scholarly journals Climate Change and Sugarcane Productivity in India: An Econometric Analysis

2014 ◽  
Vol 5 (2) ◽  
pp. 111-122 ◽  
Author(s):  
Ajay Kumar
Keyword(s):  
Minimum Temperature ◽  
Rainy Season ◽  
Climatic Factors ◽  
Maximum Temperature ◽  
Empirical Results ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Cane Productivity ◽  
Sugarcane Productivity ◽  
Average Minimum Temperature

This study provides an understanding for the relationship between climatic factors and sugarcane productivity in India. The main objective of this paper is to estimates the impact of climatic and non-climatic factors on sugarcane productivity. To check the consistency of empirical results, simple linear regression model, Ricardian productivity regression (non-linear) model and Cobb-Douglas production function models are employed. The data set incorporates 390 observations corresponding to thirteen states with panel data for 30 years during 1980 to 2009. These all models include sugarcane productivity as dependent variable. Irrigated area, agriculture labour, consumption of fertilizers, literacy rate, tractors and farm harvest price (at constant level) are considered as explanatory variables. Average rainfall, average maximum and average minimum temperature include as climatic factors to capture the effect of climatic conditions on cane productivity. These climatic factors are incorporate for three weather seasons such as rainy, winter and summer. Empirical results based on Prais Winsten models with panels corrected standard errors (PCSEs) estimation shows that climatic factors i.e. actual rainfall, average maximum and average minimum temperature have a statistically significant impact on sugarcane productivity. The climatic effect for various factors on cane productivity are varies within different seasons. Average maximum temperature in summer and average minimum temperature in rainy season have a negative and statistically significant effect on sugarcane productivity. While, sugarcane productivity positively get affect with increasing average maximum temperature in rainy season and winter seasons. The study concluded that there is non-linear relationship between climatic factors and sugarcane productivity in India.

scholarly journals Effects of Climate Variables on Kala-azar Prevalence at Major Affected Districts in Bangladesh

2015 ◽  
Vol 6 (1) ◽  
pp. 79-87 ◽  
Author(s):  
MR Amin ◽  
SM Tareq ◽  
SH Rahman
Keyword(s):  
Negative Correlation ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Climate Variables ◽  
Total Rainfall ◽  
Kala Azar ◽  
Average Maximum ◽  
Yearly Average ◽  
Average Maximum Temperature ◽  
Average Minimum Temperature

An attempt was made to explore correlation between climate variables and Kala-azar prevalence at four highly affected districts in Bangladesh: Mymensingh, Tangail, Pabna, and Rajshahi. The climate variables included were temperature, rainfall and relative humidity. With the rise of yearly average humidity in Mymensingh, Tangail and Rajshahi districts Kala-azar prevalence was significantly increased and with the rise of yearly total rainfall positive but not significant correlation was observed in Mymensingh,Tangail and Rajshahi. In Mymensingh negative correlation was found with yearly average maximum and minimum temperature. Positive association with yearly total rainfall in Mymensingh, Pabna & Rajshahi and yearly average minimum temperature in Rajshahi and yearly average maximum temperature in Tangail was observed. The prevalence of the disease was found to have negative correlation with yearly average maximum temperature in both Pabna & Rajshahi, yearly average minimum temperature in both Tangail & Pabna and yearly total rainfall in Tangail.DOI: http://dx.doi.org/10.3329/jesnr.v6i1.22045 J. Environ. Sci. & Natural Resources, 6(1): 79-87 2013

scholarly journals Impact Of Temperature and Sunshine Duration on Daily New Cases and Death due to COVID-19

2020 ◽  
Author(s):  
Swati Thangariyal ◽  
Aayushi Rastogi ◽  
Arvind Tomar ◽  
Ajeet Bhadoria ◽  
Sukriti Baweja
Keyword(s):  
Sunshine Duration ◽  
Ecological Factors ◽  
Critical Issue ◽  
Climatic Conditions ◽  
Maximum Temperature ◽  
Average Temperature ◽  
Climate Indicators ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Average Minimum Temperature

