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

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.

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VEGETATION CHANGES AND THE RELATIONSHIP WITH CLIMATE VARIABILITY IN THE UPPER AND MIDDLE REACHES OF THE NENJIANG RIVER BASIN, CHINA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-889-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 889-895

Author(s):

F. Huang ◽

D. H. Wen ◽

P. Wang

Keyword(s):

Relative Humidity ◽

River Basin ◽

Wind Velocity ◽

Land Surface ◽

Sunshine Duration ◽

Meteorological Data ◽

Vegetation Coverage ◽

Spring Temperature ◽

Rescaled Range ◽

Nenjiang River Basin

To detect changes in vegetation is desirable for modeling and predicting interactions between land surface and atmosphere. Multitemporal series of SPOT VEGETATION NDVI dataset and meteorological data were integrated to interpret vegetation dynamics and the linkage with climate variations in the upper and middle reaches of the Nenjiang River Basin (NRB) from 1999 to 2010 using the correlation analysis and the rescaled range (R/S) analysis. The results demonstrate that annual NDVI increased slightly and 26.02% vegetation coverage of the study area significantly improved. The area of significantly decreased in vegetation cover took up 13.33% of the total land in spring. In autumn, 26.2% of the study area showed a significant vegetation increase. The improved activity of vegetation might reinforce in summer and autumn, while the decreasing tendency in spring might be persistent in the future. The yearly NDVI had significant positive linkages with precipitation and relative humidity. NDVI related significantly and negatively with temperature, sunshine hours and wind velocity, because they may have effects of increasing evapotranspiration and risk of drought and cold damage of vegetation. The variations of annual NDVI were much affected by summer temperature, relative humidity and sunshine duration in autumn and spring wind velocity. Seasonal NDVI decreased in parallel with elevated temperature, but there was no correlation between NDVI and precipitation. Spring temperature, relative humidity in summer and autumn contributed markedly to NDVI variations in the same season. The vegetation improving trend may induce by the warm-wetting climate in recent twelve years.

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VEGETATION CHANGES AND THE RELATIONSHIP WITH CLIMATE VARIABILITY IN THE UPPER AND MIDDLE REACHES OF THE NENJIANG RIVER BASIN, CHINA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b8-889-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 889-895

Author(s):

F. Huang ◽

D. H. Wen ◽

P. Wang

Keyword(s):

Relative Humidity ◽

River Basin ◽

Wind Velocity ◽

Land Surface ◽

Sunshine Duration ◽

Meteorological Data ◽

Vegetation Coverage ◽

Spring Temperature ◽

Rescaled Range ◽

Nenjiang River Basin

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Associations of Ambient Air Pollutants and Meteorological Factors With COVID-19 Transmission in 31 Chinese Provinces: A Time Series Study

INQUIRY The Journal of Health Care Organization Provision and Financing ◽

10.1177/00469580211060259 ◽

2021 ◽

Vol 58 ◽

pp. 004695802110602

Author(s):

Han Cao ◽

Bingxiao Li ◽

Tianlun Gu ◽

Xiaohui Liu ◽

Kai Meng ◽

...

Keyword(s):

