scholarly journals Trend Detection in Rainfall and Temperature Data [1960-2014] of Anand, Gujrat, India

2021 ◽  
pp. 125-133
Author(s):  
S. S. Chinchorkar ◽  
G. J. Kamani
Keyword(s):  
Linear Trend ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Kendall Test ◽  
Trend Detection ◽  
Growth Stages ◽  
Climate Risks ◽  
Mann Kendall Test ◽  
Rainy Days

The temperature and rainfall trends are analyzed for meteorological data of Anand in Gujarat, India over approximately last three decades stretching between years 1960 to 2014. The long–term change in temperature and rainfall has been assessed by linear trend analysis. Due to their biophysical characteristics, dry lands ecosystems are most Vulnerable the Climate risks. Climate variability has serious implications on major livelihoods of the region i.e. Agriculture and livestock. In this paper, attempts have been made to study variations in temperature and rainfall in Anand of Gujarat, India. Data at annual, seasonal and monthly time scales for the period of 1960-2014 (Temperature) and 1960-2014 (Rainfall) were examined. Study of monthly variations revealed rise in the temperatures in the month of September. Rainfall and Rainy days have also increased in past 4 decades. Annual and Monsoon rainfall have been observed to increase, where the month of August shows a statistically significant increasing trend. Any variability in monsoon season will have implications on agricultural activities as the season overlaps with Kharif, a major cropping season for the country. The variations of temperature and rainfall during monsoons may have impacts on the various growth stages of the crops. Changing weather conditions may lead to increase in pest infestations. Macro level studies may or may not be relevant at village level and therefore the advisories generated may not benefit the locals. Trends in temperature, rainfall and rainy days have been assessed by Non-parametric tests (Mann-Kendall or Pre Whitened Mann-Kendall test for trend detection and Theil and Sen's Slope for magnitude of trend). Temperature and Rainfall variations, Climate Change, Mann-Kendall Test.

scholarly journals Trend assessment in climate variable by Mann Kendall test of Bastar district of Chhattisgarh

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 79-82
Author(s):  
RAJESH KHAVSE ◽  
J.L. CHAUDHARY
Keyword(s):  
Linear Trend ◽  
Anthropogenic Activities ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Kendall Test ◽  
Atmospheric Temperature ◽  
Natural Phenomenon ◽  
Trend Test ◽  
Agricultural Planning ◽  
Rainy Days

Climate change is a natural phenomenon but in present decades its variability of change mainly due to anthropogenic activities is alarming. Agriculture of Chhattisgarh state is mainly dependant on monsoon rain and its distribution. Considering this fact, the present study  has been tried to analyze the most important climatic variables,              viz., precipitation and temeperature for analyzing their trend in the area. The trends of maximum atmospheric temperature, rainfall and rainy days are analysed statistically for meteorological data of Jagdalpur station of Bastar district, over last three decades stretching between years 1980 to 2014. The long term change in temperature, rainfall and rainy days has been analysed by correlation and linear trend analysis. The annual MMAX temperature has decreased at a rate of -0.465 °C per year during this period at Jagdalpur station and decreasing trend for rainy days during monsoonal season (June to September) is also found and is confirmed by Mann-Kendall trend test. Very weak increasing trend is observed in total month rainfall (TMRF) during season June to September. There are decreasing trends of mean monthly rainfall and south west (June - September) rainfall observed in Bastar district of Chhattisgarh. The agricultural planning and utilization of water is dependent on monsoon rainfall and more than 75% of rainfall occurring during the monsoon season is uneven both in time and space. Therefore its analysis is important for crop planning.  

scholarly journals Trend analysis of time series rainfall data using robust statistics

