Analysis of Meteorological Elements Variations of Chongqing over the Past 60 Years

2014 ◽  
Vol 501-504 ◽  
pp. 2016-2019
Author(s):  
Xun Jian Long ◽  
Chun Min Zhang ◽  
Tao Hong Yang ◽  
Yu Lin Huang
Keyword(s):  
Wind Speed ◽  
Sunshine Duration ◽  
Kendall Test ◽  
Trend Detection ◽  
Annual Data ◽  
Annual Variations ◽  
Mann Kendall Test ◽  
Mean Wind Speed ◽  
Meteorological Elements ◽  
Non Parametric

The power of a test is the probability that it cannot reject a null hypothesis when it is true. With interchangeably of non-parametric Mann-Kendall test, practical application is used in meteorological elements analysis. In this study, trend detection of meteorological elements data of Shapingba district in Chongqing, during 1951 to 2011, was estimated by non-parametric Mann-Kendall test. The analyzed elements are composed by mean precipitation, annual sunshine hours, annual humidity, annual mean temperature and annual mean wind speed. And the results show that inter-annual variations of precipitation and mean annual relative humidity are not significant. However, inter-annual variation of sunshine duration is significantly reduced, while inter-annual temperature and wind speed are significantly increased. At the same time, the non-parametric Mann-Kendall test also detects the trend on seasonal data. It is different from the annual data, and trends in different seasons show markedly different.

scholarly journals Searching evidence for the existence of evaporation paradox in arid environments of northwest India

2014 ◽  
Vol 17 (1) ◽  
pp. 3-11 ◽  
Keyword(s):  
Wind Speed ◽  
Sunshine Duration ◽  
Monsoon Season ◽  
Kendall Test ◽  
Arid Environments ◽  
Thar Desert ◽  
Pan Evaporation ◽  
Sunshine Hours ◽  
Northwest India ◽  
Increasing Trends

<div> <p>Trends in pan evaporation (E<sub>pan</sub>) and temperature were identified through the Mann-Kendall test over Jaisalmer to probe the existence of evaporation paradox in arid environments of Thar Desert, northwest India. We also analyzed trends in rainfall, relative humidity, wind speed, and sunshine duration in the context of climate change. Decreasing trends in E<sub>pan </sub>were witnessed over Jaisalmer in the months of January, June, October and November in the range of -2.04 to -4.1 mm/year. Significant rainfall decreases were witnessed in the three crucial months of monsoon season, i.e., July, August and September, in range of -0.23 to -1.25 mm/year. Increasing trends in mean temperature were witnessed corresponding to annual and monthly (January, April, September, October and November) time scales in the range of 0.03 to 0.07 &deg;C/year. The simultaneous E<sub>pan </sub>decrease and temperature rise at Jaisalmer confirmed the existence of evaporation paradox in the months of winter and post-monsoon seasons, which may be due to decreases in wind speed and bright sunshine hours. The increase in temperature along with decreases in E<sub>pan</sub>, rainfall, sunshine duration, and wind speed over Jaisalmer may have far reaching consequences for the fragile ecosystem of the Thar Desert.</p> </div> <p>&nbsp;</p>

scholarly journals Future scenarios of thermal bioclimatic conditions in a humid tropical city under urban development

2018 ◽  
Vol 13 (5) ◽  
pp. 1
Author(s):  
Vicente De Paulo Rodrigues da Silva ◽  
Joel Silva Santos ◽  
Eduardo Rodrigues Viana de Lima ◽  
Romildo Morant de Holanda ◽  
Enio Pereira de Sousa ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Air Temperature ◽  
Urban Areas ◽  
Kendall Test ◽  
Future Scenarios ◽  
Rapid Urbanization ◽  
Mann Kendall Test ◽  
Bioclimatic Conditions ◽  
The City