Air Pollution ◽

Relative Humidity ◽

Wind Velocity ◽

Air Pollutants ◽

Meteorological Factors ◽

Meta Analysis ◽

Ambient Air ◽

Air Pollutant ◽

Pollutant Concentrations ◽

Air Pollutant Concentrations

Evidence regarding the effects of environmental factors on COVID-19 transmission is mixed. We aimed to explore the associations of air pollutants and meteorological factors with COVID-19 confirmed cases during the outbreak period throughout China. The number of COVID-19 confirmed cases, air pollutant concentrations, and meteorological factors in China from January 25 to February 29, 2020, (36 days) were extracted from authoritative electronic databases. The associations were estimated for a single-day lag as well as moving averages lag using generalized additive mixed models. Region-specific analyses and meta-analysis were conducted in 5 selected regions from the north to south of China with diverse air pollution levels and weather conditions and sufficient sample size. Nonlinear concentration–response analyses were performed. An increase of each interquartile range in PM2.5, PM10, SO2, NO2, O3, and CO at lag4 corresponded to 1.40 (1.37–1.43), 1.35 (1.32–1.37), 1.01 (1.00–1.02), 1.08 (1.07–1.10), 1.28 (1.27–1.29), and 1.26 (1.24–1.28) ORs of daily new cases, respectively. For 1°C, 1%, and 1 m/s increase in temperature, relative humidity, and wind velocity, the ORs were 0.97 (0.97–0.98), 0.96 (0.96–0.97), and 0.94 (0.92–0.95), respectively. The estimates of PM2.5, PM10, NO2, and all meteorological factors remained significantly after meta-analysis for the five selected regions. The concentration–response relationships showed that higher concentrations of air pollutants and lower meteorological factors were associated with daily new cases increasing. Higher air pollutant concentrations and lower temperature, relative humidity and wind velocity may favor COVID-19 transmission. Controlling ambient air pollution, especially for PM2.5, PM10, NO2, may be an important component of reducing risk of COVID-19 infection. In addition, as winter months are arriving in China, the meteorological factors may play a negative role in prevention. Therefore, it is significant to implement the public health control measures persistently in case another possible pandemic.

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SEASONAL AND INTERANNUAL PATTERN OF METEOROLOGICAL VARIABLES IN CUIABÁ, MATO GROSSO STATE, BRAZIL

Brazilian Journal of Geophysics ◽

10.22564/rbgf.v33i3.949 ◽

2015 ◽

Vol 33 (3) ◽

pp. 477 ◽

Cited By ~ 2

Author(s):

Nadja Gomes Machado ◽

Marcelo Sacardi Biudes ◽

Carlos Alexandre Santos Querino ◽

Victor Hugo De Morais Danelichen ◽

Maísa Caldas Souza Velasque

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Meteorological Data ◽

Seasonal Pattern ◽

Global Radiation ◽

Meteorological Variables ◽

Maximum Temperature ◽

Wet Season ◽

Agricultural Producers ◽

Mato Grosso

ABSTRACT. Cuiab´a is located on the border of the Pantanal and Cerrado, in Mato Grosso State, which is recognized as one of the biggest agricultural producers of Brazil. The use of natural resources in a sustainable manner requires knowledge of the regional meteorological variables. Thus, the objective of this study was to characterize the seasonal and interannual pattern of meteorological variables in Cuiab´a. The meteorological data from 1961 to 2011 were provided by the Instituto Nacional de Meteorologia (INMET – National Institute of Meteorology). The results have shown interannual and seasonal variations of precipitation, solar radiation, air temperature and relative humidity, and wind speed and direction, establishing two main distinct seasons (rainy and dry). On average, 89% of the rainfall occurred in the wet season. The annual average values of daily global radiation, mean, minimum and maximum temperature and relative humidity were 15.6 MJ m–2 y–1, 27.9◦C, 23.0◦C, 30.0◦C and 71.6%, respectively. Themaximum temperature and the wind speed had no seasonal pattern. The wind speed average decreased in the NWdirectionand increased in the S direction.Keywords: meteorological variables, climatology, ENSO. RESUMO. Cuiabá está localizado na fronteira do Pantanal com o Cerrado, no Mato Grosso, que é reconhecido como um dos maiores produtores agrícolas do Brasil. A utilização dos recursos naturais de forma sustentável requer o conhecimento das variáveis meteorológicas em escala regional. Assim, o objetivo deste estudo foi caracterizar o padrão sazonal e interanual das variáveis meteorológicas em Cuiabá. Os dados meteorológicos de 1961 a 2011 foram fornecidos pelo Instituto Nacional de Meteorologia (INMET). Os resultados mostraram variações interanuais e sazonais de precipitação, radiação solar, temperatura e umidade relativa do ar e velocidade e direção do vento, estabelecendo duas principais estações distintas (chuvosa e seca). Em média, 89% da precipitação ocorreu na estação chuvosa. Os valores médios anuais de radiação diária global, temperatura do ar média, mínima e máxima e umidade relativa do ar foram 15,6 MJ m–2 y–1, 27,9◦C, 23,0◦C, 30,0◦C e 71,6%, respectivamente. A temperatura máxima e a velocidade do vento não tiveram padrão sazonal. A velocidade média do vento diminuiu na direção NW e aumentou na direção S.Palavras-chave: variáveis meteorológicas, climatologia, ENOS.

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Estimation and Comparative Analysis of Daily Reference Evapotranspiration Based on Different Input Combinations and Different Models

10.21203/rs.3.rs-636505/v1 ◽

2021 ◽

Author(s):

Chaojie Niu ◽

Xiang Li ◽

Chengshuai Liu ◽

Shan-e-hyder Soomro ◽

Caihong Hu

Keyword(s):

Reference Evapotranspiration ◽

Meteorological Factors ◽

Meteorological Data ◽

Pearson Correlation ◽

Back Propagation ◽

Maximum Temperature ◽

Least Squares Regression ◽

Simulation Performance ◽

Bp Model ◽

Plsr Model

Abstract Daily reference evapotranspiration (ET0) is the most crucial link in estimating crop water demand. In this study, Levenberg-Marquardt (L-M), Genetic Algorithm-Back Propagation (GA-BP) and Partial Least Squares Regression (PLSR) models were introduced to calculate the ET0 values, Based on the Pearson Correlation analysis method, five meteorological factors were obtained, which were combined into six different input scenarios. Compared with the values that calculated by the the Penman Monteith (PM) formula. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Nash-Sutcliffe Efficiency (NSE), and Scatter Index (SI) were used to evaluate the simulation performance of the models. The results showed that the simulation effect of the L-M model is better than that of the GA-BP model and PLSR model in all scenarios. PLSR model has the worst performance. The SI index of L-M6 was 46.69% lower than that of GA-BP6 and 65.78% lower than that of PLSR6. When the input factors are 3, the simulation effect of the input wind speed, the maximum temperature and the minimum temperature is the best. L-M model and GA-BP model can predict the ET0 in the region with a lack of meteorological data. This study provides an important reference for high-precision prediction of ET0 under different input combinations of meteorological factors.

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Spatiotemporal Variability of Potential Evaporation in Heihe River Basin Influenced by Irrigation

10.5194/egusphere-egu2020-12520 ◽

2020 ◽

Author(s):

Congying Han

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Spatial Pattern ◽

River Basin ◽

Meteorological Factors ◽

Heihe River Basin ◽

Spatiotemporal Variability ◽

Maximum Temperature ◽

Heihe River ◽

Potential Evaporation

Spatiotemporal Variability of Potential Evaporation in Heihe River Basin Influenced by Irrigation Congying Han1,2, Baozhong Zhang1,2, Songjun Han1,21 State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China.2 National Center of Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China.Corresponding author: Baozhong Zhang ([email protected])Abstract: Potential evaporation is a key factor in crop water requirement estimation and agricultural water resource planning. The spatial pattern and temporal changes of potential evaporation calculated by Penman equation (EPen) (1970-2017) in Heihe River Basin (HRB), Northwest China were evaluated by using data from 10 meteorological stations, with a serious consideration of the influences of irrigation development. Results indicated that the spatial pattern of annual EPen in HRB was significantly different, among which the EPen of agricultural sites (average between 1154 mm and 1333 mm) was significantly higher than that of natural sites (average between 794 mm and 899 mm). Besides, the coefficient of spatial variation of the aerodynamic term (Eaero) was 0.4, while that of the radiation term (Erad) was 0.09. The agricultural irrigation water withdrawal increased annually before 2000, but decreased significantly after 2000 which was influenced by the agricultural development and the water policy. Coincidentally, the annual variation of Epen in agricultural sites decreased at -40 mm/decade in 1970-2000 but increased at 60 mm/decade in 2001-2017, while that in natural sites with little influence of irrigation, only decreased at -0.5mm/decade in 1970-2000 but increased at 11 mm/decade in 2001-2017. So it was obvious that irrigation influenced Epen significantly and the change of Epen was mainly caused by the aerodynamic term. The analysis of the main meteorological factors that affect Epen showed that wind speed had the greatest impact on Epen of agricultural sites, followed by relative humidity and average temperature, while the meteorological factors that had the greatest impact on Epen of natural sites were maximum temperature, followed by wind speed and relative humidity.

