No Arabic abstract
Sunspot number series are subject to various uncertainties, which are still poorly known. The need for their better understanding was recently highlighted by the major makeover of the international Sunspot Number [Clette et al., Space Science Reviews, 2014]. We present the first thorough estimation of these uncertainties, which behave as Poisson-like random variables with a multiplicative coefficient that is time- and observatory-dependent. We provide a simple expression for these uncertainties, and reveal how their evolution in time coincides with changes in the observations, and processing of the data. Knowing their value is essential for properly building composites out of multiple observations, and for preserving the stability of the composites in time.
The present study is an attempt to investigate the long term variations in coronal rotation by analyzing the time series of the solar radio emission data at 2.8 GHz frequency for the period 1947 - 2009. Here, daily adjusted radio flux (known as Penticton flux) data are used. The autocorrelation analysis shows that the rotation period varies between 19.0 to 29.5 sidereal days (mean sidereal rotation period is 24.3 days). This variation in the coronal rotation period shows evidence of two components in the variation; (1) 22-years component which may be related to the solar magnetic field reversal cycle or Hales cycle, and (3) a component which is irregular in nature, but dominates over the other components. The crosscorrelation analysis between the annual average sunspots number and the coronal rotation period also shows evidence of its correlation with the 22-years Hales cycle. The 22-years component is found to be almost in phase with the corresponding periodicities in the variation of the sunspots number.
One of the important open questions in solar irradiance studies is whether long-term variability (i.e. on timescales of years and beyond) can be reconstructed by means of models that describe short-term variability (i.e. days) using solar proxies as inputs. Preminger and Walton (2005, GRL, 32, 14109) showed that the relationship between spectral solar irradiance and proxies of magnetic-flux emergence, such as the daily sunspot area, can be described in the framework of linear system theory by means of the impulse response. We significantly refine that empirical model by removing spurious solar-rotational effects and by including an additional term that captures long-term variations. Our results show that long-term variability cannot be reconstructed from the short-term response of the spectral irradiance, which cautions the extension of solar proxy models to these timescales. In addition, we find that the solar response is nonlinear in such a way that cannot be corrected simply by applying a rescaling to sunspot area.
We create a continuous series of daily and monthly hemispheric sunspot numbers (HSNs) from 1874 to 2020, which will be continuously expanded in the future with the HSNs provided by SILSO. Based on the available daily measurements of hemispheric sunspot areas from 1874 to 2016 from Greenwich Royal Observatory and NOAA, we derive the relative fractions of the northern and southern activity. These fractions are applied to the international sunspot number (ISN) to derive the HSNs. This method and obtained data are validated against published HSNs for the period 1945--2020. We provide a continuous data series and catalogue of daily, monthly mean, and 13-month smoothed monthly mean HSNs for the time range 1874--2020 that are consistent with the newly calibrated ISN. Validation of the reconstructed HSNs against the direct data available since 1945 reveals a high level of consistency, with a correlation of r=0.94 (0.97) for the daily (monthly) data. The cumulative hemispheric asymmetries for cycles 12-24 give a mean value of 16%, with no obvious pattern in north-south predominance over the cycle evolution. The strongest asymmetry occurs for cycle no. 19, in which the northern hemisphere shows a cumulated predominance of 42%. The phase shift between the peaks of solar activity in the two hemispheres may be up to 28 months, with a mean absolute value of 16.4 months. The phase shifts reveal an overall asymmetry of the northern hemisphere reaching its cycle maximum earlier (in 10 out of 13 cases). Relating the ISN and HSN peak growth rates during the cycle rise phase with the cycle amplitude reveals higher correlations when considering the two hemispheres individually, with r = 0.9. Our findings demonstrate that empirical solar cycle prediction methods can be improved by investigating the solar cycle dynamics in terms of the hemispheric sunspot numbers.
The prediction of solar activity is important for advanced technologies and space activities. The peak sunspot number (SSN), which can represent the solar activity, has declined continuously in the past four solar cycles (21$-$24), and the Sun would experience a Dalton-like minimum, or even the Maunder-like minimum, if the declining trend continues in the following several cycles, so that the predictions of solar activity for cycles 25 and 26 are crucial. In Qin & Wu, 2018, ApJ, we established an SSN prediction model denoted as two-parameter modified logistic prediction (TMLP) model, which can predict the variation of SSNs in a solar cycle if the start time of the cycle has been determined. In this work, we obtain a new model denoted as TMLP-extension (TMLP-E). If the start time of a cycle $n$ is already known, TMLP-E can predict the variation of SSNs in the cycle $n+1$. Cycle 25 is believed to start in December 2019, so that the predictions of cycles 25 and 26 can be made with our models. It is found that the predicted solar maximum, ascent time, and cycle length are 115.1, 4.84 yr, and 11.06 yr, respectively, for cycle 25, and 107.3, 4.80 yr, and 10.97 yr, respectively, for cycle 26. The solar activities of cycles 25 and 26 are predicted to be at the same level as that of cycle 24, but will not decrease further. We therefore suggest that the cycles 24$-$26 are at a minimum of Gleissberg cycle.
Sunspot numbers are important tracers of historical solar activity. They are important in the prediction of oncoming solar maximum, in the design of lifetimes of space assets, and in assessing the extent of solar-radiation impact on the space environment. Sunspot numbers were obtained visually from sunspot drawings. The availability of digital images from the US Air Force Improved Solar Optical Observing Network (ISOON) prototype telescope concurrent to observer-dependent sunspot numbers recorded at the National Solar Observatory (NSO) has provided a basis for comparing sunspot numbers determined from the two methods. We compare sunspot numbers from visual and digital methods observed nearly simultaneously. The advantages of digital imagery are illustrated.