Evaluation of SWER(Ze) Relationships by Precipitation Imaging Package (PIP) during ICE-POP 2018

Author:

Tokay Ali12ORCID,Helms Charles N.23,Kim Kwonil4,Gatlin Patrick N.5,Wolff David B.6

Affiliation:

1. a Goddard Earth Sciences Technology and Research (GESTAR-II), University of Maryland, Baltimore County, Baltimore, Maryland

2. b NASA Goddard Space Flight Center, Greenbelt, Maryland

3. c Earth System Science Interdisciplinary Center, University of Maryland, College Park, College Park, Maryland

4. d Center for Atmospheric Remote Sensing (CARE), Kyungpook National University, Daegu, South Korea

5. e NASA Marshall Space Flight Center, Huntsville, Alabama

6. f NASA Goddard Space Flight Center Wallops Flight Facility, Wallops Island, Virginia

Abstract

Abstract Improving estimation of snow water equivalent rate (SWER) from radar reflectivity (Ze), known as a SWER(Ze) relationship, is a priority for NASA’s Global Precipitation Measurement (GPM) mission ground validation program as it is needed to comprehensively validate spaceborne precipitation retrievals. This study investigates the performance of eight operational and four research-based SWER(Ze) relationships utilizing Precipitation Imaging Probe (PIP) observations from the International Collaborative Experiment for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018) field campaign. During ICE-POP 2018, there were 10 snow events that are classified by synoptic conditions as either cold low or warm low, and a SWER(Ze) relationship is derived for each event. Additionally, a SWER(Ze) relationship is derived for each synoptic classification by merging all events within each class. Two new types of SWER(Ze) relationships are derived from PIP measurements of bulk density and habit classification. These two physically based SWER(Ze) relationships provided superior estimates of SWER when compared to the operational, event-specific, and synoptic SWER(Ze) relationships. For estimates of the event snow water equivalent total, the event-specific, synoptic, and best-performing operational SWER(Ze) relationships outperformed the physically based SWER(Ze) relationship, although the physically based relationships still performed well. This study recommends using the density or habit-based SWER(Ze) relationships for microphysical studies, whereas the other SWER(Ze) relationships are better suited toward hydrologic application.

Funder

NASA Headquarters

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference45 articles.

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