmili ◽  
Halima Soussi ◽  
Imane Jaouda ◽  
Maha Bentaher
Keyword(s):  
Water Resources ◽  
Flash Flood ◽  
Groundwater Resources ◽  
Climatic Conditions ◽  
Annual Rainfall ◽  
Series Data ◽  
Maximum Temperature ◽  
Data Set ◽  
Monotonic Trend ◽  
Increasing Trend

The Souss-Massa region in southwestern Morocco is characterized by a semi-arid climate with high variability in rainfall. Frequent droughts and flash flood events combined with overexploitation of water resources in recent decades have had a significant impact on the human security and the economy which is mainly based on agriculture, tourism and fishery. For better management of extreme events and water resources under changing climatic conditions, a study was carried out to quantify the seasonal and annual variability and trends in rainfall and temperature over the past three decades with data from three stations. Climatological representative of the Souss-Massa region. The Mann-Kendall (MK) non-parametric test and the Sen’s slope are used to estimate the monotonic trend and magnitude of the trend of the variables, respectively. Statistical analysis of the rainfall series data set highlights that the occurrence of rainfall is unpredictable and irregular and the both the seasonal and annual rainfall trend appears negative (downward) for all the three climatological stations. The minimum temperature shows a remarkable increasing trend both on annual and seasonal scale while the maximum temperature registers a slightly increasing trend. The study presents some new insights on rainfall and temperature trends that will have significant impacts on the surface and groundwater resources of the region under changing climatic conditions. The results can help to prioritize new strategies to mitigate the risk of droughts, of floods and to manage water resources to sustain the dependence of agriculture tourism and fishery sectors in the region. Doi: 10.28991/cej-2021-03091765 Full Text: PDF

scholarly journals Analysis of trend in area, production and yield of major vegetables of Nepal

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Deepak Ghimire ◽  
Gunakeshari Lamsal ◽  
Bindu Paudel ◽  
Sushila Khatri ◽  
Bandana Bhusal
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Recent Trend ◽  
Series Data ◽  
Cruciferous Vegetables ◽  
Vegetable Production ◽  
Microsoft Excel ◽  
Production Sector ◽  
Reliable Source ◽  
Increasing Trend

Vegetable production is an important sector of economy for farmers in Nepal. The analysis was carried out to explore the trends in vegetable production sector in Nepal along with the recent trend of some major vegetables in terms of area, production and yield. The time series data from 1977/78 to 2016/17 (40 years) of vegetables production and 5 years data (2011/12 - 2015/16) of major vegetables were collected from reliable source and analysis was done through Microsoft Excel. The results show that between 1977/78 and 2016/17 the area under vegetables cultivation has jumped by 222.8% while production is increased by 728.21% and productivity is increased by 156.6% during this course. The result also reveals that during the period of 5 years (2011/12 - 2015/16), solanaceous and cruciferous vegetables has an increasing trend in area, production and yield except for the area under cultivation for eggplant (declined by 5.2%) and for radish (declined by 6.0%) respectively while cucurbitaceous vegetables has increasing trend in area and production but an declining trend in yield except for the yield of cucumber (increased by 15.8%). However, the trend of other major vegetables is seen highly fluctuating over the years. 

scholarly journals Trend analysis of rainfall using Mann-Kendall, Sen’s slope, moving average and least square techniques for Ahmednagar district of Maharashtra

2021 ◽  
Vol 17 (1) ◽  
pp. 19-25
Author(s):  
Virendra N. Barai ◽  
Rohini M. Kalunge
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Moving Average ◽  
Rainfall Variability ◽  
Least Square ◽  
Annual Rainfall ◽  
Series Data ◽  
Sen’S Slope ◽  
Increasing Trend ◽  
The Impact

The long-term behaviour of rainfall is necessary to study over space with different time series viz., annual, monthly and weekly as it is one of the most significant climatic variables. Rainfall trend is an important tool which assesses the impact of climate change and provides direction to cope up with its adverse effects on the agriculture. Several studies have been performed to establish the pattern of rainfall over various time periods for different areas that can be used for better agricultural planning, water supply management, etc. Consequently, the present report, entitled “Trend analysis of rainfall in Ahmednagar district of Maharashtra,” was carried out. 13 tahsils of the district of Ahmednagar were selected to carry out trend analysis. The daily rainfall data of 33 years (1980- 2012) of all stations has been processed out study the rainfall variability. The Mann Kendall (MK) Test, Sen’s slope method, moving average method and least square method were used for analysis. The statistical analysis of whole reference time series data highlighted that July and August month contributes highest amount of rainfall at all tahsils. Regarding trend in annual rainfall, these four methods showed increasing trend at most of the tahsils whereas a decreasing trend only at Shrigonda tahsil. For monthly trend analysis, Kopargaon, Newasa, Shevgaon and Shrirampur tahsils showed an increasing trend during July. During August and September month, most of the tahsils i.e. Kopargaon, Nagar, Parner and Sangamner showed increasing trends, whereas in June, only Shrigonda tahsil showed decreasing trend.