AbstractBackgroundThe coronavirus pandemic (COVID-19) control has now become a critical issue for public health. Many ecological factors are proven to influence the transmission and survival of the virus. In this study, we aim to determine the association of different climate factors with the spread and mortality due to COVID-19.MethodsThe climate indicators included in the study were duration of sunshine, average minimum temperature and average maximum temperature, with cumulative confirmed cases, deceased and recovered cases. The data was performed for 138 different countries of the world, between January 2020 to May 2020. Both univariate and multivariate was performed for cumulative and month-wise analysis using SPSS software.ResultsThe average maximum temperature, and sunshine duration was significantly associated with COVID-19 confirmed cases, deceased and recovered. For every one degree increase in mean average temperature, the confirmed, deceased and recovered cases decreased by 2047(p=0.03), 157(p=0.016), 743 (p=0.005) individuals. The association remained significant even after adjusting for environmental such as sunshine duration as well as non-environmental variables. Average sunshine duration was inveserly correlated with increase in daily new cases (ρ= -2261) and deaths (ρ= -0.2985).ConclusionHigher average temperature and longer sunshine duration was strongly associated with COVID-19 cases and deaths in 138 countries. Hence the temperature is an important factor in SARS CoV-2 survival and this study will help in formulating better preventive measures to combat COVID-19 based on their climatic conditions.

scholarly journals Time-series forecasting models

2021 ◽  
Vol 9 (8) ◽  
pp. 24-47
Author(s):  
Douglas Matheus das Neves Santos ◽  
Yuri Antônio da Silva Rocha ◽  
Danúbia Freitas ◽  
Paulo Beltrão ◽  
Paulo Santos Junior ◽  
...  
Keyword(s):  
Time Series ◽  
Statistical Models ◽  
Weather Forecasting ◽  
Real Data ◽  
Information Criterion ◽  
Maximum Temperature ◽  
Forecasting Models ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Average Minimum Temperature

Statistical and mathematical models of forecasting are of paramount importance for the understanding and study of databases, especially when applied to data of climatological variables, which enables the atmospheric study of a city or region, enabling greater management of the anthropic activities and actions that suffer the direct or indirect influence of meteorological parameters, such as precipitation and temperature. Therefore, this article aimed to analyze the behavior of monthly time series of Average Minimum Temperature, Average Maximum Temperature, Average Compensated Temperature, and Total Precipitation in Belém (Pará, Brazil) on data provided by INMET, for the production and application forecasting models. A 30-year time series was considered for the four variables, from January 1990 to December 2020. The Box and Jenkins methodology was used to determine the statistical models, and during their applications, models of the SARIMA and Holt-Winters class were estimated. For the selection of the models, analyzes of the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Autocorrelation Correlogram (ACF), and Partial Autocorrelation (PACF) and tests such as Ljung-Box and Shapiro-Wilk were performed, in addition to Mean Square Error (NDE) and Absolute Percent Error Mean (MPAE) to find the best accuracy in the predictions. It was possible to find three SARIMA models: (0,1,2) (1,1,0) [12], (1,1,1) (0,0,1) [12], (0,1,2) (1,1,0) [12]; and a Holt-Winters model with additive seasonality. Thus, we found forecasts close to the real data for the four-time series worked from the SARIMA and Holt-Winters models, which indicates the feasibility of its applicability in the study of weather forecasting in the city of Belém. However, it is necessary to apply other possible statistical models, which may present more accurate forecasts.

scholarly journals Agro-metrological investigation of bumper apple productivity in Himachal Pradesh, India

2016 ◽  
Vol 8 (1) ◽  
pp. 133-139
Author(s):  
Ranbir Singh Rana ◽  
Manmohan Singh ◽  
Ramesh Ramesh ◽  
Aditya Aditya ◽  
Ranu Pathania
Keyword(s):  
Low Temperature ◽  
Temperature Rise ◽  
Minimum Temperature ◽  
Fruit Set ◽  
Himachal Pradesh ◽  
Maximum Temperature ◽  
Metrological Investigation ◽  
Bloom Period ◽  
Average Maximum ◽  
Average Maximum Temperature

