Thursday, 1 February 2024
Hall E (The Baltimore Convention Center)
The NASA Investigation of Microphysics and Precipitation for Atlantic Coast Threatening Snowstorms (IMPACTS) field campaign provides high quality, co-located high-altitude lidar (532 nm), radar (W-band) and in-cloud microphysical aircraft data during a wide range of intense winter storm events impacting the United States. This study evaluates the capability of well-used mass-dimensional relationships (Brown and Francis (1995, BF95); Heymsfield (2014, H14) and two lidar-radar microphysical retrieval algorithms (Cloudsat and CALIPSO Ice Cloud Property Product (2C-ICE); VarPy) to aircraft-retrieved ice water content (IWC), effective radius (re), and the volume extinction coefficient (σ) during the IMPACTS deployments in 2020, 2022, and 2023.
Our preliminary results from four co-located 2020 flight data revealed several key findings. First, BF95 and H14 proved equally capable of estimating σ, yet BF95 has a systematic low bias in its IWC and re estimates, which likely stems from it sampling dataset being sourced solely from cirrus clouds rather than thicker ice clouds with characteristics cloud to that in mid-latitude wintertime cyclones. Second, for all three microphysical parameters, VarPy and 2C-ICE retrieval errors became notably more pronounced around the dendritic growth zone (-15°C to -10°C) and near freezing (≥-5°C), which suggests that both algorithms experience difficulty addressing riming and aggregation processes and with larger particles (dendrites and plates) due in part to their simplified ice particle assumptions. Third, the mean-melt diameter ice-particle assumption of VarPy did generally yield improved IWC estimates, when compared 2C-ICE, which assumes all ice crystals to be hexagonal columns.
This initial work however is based solely upon the radar-only components of the 2C-ICE and VarPy algorithms due to in-situ, P-3 aircraft, flying below the lidar beam attenuation altitude. On-going work will apply this same analysis to 19 additional missions from IMPACTS 2022 and 2023 that had improved co-location between two mission aircrafts and where the P-3 was able to sample above the lidar beam attenuation altitude. These additional data will provide further insights into the performance of each algorithm, but also specifically target their lidar-only, radar-only, and radar-lidar combined components. Insights gained from this investigation will provide data and insights back to microphysical algorithm developers to help further refine or develop new microphysical algorithms for use in airborne and spaceborne retrievals.
Our preliminary results from four co-located 2020 flight data revealed several key findings. First, BF95 and H14 proved equally capable of estimating σ, yet BF95 has a systematic low bias in its IWC and re estimates, which likely stems from it sampling dataset being sourced solely from cirrus clouds rather than thicker ice clouds with characteristics cloud to that in mid-latitude wintertime cyclones. Second, for all three microphysical parameters, VarPy and 2C-ICE retrieval errors became notably more pronounced around the dendritic growth zone (-15°C to -10°C) and near freezing (≥-5°C), which suggests that both algorithms experience difficulty addressing riming and aggregation processes and with larger particles (dendrites and plates) due in part to their simplified ice particle assumptions. Third, the mean-melt diameter ice-particle assumption of VarPy did generally yield improved IWC estimates, when compared 2C-ICE, which assumes all ice crystals to be hexagonal columns.
This initial work however is based solely upon the radar-only components of the 2C-ICE and VarPy algorithms due to in-situ, P-3 aircraft, flying below the lidar beam attenuation altitude. On-going work will apply this same analysis to 19 additional missions from IMPACTS 2022 and 2023 that had improved co-location between two mission aircrafts and where the P-3 was able to sample above the lidar beam attenuation altitude. These additional data will provide further insights into the performance of each algorithm, but also specifically target their lidar-only, radar-only, and radar-lidar combined components. Insights gained from this investigation will provide data and insights back to microphysical algorithm developers to help further refine or develop new microphysical algorithms for use in airborne and spaceborne retrievals.
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