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Wavelet Analysis of Average Monthly Temperature New Delhi 1931- 2021 and Forecast until 2110 DOI:  https://doi.org/10.30564/jasr.v6i2.5447 Abstract The identification method in the CurveExpert-1.40 software environment revealed asymmetric wavelets of changes in the average monthly temperature of New Delhi from 1931 to 2021. The maximum increment for 80 years of the average monthly temperature of 5.1°C was in March 2010. An analysis of the wave patterns of the dynamics of the average monthly temperature up to 2110 was carried out. For forecasting, formulas were adopted containing four components, among which the second component is the critical heat wave of India. The first component is the Mandelbrot law (in physics). It shows the natural trend of decreasing temperature. The second component increases according to the critical law. The third component with a correlation coefficient of 0.9522 has an annual fluctuation cycle. The fourth component with a semi-annual cycle shows t...

Wavelet Analysis of Average Monthly Temperature New Delhi 1931- 2021 and Forecast until 2110 DOI:  https://doi.org/10.30564/jasr.v6i2.5447 Abstract The identification method in the CurveExpert-1.40 software environment revealed asymmetric wavelets of changes in the average monthly temperature of New Delhi from 1931 to 2021. The maximum increment for 80 years of the average monthly temperature of 5.1°C was in March 2010. An analysis of the wave patterns of the dynamics of the average monthly temperature up to 2110 was carried out. For forecasting, formulas were adopted containing four components, among which the second component is the critical heat wave of India. The first component is the Mandelbrot law (in physics). It shows the natural trend of decreasing temperature. The second component increases according to the critical law. The third component with a correlation coefficient of 0.9522 has an annual fluctuation cycle. The fourth component with a semi-annual cycle shows t...

Wave Dynamics of the Average Annual Temperature Surface Air Layer New Delhi for 1931-2021 DOI:  https://doi.org/10.30564/jasr.v5i2.4639 Abstract The identification method revealed asymmetric fluctuations in the dynamics of the average annual temperature in New Delhi from 1931 to 2021, that is, for 90 years. An analysis of the wave patterns of climate until 2110 was carried out. Geotechnology of the Himalayan passage was proposed to reduce heat waves in India and China. Formulas containing four and 18 fluctuations were adopted for forecasting. Models give an increase in the heat wave from 2021, which is the fourth component. As a result, the landscape of the Himalayan mountains and the deserts of Thar and Takla Makan create a regional climate system that is original for the land of the Earth. In this system, oscillatory temperature adaptation in the future will be several times greater than the global warming rate predicted in the IPCC CMIP5 report. Between 2001 and 2019 the largest...

Wave Dynamics of the Average Annual Temperature Surface Air Layer New Delhi for 1931-2021 Abstract The identification method revealed asymmetric fluctuations in the dynamics of the average annual temperature in New Delhi from 1931 to 2021, that is, for 90 years. An analysis of the wave patterns of climate until 2110 was carried out. Geotechnology of the Himalayan passage was proposed to reduce heat waves in India and China. Formulas containing four and 18 fluctuations were adopted for forecasting. Models give an increase in the heat wave from 2021, which is the fourth component. As a result, the landscape of the Himalayan mountains and the deserts of Thar and Takla Makan create a regional climate system that is original for the land of the Earth. In this system, oscillatory temperature adaptation in the future will be several times greater than the global warming rate predicted in the IPCC CMIP5 report. Between 2001 and 2019 the largest temperature increase wave maximum was observed in...