scholarly journals Impact of Meteorological Conditions on the Dynamics of the COVID-19 Pandemic in Poland

2021 ◽  
Vol 18 (8) ◽  
pp. 3951
Author(s):  
Bogdan Bochenek ◽  
Mateusz Jankowski ◽  
Marta Gruszczynska ◽  
Grzegorz Nykiel ◽  
Maciej Gruszczynski ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Negative Impact ◽  
Sunshine Duration ◽  
Principal Component ◽  
Meteorological Conditions ◽  
Maximum Temperature ◽  
Sunshine Hours ◽  
Meteorological Observations ◽  
Novel Coronavirus ◽  
Nonpharmaceutical Interventions

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel coronavirus. The role of environmental factors in COVID-19 transmission is unclear. This study aimed to analyze the correlation between meteorological conditions (temperature, relative humidity, sunshine duration, wind speed) and dynamics of the COVID-19 pandemic in Poland. Data on a daily number of laboratory-confirmed COVID-19 cases and the number of COVID-19-related deaths were gatheredfrom the official governmental website. Meteorological observations from 55 synoptic stations in Poland were used. Moreover, reports on the movement of people across different categories of places were collected. A cross-correlation function, principal component analysis and random forest were applied. Maximum temperature, sunshine duration, relative humidity and variability of mean daily temperature affected the dynamics of the COVID-19 pandemic. An increase intemperature and sunshine hours decreased the number of confirmed COVID-19 cases. The occurrence of high humidity caused an increase in the number of COVID-19 cases 14 days later. Decreased sunshine duration and increased air humidity had a negative impact on the number of COVID-19-related deaths. Our study provides information that may be used by policymakers to support the decision-making process in nonpharmaceutical interventions against COVID-19.

scholarly journals The Effects of Ecological Factors on the Main Medicinal Components of Dendrobium officinale under Different Cultivation Modes

Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 94 ◽  
Author(s):  
Yingdan Yuan ◽  
Xinggang Tang ◽  
Zhaohui Jia ◽  
Chong Li ◽  
Jieyi Ma ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Sunshine Duration ◽  
Ecological Factors ◽  
Principal Component ◽  
Dendrobium Officinale ◽  
Maximum Temperature ◽  
Available Phosphorus ◽  
Quality Factors ◽  
Soil Available Phosphorus ◽  
Total Alkaloids

Dendrobium officinale is an important traditional Chinese medicinal plant and crop, which contains many kinds of medicinal components. The quality of medicinal plants is closely related to the ecological factors in a growing environment. The main components of D. officinale determined in this study were polysaccharides, total alkaloids and total flavonoids. In addition, this study dealt with the correlation of these components to 16 ecological factors under three different cultivation modes (Greenhouse, Bionic, Wild; Lu’an, Anhui Province, China). The relationship between ecological factors and quality factors was analyzed step by step using correlation analysis, principal component analysis and stepwise multiple linear regression. Eight ecological factors: maximum relative humidity, minimum relative humidity, maximum temperature, sunshine duration, soil pH, soil total nitrogen, soil total phosphorus and soil available phosphorus were considered as key factors that influenced the main medicinal qualities of cultivated D. officinale. This study provides an insight for exploring the complex relationship between ecological factors and D. officinale medicinal value in artificial cultivation.

Clustering analysis of regional reference evapotranspiration and its components based on climatic variables across northeast China, 1961–2010

2015 ◽  
Vol 7 (1) ◽  
pp. 128-141 ◽  
Author(s):  
Yuan Liu ◽  
Buchun Liu ◽  
Xiaojuan Yang ◽  
Wei Bai
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Northeast China ◽  
Reference Evapotranspiration ◽  
Potential Evapotranspiration ◽  
Sunshine Duration ◽  
Regional Distribution ◽  
Climatic Variables ◽  
Maximum Temperature ◽  
Sunshine Hours

Evapotranspiration integrates atmospheric demand and surface conditions. The Penman-Monteith equation was used to calculate annual and seasonal reference evapotranspiration (ET0) and thermodynamic and aerodynamic components (ETrad and ETaero) at 77 stations across northeast China, 1961–2010. The results were: (1) annual ETrad and ETaero had different regional distribution, annual ETrad values decreased from south to north, whereas the highest ETaero values were recorded in the eastern and western regions, the lowest in the central region; (2) seasonal ETaero distributions were similar to seasonal ET0, with a south–north longitudinal pattern, while seasonal ETrad distributions had a latitudinal east-west pattern; and (3) in the group for ET0 containing 69 sampling stations, effects of climatic variables on ET0 followed sunshine hours > relative humidity > maximum temperature > wind speed. Changes in sunshine hours had the greatest effect on ETrad, but wind speed and relative humidity were the most important variables to ETaero. The decline in sunshine duration, wind speed, or both over the study period appeared to be the major cause of reduced potential evapotranspiration in most of NEC. Wind speed had opposite effects on ETrad and ETaero, and therefore the effect of wind speed on ET0 was not significant.

