Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 21 ◽  
Author(s):  
Mohan Chand ◽  
Bikas Bhattarai ◽  
Prashant Baral ◽  
Niraj Pradhananga
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Climate Data ◽  
Seasonal Trends

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin are analyzed. The elevation of these stations ranges from 460 to 3800 m asl. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods are applied to fill in the missing data. Annual as well as seasonal trends are analyzed and Mann-Kendall test is employed for testing the statistical significance of detected trend. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 ∘ C per year to 0.035 ∘ C per year with a mean increasing trend of 0.03 ∘ C per year after 1971. Seasonal trends show highest warming trends in monsoon season followed by winter, pre-monsoon, and post-monsoon season. However, difference in warming rates between different seasons isn’t sufficiently large. An average temperature lapse rate of −0.006 ∘ C per m with the steepest value (−0.0064 ∘ C per m) in pre-monsoon season and least negative (−0.0052 ∘ C per m) in winter season is observed for this basin. A comparative analysis of the gap-filled data with freely available global climate data sets shows reasonable correlation thus confirming the suitability of the gap filling methods.

Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (2) ◽  
pp. 38
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Prashant Baral ◽  
Niraj Shankar Pradhananga
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann-Kendall test was employed to test the statistical significance of detected trends. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 °C year−1 to 0.035 °C year−1 with a mean increasing trend of 0.03 °C year−1 after 1971. Seasonal trends show highest warming trends in the monsoon season followed by winter, pre-monsoon, and the post-monsoon season. However, difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 °C m−1 with the steepest value (−0.0064 °C m−1) in pre-monsoon season and least negative (−0.0052 °C m−1) in winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate datasets shows reasonable correlation thus confirming the suitability of the gap filling methods.

Trend Analysis of Temperature Data for Narayani River Basin, Nepal

Sci ◽  
2019 ◽  
Vol 1 (2) ◽  
pp. 49
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Niraj Shankar Pradhananga ◽  
Prashant Baral
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

Study of spatiotemporal dynamics of temperature is vital to assess changes in climate, especially in the Himalayan region where livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in Narayani river basin, a major river basin of Nepal characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann-Kendall test was employed to test the statistical significance of detected trends. Results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 ∘C year−1 to 0.035 ∘C year−1 with a mean increasing trend of 0.03 ∘C year−1 after 1971. Seasonal trends show highest warming trends in the monsoon season followed by winter, pre-monsoon, and the post-monsoon season. However, difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 ∘C m−1 with the steepest value (−0.0064 ∘C m−1) in pre-monsoon season and least negative (−0.0052 ∘C m−1) in winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate datasets show reasonable correlation thus confirming the suitability of the gap filling methods.

scholarly journals Trend Analysis of Temperature Data for the Narayani River Basin, Nepal

Sci ◽  
2020 ◽  
Vol 3 (1) ◽  
pp. 1
Author(s):  
Mohan Bahadur Chand ◽  
Bikas Chandra Bhattarai ◽  
Niraj Shankar Pradhananga ◽  
Prashant Baral
Keyword(s):  
Trend Analysis ◽  
River Basin ◽  
Global Climate ◽  
Monsoon Season ◽  
Statistical Significance ◽  
Winter Season ◽  
Temperature Data ◽  
Lapse Rate ◽  
Seasonal Trends ◽  
Temperature Lapse Rate

The study of spatiotemporal variation in temperature is vital to assess changes in climate, especially in the Himalayan region, where the livelihoods of billions of people living downstream depends on water coming from the melting of snow and glacier ice. To this end, temperature trend analysis is carried out in the Narayani River basin, a major river basin of Nepal, characterized by three climatic regions: tropical, subtropical and alpine. Temperature data from six stations located within the basin were analyzed. The elevation of these stations ranges from 460 to 3800 m a.s.l. and the time period of available temperature data ranges from 1960–2015. Multiple regression and empirical mode decomposition (EMD) methods were applied to fill in missing data and to detect trends. Annual as well as seasonal trends were analyzed and a Mann–Kendall test was employed to test the statistical significance of detected trends. The results indicate significant cooling trends before 1970s, and warming trends after 1970s in the majority of the stations. The warming trends range from 0.028 to 0.035 °C year−1 with a mean increasing trend of 0.03 °C year−1 after 1971. Seasonal trends show the highest warming trends in the monsoon season, followed by winter and the premonsoon and postmonsoon season. However, the difference in warming rates between different seasons was not significant. An average temperature lapse rate of −0.006 °C m−1 with the steepest value (−0.0064 °C m−1) in the premonsoon season and the least negative (−0.0052 °C m−1) in the winter season was observed for this basin. A comparative analysis of the gap-filled data with freely available global climate dataset show reasonable correlation, thus confirming the suitability of the gap filling methods.

scholarly journals Hydro-Climatic Variability in the Karnali River Basin of Nepal Himalaya

