It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the sol...It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the solar dynamo of simulation and space mission planning. In this paper, we employ the long-shortterm memory(LSTM) and neural network autoregression(NNAR) deep learning methods to predict the upcoming 25 th solar cycle using the sunspot area(SSA) data during the period of May 1874 to December2020. Our results show that the 25 th solar cycle will be 55% stronger than Solar Cycle 24 with a maximum sunspot area of 3115±401 and the cycle reaching its peak in October 2022 by using the LSTM method. It also shows that deep learning algorithms perform better than the other commonly used methods and have high application value.展开更多
In the present work,we study the time evolution,significance of the N-S asymmetry excesses presented as a function of the solar cycle and prominent rotational periods(~27 d)separately for the northern and southern hem...In the present work,we study the time evolution,significance of the N-S asymmetry excesses presented as a function of the solar cycle and prominent rotational periods(~27 d)separately for the northern and southern hemispheres.We have investigated short-term variations of the hemispheric solar activity(sunspot numbers and sunspot areas)during the time period 2010-2015,which covers the ascending and the maximum phase of solar cycle 24.We have implemented the Lomb-Scargle periodogram and continuous wavelet transform power spectrum techniques to study the time evolution and dominant rotational periods separately for the northern and southern hemispheres,and whole solar disk.Our results showed that the northern hemisphere exhibited longer solar synodic periods than the southern hemisphere,indicating that the northern hemisphere has a lower rotation rate.Moreover,the northern hemisphere was found to be dominant before transferring to the southern hemisphere during mid-2013.Also,the sunspot areas clearly demonstrated a two-peak structure of solar activity in the northern and southern hemispheres respectively during 2012 and 2014.The statistical significance of the southern hemisphere affirmed enhanced excess during the maximum phase of solar cycle 24.展开更多
The correlation of the Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), Pacific North American Oscillation (PNA), Arctic Oscillation (AO), and Scandinavia (SCAND) indices with winter (DJF) temperat...The correlation of the Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), Pacific North American Oscillation (PNA), Arctic Oscillation (AO), and Scandinavia (SCAND) indices with winter (DJF) temperature and precipitation for the period of 1943 to 2011 was analyzed to study climate change and variability of Yellowknife, NWT. SOI correlated negatively with both temperature (r = -0.14) and precipitation (r = -0.06) causing colder, drier conditions during La Nina and warmer, wetter conditions during El Nino. PDO was shown to have a strong positive correlation with both temperature (r = 0.60) and precipitation (r = 0.33) causing warmer, wetter weather in the positive phase and colder, drier weather in the negative phase. PNA showed the strongest positive correlation for both temperature (r = 0.69) and precipitation (r = 0.37) causing very warm and wet conditions in the positive phase and very cold and dry conditions during the negative phase. AO correlated negatively with temperature (r = -0.04) and positively with precipitation (r = 0.24) causing colder, wetter conditions in the positive phase and warmer, drier conditions in the negative phase. Finally SCAND was shown to have a weak negative correlation with both temperature (r = -0.10) and precipitation (r = -0.18). Sunspot area showed a strong negative correlation (r = -0.30) with temperature and a very weak positive correlation (r = 0.07) with total annual precipitation. Yellowknife’s average annual temperature and precipitation has increased by 2.5°C and 120 mm, respectively throughout the past 69 years.展开更多
太阳黑子变化是太阳强磁扰动的表征。结合长短期记忆单元神经网络和一维卷积神经网络预测太阳黑子变化,使用3种不同的数据集,分别为1700—2020年年均太阳黑子数(yearly mean sunspot number,YSSN)、1749—2021年月均太阳黑子数(monthly ...太阳黑子变化是太阳强磁扰动的表征。结合长短期记忆单元神经网络和一维卷积神经网络预测太阳黑子变化,使用3种不同的数据集,分别为1700—2020年年均太阳黑子数(yearly mean sunspot number,YSSN)、1749—2021年月均太阳黑子数(monthly mean sunspot number,MSSN)和1874—2021年月均太阳黑子面积(monthly mean sunspot area,MSSA)。首先,基于YSSN数据集,预测得到2021年YSSN以及第25太阳周YSSN,2025年预测值达到最大,其值为163.4;其次,基于MSSN数据集,预测得到2021年6月MSSN以及第25太阳周MSSN,2024年10月预测值达到最大,其值为245.9;接着,基于MSSA数据集,预测得到2021年6月MSSA,其值为73.1;最后,基于MSSA数据集,将纬度划分为13个分区,发现可以重建太阳黑子蝴蝶图。以上均表明神经网络方法为探测太阳黑子变化提供了新的解决思路。展开更多
