Abstract
Satellite remote sensing of frozen hydrometeors in deep convective systems is essential for understanding precipitation systems and the formation of upper-level clouds. To reduce uncertainties in ice cloud microphysical properties inside convective clouds, a combined use of millimeter-wave sensors sensitive to frozen particles in deep convective clouds is a promising strategy. This study uses the CloudSat Cloud Profiling Radar (CPR) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) to retrieve the vertical profiles of ice water content (IWC), number concentration (Nt), and mass-weighted diameter (Dm). A new retrieval method is developed by a combination of a deep neural network (DNN) and an optimal estimation method (OEM). In the first step of the algorithm, an initial guess is estimated by DNN based on an a priori database, followed by the next step where OEM seeks a more optimal frozen hydrometer profile. The retrieval performance is evaluated against selected match-up observations of CloudSat and GPM. The combined use of CPR and GMI observations reduces retrieval errors compared to the CPR-only observations. The retrieved frozen hydrometer profiles excellently reproduce CPR reflectivity and GMI brightness temperatures (Tb) when computed by forward simulations. The Dual-frequency Precipitation Radar (DPR) reflectivity is also reasonably reproduced, indicating some ability to retrieve large snow and graupel particles detectable by the low-frequency radars. A significant spread in simulated Tb is found for large ice water paths (IWPs) among different ice habit models tested, of which the optimal models are dendrite snowflake and soft sphere for the ice density model used in this algorithm. The combined algorithm developed by this work implies the potential of passive and active millimeter-wave instruments for retrieving multiple aspects of the cloud ice properties when combined in tandem. Future work will incorporate new satellite missions, including EarthCARE Doppler millimeter-wave radar and submillimeter-wave radiometers such as Ice Cloud Imager.
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CITATION STYLE
Ohara, K., & Masunaga, H. (2025). Synergy of millimeter-wave radar and radiometer measurements for retrieving frozen hydrometeors in deep convective systems. Atmospheric Measurement Techniques, 18(18), 4791–4807. https://doi.org/10.5194/amt-18-4791-2025
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