Abstract

Long-term sunspot observations are key to understand and predict the solar activities and its effects on the space weather.Consistent observations which are crucial for long-term variations studies,are generally not available due to upgradation/modifications of observatories over the course of time. We present the data for a period of 90 years acquired from persistent observation at the Kodaikanal observatory in India. We use an advanced semi-automated algorithm to detect the sunspots form each calibrated white-light image. Area, longitude and latitude of each of the detected sunspots are derived. Implementation of a semi-automated method is very necessary in such studies as it minimizes the human bias in the detection procedure. Daily, monthly and yearly sunspot area variations obtained from the Kodaikanal, compared well with the Greenwich sunspot area data. We find an exponentially decaying distribution for the individual sunspot area for each of the solar cycles. Analyzing the histograms of the latitudinal distribution of the detected sunspots, we find Gaussian distributions, in both the hemispheres, with the centers at $\sim$15$^{\circ}$ latitude. The height of the Gaussian distributions are different for the two hemispheres for a particular cycle. Using our data, we show clear presence of Waldmeier effect which correlates the rise time with the cycle amplitude. Using the wavelet analysis, we explored different periodicities of different time scales present in the sunspot area times series.

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