Sunspot number, sunspot area and sunspot unit area are usually used to show sunspot activity. In this paper, periodicity of sunspot activity of modern solar cycles has been investigated through analyzing the monthly m...Sunspot number, sunspot area and sunspot unit area are usually used to show sunspot activity. In this paper, periodicity of sunspot activity of modern solar cycles has been investigated through analyzing the monthly mean val- ues of the three indices in the time interval of May 1874 to May 2004 by use of the wavelet transform. Their global power spectra and local power spectra are given while the statistical tests of these spectra are taken into account. The main results are (1) the local wavelet power spectrum of the sunspot number seems like that of the sunspot area, indicat- ing that the periodicity of the both indices is similar. The local power spectrum of the sunspot unit area resembles the local power spectra of the previous two indices, but looks more complicated. (2) the possible periods in sunspot activity are about 10.6 (or 10.9 years for the sunspot unit area), 31, and 42 years, and the period of about 10.6 years is statisti- cally significant in the considered time. For the periods of about 31 and 42 years, their power peaks are under the 95% confidence level line but over the mean red-noise spectral line, and for the other rest periods, their power peaks are even under the mean red-noise spectral line, which are sta- tistically insignificant. (3) the local power of the three periods is higher in the late stage than in the early stage of the con- sidered time. (4) the period characteristics of the three indi- ces, shown in the global power spectra and the local power spectra, are similar but there is difference in detail.展开更多
基金supported by the National Natural Science Foundation of China under Grant numbers U2031202,U1731124 and U1531247the special foundation work of the Ministry of Science and Technology of the People’s Republic of China under Grant number 2014FY120300the 13th Five-year Informatization Plan of Chinese Academy of Sciences under Grant number XXH13505-04。
文摘It is a significant task to predict the solar activity for space weather and solar physics. All kinds of approaches have been used to forecast solar activities, and they have been applied to many areas such as the solar dynamo of simulation and space mission planning. In this paper, we employ the long-shortterm memory(LSTM) and neural network autoregression(NNAR) deep learning methods to predict the upcoming 25 th solar cycle using the sunspot area(SSA) data during the period of May 1874 to December2020. Our results show that the 25 th solar cycle will be 55% stronger than Solar Cycle 24 with a maximum sunspot area of 3115±401 and the cycle reaching its peak in October 2022 by using the LSTM method. It also shows that deep learning algorithms perform better than the other commonly used methods and have high application value.
文摘In the present work,we study the time evolution,significance of the N-S asymmetry excesses presented as a function of the solar cycle and prominent rotational periods(~27 d)separately for the northern and southern hemispheres.We have investigated short-term variations of the hemispheric solar activity(sunspot numbers and sunspot areas)during the time period 2010-2015,which covers the ascending and the maximum phase of solar cycle 24.We have implemented the Lomb-Scargle periodogram and continuous wavelet transform power spectrum techniques to study the time evolution and dominant rotational periods separately for the northern and southern hemispheres,and whole solar disk.Our results showed that the northern hemisphere exhibited longer solar synodic periods than the southern hemisphere,indicating that the northern hemisphere has a lower rotation rate.Moreover,the northern hemisphere was found to be dominant before transferring to the southern hemisphere during mid-2013.Also,the sunspot areas clearly demonstrated a two-peak structure of solar activity in the northern and southern hemispheres respectively during 2012 and 2014.The statistical significance of the southern hemisphere affirmed enhanced excess during the maximum phase of solar cycle 24.