Urbanization modifies the heat balance in urban areas and has negative effects on landscape, aesthetics, energy efficiency, human health and the inhabitants’ quality of life. This work evaluated future scenarios of bioclimatic conditions for João Pessoa, a humid tropical city in Northeast Brazil. The scenarios were determined based on trends in air temperature, relative humidity and wind speed for the time period from 1968 to 2015. The study was performed for two distinct periods of three months each (dry and wet seasons) using data from weather stations equipped with thermo-hygrometers and cup anemometers located in nine representative areas of the city. Trends in air temperature, relative humidity, wind speed, and effective temperature index (ET index) time series were evaluated using the Mann-Kendall test. Results indicated that the air temperature showed an increasing trend of 0.34°C/decade, whereas the relative humidity showed a decreasing trend of 0.49%/decade and the wind speed values ranged from 1.3 ms-1 to 3.80 ms-1. These trends are statistically significant according to the Mann-Kendall test (p<0.05). The air temperature increased between the 1980s and 2010s, which corresponds to a period of rapid urbanization of the city. Future environmental conditions in João Pessoa will be determined in accordance with the urbanization processes.

scholarly journals Fitting and testing the significance of linear trends in Gumbel-distributed data

2002 ◽  
Vol 6 (1) ◽  
pp. 17-24 ◽  
Author(s):  
R. T. Clarke
Keyword(s):  
Maximum Likelihood ◽  
Linear Regression ◽  
Gumbel Distribution ◽  
Kendall Test ◽  
Mean Value ◽  
Return Periods ◽  
Testing Procedures ◽  
Mann Kendall Test ◽  
Linear Trends ◽  
Non Parametric

Abstract. The widely-used hydrological procedures for calculating events with T-year return periods from data that follow a Gumbel distribution assume that the data sequence from which the Gumbel distribution is fitted remains stationary in time. If non-stationarity is suspected, whether as a consequence of changes in land-use practices or climate, it is common practice to test the significance of trend by either of two methods: linear regression, which assumes that data in the record have a Normal distribution with mean value that possibly varies with time; or a non-parametric test such as that of Mann-Kendall, which makes no assumption about the distribution of the data. Thus, the hypothesis that the data are Gumbel-distributed is temporarily abandoned while testing for trend, but is re-adopted if the trend proves to be not significant, when events with T-year return periods are then calculated. This is illogical. The paper describes an alternative model in which the Gumbel distribution has a (possibly) time-variant mean, the time-trend in mean value being determined, for the present purpose, by a single parameter β estimated by Maximum Likelihood (ML). The large-sample variance of the ML estimate ˆβMR is compared with the variance of the trend βLR calculated by linear regression; the latter is found to be 64% greater. Simulated samples from a standard Gumbel distribution were given superimposed linear trends of different magnitudes, and the power of each of three trend-testing procedures (Maximum Likelihood, Linear Regression, and the non-parametric Mann-Kendall test) were compared. The ML test was always more powerful than either the Linear Regression or Mann-Kendall test, whatever the (positive) value of the trend β; the power of the MK test was always least, for all values of β. Keywords: Extreme value probability distribution, Gumbel distribution, statistical stationarity, trend-testing procedures

scholarly journals GIS TECHNIQUES FOR MAPPING OF WIND SPEED OVER IRAQ

2019 ◽  
Vol 50 (6) ◽  
Author(s):  
Adeeb & Al-Timimi
Keyword(s):  
Wind Speed ◽  
Kendall Test ◽  
Northern Region ◽  
Annual Average ◽  
Wind Speeds ◽  
Gis Techniques ◽  
Mean Wind Speed ◽  
Seasonal Wind ◽  
Autumn And Winter ◽  
Climate Studies

This study was aimed to use GIS techniques in climate studies. Analysis of monthly wind speed data for the period 1981 to 2017, and mapping of monthly, seasonal and annual wind speed in Iraq has been investigated in this study. The area of study was divided into three regions. the results of  Mann Kendall test of the middle and southern region reveal a significant decreasing trend in the months of the summer season. While positive trends of mean wind speed were found in the northern region for the whole period. Wind speed value reaches its highest value in (Jun and July), and the lowest value of wind speed was in December.  Seasonal wind speeds show the highest values recorded in the summer and spring seasons and the lowest in the autumn and winter seasons. Wind speed maps were obtained using IDW techniques in G I S, the results show that the annual average of wind speed in the northern, middle and southern regions was 2.7 m/s, 3.6 m/s and 4.1 m/s respectively. While the annual average of wind speed in the study area "Iraq" was 3.6 m/s. The winds were low in the northern region compared to the middle and southern regions. The wind speed maps show the appropriate sites for the installation of wind turbines.

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.

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