scholarly journals Investigation of Climate Change Anomaly by Using Nonparametric Test for Navsari District of South Gujarat

2021 ◽  
Vol 9 (3) ◽  
pp. 266-275
Author(s):  
Neeraj Kumar ◽  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Relative Humidity ◽  
Nonparametric Test ◽  
Maximum Temperature ◽  
Rainfall Trend ◽  
Regression Slope ◽  
Sunshine Hours ◽  
Increasing Trend ◽  
Daily Sunshine

Navsari district of rainfall was shows highest increasing rainfall trend obtained September and negative January, July, October, November and December. The regression slope of the yearly time series is about 12.35 mm/36 years. Maximum temperature shows the highest increasing trend in month October, followed by December and August. The month highest decreasing trend was noticed that January, followed by February and July. The regression slope of the yearly time series is about 0.025°C/36 years. Minimum temperature highest values of the slope (0.109°C/36 year) with high value of regression Slope of determination (0.111°C), the annual Kendall’s tau statistic (0.492°C/36 year), the Kendall Score (310). All the month January to December shows increasing trend. The highest increasing trend found that November, followed by March and July, respectively. This finding shows that all the month shows increasing trend with the range between 0.308°C to 0.390°C. In case of RH-I the highest increasing trend shows September, followed by April and June. Similarly decreasing trend was found that January, followed by February and October, respectively. Relative humidity-II increasing trend was found only at the September month 0.084%, the increasing trend was detected in January to August and October to December, respectively. The strongest trend in the Bright sunshine hour’s decline of all month’s average daily sunshine hours was for the Navsari district. No significant trends were detected in all months and seasons for all weather elements. A similar trend was found in Sen’s slope and regression slope all the months for all the weather elements.

scholarly journals Long term monthly and inter-seasonal weather variability analysis for the lower Shivalik foothills of Punjab

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 173-180
Author(s):  
NAVNEET KAUR ◽  
M.J. SINGH ◽  
SUKHJEET KAUR
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Linear Regression Method ◽  
Post Monsoon ◽  
Sunshine Hours ◽  
Annual Minimum Temperature ◽  
Weather Parameters

This paper aims to study the long-term trends in different weather parameters, i.e., temperature, rainfall, rainy days, sunshine hours, evaporation, relative humidity and temperature over Lower Shivalik foothills of Punjab. The daily weather data of about 35 years from agrometeorological observatory of Regional Research Station Ballowal Saunkhri representing Lower Shivalik foothills had been used for trend analysis for kharif (May - October), rabi (November - April), winter (January - February), pre-monsoon (March - May), monsoon (June - September) and post monsoon (October - December) season. The linear regression method has been used to estimate the magnitude of change per year and its coefficient of determination, whose statistical significance was checked by the F test. The annual maximum temperature, morning and evening relative humidity has increased whereas rainfall, evaporation sunshine hours and wind speed has decreased significantly at this region. No significant change in annual minimum temperature and diurnal range has been observed. Monthly maximum temperature revealed significant increase except January, June and December, whereas, monthly minimum temperature increased significantly for February, March and October and decreased for June. Among different seasons, maximum temperature increased significantly for all seasons except winter season, whereas, minimum temperature increased significantly for kharif and post monsoon season only. The evaporation, sunshine hours and wind speed have also decreased and relative humidity decreased significantly at this region. Significant reduction in kharif, monsoon and post monsoon rainfall has been observed at Lower Shivalik foothills. As the region lacks assured irrigation facilities so decreasing rainfall and change in the other weather parameters will have profound effects on the agriculture in this region so there is need to develop climate resilient agricultural technologies.

scholarly journals Effect of weather on growth and yield of cotton grown in the dry farming tract of peninsular India

MAUSAM ◽  
2021 ◽  
Vol 59 (3) ◽  
pp. 339-346
Author(s):  
N. CHATTOPADHYAY ◽  
R. P. SAMUI ◽  
S. K. BANERJEE
Keyword(s):  
Relative Humidity ◽  
Minimum Temperature ◽  
Meteorological Parameters ◽  
Growth And Yield ◽  
Maximum Temperature ◽  
Peninsular India ◽  
Development Stages ◽  
Sunshine Hours ◽  
Dry Farming

