Temperature changes in the Arctic lower stratosphere on both the short-and long-term timescales are critical for changing the magnitude of ozone losses in the Arctic vortex.In the present paper,first we give an approximate thermodynamic equation,which is in the form of that described by Hu and Tung (2002),for diagnosing the polar stratospheric temperature changes,along with its time-sliding calculation scheme.Next,according to this scheme and using the MERRA-2 reanalysis daily data for the period of 1980-2000,we calculate the terms of monthly temperature increment,dynamical heating and diabatic heating,as well as their respective linear trends,at 100 hPa in the Arctic lower stratosphere.The results show that the monthly temperature increment term and sum of the cumulative dynamical and diabatic heating,as well as their trends,are approximately balanced during the annual cycle of climatological average.Then,based on a multivariate linear regression,we further obtain the respective contributions of the dynamical and diabatic heating to the current month temperature trends.It is shown that the dynamical contribution to the temperature trend is dominant and varied with the different months in the Arctic lower stratosphere wintertime,while the diabatic contribution is dominant in other seasons.This is particularly pertinent to the attribution of decadal scale Arctic stratospheric temperature changes,due to the internal dynamics variability and anthropogenic climate forcings.In future work,it would be desirable to determine the reasonable range of the eddy heat flux approximation with regard to the reference latitude,pressure height and integration timescale,as well as to disclose more application aspects of the simplified thermodynamic energy equation.An assessment for the relative impact of each deviation factor is also required to obtain an accurate explanation for sources of some large departures and limits of the approximate temperature change equation.Of course,verifications and comparisons using greater numbers of and more varied data sets are required.