Dear Colleagues, This is shu-peng Ben Ho from NOAA/STAR. You are cordially invited to submit your recent studies on GNSS RO to the Remote Sensing GNSS RO special issue ( https://www.mdpi.com/journal/remotesensing/special_issues/31G3890CC5#editors ). This Special Issue is designed to highlight a pivotal phase in the evolution of GNSS radio occultation. The field is moving beyond merely demonstrating broad usefulness—it is now increasingly defined by deeper scientific and technological questions, including bias diagnosis, uncertainty characterization, multi-mission consistency, lower-atmospheric retrieval challenges, operational value in numerical weather prediction, and emerging roles in ionospheric and space weather applications. With the rapid expansion of commercial constellations, international missions, and advanced processing approaches, GNSS RO is evolving from a mature observing technique into a more accurate, traceable, and integrable benchmark for remote sensing observations of Earth systems. This Special Issue aims to collect high-quality contributions that advance GNSS RO through methodological innovation, observational physics insights, rigorous inter-mission assessment, impactful applications, and the use of AI to improve the RO retrievals. This Special Issue will focus on recent advances in GNSS radio occultation in remote sensing, with particular emphasis on observational physics, bias and uncertainty diagnosis, multi-mission harmonization, advanced retrieval methods, and innovative applications in weather, climate, boundary-layer studies, high-impact events, ionospheric research, and space weather. We especially welcome contributions that address the following broader questions: How should GNSS RO observation errors and biases be characterized? How can consistency and long-term comparability be established across missions and processing systems? How can lower-tropospheric and boundary-layer retrieval be further improved? In what ways can GNSS RO serve as a benchmark for data assimilation and model evaluation? How might new signals, commercial constellations, AI-based methods, and future observing-system designs reshape the field? The Special Issue welcomes original research articles, review papers, and perspective articles covering, but not limited to, neutral atmospheric and ionospheric GNSS RO observations, retrievals, validation, data quality control, standardization, application assessment, and future system concepts. Topics include, but are not limited to, the following: - GNSS RO observation bias, uncertainty quantification, and error characterization; - Multi-mission consistency, harmonization, and climate data record development; - Geometry-related effects, tangent-point drift, antenna-viewing dependencies, and non-sphericity; - Advances in lower-tropospheric and boundary-layer GNSS RO retrieval; - GNSS RO data assimilation in global, regional, and convective-scale NWP; - GNSS RO as a benchmark observation for weather and climate model evaluation; - GNSS RO applications to tropical cyclones, heavy rainfall, severe weather, and other high-impact events; - Scientific and operational assessment of commercial GNSS RO constellations; - Ionospheric GNSS RO, TEC retrieval, and space weather applications; - AI, machine learning, and advanced inverse methods for GNSS RO; - Next-generation GNSS signals, receiver technologies, and future observing-system design; - Data quality control, metadata standards, reproducibility, and best practices in GNSS RO science; - The use of AI to improve the RO retrievals. Dr. Shu-peng Ho Dr. Michael E. Gorbunov *Guest Editors* *Manuscript Submission Information* Manuscripts should be submitted online at *www.mdpi.com* <https://www.mdpi.com/> by *registering* <https://www.mdpi.com/user/register/> and *logging in to this website* <https://www.mdpi.com/user/login/>. Once you are registered, *click here to go to the submission form* <https://susy.mdpi.com/user/manuscripts/upload/?journal=remotesensing>. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles, and short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-masked peer-review process. A guide for authors and other relevant information for manuscript submission are available on the *Instructions for Authors* <https://www.mdpi.com/journal/remotesensing/instructions> page. *Remote Sensing* <https://www.mdpi.com/journal/remotesensing/> is an international, peer-reviewed, open-access, semimonthly journal published by MDPI. Please visit the *Instructions for Authors* <https://www.mdpi.com/journal/remotesensing/instructions> page before submitting a manuscript. The *Article Processing Charge (APC)* <https://www.mdpi.com/about/apc/> for publication in this *open-access* <https://www.mdpi.com/about/openaccess/> journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's *English editing service* <https://www.mdpi.com/authors/english> before publication or during author revisions. *Keywords* - GNSS RO - boundary-layer retrievals - weather applications - atmospheric applications - benchmark observation for weather and climate model evaluation - AI applications on RO inversion *==============================================* *Shu-peng Ben Ho, Ph. D.* *GNSS Radio Occultation Physical** Scientist* *NOAA Center for Satellite Applications and Research (STAR)* *NCWCP, E/RA-21 Office# 2824* *5830 University Research Court, * *Riverdale Park, MD 20737* *Tel : (301) 683-3596* *Email: shu-peng.ho@noaa.gov <shu-peng.ho@noaa.gov>* *STAR GNSS RO Center: **https://gpsmet.umd.edu/gnssro/index.php <https://gpsmet.umd.edu/gnssro/index.php>* *STAR GNSS RO Data Service: **https://gpsmet.umd.edu/gnssro/download.php <https://gpsmet.umd.edu/gnssro/download.php>* *Publication: researchgate.net/profile/Shu-Peng-Ho/publications <http://researchgate.net/profile/Shu-Peng-Ho/publications>* *==============================================*