In the present study the effect of meteorological parameters on cotton growth at three different stations in the dry farming tract of peninsular India were studied critically. Increase in minimum temperature                (above normal) particularly at vegetative and flowering stages favoured the yield of three varieties of cotton (AHH - 468, MCU - 9 and MCU - 10) under study.  Decrease in maximum temperature at flowering and boll development stages was found to be conducive for the higher yield of AHH – 468 variety of cotton at Akola.  In general, relative humidity was positively correlated with the yield of AHH – 468 varieties at Akola and MCU – 10 varieties at Kovilpatti. Lower values of bright sunshine hours (<5 hours) during vegetative and flowering were found to be helpful for increased yield of cotton at Akola. Rainfall at the beginning of the season favoured the yield of the crop. 

scholarly journals General Formula for Estimation of Monthly Mean Global Solar Radiation in Different Climates on the South and North Coasts of Iran

2007 ◽  
Vol 2007 ◽  
pp. 1-7 ◽  
Author(s):  
Ali A. Sabziparvar
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
General Formula ◽  
Sunshine Duration ◽  
Global Radiation ◽  
Global Solar Radiation ◽  
Maximum Temperature ◽  
The South ◽  
Coastal Regions ◽  
Different Climates

Using sunshine duration, cloud cover, relative humidity, average of maximum temperature, and ground albedo as the input of several radiation models, the monthly average daily solar radiation on horizontal surface in various coastal cities of the South (25.23∘N) and the North (38.42∘N) of Iran are estimated. Several radiation models are tested and further are revised by taking into consideration the effects of relative humidity, ground albedo, and Sun-Earth distance. Model validation is performed by using up to 13 years (1988–2000) of daily solar observations. Errors are calculated using MBE, MABE, MPE, and RMSE statistical criteria (see nomenclature) and further a general formula which estimates the global radiation in different climates of coastal regions is suggested. The proposed method shows a good agreement (less than7%deviation) with the long-term pyranometric data. In comparison with other works done so far, the suggested method performs a higher degree of accuracy for those of two regions. The model results can be extended to other locations in coastal regions where solar data are not available.

scholarly journals Influence of Weather Parameters and Thermal Time Approach on Green Gram at Coimbatore, Tamil Nadu

2020 ◽  
pp. 1-5
Author(s):  
S. A. Naveen ◽  
S. Kokilavani ◽  
S. P. Ramanathan ◽  
G. A. Dheebakaran ◽  
S. Anitta Fanish
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Tamil Nadu ◽  
Green Gram ◽  
Research Centre ◽  
Maximum Temperature ◽  
Sowing Dates ◽  
Sunshine Hours ◽  
Diurnal Range ◽  
Weather Parameters

An investigation was carried out at the Agro Climate Research Centre, Tamil Nadu Agricultural University, on the effect of weather parameters on the green gram yield sown at various sowing dates during the rabi season of 2019. At various sowing dates, two green gram cultivars, VBN 4 and ADT 3, were sown. For both cultivars, the phonological crop length decreased with delays in sowing dates beyond October 23rd. The yield of green gram sown on 23rd October was significantly higher than the crops sown on 30th October and 6th November. The weather parameters Maximum Temperature (Tmax), Diurnal Range (Trange), Bright Sunshine Hours (BSS), Relative Humidity (RH I), Wind Speed (WS) were found to be negatively correlated with seed yield whereas Minimum Temperature (Tmin), Relative Humidity (RH II), Vapour Pressure (VP) were found to be positively correlated with the yield of green gram. The accurate prediction of green gram yield could be done with the maximum temperature, bright sunshine hours, wind speed and with thermal indices especially hygrothermal unit II with 82 percent, accuracy level.

scholarly journals Climatic Factors Affecting The Population Dynamics Of Lentil Aphid In Inner Terai Region Of Nepal

2020 ◽  
Vol 17 (2) ◽  
pp. 155-164
Author(s):  
S Neupane ◽  
S Subedi
Keyword(s):  
Population Dynamics ◽  
Relative Humidity ◽  
Minimum Temperature ◽  
Negative Impact ◽  
Climatic Factors ◽  
Block Design ◽  
Winter Season ◽  
Research Field ◽  
Aphid Population ◽  
Maximum Temperature

