Dataset on Soil Temperature, Meteorological Factors and their Correlation Coefficients in Nagqu, Tibet, China (2017-2019)

GCdataPR ◽  
2020 ◽  
Author(s):  
Hongbo YANG ◽  
Xiaodan YU ◽  
Haimei FU ◽  
Huiting LI ◽  
Jinling ZHAO
Keyword(s):  
Soil Temperature ◽  
Meteorological Factors ◽  
Correlation Coefficients

scholarly journals Meteorological factors and its association with hand, foot and mouth disease in Southeast and East Asia areas: a meta-analysis

2018 ◽  
Vol 147 ◽  
Author(s):  
Chunxiao Duan ◽  
Xuefeng Zhang ◽  
Hui Jin ◽  
Xiaoqing Cheng ◽  
Donglei Wang ◽  
...  
Keyword(s):  
East Asia ◽  
Meteorological Factors ◽  
Global Climate ◽  
Meta Analysis ◽  
Foot And Mouth Disease ◽  
Correlation Coefficients ◽  
Mouth Disease ◽  
Asia Pacific ◽  
China National Knowledge Infrastructure ◽  
Foot And Mouth

AbstractSince the late 1990s, hand, foot and mouth disease (HFMD) has become a common health problem that mostly affects children and infants in Southeast and East Asia. Global climate change is considered to be one of the major risk factors for HFMD. This study aimed to assess the correlation between meteorological factors and HFMD in the Asia-Pacific region. PubMed, Web of Science, Embase, China National Knowledge Infrastructure, Wanfang Data and Weipu Database were searched to identify relevant articles published before May 2018. Data were collected and analysed using R software. We searched 2397 articles and identified 51 eligible papers in this study. The present study included eight meteorological factors; mean temperature, mean highest temperature, mean lowest temperature, rainfall, relative humidity and hours of sunshine were positively correlated with HFMD, with correlation coefficients (CORs) of 0.52 (95% confidence interval (CI) 0.42–0.60), 0.43 (95% CI 0.23–0.59), 0.43 (95% CI 0.23–0.60), 0.27 (95% CI 0.19–0.35), 0.19 (95% CI 0.02–0.35) and 0.19 (95% CI 0.11–0.27), respectively. There were sufficient data to support a negative correlation between mean pressure and HFMD (COR = −0.51, 95% CI −0.63 to −0.36). There was no notable correlation with wind speed (COR = 0.10, 95% CI −0.03 to 0.23). Our findings suggest that meteorological factors affect the incidence of HFMD to a certain extent.

scholarly journals METHODOLOGICAL PROBLEMS OF THE MATHEMATICAL ESTIMATION OF THE IMPACT OF METEOROLOGICAL FACTORS ON ADAPTIVE FUNCTIONS OF THE HUMAN

2019 ◽  
Vol 96 (3) ◽  
pp. 253-257
Author(s):  
Nurlan K. Smagulov ◽  
A. A. Adilbekova
Keyword(s):  
High School ◽  
Mathematical Analysis ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Correlation Coefficients ◽  
Dose Effect ◽  
Output Factors ◽  
The Central Nervous System ◽  
Methodological Problems ◽  
The Impact

The work is dedicated to methodological problems of the mathematical assessment of the impact of meteorological factors on the adaptive function of the teachers of the High School Institutions. Objects of research. Male teachers of the High School Institution, aged of from 24 to 49 years. Meteorological data were evaluated during the investigation of anthropometric indices of height and weight, individual-typological features and the physiological assessment of the central nervous system, cardiovascular system of the High School teachers. Statistical analysis was performed with the use of Statistica 6.0 package and special statistical software. Paired correlation coefficients obtained as a result of calculation were used to estimate the proportion of the influence of input factors (arguments) on the output factors (functions). A mathematical analysis has allowed to reveal leading meteorological factors that cause a certain level of functional exhaustion during the investigated period. The use of a non-linear correlation analysis allowed to enhance significantly the ability for analytical processing of the results, increase of the effectiveness and the possibility of interpreting the interaction of factors in achieving optimal adaptation of teachers in the working process and to identify the role of meteorological factors in this process. Knowledge of leading factors and the percentage of their contribution to the functional state allowed to give the more accurate assessment of stress to the organism in specific circumstances. The ultimate aim of the mathematical analysis should be not only to find the critical value defined the priority factor characterizing the degree of of information load, but the critical combination of all priority factors causing disruption and the beginning of “start-up” adaptation process in the system “dose-effect. “

scholarly journals SARS-CoV-2 and the Weather: Correlation between COVID-19 and Meteorological Variables in 3 Cities in Mexico

