<p><strong>Abstract.</strong> The radar-based estimation of intense precipitation produced by convective storms is a challenging task and the verification through comparison with gauges is questionable due to the very high spatial variability of such types of precipitation. In this study, we explore the potential benefit of using a superconducting gravimeter as a new source of in situ observations for the evaluation of radar-based precipitation estimates. The superconducting gravimeter used in this study is installed in Membach (BE), 48<span class="thinspace"></span>m underneath the surface, at 85<span class="thinspace"></span>km distance from a C-band weather radar located in Wideumont (BE). The 15-year observation record 2003–2017 is available for both gravimeter and radar with 1 and 5<span class="thinspace"></span>min time steps, respectively. Water mass increase at ground due to precipitation results in a decrease in underground measured gravity. The gravimeter integrates soil water in a radius of about 400<span class="thinspace"></span>m around the instrument. This allows capture of rainfall at a larger spatial scale than traditional rain gauges. The precision of the gravimeter is a few tenths of nm<span class="thinspace"></span>s<span class="inline-formula"><sup>−2</sup></span>, 1<span class="thinspace"></span>nm<span class="thinspace"></span>s<span class="inline-formula"><sup>−2</sup></span> corresponding to 2.6<span class="thinspace"></span>mm of water. The comparison of reflectivity and gravity time series shows that short-duration intense rainfall events produce a rapid decrease in the underground measured gravity. A remarkable correspondence between radar and gravimeter time series is found. The precipitation amounts derived from gravity measurements and from radar observations are further compared for 505 rainfall events. A correlation coefficient of 0.58, a mean bias (radar–gravimeter)/gravimeter of 0.24 and a mean absolute difference (MAD) of 3.19<span class="thinspace"></span>mm are obtained. A better agreement is reached when applying a hail correction by truncating reflectivity values to a given threshold. No bias, a correlation coefficient of 0.64 and a MAD of 2.3<span class="thinspace"></span>mm are reached using a 48<span class="thinspace"></span>dBZ threshold. The added value of underground gravity measurements as a verification dataset is discussed. The two main benefits are the spatial scale at which precipitation is captured and the interesting property that gravity measurements are directly influenced by water mass at ground no matter the type of precipitation: hail or rain.</p>