2017 ◽  
Vol 8 (4) ◽  
pp. 691-700 ◽  
Author(s):  
Arati Paul ◽  
Riddhidipa Bhowmik ◽  
V. M. Chowdary ◽  
Dibyendu Dutta ◽  
U. Sreedhar ◽  
...  
Keyword(s):  
Robust Regression ◽  
Robust Statistics ◽  
Monsoon Season ◽  
Kendall Test ◽  
Negative Trend ◽  
Positive Trend ◽  
Rainfall Analysis ◽  
Mann Kendall Test ◽  
Rainy Days ◽  
Non Parametric

Abstract A temporal rainfall analysis was carried out for the study area, Rajahmundry city located in lower Godavari basin, India, during the period 1960–2013. Both the parametric and non-parametric approaches were envisaged for identifying the trends at different temporal scales. Linear and robust regression analysis revealed a negative trend at weekly scale during monsoon months, but failed to signify the slope at 95% confidence level. The magnitude of Sen's slope was observed to be negative during the months of April–September. Results of the Mann–Kendall test ascertained the negative rainfall trends during the monsoon months of June and July with a significant trend at 95% confidence interval. Application of robust statistics for long-term rainfall analysis helped to address the outlier's problem in the dataset. The Mann–Kendall test rejected the null hypothesis for all months except February–May and August after exclusion of outliers. Overall, a negative trend during monsoon season and a positive trend during post-monsoon season were observed using a robust non-parametric approach. Further, good correlation was found between the total rainfall and rainy days during the study period. On average, 21.25% days of a year is considered as rainy, while heavy and extreme rainfall in this region together occupies nearly 15% of the rainy days.

scholarly journals STUDY OF GPM-IMERG RAINFALL DATA PRODUCT FOR GANGOTRI GLACIER

2018 ◽  
Vol XLII-5 ◽  
pp. 383-388
Author(s):  
P. Verma ◽  
S. K. Ghosh
Keyword(s):  
Field Data ◽  
Monsoon Season ◽  
Meteorological Data ◽  
Data Product ◽  
Precipitation Measurement ◽  
Post Monsoon Season ◽  
Gangotri Glacier ◽  
New Generation ◽  
Global Precipitation ◽  
Rainy Days

<p><strong>Abstract.</strong> This study presents a comparison of new generation weather observatory satellites Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) rainfall products with field data collected for Gangotri glacier in India. The meteorological analysis of rainfall estimates has been performed on GPM IMERG Final, Late and Early precipitation products available at daily scale with a spatial resolution of 0.1&amp;deg;<span class="thinspace"></span>&amp;times;<span class="thinspace"></span>0.1&amp;deg; for melting season from May to September for the year 2014 and 2015 respectively. The comparison of satellite products with field data was done using correlation coefficient and standard anomaly. The Late run curve showed a high degree of similarity with final run curve while early run showed variation from them. The satellite meteorological data correctly identified non-rainy days with an average of &amp;sim;86.7%, &amp;sim;67.5% and &amp;sim;95% for pre-monsoon, monsoon and post-monsoon season respectively. The rmse for final run data product for 2014 and 2015 are 4.5, 1.23, 1.55, 1.24, 0.8 and 1.14, 7.1, 1.82, 1.15, 1.52 from May to September respectively. Overall, it has been observed that for medium to heavy rainfall final run estimates are close to field data and for light to medium rainfall late run estimates are close. Similar results have been obtained from both datasets for non-rainy days in the study area.</p>

scholarly journals Association among Weather Conditions, Ambient Air Temperature, and Sedentary Time in Chinese Adults

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Xu Wen ◽  
Yiqun Ma ◽  
Bing Yuan ◽  
Fubaihui Wang
Keyword(s):  
Air Temperature ◽  
Sedentary Time ◽  
Meteorological Data ◽  
Weather Condition ◽  
Weather Conditions ◽  
Ambient Air ◽  
Chinese Adults ◽  
Ambient Air Temperature ◽  
Meteorological Observatory ◽  
Rainy Days