2021 ◽  
pp. 74-91
Author(s):  
Hermes Ulises Ramirez-Sanchez ◽  
Alma Delia Ortiz-Bañuelos ◽  
Aida Lucia Fajardo-Montiel
Keyword(s):  
Wind Speed ◽  
Atmospheric Pressure ◽  
Ecological Study ◽  
Metropolitan Areas ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Dew Point ◽  
Meteorological Variables ◽  
Infected Person

Meteorological factors such as temperature, humidity, atmospheric pressure, wind speed and direction are associated with the dispersion of the SARS-CoV-2 virus through aerosols, particles <5μm are suspended in the air being infective at least three hours and dispersing from eight to ten meters. It has been shown that a 10-minute conversation, an infected person produces up to 6000 aerosol particles, which remain in the air from minutes to hours, depending on the prevailing weather conditions. Objective: To establish the correlation between meteorological variables, confirmed cases and deaths from COVID-19 in the 3 most important cities of Mexico. Methodology: A retrospective ecological study was conducted to evaluate the correlation of meteorological factors with COVID-19 cases and deaths in three Mexican cities. Results: The correlations between health and meteorological variables show that in the CDMX the meteorological variables that best correlate with the health variables are Temperature (T), Dew Point (DP), Wind speed (WS), Atmospheric Pressure (AP) and Relative Humidity (RH) in that order. In the ZMG are T, WS, RH, DP and AP; and in the ZMM are RH, WS, DP, T and AP. Conclusions In the 3 Metropolitan Areas showed that the meteorological factors that best correlate with the confirmed cases and deaths from COVID-19 are the T, RH; however, the correlation coefficients are low, so their association with health variables is less than other factors such as social distancing, hand washing, use of antibacterial gel and use of masks.

scholarly journals The influence of meteorological factors on rockfall in the Moravskoslezské Beskydy Mts.

Geografie ◽  
2012 ◽  
Vol 117 (1) ◽  
pp. 1-20
Author(s):  
Rudolf Brázdil ◽  
Karel Šilhán ◽  
Tomáš Pánek ◽  
Petr Dobrovolný ◽  
Lucie Kašičková ◽  
...  
Keyword(s):  
Linear Regression ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Meteorological Variables ◽  
Stepwise Linear Regression ◽  
Process Uncertainty ◽  
Air Temperatures ◽  
Rr Variability

Rockfall rate (RR) series for four sites in the Moravskoslezské Beskydy Mountains (Smrk1, Smrk2, Ropice and Satina) were created for the period 1931–2008, using a dendrogeomorphic approach. Meteorological stations from the immediate area were also selected to study the influence of meteorological factors on rockfall. Monthly, seasonal, and annual mean air temperatures (TM), number of days with transitions of temperatures through 0 °C (Tr0) and precipitation totals (Pr) were used for this analysis. Despite the complexity of the rockfall process, uncertainty in the development of RR series and uncertainty in local meteorological patterns, there exist statistically significant correlation coefficients between RR series and meteorological variables. Multiple stepwise linear regression allows explanation of up to 43% (Satina in 1975–2008) of the RR variability by meteorological factors. Tr0, followed by TM, are the most important factors, while the influence of Pr was demonstrated only randomly.

scholarly journals Forecasting the yield of principal crops in India on the basis of weather -Paddy / Rice

MAUSAM ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 47-58
Author(s):  
J. A. DAS ◽  
A. K. MEHRA ◽  
M. L. MADNANI
Keyword(s):  
Regression Analysis ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Paddy Rice ◽  
Average Yield ◽  
Weather Factors ◽  
Mysore State ◽  
Cent Level ◽  
Effect On Yield ◽  
Rainy Days

