The 27-Day and 22-Year Cycles in Solar and Geomagnetic Activity

We study the evolution of the longitudinal asymmetry in solar activity through the wave packet technique applied to the period domain of 25 – 31 days (centered at the 27-day solar rotation period) for the sunspot number and geomagnetic aa index. We observe the occurrence of alternating smaller and larger amplitudes of the 11-year cycle, resulting in a 22-year periodicity in the 27-day signal. The evolution of the 22-year cycle shows a change of regime around the year 1912 when the 22-year period disappears from the sunspot number series and appears in the aa index. Other changes, such as a change in the correlation between solar and geomagnetic activity, took place at the same time. Splitting the 27-day frequency domain of aa index shows an 11-year cycle for higher frequencies and a pure22-year cycle for lower frequencies, which we attribute to higher latitude coronal holes. This evidence is particularly clear after 1940, which is another benchmark in the evolution of the aa index. We discuss briefly the mechanisms that could account for the observed features of the 22-year cycle evolution.     

Time Series Modeling of Sunspot Numbers Using Long-Range Cyclical Dependence

This paper deals with the analysis of the sunspot number time series using a new technique based on cyclical long-range dependence. The results show that sunspot numbers have a periodicity of 130 months but, more importantly, that the series is highly persistent, with an order of cyclical fractional integration slightly above 0.30. That means that the series displays long memory, with a large degree of dependence between the observations that tends to disappear very slowly in time.     

The rotational temperatures of Silicon hydride isotopomer lines in sunspot umbrae

The published sunspot spectrum obtained with National Solar Observatory/Kitt Peak laboratory’s high signal to noise ratio telescope and high resolution Fourier Transform Spectrometer were used for the study. A search was made for the prominent lines of the (0, 0) and (1, 1) A²Δ − X²Π for Silicon hydride isotopomers which lie between 23500 cm⁻¹ and 24500 cm⁻¹. The presence of lines from the (0, 0) and (1, 1) A²Δ − X²Π transition of SiH molecule coincided with the sunspot umbral lines suggest that Silicon hydride appears to be a non-negligible component of sunspot umbrae. However, the presence of A²Δ − X²Π (0, 0) and (1, 1) bands of SiD was found to be doubtful because of the lack of number of well identified lines in sunspot umbral spectra. Equivalent widths have been measured for well-resolved lines and, thereby, the rotational temperatures have been estimated for the band systems for which the presence is confirmed.     

Parametric identification of solar series based on an adaptive parallel methodology

In this work we present an adaptive parallel methodology to optimize the identification of time series through parametric models, applying it to the case of sunspot series. We employ high precision computation of system identification algorithms, and use recursive least squares processing and ARMAX (Autoregressive Moving Average Extensive) parametric modelling. This methodology could be very useful when the high precision mathematical modelling of dynamic complex systems is required. After explaining the proposed heuristics and the tuning of its parameters, we show the results we have found for several solar series using different implementations. Thus, we demonstrate how the result precision improves.     

Automatic Detection of Sunspots and Extractionof Their Feature Parameters

Sunspots are solar features located in active regions of the Sun, whose number is an indicator of the Sun's magnetic activity. With a substantial increase in the quantity of solar image data, the automated detection and verification of various solar features have become increasingly important for the accurate and timely forecasts of solar activity and space weather. In order to use the high time-cadence SDO/HMI data to extract the main sunspot features for forecasting solar activities, we have established an automatic detection method of sunspots based on mathematical morphology, and calculated the sunspot group area and sunspot number. By comparing our results with those obtained from the Solar Region Summary compiled by NOAA/SWPC, it is found that the sunspot group areas and sunspot numbers computed with our algorithm are in good agreement with the active region values released by SWPC, and the corresponding correlation coefficients for the sunspot group area and sunspot number are 0.77 and 0.79, respectively. By using the method of this paper, the high time-cadence feature parameters can be obtained from the HMI data to provide the timely and accurate inputs for the solar activity forecast.     

河南省2002年夏季高温少雨成因

从副高特征量和500hPa高度场以及高度距平场角度，分析了2002年夏季河南省气候特征，并分析了海温、太阳黑子等特征量对夏季降水的影响。结果表明：2002年夏季副热带高压偏南，北方冷空气活动偏弱，大陆暖高压强盛发展并维持，是造成河南省夏季高温少雨的直接原因；赤道中、东太平洋维持弱的暖事件和太阳活动异常以及天文背景的影响，是造成2002年河南省夏季高温少雨的间接原因。     

用径向基函数神经网络方法预报太阳黑子数平滑月均值

简单介绍了径向基函数神经网络方法的原理和应用,发展了用径向基函数（RBF）对平滑月平均黑子数进行预报的方法. 用不同的数据序列对网络进行训练,对未来8个月的平滑月平均黑子数进行预报. 用该方法对第23周开始后的平滑月平均黑子数进行逐月预报,并与实测值进行比较,结果表明随着预报实效的延长预报误差被逐渐放大,该方法可以较准确地做出未来４个月的预报,绝对误差可以控制在20以内,标准差为4.8,相对误差控制在38％以内,大部分相对误差不超过15%（占总预报数的89％）,具有较好的应用价值. 用于网络训练的样本数量对预报结果会产生一定的影响.     

太阳黑子对东海气旋及热带气旋活动的影响

本文利用１９４９～１９９７年的资料,以统计分析的方法,对太阳黑子及东海气旋①,热带气旋②活动的互相关系,进行了初步探讨,归纳出几点有参考价值的结论     

Recent Progress of Hemispheric Coupling of Solar Activity Cycle

The hemispheric coupling phenomenon of solar activity cycle was discovered as early as the mid-20th century, and it is one of the most common topic in the long-term spatio-temporal evolution of the Sun, while the observational features and physical mechanism of hemispheric coupling have not been completely understood. The theoretical model of solar magnetohydrodynamics driven by this phenomenon is helpful in studying the basic information of the spatio-temporal evolution of solar activity cycle, and is also of great value to the short- and medium-term forecast of solar activity as well as the space weather. Here, we first give the discovery and observational history of the hemispheric coupling of solar activity. And then, the basic observational features of hemispheric coupling at different spatio-temporal scales and their possible mechanism are summarized. Finally, we give a discussion about the important unresolved issues and development trends in this important field.     

An application of artificial intelligence for investigating the effect of COVID-19 lockdown on three-dimensional temperature variation in equatorial Africa

We present interesting application of artificial intelligence for investigating effect of the COVID-19 lockdown on 3-dimensional temperature variation across Nigeria (2°–15° E, 4°–14° N), in equatorial Africa. Artificial neural networks were trained to learn time-series temperature variation patterns using radio occultation measurements of atmospheric temperature from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). Data used for training, validation and testing of the neural networks covered period prior to the lockdown. There was also an investigation into the viability of solar activity indicator (represented by the sunspot number) as an input for the process. The results indicated that including the sunspot number as an input for the training did not improve the network prediction accuracy. The trained network was then used to predict values for the lockdown period. Since the network was trained using pre-lockdown dataset, predictions from the network are regarded as expected temperatures, should there have been no lockdown. By comparing with the actual COSMIC measurements during the lockdown period, effects of the lockdown on atmospheric temperatures were deduced. In overall, the mean altitudinal temperatures rose by about 1.1 °C above expected values during the lockdown. An altitudinal breakdown, at 1 km resolution, reveals that the values were typically below 0.5 °C at most of the altitudes, but exceeded 1 °C at 28 and 29 km altitudes. The temperatures were also observed to drop below expected values at altitudes of 0–2 km, and 17–20 km.