Index Catalog // Deep Blue Data

Start Over

Filtering by: Creator Richter, Jack Discipline Other

Marquette, Michigan Snowfall Instrument Site: Micro Rain Radar Dataset

Creator:

Richter, Jack and Pettersen, Claire

Description:

Radar observations supply detailed information about the structure and evolution of precipitation. These observations allow one to evaluate the macro- and/or micro-physical properties of precipitation at high spatial and temporal resolution. This dataset provides a nearly continuous collection of radar observations from a Metek Micro Rain Radar 2 (MRR) in Marquette, Michigan, USA (MQT). The MRR is a relatively low-cost, low-power K-band (24 GHz) profiling radar that scans the atmosphere at a fixed 90° zenith angle (i.e., directly overhead). The MRR in MQT is configured such that observations are provided every minute at a vertical resolution of 100m up to 3000m AGL (note: due to ground clutter, the effective operating range is 400m–3000m AGL). The MRR data are processed using IMProToo (Maahn and Kollias, 2012; https://doi.org/10.5194/amt-5-2661-2012) to increase the sensitivity of the radar to -10 dBZ and are “de-noised” using a principal component analysis method on the MRR raw power spectra to remove interference from a nearby broadcasting tower (Pettersen et al., 2020; https://doi.org/10.1175/JAMC-D-19-0099.1). Within this dataset, users will find observations such as the equivalent reflectivity factor, Doppler velocity, and reflectivity power spectra.

Keyword:

radar, snowfall, precipiation, microphysics, and in situ

Citation to related publication:

https://doi.org/10.1175/JAMC-D-19-0099.1, https://doi.org/10.1175/BAMS-D-19-0128.1, and https://doi.org/10.1029/2022JD037132

Discipline:

Other and Science

Marquette, Michigan Snowfall Instrument Site: Micro Rain Radar Dataset

Limit your search

Resource type

Creator

Discipline

Language

Search Results

Search Constraints

Search Results

Marquette, Michigan Snowfall Instrument Site: Micro Rain Radar Dataset

Limit your search

Resource type

Creator

Discipline

Language