The study aimed to investigate the productivity and weather relationship for the apple growing areas of Himachal Pradesh viz., Kalpa, Bhuntar and Shimla in district Kinnaur, Kullu and Shimla, respectively. The results revealed that pre bloom period (November to February) in the year 2009-10 remained cooler. The minimum temperature of 0.4 to 0.9, 1.0 to 1.1°C and 1.9 to 2.2°C and maximum temperature of 6.7, 1.0 to 1.1 and 1.7°C were lower in Shimla, Bhuntar and Kalpa region, respectively compared to 1995-2009.. The maximum temperature for the chill accumulation months of November, December, January and February during 2009-10 showed 13 to 19 per cent lower compared to 1995-2009. The average pre bloom rainfall during 2010 was 39 to 57 per cent higher than 1995-2009 indicating sustainable bloom period. The 3 to 4°C temperature rise during March 2010 (19 to 24°C) as compared to 1995-2009 (16 to 21.4°C) coupled with 52 per cent higher precipitation benefited the crop in profuse flowering and hence good fruit set. The average maximum temperature during the post bloom period (May-June) in 2009-10 was 1°C higher compared to the previous years coupled with 23 per cent higher rainfall resulting in an highest productivity. The highest productivity (8.57 MT/ha) during 2010 which was 58 per cent higher than the previous years can be ascribed due to the favorable low temperature in pre bloom period and increase in the temperature inthe month of March along with adequate rainfall in the bloom and post bloom period.

ANNUAL AND SEASONAL VARIATIONS IN TEMPERATURE EXTREMES AND RAINFALL IN BANGLADESH, 1989–2018

2021 ◽  
pp. 2150004
Author(s):  
LIPON CHANDRA DAS ◽  
ZHIHUA ZHANG
Keyword(s):  
Winter Season ◽  
Temperature Data ◽  
Maximum Temperature ◽  
Average Maximum ◽  
Yearly Average ◽  
Average Rainfall ◽  
Increasing Trend ◽  
Average Maximum Temperature ◽  
Average Minimum Temperature ◽  
Increasing Trends

Based on temperature and rainfall recorded at 34 meteorological stations in Bangladesh during 1989–2018, the trends of yearly average maximum and minimum temperatures have been found to be increasing at the rates of 0.025∘C and 0.018∘C per year. Analysis of seasonal average maximum temperature showed increasing trend for all seasons except the late autumn season. The increasing trend was particularly significant for summer, rainy and autumn seasons. Seasonal average minimum temperature data also showed increasing trends for all seasons. The trend of yearly average rainfall has been found to be decreasing at a rate of 0.014[Formula: see text]mm per year in the same period; especially, for most of the meteorological stations the rainfall demonstrates an increasing trend for rainy season and a decreasing trend in the winter season. It means that in Bangladesh dry periods became drier and wet periods became wetter.

scholarly journals Influence of prevailing weather parameters on population dynamics of spotted stem borer, Chilo partellus (Swinhoe) and its natural enemies on maize in Haryana

2021 ◽  
Vol 22 (3) ◽  
pp. 295-304
Author(s):  
GAURAV SINGH ◽  
MAHA SINGH JAGLAN ◽  
TARUN VERMA ◽  
SHIVANI KHOKHAR
Keyword(s):  
Population Dynamics ◽  
Chilo Partellus ◽  
Natural Enemies ◽  
Minimum Temperature ◽  
Significant Positive Correlation ◽  
Maximum Temperature ◽  
Positive Correlation ◽  
Average Maximum ◽  
Weather Parameters ◽  
Average Minimum Temperature

