The identification method revealed asymmetric wavelets of dynamics, as fractal quanta of the behavior of the surface air layer at a height of 2 m, according to the average monthly temperature at four weather stations ...The identification method revealed asymmetric wavelets of dynamics, as fractal quanta of the behavior of the surface air layer at a height of 2 m, according to the average monthly temperature at four weather stations in India (Srinagar, Jolhpur, New Delhi and Guvahati). For Srinagar station, the maximum for all years is observed in July, for Jolhpur and New Delhi stations it shifts to June, and for Guvahati it shifts to August. With a high correlation coefficient of 0.9659, 0.8640 and 0.8687, a three-factor model of the form was obtained. The altitude, longitude and latitude of the station are given sequentially. The hottest month for Srinagar over a period of 130 years is in July. At the same time, the temperature increased from 23.4 °C to 24.2 °C (by 3.31%). A noticeable decrease in the intensity of heat flows in June occurred at Jolhpur (over 125 years, a decrease from 36.2 °C to 33.3 °C, or by 8.71%) and New Delhi (over 90 years, a decrease from 35.1 °C to 32.4 °C, or by 7.69%). For almost 120 years, Guvahati has experienced complex climate changes: In 1902, the hottest month was July, but in 2021 it has shifted to August. The increase in temperature at various stations is considered. At Srinagar station in 2021, compared to 1892, temperatures increased in June, September and October. Guvahati has a 120-year increase in December, January, March and April. Temperatures have risen in February, March and April at Jolhpur in 125 years, but have risen in February and March at New Delhi Station in 90 years. Despite the presence of tropical evergreen forests, the area around Guvahati Station is expected to experience strong warming.展开更多
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 th...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℃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 the influence of vegetation cover.The warming level of 2010 will repeat again in 2035-2040.From 2040 the temperature will rise steadily.June is the hottest month.At the same time,the maximum temperature of 35.1℃in 2010 in June will again reach by 2076.But according to the second component of the heat wave,the temperature will rise from 0.54℃to 16.29°C.The annual and semi-annual cycles had an insignificant effect on the June temperature dynamics.Thus,the identification method on the example of meteorological observations in New Delhi made it possible to obtain summary models containing a different number of components.The temperature at a height of 2 m is insufficient.On the surface,according to space measurements,the temperature reaches 55°C.As a result,in order to identify more accurate asymmetric wavelets for forecasting,the results of satellite measurements of the surface temperature of India at various geographical locations of meteorological stations are additionally required.展开更多
文摘The identification method revealed asymmetric wavelets of dynamics, as fractal quanta of the behavior of the surface air layer at a height of 2 m, according to the average monthly temperature at four weather stations in India (Srinagar, Jolhpur, New Delhi and Guvahati). For Srinagar station, the maximum for all years is observed in July, for Jolhpur and New Delhi stations it shifts to June, and for Guvahati it shifts to August. With a high correlation coefficient of 0.9659, 0.8640 and 0.8687, a three-factor model of the form was obtained. The altitude, longitude and latitude of the station are given sequentially. The hottest month for Srinagar over a period of 130 years is in July. At the same time, the temperature increased from 23.4 °C to 24.2 °C (by 3.31%). A noticeable decrease in the intensity of heat flows in June occurred at Jolhpur (over 125 years, a decrease from 36.2 °C to 33.3 °C, or by 8.71%) and New Delhi (over 90 years, a decrease from 35.1 °C to 32.4 °C, or by 7.69%). For almost 120 years, Guvahati has experienced complex climate changes: In 1902, the hottest month was July, but in 2021 it has shifted to August. The increase in temperature at various stations is considered. At Srinagar station in 2021, compared to 1892, temperatures increased in June, September and October. Guvahati has a 120-year increase in December, January, March and April. Temperatures have risen in February, March and April at Jolhpur in 125 years, but have risen in February and March at New Delhi Station in 90 years. Despite the presence of tropical evergreen forests, the area around Guvahati Station is expected to experience strong warming.
文摘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℃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 the influence of vegetation cover.The warming level of 2010 will repeat again in 2035-2040.From 2040 the temperature will rise steadily.June is the hottest month.At the same time,the maximum temperature of 35.1℃in 2010 in June will again reach by 2076.But according to the second component of the heat wave,the temperature will rise from 0.54℃to 16.29°C.The annual and semi-annual cycles had an insignificant effect on the June temperature dynamics.Thus,the identification method on the example of meteorological observations in New Delhi made it possible to obtain summary models containing a different number of components.The temperature at a height of 2 m is insufficient.On the surface,according to space measurements,the temperature reaches 55°C.As a result,in order to identify more accurate asymmetric wavelets for forecasting,the results of satellite measurements of the surface temperature of India at various geographical locations of meteorological stations are additionally required.