Climate ◽  
2016 ◽  
Vol 4 (2) ◽  
pp. 17 ◽  
Author(s):  
Kabi Khatiwada ◽  
Jeeban Panthi ◽  
Madan Shrestha ◽  
Santosh Nepal
Keyword(s):  
River Basin ◽  
River Discharge ◽  
Global Climate ◽  
Monsoon Season ◽  
Climatic Variability ◽  
Kendall Test ◽  
Temperature Trend ◽  
Maximum Temperature ◽  
Spatial And Temporal Variability ◽  
Climate Data

Global climate change has local implications. Focusing on datasets from the topographically-challenging Karnali river basin in Western Nepal, this research provides an overview of hydro-climatic parameters that have been observed during 1981–2012. The spatial and temporal variability of temperature and precipitation were analyzed in the basin considering the seven available climate stations and 20 precipitation stations distributed in the basin. The non-parametric Mann–Kendall test and Sen’s method were used to study the trends in climate data. Results show that the average precipitation in the basin is heterogeneous, and more of the stations trend are decreasing. The precipitation shows decreasing trend by 4.91 mm/year, i.e., around 10% on average. Though the increasing trends were observed in both minimum and maximum temperature, maximum temperature trend is higher than the minimum temperature and the maximum temperature trend during the pre-monsoon season is significantly higher (0.08 °C/year). River discharge and precipitation observations were analyzed to understand the rainfall-runoff relationship. The peak discharge (August) is found to be a month late than the peak precipitation (July) over the basin. Although the annual precipitation in most of the stations shows a decreasing trend, there is constant river discharge during the period 1981–2010.

scholarly journals Bulk Processing of Multi-Temporal Modis Data, Statistical Analyses and Machine Learning Algorithms to Understand Climate Variables in the Indian Himalayan Region

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7416
Author(s):  
Mohd Anul Haq ◽  
Prashant Baral ◽  
Shivaprakash Yaragal ◽  
Biswajeet Pradhan
Keyword(s):  
Machine Learning ◽  
Global Climate ◽  
Learning Algorithms ◽  
Remotely Sensed ◽  
Machine Learning Algorithms ◽  
Himalayan Region ◽  
Lapse Rate ◽  
Climate Data ◽  
Modis Data ◽  
Bulk Processing

Studies relating to trends of vegetation, snowfall and temperature in the north-western Himalayan region of India are generally focused on specific areas. Therefore, a proper understanding of regional changes in climate parameters over large time periods is generally absent, which increases the complexity of making appropriate conclusions related to climate change-induced effects in the Himalayan region. This study provides a broad overview of changes in patterns of vegetation, snow covers and temperature in Uttarakhand state of India through bulk processing of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) data, meteorological records and simulated global climate data. Additionally, regression using machine learning algorithms such as Support Vectors and Long Short-term Memory (LSTM) network is carried out to check the possibility of predicting these environmental variables. Results from 17 years of data show an increasing trend of snow-covered areas during pre-monsoon and decreasing vegetation covers during monsoon since 2001. Solar radiation and cloud cover largely control the lapse rate variations. Mean MODIS-derived land surface temperature (LST) observations are in close agreement with global climate data. Future studies focused on climate trends and environmental parameters in Uttarakhand could fairly rely upon the remotely sensed measurements and simulated climate data for the region.

scholarly journals Detection of annual and seasonal temperature variability and change using non-parametric test- A case study of Bundelkhand region of central India

2021 ◽  
Vol 23 (4) ◽  
pp. 402-408
Author(s):  
SUCHIT K. RAI ◽  
SUNIL KUMAR ◽  
MANOJ CHAUDHARY
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Monsoon Season ◽  
Economic Status ◽  
Winter Season ◽  
Central India ◽  
Warming Trend ◽  
Temperature Variability ◽  
Seasonal Temperature ◽  
Economic Activities

Consequences of global warming and climate change are major threat to humans and their socio-economic activities. Agriculture of Bundelkhand region is supposed to be more vulnerable due to emerging scenario of climate change and poor socio-economic status of farming community. Many studies carried out elsewhere have shown evidence of regional temperature variability along with global climate changes. This study focuses on the temporal variability and trend in annual and seasonal temperature (1901-2012) at six locations of Bundelkhand region. The results of the analysis reveal that the annual maximum (TMax) and minimum (TMin) temperature has significantly increasing trend in all the locations in the range of 0.5 to 2.0oC 100 year-1 and 0.5 to 1.1 oC 100 year-1, respectively. Seasonal analysis revealed warming trend in both TMax (0.6-2.6oC100 year-1) and TMin (0.9 to 2.3 oC 100 year-1) during post-monsoon and winter season in all the locations. Majority of the locations showed cooling trend (0.3-1.0 oC 100 year-1), in the mean maximum and minimum temperature during monsoon season except at two locations i.e Jhansi and Banda. However, a significant positive trends (2.9 oC) in the TMin was found for the period of hundred years at Banda district during monsoon season.

