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The geomagnetic Kp index is derived from the K index measurements obtainedfrom thirteen stations located around the Earth geomagnetic latitudes between$48^\circ$ and $63^\circ$. This index is processed every three hours, isquasi-logarithmic and estimates the geomagnetic activity. The Kp values fallwithin a range of 0 to 9 and are organized as a set of 28 discrete values. Thedata set is important because it is used as one of the many input parameters ofmagnetospheric and ionospheric models. The objective of this work is to usehistorical data from the Kp index to develop a methodology to make a predictionin a time interval of at least three hours. Five different models to forecastgeomagnetic indices Kp and ap are tested. Time series of values of Kp indexfrom 1932 to 15/12/2012 at 21:00 UT are used as input to the models. Thepurpose of the model is to predict the three measured values after the lastmeasured value of the Kp index (it means the next 9 hours values). The AR modelprovides the lowest computational cost with satisfactory results. The ARIMAmodel is efficient for predicting Kp index during geomagnetic disturbanceconditions. This paper provides a quick and efficient way to make a predictionof Kp index, without using satellite data. Although it is reported that theforecast results are better when satellite data are used. In the literature wefind that the linear correlation between predicted values and actual values is$77\%$, which is better than the $68.5\%$ obtained in this work. However,taking into account that our results are based only on Kp stochastic timeseries, the correlation value can be considered satisfactory.

Planetary Kp index forecast using autoregressive models