Next Article in Journal
Mapping Panax Notoginseng Plantations by Using an Integrated Pixel- and Object-Based (IPOB) Approach and ZY-3 Imagery
Next Article in Special Issue
Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset
Previous Article in Journal
Cascaded Microwave Frequency Transfer over 300-km Fiber Link with Instability at the 10−18 Level
Previous Article in Special Issue
Performance of the IMERG Precipitation Products over High-latitudes Region of Finland
Article

The Precipitation Imaging Package: Phase Partitioning Capabilities

1
Space Science and Engineering Center, University of Wisconsin–Madison, Madison, WI 53706, USA
2
NASA Goddard Space Flight Center, Wallops Flight Facility, Wallops Island, VA 23337, USA
3
Advanced Satellite Products Branch, NOAA/NESDIS/Center for Satellite Applications and Research, Madison, WI 53706, USA
4
Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, WI 53706, USA
5
National Weather Service, NOAA, Milwaukee, WI 53118, USA
6
NASA Marshall Space Flight Center, Huntsville, AL 35808, USA
7
Finnish Meteorological Institute, 00560 Helsinki, Finland
*
Author to whom correspondence should be addressed.
Academic Editor: Gareth Rees
Remote Sens. 2021, 13(11), 2183; https://doi.org/10.3390/rs13112183
Received: 28 April 2021 / Revised: 30 May 2021 / Accepted: 31 May 2021 / Published: 3 June 2021
(This article belongs to the Special Issue Remote Sensing of Precipitation at the Mid- to High-Latitudes)
Surface precipitation phase is a fundamental meteorological property with immense importance. Accurate classification of phase from satellite remotely sensed observations is difficult. This study demonstrates the ability of the Precipitation Imaging Package (PIP), a ground-based, in situ precipitation imager, to distinguish precipitation phase. The PIP precipitation phase identification capabilities are compared to observer records from the National Weather Service (NWS) office in Marquette, Michigan, as well as co-located observations from profiling and scanning radars, disdrometer data, and surface meteorological measurements. Examined are 13 events with at least one precipitation phase transition. The PIP-determined onsets and endings of the respective precipitation phase periods agree to within 15 min of NWS observer records for the vast majority of the events. Additionally, the PIP and NWS liquid water equivalent accumulations for 12 of the 13 events were within 10%. Co-located observations from scanning and profiling radars, as well as reanalysis-derived synoptic and thermodynamic conditions, support the accuracy of the precipitation phases identified by the PIP. PIP observations for the phase transition events are compared to output from a parameterization based on wet bulb and near-surface lapse rates to produce a probability of solid precipitation. The PIP phase identification and the parameterization output are consistent. This work highlights the ability of the PIP to properly characterize hydrometeor phase and provide dependable precipitation accumulations under complicated mixed-phase and rain and snow (or vice versa) transition events. View Full-Text
Keywords: precipitation; mixed-phase precipitation; rain rate; snowfall rate; snow mass retrieval; video disdrometers precipitation; mixed-phase precipitation; rain rate; snowfall rate; snow mass retrieval; video disdrometers
Show Figures

Figure 1

MDPI and ACS Style

Pettersen, C.; Bliven, L.F.; Kulie, M.S.; Wood, N.B.; Shates, J.A.; Anderson, J.; Mateling, M.E.; Petersen, W.A.; von Lerber, A.; Wolff, D.B. The Precipitation Imaging Package: Phase Partitioning Capabilities. Remote Sens. 2021, 13, 2183. https://doi.org/10.3390/rs13112183

AMA Style

Pettersen C, Bliven LF, Kulie MS, Wood NB, Shates JA, Anderson J, Mateling ME, Petersen WA, von Lerber A, Wolff DB. The Precipitation Imaging Package: Phase Partitioning Capabilities. Remote Sensing. 2021; 13(11):2183. https://doi.org/10.3390/rs13112183

Chicago/Turabian Style

Pettersen, Claire, Larry F. Bliven, Mark S. Kulie, Norman B. Wood, Julia A. Shates, Jaclyn Anderson, Marian E. Mateling, Walter A. Petersen, Annakaisa von Lerber, and David B. Wolff. 2021. "The Precipitation Imaging Package: Phase Partitioning Capabilities" Remote Sensing 13, no. 11: 2183. https://doi.org/10.3390/rs13112183

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop