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Atmosphere
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Meteorological Models: Recent Trends, Current Progress and Future Directions (2nd...
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Meteorological Models: Recent Trends, Current Progress and Future Directions (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 30 March 2027 | Viewed by 3732

Editors

Dr. Fei Yang

E-Mail Website
Guest Editor
College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
Interests: atmospheric parameter inversion and analysis; GNSS meteorology; atmospheric remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Lei Wang

E-Mail Website
Guest Editor
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Interests: GNSS positioning; GNSS remote sensing; atmosphere modeling; LEO navigation augmentation
Special Issues, Collections and Topics in MDPI journals
Dr. Qingzhi Zhao

E-Mail Website
Guest Editor
College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
Interests: GNSS meteorology and its applications; PWV retrieval; GNSS tomography
Special Issues, Collections and Topics in MDPI journals
Dr. Liangke Huang

E-Mail Website
Guest Editor
College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China
Interests: GNSS precise positioning; GNSS atmospheric sounding; tropospheric modeling
Special Issues, Collections and Topics in MDPI journals
Dr. Ming Shangguan

E-Mail Website
Guest Editor
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Interests: GNSS meteorology; atmosphere remote sensing; weather monitoring
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Di Zhang

E-Mail Website
Guest Editor
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079，China
Interests: GNSS; precise engineering surveying; surveying adjustment; multi-source fusion positioning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the second volume in a series of publications dedicated to recent trends, current progress and future directions in meteorological models (https://www.mdpi.com/journal/atmosphere/special_issues/meteorological_models).

The radio signals from Earth observation satellites, including GNSS and SAR, used in remote sensing are delayed and bent during their journey from the satellite to the Earth’s surface. To establish atmospheric models with high accuracy is a crucial task in Earth observation data processing. For this Special Issue, we welcome submissions of articles that discuss recent trends, current progress and future directions for the tropospheric model, ionospheric model, and other relevant atmospheric models, as well as articles that describe the establishment, comparison and application of various atmospheric models. New research relevant to atmospheric modeling, including radio occultation measurements, atmospheric inversion techniques, assimilation techniques and GNSS-R is also welcome.

Dr. Fei Yang
Dr. Lei Wang
Dr. Qingzhi Zhao
Dr. Liangke Huang
Dr. Ming Shangguan
Prof. Dr. Di Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. 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 as well as 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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • troposphere
  • ionosphere
  • atmospheric model
  • radio occultation measurement
  • atmospheric inversion
  • assimilation technique
  • GNSS-R
  • earth observation satellite

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Published Papers (3 papers)

