Precipitation and temperature changes in eastern India by multiple trend detection methods

2016 ◽  
Vol 180 ◽  
pp. 211-225 ◽  
Author(s):  
Chandra Shekhar Sharma ◽  
Sudhindra N. Panda ◽  
Rudra P. Pradhan ◽  
Amanpreet Singh ◽  
Akira Kawamura
Keyword(s):  
Trend Detection ◽  
Detection Methods ◽  
Eastern India ◽  
Temperature Changes ◽  
Precipitation And Temperature

scholarly journals Analysis of the Recent Trends of Two Climate Parameters over Two Eco-Regions of Ethiopia

Water ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 161 ◽  
Author(s):  
Mohammed Gedefaw ◽  
Denghua Yan ◽  
Hao Wang ◽  
Tianling Qin ◽  
Kun Wang
Keyword(s):  
Meteorological Data ◽  
Decision Makers ◽  
Trend Detection ◽  
Bahir Dar ◽  
Temperature Changes ◽  
Temperature Trends ◽  
Increasing Trend ◽  
Recent Trends ◽  
Slope Estimator ◽  
Precipitation And Temperature

The changes in climatic variables in Ethiopia are not entirely understood. This paper investigated the recent trends of precipitation and temperature on two eco-regions of Ethiopia. This study used the observed historical meteorological data from 1980 to 2016 to analyze the trends. Trend detection was done by using the non-parametric Mann-Kendall (MK), Sen’s slope estimator test, and Innovative Trend Analysis Method (ITAM). The results showed that a significant increasing trend was observed in the Gondar, Bahir Dar, Gewane, Dembi-Dolo, and Negele stations. However, a slightly decreasing trend was observed in the Sekoru, Degahabur, and Maichew stations regarding precipitation trends. As far as the trend of temperature was concerned, an increasing trend was detected in the Gondar, Bahir Dar, Gewane, Degahabur, Negele, Dembi-Dolo, and Maichew stations. However, the temperature trend in Sekoru station showed a sharp decreasing trend. The effects of precipitation and temperature changes on water resources are significant after 1998. The consistency in the precipitation and temperature trends over the two eco-regions confirms the robustness of the changes. The findings of this study will serve as a reference for climate researchers, policy and decision makers.

scholarly journals Effect of Climate Change on Soil Erosion in a Mountainous Mediterranean Catchment (Central Pindus, Greece)

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1469 ◽  
Author(s):  
Stefanos Stefanidis ◽  
Dimitrios Stathis
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Potential Model ◽  
Climate Model ◽  
Regional Climate ◽  
Baseline Period ◽  
Mean Annual Temperature ◽  
Temperature Changes ◽  
Mountainous Catchment ◽  
Precipitation And Temperature

The aim of this study was to assess soil erosion changes in the mountainous catchment of the Portaikos torrent (Central Greece) under climate change. To this end, precipitation and temperature data were derived from a high-resolution (25 × 25 km) RegCM3 regional climate model for the baseline period 1974–2000 and future period 2074–2100. Additionally, three GIS layers were generated regarding land cover, geology, and slopes in the study area, whereas erosion state was recognized after field observations. Subsequently, the erosion potential model (EPM) was applied to quantify the effects of precipitation and temperature changes on soil erosion. The results showed a decrease (−21.2%) in annual precipitation (mm) and increase (+3.6 °C) in mean annual temperature until the end of the 21st century, and the above changes are likely to lead to a small decrease (−4.9%) in soil erosion potential.

scholarly journals Assessing runoff sensitivities to precipitation and temperature changes under global climate-change scenarios

2018 ◽  
Vol 50 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Lei Chen ◽  
Jianxia Chang ◽  
Yimin Wang ◽  
Yuelu Zhu
Keyword(s):  
Climate Change ◽  
Minimum Temperature ◽  
Yellow River ◽  
Control Variable ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Temperature Changes ◽  
Runoff Change ◽  
Precipitation And Temperature

Abstract An accurate grasp of the influence of precipitation and temperature changes on the variation in both the magnitude and temporal patterns of runoff is crucial to the prevention of floods and droughts. However, there is a general lack of understanding of the ways in which runoff sensitivities to precipitation and temperature changes are associated with the CMIP5 scenarios. This paper investigates the hydrological response to future climate change under CMIP5 RCP scenarios by using the Variable Infiltration Capacity (VIC) model and then quantitatively assesses runoff sensitivities to precipitation and temperature changes under different scenarios by using a set of simulations with the control variable method. The source region of the Yellow River (SRYR) is an ideal area to study this problem. The results demonstrated that the precipitation effect was the dominant element influencing runoff change (the degree of influence approaching 23%), followed by maximum temperature (approaching 12%). The weakest element was minimum temperature (approaching 3%), despite the fact that the increases in minimum temperature were higher than the increases in maximum temperature. The results also indicated that the degree of runoff sensitivity to precipitation and temperature changes was subject to changing external climatic conditions.

scholarly journals Trend detection of atmospheric time series

Elem Sci Anth ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Kai-Lan Chang ◽  
Martin G. Schultz ◽  
Xin Lan ◽  
Audra McClure-Begley ◽  
Irina Petropavlovskikh ◽  
...  
Keyword(s):  
Time Series ◽  
Atmospheric Chemistry ◽  
Surface Ozone ◽  
High Surface ◽  
Effective Means ◽  
Environmental Data ◽  
Model Specification ◽  
Trend Detection ◽  
Detection Methods ◽  
Sources Of Uncertainty

This paper is aimed at atmospheric scientists without formal training in statistical theory. Its goal is to (1) provide a critical review of the rationale for trend analysis of the time series typically encountered in the field of atmospheric chemistry, (2) describe a range of trend-detection methods, and (3) demonstrate effective means of conveying the results to a general audience. Trend detections in atmospheric chemical composition data are often challenged by a variety of sources of uncertainty, which often behave differently to other environmental phenomena such as temperature, precipitation rate, or stream flow, and may require specific methods depending on the science questions to be addressed. Some sources of uncertainty can be explicitly included in the model specification, such as autocorrelation and seasonality, but some inherent uncertainties are difficult to quantify, such as data heterogeneity and measurement uncertainty due to the combined effect of short and long term natural variability, instrumental stability, and aggregation of data from sparse sampling frequency. Failure to account for these uncertainties might result in an inappropriate inference of the trends and their estimation errors. On the other hand, the variation in extreme events might be interesting for different scientific questions, for example, the frequency of extremely high surface ozone events and their relevance to human health. In this study we aim to (1) review trend detection methods for addressing different levels of data complexity in different chemical species, (2) demonstrate that the incorporation of scientifically interpretable covariates can outperform pure numerical curve fitting techniques in terms of uncertainty reduction and improved predictability, (3) illustrate the study of trends based on extreme quantiles that can provide insight beyond standard mean or median based trend estimates, and (4) present an advanced method of quantifying regional trends based on the inter-site correlations of multisite data. All demonstrations are based on time series of observed trace gases relevant to atmospheric chemistry, but the methods can be applied to other environmental data sets.

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