The experiment was conducted at CCS Haryana Agricultural University Regional Research Station, Karnal to ascertain the influence of prevailing meteorological parameters on population dynamics of Chilo partellus and its natural enemies on maize during Kharif, 2017. Maximum oviposition (0.75 egg masses per plant) was recorded during 28th standard meteorological week (SMW) whereas larval population was at peak during 31st SMW (3.8 larvae per plant). Cumulative (47.5%) and fresh plant infestation (11.5%) were maximum during 34th and 28th SMW, respectively. Maximum egg parasitisation (6.53%) by Trichogramma sp. and larval parasitisation (31.64%) by Cotesia flavipes was recorded during 28th and 33rd SMW, respectively. Changes in pest population were correlated and regressed with weather parameters. Egg and larval populations of C. partellus and parasitisation by Trichogramma sp. exhibited significant positive correlation with average minimum temperature whereas C. flavipes exhibited significant negative correlation with average maximum temperature (r = -0.741) and highly significant positive correlation with evening relative humidity (r = 0.695). Plant infestation and dead heart formation were significantly correlated with average minimum temperature and non-significantly correlated with all other weather parameters. The multiple linear regression analysis explained the variability due to various weather parameters. This information can be utilised while formulating integrated management tactics against this pest.

scholarly journals Nature of transmission of Covid19 in India

2020 ◽  
Author(s):  
Anushree Roy ◽  
Sayan Kar
Keyword(s):  
Population Density ◽  
Minimum Temperature ◽  
Maximum Temperature ◽  
Weak Correlation ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Average Relative Humidity ◽  
Maximum Temperatures ◽  
Number Of Individuals

AbstractWe examine available data on the number of individuals infected by the Covid-19 virus, across several different states in India, over the period January 30, 2020 to April 10, 2020. It is found that the growth of the number of infected individuals N(t) can be modeled across different states with a simple linear function N(t) = γ + αt beyond the date when reasonable number of individuals were tested (and when a countrywide lockdown was imposed). The slope α is different for different states. Following recent work by Notari (arxiv:2003.12417), we then consider the dependency of the α for different states on the average maximum and minimum temperatures, the average relative humidity and the population density in each state. It turns out that like other countries, the parameter α, which determines the rate of rise of the number of infected individuals, seems to have a weak correlation with the average maximum temperature of the state. In contrast, any significant variation of α with humidity or minimum temperature seems absent with almost no meaningful correlation. Expectedly, α increases (slightly) with increase in the population density of the states; however, the degree of correlation here too is negligible. These results seem to barely suggest that a natural cause like a hot summer (larger maximum temperatures) may contribute towards reducing the transmission of the virus, though the role of minimum temperature, humidity and population density remains somewhat obscure from the inferences which may be drawn from presently available data.

scholarly journals Perspective Response of Climate Change Impacts on Agricultural Crops in Sauraha-Pharsatikar VDC, Rupandehi District, Nepal

2017 ◽  
Vol 5 (3) ◽  
pp. 345-355
Author(s):  
Kapil Khanal ◽  
Subodh Khanal ◽  
Surya Mani Dhungana
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Household Survey ◽  
Maximum Temperature ◽  
Cereal Crops ◽  
Agricultural Crops ◽  
Farming Communities ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Average Minimum Temperature

A survey research was conducted in Sauraha-Pharsatikar VDC of the Rupandehi district to study the perspective response of the farming communities on the impacts of the climate change in agricultural crops. Primary information was collected from household survey by administering pre-tested questionnaire and necessary data were collected from National Wheat Research Project (NWRP), Bhairahawa. Several results are obtained on the recall basis of the respondents thus they can not assumed correctly and all the past information provided by the farmers cannot be cross checked due to the lack of sufficient and reliable system for recording and checking. The trend analysis of rainfall data of Bhairahawa of 30 years (1984-2013) showed that the pattern of rainfall was irregular and it was in a decreasing trend by 1.944 mm per year and average maximum temperature has increased by 0.0.15oC and average minimum temperature has increased by 0.0.61oC per year which justifies that the summers are growing hotter and winters are growing warmer. About 52% of the respondents suggested monsoon starts earlier, 85% suggested there is more intense rain during the monsoon and 91.75% suggested drought has increased. 98.33% of the respondents perceived that the summer has become hotter. In general there is increase in the yield of cereal crops whereas the yield of pulses, legumes and vegetables had declined. Int. J. Appl. Sci. Biotechnol. Vol 5(3): 345-355

scholarly journals Immune function differs among tropical environments but is not downregulated during reproduction in three year-round breeding equatorial lark populations

