Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data
Blanke, A., Heymsfield, A. J., Moser, M., & Trömel, S. (2023). Evaluation of polarimetric ice microphysical retrievals with OLYMPEX campaign data. Atmospheric Measurement Techniques, 16, 2089-2106. doi:10.5194/amt-16-2089-2023
Polarimetric microphysical retrievals reveal a great potential for the evaluation of numerical models and data assimilation. However, the accuracy of ice microphysical retrievals is still poorly explored. To evaluate these retrievals and assess their accuracy, polarimetric radar measurements are ... Show morePolarimetric microphysical retrievals reveal a great potential for the evaluation of numerical models and data assimilation. However, the accuracy of ice microphysical retrievals is still poorly explored. To evaluate these retrievals and assess their accuracy, polarimetric radar measurements are spatially and temporally collocated with in situ aircraft measurements obtained during the OLYMPEX campaign (Olympic Mountain Experiment). Retrievals for ice water content (IWC), total number concentration N-t, and mean volume diameter D-m of ice particles are assessed by comparing an in situ dataset obtained by the University of North Dakota (UND) Citation II aircraft with X-band Doppler on Wheels (DOW) measurements. Sector-averaged range height indicator (RHI) scans are used to derive vertical profiles of microphysical retrievals. The comparison of these estimates with in situ data provides insights into strengths, weaknesses, and the accuracy of the different retrievals and quantifies the improvements in polarimetry-informed retrievals compared to conventional, non-polarimetric ones. In particular, the recently introduced hybrid ice water content retrieval exploiting reflectivity Z(H), differential reflectivity Z(DR), and specific differential phase KDP outperforms other retrievals based on either (Z(H), Z(DR)) or (Z(H), K-DP) or non-polarimetric retrievals in terms of correlations with in situ measurements and the root mean square error. Show less