scholarly journals Impact of Climate Change on Milk Production and Perceptions of Farmers in the West Bengal

2021 ◽  
pp. 533-540
Author(s):  
Subhankar Biswas ◽  
Ajay Verma ◽  
R. Sendhil ◽  
AK Dixit ◽  
Ajmer Singh ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Milk Production ◽  
West Bengal ◽  
Late Onset ◽  
Adaptation Strategy ◽  
Cow Milk ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Annual Minimum Temperature ◽  
Annual Maximum Temperature

The cause and effect relationship of climatic variables on milk production of indigenous cattle and buffalo had been carried in West Bengal state during 2019-2020. Regression analysis indicated the indigenous cow milk production was directly responsive to annual minimum temperature, while crossbred cow milk production was indirectly responsive to annual maximum temperature and relative humidity. The buffalo milk production was inversely related to annual maximum temperature and relative humidity. More than half of surveyed farmers had a medium level of experience in farming. Majority of farmers were perceived climate variability in general like increase in temperature during the summer season, late onset of monsoon and early withdrawal of monsoon season. For crop farming, crop diversification was the most preferred adaptation strategy among the farmers followed by changing crop variety. For dairy farming, provide proper shed and shelter was most preferred adaptation strategy followed by provide additional fresh drinking water in summer.

scholarly journals Modeling the global distribution of Culicoides imicola: an Ensemble approach

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Samson Leta ◽  
Eyerusalem Fetene ◽  
Tesfaye Mulatu ◽  
Kebede Amenu ◽  
Megarsa Bedasa Jaleta ◽  
...  
Keyword(s):  
Land Cover ◽  
Climatic Factors ◽  
Southern China ◽  
Global Distribution ◽  
Maximum Temperature ◽  
Ensemble Model ◽  
Culicoides Imicola ◽  
Annual Minimum Temperature ◽  
The Tropics ◽  
Annual Maximum Temperature

Abstract Culicoides imicola is a midge species serving as vector for a number of viral diseases of livestock, including Bluetongue, and African Horse Sickness. C. imicola is also known to transmit Schmallenberg virus experimentally. Environmental and demographic factors may impose rapid changes on the global distribution of C. imicola and aid introduction into new areas. The aim of this study is to predict the global distribution of C. imicola using an ensemble modeling approach by combining climatic, livestock distribution and land cover covariates, together with a comprehensive global dataset of geo-positioned occurrence points for C. imicola. Thirty individual models were generated by ‘biomod2’, with 21 models scoring a true skill statistic (TSS) >0.8. These 21 models incorporated weighted runs from eight of ten algorithms and were used to create a final ensemble model. The ensemble model performed very well (TSS = 0.898 and ROC = 0.991) and indicated high environmental suitability for C. imicola in the tropics and subtropics. The habitat suitability for C. imicola spans from South Africa to southern Europe and from southern USA to southern China. The distribution of C. imicola is mainly constrained by climatic factors. In the ensemble model, mean annual minimum temperature had the highest overall contribution (42.9%), followed by mean annual maximum temperature (21.1%), solar radiation (13.6%), annual precipitation (11%), livestock distribution (6.2%), vapor pressure (3.4%), wind speed (0.8%), and land cover (0.1%). The present study provides the most up-to-date predictive maps of the potential distributions of C. imicola and should be of great value for decision making at global and regional scales.

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 A bayesian analysis of the annual maximum temperature using generalized extreme value distribution

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 607-618
Author(s):  
CHERAITIA HASSEN
Keyword(s):  
Goodness Of Fit ◽  
Estimation Method ◽  
Gumbel Distribution ◽  
Extreme Value ◽  
Generalized Extreme Value Distribution ◽  
Maximum Temperature ◽  
Ratio Test ◽  
Annual Maximum ◽  
Generalized Extreme Value ◽  
Annual Maximum Temperature

The annual maximum temperature was modeled using the Generalized Extreme Value (GEV) distribution to Jijel weather station. The Mann-Kendall (MK) and Kwiatkowski Phillips, Schmidt and Shin (KPSS) tests suggest a stationary model without linear trend in the location parameter. The Kurtosis and the Skewness statistics indicated that the normality assumption was rejected. The Likelihood Ratio test was used to determine the best model and the goodness-of-fit tests showed that our data is suitable with a stationary Gumbel distribution. The Maximum Likelihood estimation method and the Bayesian approach using the Monte Carlo method by Markov Chains (MCMC) were used to find the parameters of the Gumbel distribution and the return levels were obtained for different periods. JEL Classification: C1, C13, C46, C490.