文摘The correlation of the Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), Pacific North American Oscillation (PNA), Arctic Oscillation (AO), and Scandinavia (SCAND) indices with winter (DJF) temperature and precipitation for the period of 1943 to 2011 was analyzed to study climate change and variability of Yellowknife, NWT. SOI correlated negatively with both temperature (r = -0.14) and precipitation (r = -0.06) causing colder, drier conditions during La Nina and warmer, wetter conditions during El Nino. PDO was shown to have a strong positive correlation with both temperature (r = 0.60) and precipitation (r = 0.33) causing warmer, wetter weather in the positive phase and colder, drier weather in the negative phase. PNA showed the strongest positive correlation for both temperature (r = 0.69) and precipitation (r = 0.37) causing very warm and wet conditions in the positive phase and very cold and dry conditions during the negative phase. AO correlated negatively with temperature (r = -0.04) and positively with precipitation (r = 0.24) causing colder, wetter conditions in the positive phase and warmer, drier conditions in the negative phase. Finally SCAND was shown to have a weak negative correlation with both temperature (r = -0.10) and precipitation (r = -0.18). Sunspot area showed a strong negative correlation (r = -0.30) with temperature and a very weak positive correlation (r = 0.07) with total annual precipitation. Yellowknife’s average annual temperature and precipitation has increased by 2.5°C and 120 mm, respectively throughout the past 69 years.
文摘太阳黑子变化是太阳强磁扰动的表征。结合长短期记忆单元神经网络和一维卷积神经网络预测太阳黑子变化,使用3种不同的数据集,分别为1700—2020年年均太阳黑子数(yearly mean sunspot number,YSSN)、1749—2021年月均太阳黑子数(monthly mean sunspot number,MSSN)和1874—2021年月均太阳黑子面积(monthly mean sunspot area,MSSA)。首先,基于YSSN数据集,预测得到2021年YSSN以及第25太阳周YSSN,2025年预测值达到最大,其值为163.4;其次,基于MSSN数据集,预测得到2021年6月MSSN以及第25太阳周MSSN,2024年10月预测值达到最大,其值为245.9;接着,基于MSSA数据集,预测得到2021年6月MSSA,其值为73.1;最后,基于MSSA数据集,将纬度划分为13个分区,发现可以重建太阳黑子蝴蝶图。以上均表明神经网络方法为探测太阳黑子变化提供了新的解决思路。
文摘Sunspot number, sunspot area and sunspot unit area are usually used to show sunspot activity. In this paper, periodicity of sunspot activity of modern solar cycles has been investigated through analyzing the monthly mean val- ues of the three indices in the time interval of May 1874 to May 2004 by use of the wavelet transform. Their global power spectra and local power spectra are given while the statistical tests of these spectra are taken into account. The main results are (1) the local wavelet power spectrum of the sunspot number seems like that of the sunspot area, indicat- ing that the periodicity of the both indices is similar. The local power spectrum of the sunspot unit area resembles the local power spectra of the previous two indices, but looks more complicated. (2) the possible periods in sunspot activity are about 10.6 (or 10.9 years for the sunspot unit area), 31, and 42 years, and the period of about 10.6 years is statisti- cally significant in the considered time. For the periods of about 31 and 42 years, their power peaks are under the 95% confidence level line but over the mean red-noise spectral line, and for the other rest periods, their power peaks are even under the mean red-noise spectral line, which are sta- tistically insignificant. (3) the local power of the three periods is higher in the late stage than in the early stage of the con- sidered time. (4) the period characteristics of the three indi- ces, shown in the global power spectra and the local power spectra, are similar but there is difference in detail.