This study is aimed to quantify the association among weather conditions, ambient air temperature, and sedentary time in Chinese adults. The participants were 3,270 Chinese users of a wrist-worn activity tracker. Their daily activity data were collected using an algorithm based on raw data to determine the sedentary time. The data of ambient air temperature and weather were collected from the meteorological data released by China Central Meteorological Observatory. Two-level linear regression analyses showed that weather conditions had a significant influence on sedentary time in Chinese adults after adjustments for some covariates were made. When the weather condition changed from rainy days to sunny and cloudy days, sedentary time might decrease by about 6.89 and 5.60 min, respectively. In conclusion, weather conditions were independently associated with sedentary time in Chinese adults. The daily sedentary time was shorter on sunny and cloudy days than on rainy days.

scholarly journals Temporal Trend Analysis of Historical Climatic Data at Northeastern Hilly Region of Bangladesh Using Mann-Kendall Test

2020 ◽  
Vol 11 (2) ◽  
pp. 19-25
Author(s):  
KK Mondal ◽  
Md AE Akhter ◽  
MAK Mallik
Keyword(s):  
Temporal Trend ◽  
Monsoon Season ◽  
Kendall Test ◽  
Climatic Data ◽  
Total Rainfall ◽  
The North ◽  
Positive Tendency ◽  
Hilly Region ◽  
North Eastern ◽  
Mann Kendall Test

An attempt has been implemented to find out the temporal trend of climatic data of average temperature and total rainfall for the study period 1980-2016 at North-Eastern Hilly Region in Bangladesh. The non-parametric Mann-Kendall test is used to analyze the trend of climatic data. The objective of the study is to investigate the trend variation in the North-Eastern hilly region. Results show that in monsoon season, both Sylhet and Srimangal meteorological stations experience a positive tendency with a rate of 0.037 and 0.0170C/year, respectively which are statistically significant at 99.9% level of significance. Monthly significant positive changes are found in all months except November, December and January for Sylhet while Srimangal indicates significant positive changes except July, September, October and November. The total rainfall at both the stations reveals decreasing trend during maximum seasons and months but the trend is not significant. Journal of Engineering Science 11(2), 2020, 19-25

scholarly journals Analysis of rainfall trends over Tripura

MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 27-36
Author(s):  
RANJAN PHUKAN ◽  
D. SAHA
Keyword(s):  
Heavy Rainfall ◽  
Monsoon Season ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
The North ◽  
Rainfall Trends ◽  
Annual Scale ◽  
Increasing Trends ◽  
Rainy Days

Rainfall in India has very high temporal and spatial variability. The rainfall variability affects the livelihood and food habits of people from different regions. In this study, the rainfall trends in two stations in the north-eastern state of Tripura, namely Agartala and Kailashahar have been studied for the period 1955-2017. The state experiences an annual mean of more than 2000 mm of rainfall, out of which, about 60% occurs during the monsoon season and about 30% in pre-monsoon. An attempt has been made to analyze the trends in seasonal and annual rainfall, rainy days and heavy rainfall in the two stations, during the same period.Non-parametric Mann-Kendall test has been used to find out the significance of these trends. Both increasing and decreasing trends are observed over the two stations. Increasing trends in rainfall, rainy days and heavy rainfall are found at Agartala during pre-monsoon season and decreasing trends in all other seasons and at annual scale. At Kailashahar, rainfall amount (rainy days & heavy rainfall) is found to be increasing during pre-monsoon and monsoon seasons (pre-monsoon season). At annual scale also, rainfall and rainy days show increasing trends at Kailashahar. The parameters are showing decreasing trends during all other seasons at the station. Rainy days over Agartala show a significantly decreasing trend in monsoon, whereas no other trend is found to be significant over both the stations.  