Weather Forecasting in Coastal Districts of Odisha and Andhra Pradesh by Using Time Series Analysis

2018 ◽  
Vol 6 (8) ◽  
pp. 85
Author(s):  
Naresh Patnaik ◽  
F Baliarsingh
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Time Series Analysis ◽  
Andhra Pradesh ◽  
Maximum Temperature ◽  
Climatic Parameters ◽  
Series Analysis ◽  
Annual Maximum Temperature

Climate change in world is always one of the most important topics in Water Resources. Now the issue is so predominant that it is gradually restricting out social life, peace and harmony. Climate change is a change in the statistical distribution of weather pattern of an area, when such changes occur for a long period of time. Weather is the state of atmosphere at a particular place and time. Climate is the long term statistical expression of short term weather. This study presents a comprehensive assessment of the future climate pattern/weather prediction by taking different climatic parameters such as temperature, precipitation, solar radiation, wind speed and relative humidity by using time series analysis. The study area of research work covers the coastal districts of Odisha and some parts of Andhra Pradesh. The climatic parameters are collected over last 20 years (1993-2013) from the selected 10 stations and the prediction is made using Time Series Analysis (ARIMA Model). The annual maximum temperature, solar radiation of all districts indicates a statistically significant increase in trend, whereas in the case of wind speed and relative humidity indicates significant deceasing trend. The annual rain fall shows an increasing trend of 2.69 mm/year in all station except Srikakulam, Khordha, Jagatsinghpur and Balasore which shows a decreasing trend of 1.94, 1.29, 0.56 and 1.18 mm/year respectively. As a whole the annual maximum temperature and solar radiation shows an increase trend of 0.16 ⁰C and 0.073 MJ/m² per year respectively. Further the wind speed and relative humidity of all stations indicates a decreasing trend of 0.056 m/s and 0.003(Units in fraction) per year respectively.

scholarly journals Agro-Climatic Characterization of Two Selected Stations in the Southern West Bengal, India

2013 ◽  
Vol 8 (1-2) ◽  
pp. 49-54
Author(s):  
Saon Banerjee ◽  
Asis Mukherj ◽  
Apurba Mukhopadhayal ◽  
B Saikia ◽  
S Bandyaopadhaya ◽  
...  
Keyword(s):  
Minimum Temperature ◽  
West Bengal ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Chain Model ◽  
Climatic Trend ◽  
Annual Minimum Temperature

Maximum temperature, minimum temperature and rainfall data of Bankura (1992-2007) and Canning (1960-2006) were analyzed for assessing climatic trend and agro-climatic characterization of red-lateritic and coastal Zones of West Bengal respectively. These two zones are the most vulnerable regions to climate change in West Bengal, hence selected for the present study. While average values of annual maximum temperature and annual minimum temperature were used for climatic trend analysis, no definite trend was observed. So, maximum temperature of the hottest month and minimum temperature of the coldest month were used for detecting climatic trend. The maximum temperature shows positive trend for both the stations. An increasing trend of annual rainfall was also observed. In case of agro-climatic characterization the agricultural draught, meteorological draught, seasonal rainfall and rainfall probability using Markov-chain model were analyzed for the said two stations. Kharif crops of Bankura encountered two years (2000 & 2005) agricultural draught within 2000 -2007, whereas kharif crops of Canning encountered agricultural draught in 2006 within the said period. Likewise, the deviation of seasonal rainfall and probability of two consecutive wet weeks with different levels (10, 20,30,40,50 and 60 mm) of weekly total rainfall was worked out. DOI: http://dx.doi.org/10.3329/jsf.v8i1-2.14619 J. Sci. Foundation, 8(1&2): 49-54, June-December 2010

scholarly journals Projection of key meteorological hazard factors in Xiongan new area of Hebei Province, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dapeng Huang ◽  
Yaoming Liao ◽  
Zhenyu Han
Keyword(s):  
High Temperature ◽  
Daily Precipitation ◽  
Flood Hazard ◽  
Linear Trend ◽  
Maximum Temperature ◽  
Projection Data ◽  
Annual Maximum ◽  
High Hazard ◽  
Under Construction ◽  
Annual Maximum Temperature

AbstractIt is of great importance to explore the future spatiotemporal dynamics of key meteorological hazard factors in Xiongan New Area, an area of great strategic significance under construction in China. Based on 6.25 km high-resolution downscaling projection data under RCP4.5 and RCP8.5 scenarios, Mann–Kendall trend and linear trend were analyzed, and then stationary generalized extreme value (GEV) and time-varying GEV methods were determined to calculate the extremes of four key meteorological hazard factors with return periods of 10, 20, 30, 50 and 100 years during the projection period 1991–2050. Results show that extremes of annual maximum daily precipitation and annual maximum amount of consecutive precipitation under two climate scenarios will not increase too much. Extremes of annual maximum temperature will increase by above 1.5 °C under RCP4.5 scenario in most grids and above 1.9 °C under RCP8.5 scenario. Extremes of annual longest consecutive high-temperature days will increase by above 0.9d under RCP4.5 scenario and above 1.6d under RCP8.5 scenario. On the whole, the hazard of flood disaster will hardly show any change up to 2050, but there will be relatively higher flood hazard in Xiongxian county and its adjacent region. All regions in Xiongan New Area will face high hazard of high-temperature disaster.

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