Exploring the Statistical Characteristics of Coastal Winter Precipitation Measured using a Parsivel2 Disdrometer: A Case Study in North Carolina

Objective

The study investigates the microphysical characteristics of coastal winter precipitation in North Carolina using high-resolution data from a Parsivel2 disdrometer, with a focus on understanding particle size distribution (DSD), precipitation types, and statistical variability under different winter conditions.

Methodology

Instrument: OTT Parsivel2 disdrometer (optical precipitation sensor)

Location: Coastal region of North Carolina

Data Period: Winter months

Analysis:

Precipitation classified into stratiform, convective, and mixed precipitation

DSD and velocity-diameter relationships analyzed

Statistical properties of precipitation events studied (e.g., mean diameter, number concentration, radar reflectivity)

Key Findings

Distinct statistical signatures were identified for different precipitation types:

Rain showed narrower DSDs with higher number concentration of small drops.

Snow displayed broader distributions with larger, slower-falling particles.

Mixed precipitation demonstrated high variability, with overlapping DSD features.

The velocity-diameter relationship deviated from idealized models, especially in snow events, likely due to non-spherical particles and turbulence.

The Parsivel2 was shown to be effective in capturing microphysical transitions and providing real-time insights into coastal winter precipitation dynamics.

Conclusion

The study demonstrates the utility of disdrometer-based analysis for improving understanding of precipitation microphysics in coastal winter environments. The insights can support better forecasting, radar validation, and hydrological modeling for regions affected by rapidly changing winter weather.