THE Maximum, Minimum, and Mean Temperature of the Air in the Shade, and the Maximum, Minimum, and Mean Height of the Barometer

2014 ◽  
pp. 295-311
Author(s):  
Alexander Fisher
Keyword(s):  
Mean Temperature ◽  
Maximum Minimum

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 The Use of Bias-Corrected CMIP5 GCM Data to Analyse Temperature Variation in Puthimari River Basin- A Transnational Sub- Basin between Bhutan and India

2021 ◽  
Vol 9 (2) ◽  
pp. 132-139
Keyword(s):  
Global Warming ◽  
Temperature Variation ◽  
River Basin ◽  
Linear Trend ◽  
Historical Period ◽  
Eastern Region ◽  
Mean Temperature ◽  
North Eastern ◽  
Linear Trend Analysis ◽  
Maximum Minimum

Using fivedifferent CMIP5 climate modelsunder the scenarios of RCP4.5 and RCP8.5, we analysedmaximum, minimum and mean temperature over Puthimari river basin, that covers parts of Bhutan and North-eastern region of India. Historical period from 1970-2005 and future three periods,2025-49, 2050-74 and 2075-99 were considered to understand the effect of global warming in the basin. Monthly Maximum, minimum and mean temperature variationsanalysis showed increase in temperature from 1970 to 2099for all the models under both the scenarios. The study indicates that the averagemaximum, minimum and mean temperatureover the basinwill rise by 1.13-2.49°C, 1.3-2.64°Cand 1.21-2.6°Crespectivelyfrom in 2075-99 compared to the historical period under RCP 4.5. Again, these temperatureswill increase by 2.68-3.89°C, 2.85-4.74°Cand 2.76-4.53°Cunder RCP8.5 towards the end of the century. The linear trend analysis of maximum, minimum and mean temperature indicates rising trends in futureover the basin.

Simulation of continuous random process according to the specified sequence of extremes

2020 ◽  
Vol 86 (7) ◽  
pp. 65-71
Author(s):  
I. V. Gadolina ◽  
R. I. Zainetdinov ◽  
T. P. Gryzlova ◽  
I. M. Petrova
Keyword(s):  
Spectral Density ◽  
Random Process ◽  
Continuous Process ◽  
Continuous Processes ◽  
Regression Formula ◽  
Bending Stresses ◽  
Development And Validation ◽  
Irregular Loading ◽  
Cosine Functions ◽  
Maximum Minimum

A method has been developed for converting a discrete sequence of extrema into a continuous process. The relevancy of the problem is attributed to the necessity of an approximate estimation of spectral density in in testing materials and structures under random (irregular) loading. A great bulk of available experimental data thus can be used in development and validation of calculation methods for assessing durability in the multi-cycle region. Postulating the continuity of random stress processes and their first derivative we propose to connect piecewise the available starting points (namely, the extrema of the random process) with half-cosine functions under the condition of compatibility at the points of extrema. A distinctive feature of the method is the provision of 100% coincidence of the values and sequences of extrema in the initial discrete and simulated continuous processes. The issue of choosing the magnitude of half-periods for these half-cosine functions is addressed on the basis of information obtained from the analysis of real stress records in the form of a regression equation linking half-periods and half-ranges for some realizations of the random process for transport vehicles. The regression dependences of the half-periods and semi-ranges of bending stresses (part of a railway train) and torsion (torsion shaft of a tracked vehicle) are shown as an example. An analysis of the correlation of two random variables (half-periods and half-ranges) according to empirical data has shown that the correlation exists and is significant for the observed number of points thus providing the basis for using the regression formula for an approximate choice of the frequency composition of the process. Moreover, the lower restrictions are imposed on the number of points (at least 5) in the half-period. Since the extrema of the initial and simulated processes coincide in accordance with the principle of the proposed simulation, the distribution of the amplitudes of complete cycles, as well as the results of schematization by other known methods are identical, therefore, the estimate of the durability by hypotheses based on a linear one is also identical. The validation of the method consists in consideration of the chain: 1) the initial continuous process; 2) the discrete process of extrema; 3) simulated continuous process according to the proposed method. Auxiliary distributions, such as distributions of maximum, minimum and average cycle values also coincide in accordance with the principle of modeling. The method is proposed to be used in analysis of the comparability of two competing approaches in assessing the loading in the problems of assessing durability, namely: those that use cycle-counting methods and methods based on the spectral density of processes. Since the spectral densities of the processes can differ due to an approximate choice of the frequencies on the basis of a regression formula, methods on their base can give estimates of the durability that differ from those obtained by schematization methods. To study this phenomenon, further computational experiments are required. The developed method can be very useful for the experiment design.

A Defense Mechanism Based on Improved Allocation Strategy of VMs Co-Resident Attack in Power Cloud Platform

2020 ◽  
Vol 13 ◽  
Author(s):  
Yuancheng Li ◽  
Pan Zhang ◽  
Daoxing Li ◽  
Jing Zeng
Keyword(s):  
Virtual Machine ◽  
Simulation Experiment ◽  
Virtual Machines ◽  
Defense Mechanism ◽  
Security Threats ◽  
Allocation Strategy ◽  
Cloud Platform ◽  
Deployment Strategy ◽  
Dbscan Algorithm ◽  
Maximum Minimum

Background: Cloud platform is widely used in electric power field. Virtual machine co-resident attack is one of the major security threats to the existing power cloud platform. Objective: This paper proposes a mechanism to defend virtual machine co-resident attack on power cloud platform. Method: Our defense mechanism uses the DBSCAN algorithm to classify and output the classification results through the random forest and uses improved virtual machine deployment strategy which combines the advantages of random round robin strategy and maximum/minimum resource strategy to deploy virtual machines. Results: we made a simulation experiment on power cloud platform of State Grid and verified the effectiveness of proposed defense deployment strategy. Conclusion: After the virtual machine deployment strategy is improved, the coverage of the virtual machine is remarkably reduced which proves that our defense mechanism achieves some effect of defending the virtual machine from virtual machine co-resident attack.

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