E-mail Mark Kulie
My current research interests are related to understanding global precipitation using both ground-based and spaceborne microwave remote sensing instruments. I am particularly interested in mapping global snowfall, monitoring longer-term snowfall changes, and improving global snowfall estimates from spaceborne platforms like the Global Precipitation Measurement mission (a joint NASA/JAXA mission) and CloudSat (NASA). Snowfall estimate uncertainties associated with microwave remote sensing observations are primarily linked to microphysical complexities (e.g.,variability in snowflake type/structure and particle size distribution), so I am also interested in observing snowfall microphysics using in situ observational platforms to understand the variability in microphysical properties related to different types of snowfall modes (e.g., shallow lake-effect snow versus deeper synoptic snowfall). In cooperation with researchers at the NASA Wallops Flight Facility and Marquette, MI National Weather Service Weather Forecast Office, I have established a NASA-funded snowfall observatory to coincidentally measure snowflake size distributions with vertically-pointing radar data in a region that receives typically high annual snowfall amounts, including frequent lake-effect snow events. Finally, I am also working to improve operational forecasting of lake-effect snow events by producing satellite-derived snowfall rate estimates that help mitigate radar observational shortcomings in the Great Lakes region. All of these projects are described in further detail in the Current Projects section.
NASA New Investigator Project - Snowfall Microphysics + Radar Observatory
This National Aeronautics and Space Administration (NASA)-funded research project supports the deployment of a Micro Rain Radar (MRR) and Precipitation Imaging Package (PIP) at the Marquette, MI NWS office to observe coincident snowfall microphysics and radar reflectivity measurements. Quick look MRR and PIP images from the entire dataset can be found here. The primary purpose of this project is to collect and catalog sustained snowflake PSD and habit type measurements to understand how microphysical details affect radar signatures. The multi-season PIP snowflake particle size distribution (PSD) datasets will be made available for the remote sensing and modeling communities. We are especially interested in understanding the differences between lake-effect snow and deeper synoptic snow microphysics, and the microphysical insights gained from the ground-based datasets will be parlayed to spaceborne snowfall applications using currently available microwave observations.
Global Precipitation Measurement (GPM)
This NASA-funded project has three primary goals related to the recently launched Global Precipitation Measurement (GPM) mission. (1) Enhanced microphysical tools are being developed for microwave precipitation retrieval algorithms. Updated microphysics databases are being generated to include lookup tables for particle size distribution (PSD)-averaged quantities (e.g., multi-frequency radar reflectivity factor, PSD-integrated volume extinction, etc.) using multiple PSD parameterizations combined with standardized scattering databases using updated ice particle models as proxies for frozen hydrometeors. PSD observations from recent field campaign will also be used to assess the veracity of PSD parameterizations. (2) Multi-frequency radar observations will be analyzed to study systematic radar signature differences due to microphysical effects. These studies will reduce forward modeling uncertainties and lead to GPM-era high-latitude precipitation algorithm improvements. (3) GPM-centric datasets will be created using independent ground-based radars, including NEXRAD Great Lakes region radars. Gridded climatological and GPM overpass-specific radar products will be developed and distributed to the GPM science community. Test products during the pre-GPM era will also be produced for proof-of-concept demonstrations using currently deployed microwave sensors. Algorithm and direct observational validation for different global precipitation regimes will be facilitated with these specialized datasets.
This NASA-funded project primarily focuses on using CloudSat and CALIPSO observations to study global snowfall. A primary goal of this project is to perform global snowfall partitioning studies. CloudSat observations are used to partition mid-latitude snowfall accumulation due to synoptic-scale weather systems and lake-induced shallow convective snow. A multi-year global lake effect snowfall inventory is being produced using primarily CloudSat observations combined with back-trajectories from the NOAA HYSPLIT model to illustrate dominant air mass source regions for areas prone to lake effect snow. Potential CloudSat sampling errors, as well as the diurnal cycle of lake effect events, will also be monitored using ground-based radar data in the Great Lakes region. Phenomenological and microphysical process studies are also underway to investigate precipitation initiation and cloud morphology in lake-induced snow using coincident CloudSat, CALIPSO, and MODIS data.