By the method of regression analysis, forecast; formulae have been evolved for forecasting yield of autumn paddy/rice in Mysore State using meteorological factors. The study reveals that there is increase in average yield per acre due to technology from early fifties. In Coastal Mysore, restricted rainy days during July to 15 September and frequency of occasions of drought and floods during August and September are the principal weather factors having significant effect on yield. The corresponding factor for Interior Mysore North is occasions of droughts during July to September. In the Interior Mysore South, June and September rainfall have significant effect on  yield. By testing the formulae for the yields for 1965 to 1968, it is found that they agree well with the reported yields. All correlation coefficients obtained are significant at 0.1 per cent level.

scholarly journals Analysis of characteristic snow parameters and associated factors in a cold region in northeast China

2018 ◽  
Vol 19 (2) ◽  
pp. 511-518 ◽  
Author(s):  
Qiang Fu ◽  
Li Peng ◽  
Tianxiao Li ◽  
Song Cui ◽  
Dong Liu ◽  
...  
Keyword(s):  
Water Content ◽  
Liquid Water ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Bottom Layer ◽  
Liquid Water Content ◽  
Snow Layer ◽  
Snow Properties ◽  
Positive Correlations ◽  
Changing Rate

Abstract Snow characteristics were measured in the comprehensive experimental field and the results of a detailed analysis of physical snow properties indicated that snowpack characteristics are affected by a variety of climate parameters. The average liquid water content of snow increased from 0.5% to 3.5%. The bottom snow layer exhibited larger parameter variations than those in the surface and middle layers. The average snow porosity was 72.3% for the entire snowpack, and the changing rate of porosity ranged from 4% to 19% during the accumulation period and from 7% to 25% during the snowmelt period. The porosity of the bottom layer displayed the fastest decline and the largest range. The air temperature, snow temperature and solar radiation showed significant positive correlations with the liquid water content of the snow, and the calculated correlation coefficients were all above 0.9. In addition, relative humidity and temperature were negatively correlated. All meteorological factors studied affected the melting capacity of snow to varying degrees. This study included the design and implementation of snow experiments on bare land under natural conditions as well as measurements of snow parameters in detailed snowpack layers and explained the characteristics of snow parameters combined with meteorological factors.

scholarly journals Studies on Population Dynamics of Pratylenchus sp. (Filipjev, 1936) about Soil Abiotic Factor in the Mulberry Field at Aurangabad, Maharashtra, India

2021 ◽  
Vol 8 (S1-Feb) ◽  
pp. 67-72
Author(s):  
Avhad Sunil B ◽  
Hiware Chandrashekhar J
Keyword(s):  
Population Dynamics ◽  
Soil Temperature ◽  
Abiotic Factors ◽  
Correlation Coefficients ◽  
Economic Importance ◽  
Morus Alba ◽  
Parasitic Nematodes ◽  
Abiotic Factor ◽  
Plant Parasitic Nematodes ◽  
Plant Parasitic

In the present study, the monthly population fluctuation of Pratylenchus sp. (Filipjev, 1936) is ascertain about soil temperature, moisture, pH in mulberry (Morus alba L.) field with economic importance within the sericulture. The studies target is to grasp the influence and impact of those soil abiotic factors on the population of those plant-parasitic nematodes and Correlation coefficients (r) between mean population Pratylenchus spand different soil abiotic factors in Aurangabad Mulberry garden.

scholarly journals Variations in Nocturnal Residual Layer Height and Its Effects on Surface PM2.5 over Wuhan, China

2021 ◽  
Vol 13 (22) ◽  
pp. 4717
Author(s):  
Xin Ma ◽  
Weicheng Jiang ◽  
Hui Li ◽  
Yingying Ma ◽  
Shikuan Jin ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Meteorological Parameters ◽  
Fine Particles ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Residual Layer ◽  
Lidar Data ◽  
Environment Pollution ◽  
Layer Height ◽  
Effect Of Surface

