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Gatlin, Patrick

Publications and source records attributed to Gatlin, Patrick.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

The Evolution and Extratropical Transition of Tropical Cyclones from a GPM, ISS LIS and GLM Perspective

Not much is known about the evolution of lightning within extra-tropical cyclones traversing the mid-latitudes, especially its oceans. To facilitate such studies we combine a recently constructed precipitation features (PF) database obtained from the Global Precipitation Measurement (GPM) mission constellation of satellites with lightning observations from the Geostationary Lightning Mapper (GLM) onboard GOES-16 and the Lightning Imaging Sensor (LIS) onboard the International Space Station (ISS). The goal of this study is to provide a new observationally-based view of the tropical to extra-tropical transition and its impact on lightning production. Such data fusion approaches, as presented here, will also be important in future satellite studies of convective precipitation.

Gatlin, Patrick↗
NASA NTRS2019

Overview, Update and Science of the GPM Validation Network Radar Database

A critical component of the Global Precipitation Measurement (GPM) Mission validation strategy involves use of dual-polarimetric (DP) ground-based radar (GR) products. Both operational and research DP radars across the U.S. and several international locations are used with coincident GPM dual-frequency precipitation radar (DPR) data in a significant expansion of the original TRMM-based “validation network architecture” (VN; Schwaller and Morris, 2011, J.Tech.). The VN radar databases consist of millions of geometrically matched DPR and GR precipitation volumes. Not only does it serve as a tool for validation of satellite-based precipitation retrieval algorithms and GR calibration but also a valuable resource for precipitation science and for complimenting future convective precipitation-related satellite missions.

Precipitation Science↗
NASA NTRS2019

VISAGE - A Visualization and Exploration Framework for Environmental Data

Diverse airborne and ground-based environmental observations are important technologies for disaster assessment and response, as well as for the validation of environmental satellite observations and atmospheric models which can improve forecasts. The VISAGE (Visualization for Integrated Satellite, Airborne and Ground-based data Exploration) project is working to provide three-dimensional visualization and basic analytics capabilities for such datasets in an interactive user interface. The use of cloud-native, server less technologies for analysis optimized data storage will position VISAGE for integration with other technologies into a Data Analytic Center Framework.

Conover, Helen↗
NASA NTRS2018

Monitoring Intense Thunderstorms in the Hindu-Kush Himalayan Region

Some of the most extreme thunderstorms on the planet routinely occur in the Hindu-Kush Himalaya (HKH) region— where many government organizations lack the resources needed to fully assess the risk associated with hazards that result from high impact convective weather. This project combines innovative numerical weather prediction, satellite-based precipitation and land imagery techniques into a high impact weather assessment tool kit (HIWAT) that is building the capabilities of national meteorological departments and other weather sensitive agencies in the HKH region to predict, observe and effectively respond to threats and impacts posed by thunderstorms that affect the region, thereby enhancing extreme weather resilience in the region.

extreme weather↗
NASA NTRS2018

Using a Knowledge Graph to Discover Earth Science Information

Knowledge graphs link key entities within a specific domain to other entities via relationships. Researchers are able to mine these relationships from numerous sources to infer new knowledge. Text extraction from peer-reviewed papers and scientific reports are untapped resources that can be leveraged by knowledge graphs to accelerate scientific discovery.

Freitag, Brian↗
NASA NTRS2018

Observing the Full Spectrum of the Rain Drop Size Distribution

GPM DSD retrievals exhibit inconsistencies between GV, DPR and Combined algorithm retrievals. Development of positive bias in convective Dm rain DSD noted, and strongest in KuPR retrieval. Associated epsilons are too low and result in markedly reduced convective rain rates (a current issue in the retrievals). Source may be NUBF. Issues with the large end of the DSD not withstanding, on the small end of the DSD, combined MPS and 2DVD measurements fit with generalized gamma functions exhibit strong potential for representing the entire spectrum of the DSD and subsequently the whole rain rate spectrum.

Hydrology↗
NASA NTRS2017

VISAGE Visualization for Integrated Satellite, Airborne and Ground-Based Data Exploration

The primary goal of the VISAGE project is to facilitate more efficient Earth Science investigations via a tool that can provide visualization and analytic capabilities for diverse coincident datasets. This proof-of-concept project will be centered around the GPM Ground Validation program, which provides a valuable source of intensive, coincident observations of atmospheric phenomena. The data are from a wide variety of ground-based, airborne and satellite instruments, with a wide diversity in spatial and temporal scales, variables, and formats, which makes these data difficult to use together. VISAGE will focus on "golden cases" where most ground instruments were in operation and multiple research aircraft sampled a significant weather event, ideally while the GPM Core Observatory passed overhead. The resulting tools will support physical process studies as well as satellite and model validation.

Data fusion↗
NASA NTRS2017

Building Scalable Knowledge Graphs for Earth Science

Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.

Ramachandran, Rahul↗
NASA NTRS2017

The Extratropical Transition of Tropical Storm Cindy From a GLM, ISS LIS and GPM Perspective

The distribution of lightning with respect to tropical convective precipitation systems has been well established in previous studies and more recently by the successful Tropical Rainfall Measuring Mission (TRMM). However, TRMM did not provide information about precipitation features poleward of +/-38 deg latitude. Hence we focus on the evolution of lightning within extra-tropical cyclones traversing the mid-latitudes, especially its oceans. To facilitate such studies, lightning data from the Geostationary Lightning Mapper (GLM) onboard GOES-16 was combined with precipitation features obtained from the Global Precipitation Measurement (GPM) mission constellation of satellites.

Precipitation↗
NASA NTRS2017

Consistent Measurement and Physical Character of the DSD: Disdrometer to Satellite

Objective: Validate GPM (Global Precipitation Measurement) Drop Size Distribution Retrievals: Drop size distributions (DSD) are critical to GPM DPR (Dual-frequency Precipitation Radar)-based rainfall retrievals; NASA GPM Science Requirements stipulate that the GPM Core observatory radar estimation of D (sub m) (mean diameter) shall be within plus or minus 0.5 millimeters of GV (Ground Validation); GV translates disdrometer measurements to polarimetric radar-based DSD and precipitation type retrievals (e.g., convective vs. stratiform (C/S)) for coincident match-up to GPM core overpasses; How well do we meet the requirement across product versions, rain types (e.g., C/S partitioning), and rain rates (heavy, light) and is behavior physically and internally consistent?

Validatio↗
NASA NTRS2017

Accurate Characterization of Rain Drop Size Distribution Using Meteorological Particle Spectrometer and 2D Video Disdrometer for Propagation and Remote Sensing Applications

Accurate measurements of rain drop size distributions (DSD), with particular emphasis on small and tiny drops, are presented. Measurements were conducted in two very different climate regions, namely Northern Colorado and Northern Alabama. Both datasets reveal a combination of (i) a drizzle mode for drop diameters less than 0.7 mm and (ii) a precipitation mode for larger diameters. Scattering calculations using the DSDs are performed at S and X bands and compared with radar observations for the first location. Our accurate DSDs will improve radar-based rain rate estimates as well as propagation predictions.

disdrometer↗