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Observations on the flight pattern of some Phlaeothripidae (Thysanoptera) species by using suction trap in Hungary

Acta Universitatis Sapientiae Agriculture and Environment ◽

10.1515/ausae-2016-0002 ◽

2016 ◽

Vol 8 (1) ◽

pp. 16-26 ◽

Cited By ~ 2

Author(s):

Szilvia Orosz ◽

Ágnes Szénási ◽

János Puskás ◽

Rita Ábrahám ◽

Andrea Fülöp ◽

...

Keyword(s):

Relative Humidity ◽

Dominant Species ◽

Meteorological Factors ◽

Sunshine Duration ◽

First Record ◽

Flight Activity ◽

Air Pressure ◽

Flight Period ◽

Flight Pattern ◽

Suction Trap

Abstract In this study, the seasonal flight activity of the Phlaeothripidae (Thysanoptera) species was studied by using suction trap, in South-East Hungary, in the years 2000 and 2004 from April to October. The flight period of two dominant species, namely Haplothrips angusticornis Priesner and Haplothrips aculeatus Fabricius (Thysanoptera: Phlaeothripidae), was observed in high number in Europe. Also, it was the first record of mass flight observation of H. angusticornis. In addition, the effect of meteorological factors, such as temperature, sunshine duration, relative humidity, air pressure, and their influences, were evaluated.

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

Indian Journal of Pure & Applied Biosciences ◽

10.18782/2582-2845.8632 ◽

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.

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Effects and interaction of meteorological factors on hemorrhagic fever with renal syndrome incidence in Huludao City, northeastern China, 2007–2018

PLoS Neglected Tropical Diseases ◽

10.1371/journal.pntd.0009217 ◽

2021 ◽

Vol 15 (3) ◽

pp. e0009217

Author(s):

Wanwan Sun ◽

Xiaobo Liu ◽

Wen Li ◽

Zhiyuan Mao ◽

Jimin Sun ◽

...

Keyword(s):