Large amounts of aerosols remain in the residual layer (RL) after sunset, which may be the source of the next day’s pollutants. However, the characteristics of the nocturnal residual layer height (RLH) and its effect on urban environment pollution are unknown. In this study, the characteristics of the RLH and its effect on fine particles with diameters <2.5 μm (PM2.5) were investigated using lidar data from January 2017 to December 2019. The results show that the RLH is highest in summer (1.55 ± 0.55 km), followed by spring (1.40 ± 0.58 km) and autumn (1.26 ± 0.47 km), and is lowest in winter (1.11 ± 0.44 km). The effect of surface meteorological factors on the RLH were also studied. The correlation coefficients (R) between the RLH and the temperature, relative humidity, wind speed, and pressure were 0.38, −0.18, 0.15, and −0.36, respectively. The results indicate that the surface meteorological parameters exhibit a slight correlation with the RLH, but the high relative humidity was accompanied by a low RLH and high PM2.5 concentrations. Finally, the influence of the RLH on PM2.5 was discussed under different aerosol-loading periods. The aerosol optical depth (AOD) was employed to represent the total amount of pollutants. The results show that the RLH has an effect on PM2.5 when the AOD is small but has almost no effect on PM2.5 when the AOD is high. In addition, the R between the nighttime mean RLH and the following daytime PM2.5 at low AOD is −0.49, suggesting that the RLH may affect the following daytime surface PM2.5. The results of this study have a guiding significance for understanding the interaction between aerosols and the boundary layer.

scholarly journals The association between COVID-19 data and meteorological factors in Indonesia

2020 ◽  
Author(s):  
Supari ◽  
Danang Eko Nuryanto ◽  
Amsari Muzakir Setiawan ◽  
Ardhasena Sopaheluwakan ◽  
Furqon AlFahmi ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Relative Humidity ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Weather Data ◽  
Data Series ◽  
Distribution Analysis ◽  
Cumulative Number ◽  
Daily Data

Abstract On March 2, 2020, the first Coronavirus Disease (COVID-19) case was reported in Jakarta, Indonesia. One and half month later (15/05/2020), the cumulative number of infection cases was 16496 with a total of 1076 mortalities. This study is aimed to investigate the possible role of weather in the early cases of COVID-19 incidence in six selected cities in Indonesia. Daily data of temperature and relative humidity from weather stations nearby each city were collected during the period 3 March - 30 April 2020, together with data of COVID-19 cases. Correlation tests and regression analysis were performed to examine the association of those two data series. In addition, we analysed the distribution of COVID-19 with respect to weather data to estimate the effective range of weather data supporting COVID-19 incidence. Our results reveal that weather data is generally associated with COVID-19 incidence. The daily average temperature (T-ave) and relative humidity (RH) presents significant positive and negative correlation with COVID-19 data, respectively. However, the correlation coefficients are weak with the strongest correlations found at 5 day lag time i.e. 0.37 (-0.41) for T-ave (RH). The regression analysis consistently confirmed this relation. The distribution analysis reveals that the majority of COVID-19 cases in Indonesia occurred in the daily temperature range of 25-31oC and relative humidity of 74-92%. Our findings suggest that COVID-19 incidence in Indonesia has a weak association with weather conditions. Therefore, non-meteorological factors seem to play a larger role and should be given greater consideration in preventing the spread of COVID-19.

An examination of the sampling observations on wheat of the crop-weather scheme

1936 ◽  
Vol 26 (3) ◽  
pp. 456-487 ◽  
Author(s):  
M. M. Barnard
Keyword(s):  
Soil Temperature ◽  
Growth Rates ◽  
Meteorological Factors ◽  
Weather Conditions ◽  
Wheat Crop ◽  
Quadratic Regression ◽  
Shoot Number ◽  
The Mean ◽  
Good Agreement

The paper gives an account of the results obtained from the data provided by the first three years of the Sampling Observations on Wheat of the Crop-Weather Scheme.Section I describes the Sampling Observations on Wheat of the Crop Weather Scheme which have been initiated in order that the effect of weather conditions may be studied at all stages of the wheat crop’s growth from germination to maturity.In Section II several curves are given which illustrate the progress of the wheat crop. The shoot-number curves bear a marked resemblance to one another subsequent to the period when the shoot number is a maximum in spite of the wide divergences which exist between the maximum shoot numbers themselves.Section III indicates the statistical processes involved in the analyses given in the succeeding sections.Sections IV-VIII are devoted primarily to discussions of the effects of various meteorological factors on specific stages of the crop’s growth. The following results have emerged:The length of the interval from sowing to appearance above ground is shown to be largely dependent on the mean soil temperature during this interval, the relation being well expressed by a quadratic regression. The growth rates of the plants at this time are shown to be in good agreement with those which would be obtained by applying Van ‘t Hoff’s law. Neither the rainfall nor the variation in temperature during the period appear to affect its length.Squarehead’s Master appears above ground consistently later than Yeoman, but the amount of this lag is apparently uninfluenced by variations in soil temperature.

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