HelioWebJie Gong
flowchart
A[Jie Gong]
AC["Associated Concepts (25)"]
AW["Authored Works (10)"]
CA["Linked Co-Authors (10)"]
CI["Linked Collaborating Institutions (13)"]
A== dcterms:relation ==>AC
AW== author ==>A
AW== author ==>CA
AW== affil ==>CI
click AC "#associated-concepts"
click AW "#authored-works"
click CA "#co-authors"
click CI "#collaborating-institutions"
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NO["add outgoing edge"]
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- ORCiD
- https://orcid.org/0000-0001-5897-7023
- OpenAlex ID
- https://openalex.org/A5061240396 (API record)
Associated Concepts [?]
- Computer science
- Engineering
- Physics
- Geography
- Geology
- Operating system
- Environmental science
- Quantum mechanics
- Political science
- Remote sensing
- Law
- Meteorology
- Mathematics
- Economics
- Biology
- Optics
- Artificial intelligence
- Programming language
- History
- Astronomy
- Archaeology
- Aerospace engineering
- Thermodynamics
- Climatology
- Mechanical engineering
Authored Works
sorted by decreasing year, and then by display-name
- Unprecedented spatiotemporal coverage from COSMIC-2 and Spire GNSS-RO constellations for atmospheric and ionospheric studies
- Observing Ice Phase Clouds and Precipitation with Millimeter- and Submillimeter-wave Radiometry during the IMPACTS field campaign: Algorithm Development for the Emerging Class of Microwave Radiometers
- Lower atmospheric sounding capability from Spire and operational GNSS RO products for Arctic PBL studies
- Analyzing 2020 Total Solar Eclipse Generated Gravity Waves on Satellite Images
- A Machine-learning Based Marine Atmospheric Boundary Layer (MABL) Moisture Profile Retrieval Product from GNSS-RO Deep Refraction Signals
- 3D Reconstruction of Multi-layer cloud masks using Advanced Baseline Imager (ABI) Observations trained on CloudSat/CALIPSO data using a deep neural network approach
- Regional Ray-Tracing of Atmospheric Gravity Waves During the Total Solar Eclipse Over South America on December 14th, 2020
- Passive Microwave Precipitation Type Classification Using Machine Learning Results Comparison and Lessons Learnt
- GNSS-RO Deep Refraction Signals for Sensing PBL Water Vapor
- A GCM-Oriented and Artificial Intelligence Based Passive Microwave Diurnal Ice/Snow Cloud Retrieval Product using CloudSat/CALIPSO as the Baseline
Linked Co-Authors
- Andrew J. Heymsfield
- C. O. Ao
- C. Wang
- D. Barahona
- Daniel J. Emmons
- Dong L. Wu
- Joseph A. Santanello
- Lisa Milani
- Manisha Ganeshan
- Panagiotis Vergados
Linked Collaborating Institutions
- Catholic University, Washington DC
- Chalmers University of Technology, Sweden
- Jet Propulsion Laboratory
- Montana State University, Bozeman
- Morgan State University, Maryland
- NASA Goddard Space Flight Center, Maryland
- National Center for Atmospheric Research, Colorado
- Oklahoma State University
- Science Systems and Applications Inc., Maryland
- University of Maryland, Baltimore County
- University of Maryland, College Park
- University of Montana
- University of Utah
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