Oecologia ◽  
2021 ◽  
Author(s):  
Henry K. Ndithia ◽  
Kevin D. Matson ◽  
Muchane Muchai ◽  
B. Irene Tieleman
Keyword(s):  
Nitric Oxide ◽  
Immune Function ◽  
Environmental Conditions ◽  
Breeding Birds ◽  
Maximum Temperature ◽  
Tropical Environments ◽  
Trade Offs ◽  
Average Maximum ◽  
Average Maximum Temperature ◽  
Average Minimum Temperature

AbstractSeasonal variation in immune function can be attributed to life history trade-offs, and to variation in environmental conditions. However, because phenological stages and environmental conditions co-vary in temperate and arctic zones, their separate contributions have not been determined. We compared immune function and body mass of incubating (female only), chick-feeding (female and male), and non-breeding (female and male) red-capped larks Calandrella cinerea breeding year-round in three tropical equatorial (Kenya) environments with distinct climates. We measured four immune indices: haptoglobin, nitric oxide, agglutination, and lysis. To confirm that variation in immune function between breeding (i.e., incubating or chick-feeding) and non-breeding was not confounded by environmental conditions, we tested if rainfall, average minimum temperature (Tmin), and average maximum temperature (Tmax) differed during sampling times among the three breeding statuses per location. Tmin and Tmax differed between chick-feeding and non-breeding, suggesting that birds utilized environmental conditions differently in different locations for reproduction. Immune indices did not differ between incubating, chick-feeding and non-breeding birds in all three locations. There were two exceptions: nitric oxide was higher during incubation in cool and wet South Kinangop, and it was higher during chick-feeding in the cool and dry North Kinangop compared to non-breeding birds in these locations. For nitric oxide, agglutination, and lysis, we found among-location differences within breeding stage. In equatorial tropical birds, variation in immune function seems to be better explained by among-location climate-induced environmental conditions than by breeding status. Our findings raise questions about how within-location environmental variation relates to and affects immune function.

scholarly journals Strong controls of daily minimum temperature on the autumn photosynthetic phenology of subtropical vegetation in China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peixin Ren ◽  
Zelin Liu ◽  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Jingfeng Xiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Time Lag ◽  
Evergreen Forest ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Study Region ◽  
Cumulative Precipitation

Abstract Background Vegetation phenology research has largely focused on temperate deciduous forests, thus limiting our understanding of the response of evergreen vegetation to climate change in tropical and subtropical regions. Results Using satellite solar-induced chlorophyll fluorescence (SIF) and MODIS enhanced vegetation index (EVI) data, we applied two methods to evaluate temporal and spatial patterns of the end of the growing season (EGS) in subtropical vegetation in China, and analyze the dependence of EGS on preseason maximum and minimum temperatures as well as cumulative precipitation. Our results indicated that the averaged EGS derived from the SIF and EVI based on the two methods (dynamic threshold method and derivative method) was later than that derived from gross primary productivity (GPP) based on the eddy covariance technique, and the time-lag for EGSsif and EGSevi was approximately 2 weeks and 4 weeks, respectively. We found that EGS was positively correlated with preseason minimum temperature and cumulative precipitation (accounting for more than 73% and 62% of the study areas, respectively), but negatively correlated with preseason maximum temperature (accounting for more than 59% of the study areas). In addition, EGS was more sensitive to the changes in the preseason minimum temperature than to other climatic factors, and an increase in the preseason minimum temperature significantly delayed the EGS in evergreen forests, shrub and grassland. Conclusions Our results indicated that the SIF outperformed traditional vegetation indices in capturing the autumn photosynthetic phenology of evergreen forest in the subtropical region of China. We found that minimum temperature plays a significant role in determining autumn photosynthetic phenology in the study region. These findings contribute to improving our understanding of the response of the EGS to climate change in subtropical vegetation of China, and provide a new perspective for accurately evaluating the role played by evergreen vegetation in the regional carbon budget.

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