Synergy of millimeter-wave radar and radiometer measurements for retrieving frozen hydrometeors in deep convective systems

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.

Authors

Institutions

Publication Details

Journal
Atmospheric measurement techniques
Published
2025-09-25
DOI
https://doi.org/10.5194/amt-18-4791-2025
Citations
1
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.30
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Synergy of millimeter-wave radar and radiometer measurements for retrieving frozen hydrometeors in deep convective systems

Keiichi Ohara, Hirohiko Masunaga
1 citations
Atmospheric measurement techniques
Meteorological Phenomena and Simulations
1.30
article

Synergy of millimeter-wave radar and radiometer measurements for retrieving frozen hydrometeors in deep convective systems

Keiichi Ohara, Hirohiko Masunaga
article en
1 citations

Abstract

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.

Atmospheric measurement techniquesVol. 18(18)
Japan Aerospace Exploration Agency (JP), Nagoya University (JP)
Openalex Percentile: Top 18%
Meteorological Phenomena and Simulations
1.30
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.