scholarly journals Incidence forecasting of new invasive pest of coconut rugose spiraling whitefly (Aleurodicus rugioperculatus) in India using ARIMAX analysis

2021 ◽  
Vol 23 (2) ◽  
pp. 194-199
Author(s):  
K.ELANGO ◽  
S. JEYARAJAN NELSON ◽  
P.DINESHKUMAR
Keyword(s):  
Tamil Nadu ◽  
Prediction Models ◽  
Time Series Data ◽  
Management Strategies ◽  
Climatic Conditions ◽  
Invasive Pest ◽  
Series Data ◽  
Maximum Temperature ◽  
Weather Factors ◽  
Extent Of Damage

The rugose spiraling whitefly (RSW), Aleurodicus rugioperculatus Martin is a new invasive pest occurring in several crops including coconut since 2016 in India from Tamil Nadu, Karnataka, Kerala and Andhra Pradesh. The population dynamics of new invasive whitefly species, A. rugioperculatus study indicated that RSW was found throughout the year on coconut and the observation recorded on weekly interval basis shows that A. rugioperculatus population escalated from the first week of July 2018 (130.8 nymph/ leaf/ frond) reaching the maximum during the first week of October (161.0 nymph/ leaf/ frond) which subsequently dwindled to a minimum during April. Due to variation in the agro-climatic conditions of different regions, arthropods show varying trends in their incidence also in nature and extent of damage to the crop. Influence of weather parameters on rugose spiralling whitefly incidence is lacking, which is essential for developing management strategies. The forecasting model to predict rugose spiralling whitefly incidence in coconut was developed by ARIMAX model of weekly cases and weather factors. In exploring different prediction models by fitting covariates to the time series data, ARIMA (0,2,1) with Maximum temperature was found best model for predicting the rugose  spiralling whitefly incidence and all covariates were found non-significant predictors except maximum temperature.

Analisis Desentralisasi Fiskal terhadap Belanja Modal Pemerintah Daerah di Indonesia

2019 ◽  
Vol 3 (2) ◽  
pp. 104
Author(s):  
Hady Sutjipto ◽  
Stania Cahaya Suci ◽  
Yogi Sabarudin Umbara
Keyword(s):  
Panel Data ◽  
Time Series Data ◽  
Capital Expenditure ◽  
Panel Data Analysis ◽  
Fixed Effect Model ◽  
Series Data ◽  
Estimation Model ◽  
Section Data ◽  
Fiscal Autonomy ◽  
Directorate General

The aims of this study to determine the effect of the degree of fiscal autonomy, regional financial dependence, and population on capital expenditure of 34 provinces in Indonesia.  The Methodolody in this study employs panel data analysis method with fixed effect model (FEM) estimation model. Determination of samples based on panel data consisting of time series data for period 2014-2017 and cross section data of 34 Provinces in Indonesia. The data was obtained from the Central Statistics Agency and the Directorate General of Financial Balance.The results shows that (1) the degree of fiscal autonomy, regional financial dependence, and the population have a positive and significant effect on capital expenditure (2) the degree of fiscal autonomy, regional financial dependence, and the total population have simultaneous effect on capital expenditures. 

Seasonal and interannual variation of decapod larval abundance from two coastal locations in Scotland, UK

2011 ◽  
Vol 91 (7) ◽  
pp. 1443-1451 ◽  
Author(s):  
Maria Pan ◽  
Graham J. Pierce ◽  
Carey O. Cunningham ◽  
Steve J. Hay
Keyword(s):  
East Coast ◽  
Time Series Data ◽  
Least Square ◽  
Series Data ◽  
Larval Abundance ◽  
Square Functions ◽  
North West ◽  
North East ◽  
Increasing Trend ◽  
Decapod Larvae

The patterns of decapod larvae occurrence and abundance were studied from weekly time-series data of 8 years from Stonehaven (north-east Scotland) and 4 years and 8 months from Loch Ewe (north-west Scotland). The annual cycle observed was similar in the two locations and characterized by abundance peaks, the first in spring and another in the summer, extending into autumn. During the coldest months (December to February) decapod larvae were virtually absent in the plankton. Differences in abundance and occurrence of decapod larvae between locations and the influence of temperature, salinity and chlorophyll-a in the patterns observed, were analysed by generalized least-square functions. The results showed significant differences in the abundance of decapod larvae between locations, with higher larval abundances and an earlier appearance in the plankton in Loch Ewe (west coast). In Stonehaven (east coast), from 2003 onwards, a general increasing trend in the abundance of decapod larvae was observed, related to the increasing temperatures recorded at that site. The data demonstrate the high variability of decapod larval abundance on an annual basis and the high importance of temperature and chlorophyll-a to the occurrence and abundance of decapod larvae.

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