scholarly journals Trend analysis of weather parameters over Indian Sundarbans

2021 ◽  
Vol 21 (3) ◽  
pp. 307-615
Author(s):  
UTTAM KUMAR MANDAL ◽  
DIBYENDU BIKAS NAYAK ◽  
SOURAV MULLICK ◽  
ARPAN SAMUI ◽  
AMIT KUMAR JANA ◽  
...  
Keyword(s):  
Monsoon Season ◽  
Temporal Trends ◽  
Kendall Test ◽  
Eastern Coast ◽  
Annual Rainfall ◽  
Crop Evapotranspiration ◽  
Indian Sundarbans ◽  
Sunshine Hours ◽  
Weather Parameters ◽  
Rainy Days

Sundarbans in West Bengal of India by virtue of its strategic location in the Eastern coast on the Bay of Bengal falls in one of the most vulnerable zones of abrupt climate change. Temporal trends of weather parameters of Canning Town (22o18'10.8'' N Latitude, 88o39'58.4'' E Longitude, elevation 3.52 m msl) representing Indian Sundarbans were analysed by non-parametric Mann-Kendall test and Sen's slope approaches. Analysis of long term rainfall data (1966-2015) indicated that Canning receives a mean annual rainfall of 1821 mm (±341.8 mm) with a considerable variation (CV = 18.8%). The results revealed that total annual rainfall trend decreased non-signicantly at the rate of 0.94 mm yr-1. On an average 84.4 rainy days in a year was recorded in the region, whereas during last ten years (2006-2015), the number of rainy days was reduced to 79.7 days yr-1. There was no signicant change in maximum, minimum and mean temperature of the region. Bright sunshine hours declined signicantly at an annual rate of 0.055 hr yr-1. Reference crop evapotranspiration (ET ) calculated using FAO Penman-Monteith method revealed that annual ET signicantly decreased at the rate of 5.98 mm yr-1. There was 2.7 times surplus rainfall than  crop evapotranspiration during monsoon months indicating very high scope of water harvesting to tackle water logging during the monsoon season and unavailability of fresh water for irrigation during lean season.

scholarly journals Trend Analysis of Precipitation and Temperature over Different Districts of Karnataka: An Aid to Climate Change Detection and Cropping System Option

2020 ◽  
pp. 15-25
Author(s):  
S. Sridhara ◽  
Pradeep Gopakkali ◽  
R. Nandini
Keyword(s):  
Minimum Temperature ◽  
Monsoon Season ◽  
Cropping System ◽  
Weather Conditions ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Land Preparation ◽  
Mk Test ◽  
Increasing Trend

Aims: To know the rainfall and temperature trend for all the districts of Karnataka state to develop suitable coping mechanisms for changing weather conditions during the cropping season. Study Design: The available daily data of rainfall (1971-2011) and minimum and maximum temperature (1971-2007) for each district was collected from NICRA-ICAR website. A non-parametric model such as the Mann-Kendall (MK) test complemented with Sen’s slope estimator was used to determine the magnitude of the trend. Place and Duration of Study: The rainfall data of 41 years (1971-2011) and temperature data of 37 years (1971-2007) was collected for all 27 districts of Karnataka. Methodology: Basic statistics related to rainfall like mean, standard deviation (SD), the coefficient of variation (CV) and the percentage contribution to annual rainfall were computed for monthly and season-wise. Mann-Kendall test was used to detect trend for rainfall as well as temperature. Results: An increasing trend in rainfall during winter, monsoon and annual basis for all most all the districts of Karnataka and decreasing trend of rainfall during pre and post-monsoon season was noticed. An early cessation of rainfall during September month in all most all the districts of Karnataka was observed. Similarly, monthly mean, maximum and the minimum temperature had shown an increasing trend over the past 37 years for all the districts of Karnataka. Conclusion: The more variation in rainfall during the pre-monsoon season was observed, which is more important for land preparation and other operations. The increasing trend of maximum and minimum temperature throughout the year may often cause a reduction in crop yield. It is necessary to change crops with its short duration varieties in order to avoid late season drought.

Sign in / Sign up

Export Citation Format

Share Document