Population dynamics of lentil aphid Aphis craccivora (Hemiptera: Aphididae) was assessed in relation with climatic parameters at the research field of National Maize Research Program (NMRP), Rampur, Chitwan during winter season of two consecutive years 2016 to 2018. The experiment was organized in randomized complete block design consisting 20 lentil varieties with three replications. The crop was sown during last week of November in both the years. The daily meteorological parameters like maximum temperature (Tmax), minimum temperature (Tmin), relative humidity (RH) and rainfall (Rf) were recorded at the meteorological station located in NMRP, Rampur, Chitwan and then converted into weekly basis as the standard meteorological week (SMW) with correspondence to weekly population of aphid. The incidence of aphid was started from 2nd SMW of January (2 aphid/plant/10 cm apical twigs) during both experimentation years. Initially the population was low and gradually increased and reached to its peak (49 aphid/plant/10cm apical twigs) on 9th SMW i.e. first week of March with correspondence to weather parameters viz. maximum and minimum temperature (°C), relative humidity (%) and rainfall (mm) were 30.80, 15.34, 67.72 and 0, respectively over the years. The aphid population had significant positive correlation with Tmax (r= 0.94) while the Tmin showed highly significant correlation (r=0.99). The relative humidity (RH) had non significant negative correlation (r= -0.90) and rainfall (Rf) showed non significant negative impact (r= - 0.15) with aphid population. The regression model developed could explain 99% variation in aphid population in different cultivars of lentil. SAARC J. Agri., 17(2): 155-164 (2019)

scholarly journals Factors affecting the trends in evaporation during different crop growing seasons over India

MAUSAM ◽  
2021 ◽  
Vol 62 (3) ◽  
pp. 391-402
Author(s):  
R.P. SAMUI ◽  
G. JOHN ◽  
S.P. RANSURE ◽  
M.A. PACHANKAR
Keyword(s):  
Relative Humidity ◽  
Wind Velocity ◽  
Meteorological Factors ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Peninsular India ◽  
High Positive Correlation ◽  
Growing Seasons ◽  
Increasing Trend

Evaporation, rainfall and meteorological data for the period 1971-2004 for 58 well distributed stations over India were selected for the study. Trends of evaporation and rainfall in five regions, viz., Northwest, North, Northeast, Central and Peninsular regions of India during different crop growing seasons, viz., kharif, rabi and summer and the meteorological factors contributing towards the trend were analyzed. Annual evaporation shows decreasing trend in all the regions of the country. Trends in seasonal evaporation during kharif, rabi and summer seasons also showed decreasing trends in Northwest, North, Central and Peninsular regions of the country while few locations in Northeast India, viz., Guwahati, Dibrugarh and Tocklai showed significant increasing trend in evaporation during kharif and rabi seasons. No significant trend in annual and seasonal rainfall was observed in Indian region except a few stations in peninsular India where increasing trend was observed. Normalized anomalies of maximum temperature, relative humidity and vapour pressure showed increasing trend in Northwest and Northern regions during all the three crop growing seasons while decreasing trend or no trend in wind velocity was observed in all the regions except in central region where increasing trend was observed during summer season. As evaporation relates to the meteorological elements, viz., temperature, sunshine duration, wind velocity and relative humidity, the likely causative meteorological factors for such changes are studied. Increasing trends in maximum temperature was observed in central and peninsular inland regions of the country during rabi and summer seasons while slight decreasing trends were observed in the Northeast region during kharif season. High positive correlation found between maximum temperature and wind velocity indicates that the trend in evaporation is mostly influenced by these two factors. Increase in humidity and decrease in bright sunshine hours were both important and found correlated with the decrease in evaporation.

scholarly journals Effect of meteorological parameters on Karnal bunt incidence in wheat under different agroclimatic zones of Punjab

2022 ◽  
Vol 24 (1) ◽  
Author(s):  
SARABJOT KAUR SANDHU ◽  
ANURAG ATTRI ◽  
RITU BALA
Keyword(s):  
Relative Humidity ◽  
Negative Correlation ◽  
Significant Positive Correlation ◽  
Meteorological Parameters ◽  
Disease Incidence ◽  
Karnal Bunt ◽  
Maximum Temperature ◽  
Wheat Crop ◽  
Sunshine Hours ◽  
Rainy Days

To quantify the effect of meteorological parameters on incidence of Karnal bunt in wheat crop, an investigation was done using 9 to 12 season’s data of Bathinda and Ludhiana stations of Punjab. Maximum temperature during March in range of 25-31oC, minimum temperature of February (8.5-11.0oC), morning and evening relative humidity of March in range of 85-95 and 40-60 per cent respectively, rainfall more than 25 mm with sunshine hours 5.5-9.0 hrs/day during mid February to mid March favour Karnal bunt in wheat crop. Maximum temperature of March showed significant negative correlation with incidence of Karnal bunt whereas minimum temperature of February showed significant positive correlation with disease incidence at both locations. Morning and evening relative humidity showed significant positive correlation with disease incidence. Rain amount and rainy days during mid February to mid March significantly influenced disease incidence. Sunshine hours had negative correlation with disease incidence. Backward multiple linear regression (BMLR) analysis indicated maximum temperature, rainfall and sunshine hours play significant role in Karnal bunt incidence at Ludhiana. However, at Bathinda, maximum temperature, evening time relative humidity, rain amount and rainy days played significant role.

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