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The groundbased microwave radiometer is employing passive remote sensing techniques to achieve realtime retrieval of atmospheric temperature, humidity profiles and related parameters. It possesses advantages of high spatiotemporal resolution, unmanned operation, and continuous functionality, gradually emerging as a potent supplementary method for remote sensing of atmospheric temperature, humidity, and cloud liquid water profiles both domestically and internationally. However, the inversion methods of microwave radiometer data rely on local historical radiosonde data and are restricted by factors such as the distribution of radiosonde stations. Consequently, its utilisation in areas lacking radiosonde stations is limited. To investigate the application effectiveness of ERA5 reanalysis data in microwave radiometer data retrieval, two neural networks are trained separately using radiosonde and ERA5 data as training samples. These networks are used to invert the microwave radiometer observation data. Subsequently, utilising radiosonde data as a reference, the correlation coefficient, absolute deviation, and root mean square error of the data inverted based on radiosonde and ERA5 reanalysis data are computed to assess the application effectiveness of ERA5 reanalysis data in microwave radiometer data retrieval. The results are indicating that the temperature profile inversions based on ERA5 and radiosonde data are exhibiting correlation coefficients of 0.988 and 0.99, with absolute deviations of 2.402 ℃ and 2.607 ℃, respectively. The water vapour density inversions are showing correlation coefficients of 0.975 and 0.979, with absolute deviations of 0.412 g/m3 and 0.369 g/m3. The relative humidity inversions are exhibiting correlation coefficients of 0.663 and 0.696, with absolute deviations of 15.587% and 13.976%. Furthermore, the integrated water vapour total inversions are presenting correlation coefficients of 0.959 and 0.968, with absolute deviations of 0.258 cm and 0.227 cm. Comparison of the microwave radiometer inversions based on radiosonde and reanalysis data is revealing closely aligned temperature profiles and integrated water vapour statistics; however, noticeable overestimations are observed in relative humidity. Analysis of error distribution with altitude is indicating relatively minor changes in root mean square errors for both radiosonde and ERA5 data. Temperature and humidity profile errors from both radiosonde and ERA5 retrievaled are performing better at lower altitudes, gradually increasing with altitude. The temperature profile error derived from radiosonde retrievals is notably smaller compared to ERA5based inversions, exhibiting a distinct difference in the variation of relative humidity errors with altitude. This study is currently focusing solely on the application effectiveness of ERA5 data near the Changchun radiosonde station. To comprehensively validate the utility of ERA5 in microwave radiometer data retrieval, further research is essential in other radiosonde stations, including regions devoid of radiosonde data. Future research is necessary to investigate the application and correction methodologies of ERA5 data in microwave radiometer data retrieval in these areas.