Great Lakes Convective Snow: A GPM Passive Microwave Perspective.
Abstract
Snowfall is produced by different precipitating structures with distinctly different cloud macrophysical and microphysical compositions. Deep cloud structures related to synoptically-forced, large-scale midlatitude weather systems, represent a common snowfall regime. Alternatively, many mid- to high-latitude oceanic and coastal regions are prone to shallow convective snow produced by cold air outbreaks interacting with unfrozen large bodies of water. The regional impact of the shallow convective snow cannot be ignored since they often produce intense snowfall rates and influence regional hydrology. This work focuses on the ability of the Global Precipitation Measurement (GPM) passive microwave sensors to detect and provide quantitative precipitation estimates (QPE) for this particular snowfall mode over the US Great Lakes region. GPM's Microwave Imager (GMI) and constellation sensors brightness temperatures (TB) are used to detect any signal related to intense shallow convective snowfall events. The related Goddard PROfiling (GPROF) retrieval products are also analyzed to understand strengths and weaknesses of the algorithm. In particular, the sensitivity of GPROF to some key parameters used to partition the GPROF a-priori database and converge more efficiently to the solution is investigated. These parameters are model-derived 2-meter temperature (T2m), total precipitable water (TPW), and background surface type. GPM's official GPROF frozen surface classification (different types of snow cover or sea ice) is compared to alternative classification schemes based on the low-frequency signal at the time of the radiometer overpass. The effective dependence of the GPROF snowfall rate estimates on the representativeness of shallow convective snowfall environmental conditions in the a-priori database is investigated. The Multi-Radar/Multi-Sensor (MRMS) QPE database is used as ground reference for qualitative and statistical evaluations.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.H52C..07M
- Keywords:
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- 3354 Precipitation;
- ATMOSPHERIC PROCESSESDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSESDE: 1817 Extreme events;
- HYDROLOGYDE: 1847 Modeling;
- HYDROLOGY