Paper on Multiplatform Precipitation Features (MPFs) Synthesizing Spaceborne Radar and Lightning Observations with Ground-Based Radar Accepted in AGU Journal of Earth and Space Science

Sarah Bang (ST11), with Sarah Stough (UAH ESSC), Timothy Lang (ST11) and Patrick Gatlin (ST11) authored an article titled “The Multiplatform Precipitation Feature (MPF) Database: A Storm-Centric Synthesis of Space- and Ground-Based Precipitation and Lightning Datasets for Convective Studies” that was recently accepted to the American Geophysical Union's (AGU) journal of Earth and Space Science.

The MPF approach is applied to ground- and space-based precipitation observations and retrievals from the Global Precipitation Measurement (GPM) mission Validation Network (VN) with space-based lightning measurements from the Lightning Imaging Sensor on board the International Space Station (ISS LIS) to create a prototype MPF database. The data are synthesized in a thunderstorm-like, feature-based framework that enables broad statistical analyses of the storm-based relationships between the microphysics, kinematics, and electrical properties of convection that can contribute insight into their morphological, regional, and seasonal variations. After outlining how MPFs are constructed, the authors demonstrate a proof-of-concept example to showcase the dataset flexibility and the thunderstorm science it enables.

The first iteration of the dataset is published for the public at

Bang graphic October 23

Figure: Flow chart describing how a Multiplatform Precipitation Feature (MPF) is constructed.

(a) GPM DPR Ku-band reflectivity data are gridded to height of -10C and filtered to segment convective cores.

(b) The Scikit-learn ndimage algorithm is applied to identify and label distinct reflectivity regions. Convex hulls are determined around ndimage regions, defining the feature boundary.

(c) Coincident ISS LIS overpasses are identified within the boundary and ± 5 minutes from the radar timestamp.

(d) If lightning is detected, ISS LIS lightning data from within the boundary are appended to the MPF.

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