Public Health ◽

High Temperature ◽

Relative Humidity ◽

Meteorological Factors ◽

Meteorological Data ◽

Additive Model ◽

Hemorrhagic Fever ◽

Epidemiological Data ◽

Effect Of Temperature ◽

Delayed Effects

Background Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne disease, is a severe public health threat. Previous studies have discovered the influence of meteorological factors on HFRS incidence, while few studies have concentrated on the stratified analysis of delayed effects and interaction effects of meteorological factors on HFRS. Objective Huludao City is a representative area in north China that suffers from HFRS with primary transmission by Rattus norvegicus. This study aimed to evaluate the climate factors of lag, interaction, and stratified effects of meteorological factors on HFRS incidence in Huludao City. Methods Our researchers collected meteorological data and epidemiological data of HFRS cases in Huludao City during 2007–2018. First, a distributed lag nonlinear model (DLNM) for a maximum lag of 16 weeks was developed to assess the respective lag effect of temperature, precipitation, and humidity on HFRS incidence. We then constructed a generalized additive model (GAM) to explore the interaction effect between temperature and the other two meteorological factors on HFRS incidence and the stratified effect of meteorological factors. Results During the study period, 2751 cases of HFRS were reported in Huludao City. The incidence of HFRS showed a seasonal trend and peak times from February to May. Using the median WAT, median WTP, and median WARH as the reference, the results of DLNM showed that extremely high temperature (97.5th percentile of WAT) had significant associations with HFRS at lag week 15 (RR = 1.68, 95% CI: 1.04–2.74) and lag week 16 (RR = 2.80, 95% CI: 1.31–5.95). Under the extremely low temperature (2.5th percentile of WAT), the RRs of HFRS infection were significant at lag week 5 (RR = 1.28, 95% CI: 1.01–1.67) and lag 6 weeks (RR = 1.24, 95% CI: 1.01–1.57). The RRs of relative humidity were statistically significant at lag week 10 (RR = 1.19, 95% CI: 1.00–1.43) and lag week 11 (RR = 1.24, 95% CI: 1.02–1.50) under extremely high relative humidity (97.5th percentile of WARH); however, no statistically significance was observed under extremely low relative humidity (2.5th percentile of WARH). The RRs were significantly high when WAT was -10 degrees Celsius (RR = 1.34, 95% CI: 1.02–1.76), -9 degrees Celsius (1.37, 95% CI: 1.04–1.79), and -8 degrees Celsius (RR = 1.34, 95% CI: 1.03–1.75) at lag week 5 and more than 23 degrees Celsius after 15 weeks. Interaction and stratified analyses showed that the risk of HFRS infection reached its highest when both temperature and precipitation were at a high level. Conclusions Our study indicates that meteorological factors, including temperature and humidity, have delayed effects on the occurrence of HFRS in the study area, and the effect of temperature can be modified by humidity and precipitation. Public health professionals should pay more attention to HFRS control when the weather conditions of high temperature with more substantial precipitation and 15 weeks after the temperature is higher than 23 degrees Celsius.

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Effect of meteorological factors on the activity of influenza in Chongqing, China, 2012–2019

PLoS ONE ◽

10.1371/journal.pone.0246023 ◽

2021 ◽

Vol 16 (2) ◽

pp. e0246023

Author(s):

Li Qi ◽

Tian Liu ◽

Yuan Gao ◽

Dechao Tian ◽

Wenge Tang ◽

...

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Meteorological Factors ◽

Meteorological Data ◽

Warning System ◽

Absolute Humidity ◽

Influenza Surveillance ◽

Average Wind Speed ◽

Mean Temperature ◽

Influenza Activity

Background The effects of multiple meteorological factors on influenza activity remain unclear in Chongqing, the largest municipality in China. We aimed to fix this gap in this study. Methods Weekly meteorological data and influenza surveillance data in Chongqing were collected from 2012 to 2019. Distributed lag nonlinear models (DLNMs) were conducted to estimate the effects of multiple meteorological factors on influenza activity. Results Inverted J-shaped nonlinear associations between mean temperature, absolute humidity, wind speed, sunshine and influenza activity were found. The relative risks (RRs) of influenza activity increased as weekly average mean temperature fell below 18.18°C, average absolute humidity fell below 12.66 g/m3, average wind speed fell below 1.55 m/s and average sunshine fell below 2.36 hours. Taking the median values as the references, lower temperature, lower absolute humidity and windless could significantly increase the risks of influenza activity and last for 4 weeks. A J-shaped nonlinear association was observed between relative humidity and influenza activity; the risk of influenza activity increased with rising relative humidity with 78.26% as the break point. Taking the median value as the reference, high relative humidity could increase the risk of influenza activity and last for 3 weeks. In addition, we found the relationship between aggregate rainfall and influenza activity could be described with a U-shaped curve. Rainfall effect has significantly higher RR than rainless effect. Conclusions Our study shows that multiple meteorological factors have strong associations with influenza activity in Chongqing, providing evidence for developing a meteorology-based early warning system for influenza to facilitate timely response to upsurge of influenza activity.

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