Climate Variability and Trend Analyses of Rainfall and Temperature Data of Imphal, Manipur

2021 ◽  
Vol 14 (11) ◽  
pp. 57-63
Author(s):  
Abujam Manglem Singh
Keyword(s):  
Climate Variability ◽  
Monsoon Season ◽  
Temperature Data ◽  
Climate Mitigation ◽  
Climate Data ◽  
Local Climate ◽  
Mitigation And Adaptation ◽  
Temperature Trends ◽  
Mean Temperature ◽  
Maximum Minimum

Understanding local climate variability and change is necessary for improving future climate forecasts and also aids preparation of informed area specific climate mitigation and adaptation strategies. Climate change at local scale is best revealed by studying observed variabilities and trends in rainfall and temperature data through statistical techniques. Therefore, this study employed standard deviation and coefficient of variability and Mann-Kendall test and Sen slope determination non-parametric techniques to perform variability and trends analyses across multiple temporal scales on climate data obtained at Imphal (Tulihal) station. The results indicate prevalence of different patterns between rainfall and temperature trends. Except for the positive trends in the month May (2mm/yr) and in the pre-monsoon season (9.49mm/yr), no other discernable patterns in rainfall data were observed. Temperature trends, on the other hand, witnessed significant positive increase in maximum, minimum and mean values. For mean temperature, all months registered significant increasing trends. At the annual and seasonal scales also, maximum, minimum and mean temperatures have increased although with varying rates. It is noteworthy to mention that temperature change has occurred at two distinct phases; before 1993 slow warming and after 1993 rapid warming. Temporal distribution of annual mean temperature captures this pattern more vividly as warming rate before 1993 was less than 0.01 compared to 0.450c/year in the latter phase. Overall, it can be said that rainfall has higher variability with very little or no pattern but temperature distribution suggests existence of strong trends in the observed data.

scholarly journals Evaluation of reanalysis and global meteorological products in Beas river basin of North-Western Himalaya

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Tanmoyee Bhattacharya ◽  
Deepak Khare ◽  
Manohar Arora
Keyword(s):  
River Basin ◽  
Meteorological Data ◽  
Western Himalaya ◽  
Temperature Data ◽  
Rainfall Pattern ◽  
Climate Data ◽  
Orographic Rainfall ◽  
Hydrology Model ◽  
North Western ◽  
Good Agreement

Abstract It is a great challenge to obtain reliable gridded meteorological data in some data-scarce and complex territories like the Himalaya region. Less dense observed raingauge data are unable to represent rainfall variability in the Beas river basin of North-Western Himalaya. In this study four reanalyses (MERRA, ERA-Interim, JRA-55 and CFSR) and one global meteorological forcing data WFDEI have been used to evaluate the potential of the products to represent orographic rainfall pattern of Beas river basin using hydrology model. The modeled climate data have compared with observed climate data for a long term basis. A comparison of various rainfall and temperature products helps to determine uniformity and disparity between various estimates. Results show that all temperature data have a good agreement with gridded observed data. ERA-Interim temperature data is better in terms of bias, RMSE (Root Mean Square Error), and correlation compared to other data. On the other hand, MERRA, ERA-Interim and JRA-55 models have overestimated rainfall values, but CFSR and WFDEI models have underestimated rainfall values to the measured values. Variable Infiltration Capacity (VIC), a macroscale distributed hydrology model has been successfully applied to indirectly estimate the performance of five gridded meteorological data to represent Beas river basin rainfall pattern. The simulation result of the VIC hydrology model forced by these data reveals that the discharge of ERA-Interim has a good agreement with observed streamflow. In contrast there is an overestimated streamflow observed for MERRA reanalysis estimate. JRA-55, WFDEI, and CFSR data underestimate the streamflow. The reanalysis products are also poor in capturing the seasonal hydrograph pattern. The ERA-Interim product better represents orographic rainfall for the Beas river basin. The reason may be the ERA-Interim uses a four-dimensional variational analysis model during assimilation. The major drawback of MERRA is the non-inclusion of observed precipitation data during assimilation and modeling error. The poor performance of JRA-55, CFSR and WFDEI is due to the gauge rainfall data assimilation error. This research finding will help for broader research on hydrology and meteorology of the Himalayan region.

scholarly journals Trend Analysis of Rainfall in Prakasam District of Andhra Pradesh State in India

2020 ◽  
pp. 103-110
Author(s):  
M. Satya Swarupa Rani ◽  
R. Asha ◽  
G. M. V. Prasadarao
Keyword(s):  
Trend Analysis ◽  
Crop Production ◽  
Monsoon Season ◽  
Winter Season ◽  
Vital Role ◽  
Precipitation Trend ◽  
Large Variability ◽  
Cropping Patterns ◽  
Climate Analysis

Globally, precipitation trend analysis in different space and time has great impact on crop-planning activities. To get accurate unbiased results a long-term climate analysis of a particular area required in large variability in both spatially, temporally. For sustainable crop production long term weather analysis act as vital role in alternation of existing cropping patterns. This study aimed at analysing the trend of rainfall events in Prakasam district of Andhra state of India the data consists of annual precipitation time series from 1991-2019. Initially study concerns with analysis of data base using descriptive statistics, later trend change was detected by using non parametric tests. The results indicate an increased trend in June and monsoon season, with a decreased trend in July and winter season at 5% level of significance.

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