The last decades have shown the relevance of polarimetric radar measurements in various domains of Earth science to characterize different types of particles in natural media such as snow covers, vegetation canopy and clouds. In atmospheric physics, the need to accurately define the frozen hydrometeor properties (type, size, density) in precipitating systems is directly related to our understanding of the convective processes. These microphysical properties are also particularly critical in setting ice parameterization in models. Ground-based polarimetric radars can provide information on the most likely type of ice particles present in a sampled volume. These classifications can be used to build ice particle habit statistics once they are validated. The SPolKa classification scheme (PID, Particles IDentificator) for various types of frozen hydrometeors is compared to in-situ measurements collected during the CINDY-DYNAMO campaign in the Indian Ocean. The French Falcon-20 flew inside the polarimetric radar area measuring the particle habits with several in-situ microphysical probes (FSSP, 2DS, CPI, PIP, 2DP, Nevzorov). These in-situ data are organized as catalog of images and matched to the classifications proposed by Magono and and Lee (1966) and Kikuchi et al. (2013). The PID classification and the Precipitation Imaging Probe (PIP) data images are compared over two sequences representing two different atmospheric situations: a large stratiform area sampled on November 27th, 2011 and some convective activity embedded in stratiform precipitation on December 8th, 2011. The general agreement is very good for most species. Since the PIP only provides us with a 2D image of the particles’ shadow, some species are difficult to identify unambiguously and could be matched with more than one PID. This is particularly critical for species with complex history.