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Research

19 pages, 5547 KB  
Article
Multiscale Analysis of Drought Characteristics in China Based on Precipitable Water Vapor and Climatic Response Mechanisms
by Ruohan Liu, Qiulin Dong, Lv Zhou, Fei Yang, Yue Sun, Yanru Yang and Sicheng Zhang
Atmosphere 2026, 17(2), 119; https://doi.org/10.3390/atmos17020119 - 23 Jan 2026
Viewed by 478
Abstract
Droughts are recognized as one of the most devastating extreme climate events, leading to severe socioeconomic losses and ecological degradation globally under climate change. With global warming, the frequency and intensity of extreme droughts are increasing, posing critical challenges to water resource management. [...] Read more.
Droughts are recognized as one of the most devastating extreme climate events, leading to severe socioeconomic losses and ecological degradation globally under climate change. With global warming, the frequency and intensity of extreme droughts are increasing, posing critical challenges to water resource management. The Standardized Precipitation Conversion Index (SPCI) has demonstrated potential in drought monitoring; however, its applicability across diverse climatic zones and multiple temporal scales remains inadequately validated. This study addresses this gap by establishing a novel multi-scale inversion analysis using ERA5-based precipitable water vapor (PWV) and precipitation data. SPCI is selected for its advantage in eliminating climatic background biases through probability normalization, overcoming limitations of traditional indices such as the Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI). We systematically evaluated the spatiotemporal evolution of Precipitation Efficiency (PE) and SPCI across four climatic zones in China. Results show that the first two principal components explain over 85% of the spatiotemporal variability of PE, with PC1 independently contributing from 82.05% to 83.80%. This high variance contribution underscores that the spatiotemporal patterns of PE are dominated by a few key climatic drivers, validating the robustness of the principal component analysis. SPCI exhibits strong correlation with SPI, exceeding 0.95 in the Tropical Monsoon Zone (TMZ) at scales of 1–6 months, indicating its utility for short-to-medium-term drought monitoring. Distinct zonal differentiation in PE patterns is revealed, such as the bimodal annual cycle in the Tropical-Subtropical Monsoon Composite Zone (TSMCZ). This study evaluates the performance of the SPCI against the widely used SPI and SPEI across four major climatic zones in China. It validates the SPCI’s applicability across China’s complex climates, providing a scientific basis for region-specific drought early warning and water resource optimization. Full article
(This article belongs to the Special Issue Meteorological Models: Recent Trends, Current Progress and Future Directions (2nd Edition))
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19 pages, 1524 KB  
Article
Variability, Prediction, and Simulation of Rainfall Erosivity Risk in the State of Sinaloa, Northwest Mexico
by Gabriel E. González González, Omar Llanes Cárdenas, Mariano Norzagaray Campos, Luz A. García Serrano, Román E. Parra Galaviz, Jeován A. Ávila Díaz and Marco A. Arciniega Galaviz
Atmosphere 2026, 17(1), 80; https://doi.org/10.3390/atmos17010080 - 14 Jan 2026
Viewed by 1068
Abstract
Observed rainfall erosivity risk (ORE) index is defined as the erosivity risk in the event of extreme rainfall events. ORE measures the kinetic energy of raindrops generated during a period of maximum precipitation intensity with the formula [...] Read more.
Observed rainfall erosivity risk (ORE) index is defined as the erosivity risk in the event of extreme rainfall events. ORE measures the kinetic energy of raindrops generated during a period of maximum precipitation intensity with the formula ORE=ED·TEI/10, where ED = erosivity density, TEI = total erosivity index, and ORE is measured in MJ mm ha−1 h−1 yr−1. The goal of this study is to model ORE, estimate its spatiotemporal variability, and predict (PRE) and simulate ORE for the state of Sinaloa (1969–2018). Five indices of rainfall erosivity were calculated: the modified Fournier index, precipitation concentration index, ED, TEI, and rainfall erosivity factor. The nonparametric trend in ORE was calculated. Using multiple nonlinear regressions (MNR), PRE (dependent variable) was calculated as a function of cumulative annual, annual average, seasonal average, and seasonal cumulative rainfall (independent variables). To simulate PRE, cumulative distribution functions, adjusted return periods (ARPs), and the 99th percentile were used. ORE ranged from 51.39 MJ mm ha−1 h−1 yr−1 in 1970 (Culiacán) to 92679.40 MJ mm ha−1 h−1 yr−1 in 1998 (Sta. C. de Alaya). The only year that had very high ORE at all nine stations was 1998. The only significant trend was ORE = 34.64 MJ mm ha−1 h−1 yr−1 (Culiacán). The nine PRE models were significantly predictive (Spearman correlation > 0.280). Guatenipa, Rosario, and Siqueros registered very high PRE, since one to eight extreme erosivity events per century are predicted on average. A new methodology is proposed for calculating ORE and PRE, which can be used to develop alternatives for managing and protecting agricultural land in the state considered “the breadbasket of Mexico”. Full article
(This article belongs to the Special Issue Meteorological Models: Recent Trends, Current Progress and Future Directions (2nd Edition))
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16 pages, 8313 KB  
Article
Evaluation of WRF Planetary Boundary Layer Parameterization Schemes for Dry Season Conditions over Complex Terrain in the Liangshan Prefecture, Southwestern China
by Jinhua Zhong, Debin Su, Zijun Zheng, Wenyu Kong, Peng Fang and Fang Mo
Atmosphere 2026, 17(1), 53; https://doi.org/10.3390/atmos17010053 - 31 Dec 2025
Cited by 1 | Viewed by 1465
Abstract
The planetary boundary layer (PBL) exerts strong control on heat, moisture, and momentum exchange, yet its representation over the steep mountains and deep valleys of Liangshan remains poorly understood. This study evaluates six Weather Research and Forecasting (WRF) PBL schemes (ACM2, BL, MYJ, [...] Read more.
The planetary boundary layer (PBL) exerts strong control on heat, moisture, and momentum exchange, yet its representation over the steep mountains and deep valleys of Liangshan remains poorly understood. This study evaluates six Weather Research and Forecasting (WRF) PBL schemes (ACM2, BL, MYJ, MYNN2.5, QNSE, and YSU) using multi-source observations from radiosondes, surface stations, and wind profiling radar during clear-sky dry-season cases in spring and winter. The schemes exhibit substantial differences in governing turbulent mixing and stratification. For the specific cases studied, QNSE best reproduces 2 m temperature in both seasons by realistically capturing nocturnal stability and large diurnal ranges, while non-local schemes overestimate nighttime temperatures due to excessive mixing. MYNN2.5 performs robustly for boundary layer growth in spring, and BL aligns most closely with radar-derived PBL height (PBLH). Vertical profile comparisons show that QNSE and MYJ better represent the lower–middle level thermodynamic structure, whereas all schemes underestimate extreme near-surface winds, reflecting unresolved terrain-induced variability. PBLH simulations reproduce diurnal cycles but differ in amplitude, with QNSE occasionally producing unrealistic spikes. Overall, no scheme performs optimally for all variables. However, QNSE and MYNN2.5 show the most balanced performance across seasons. These findings provide guidance for selecting PBL schemes for high-resolution modeling and fire–weather applications over complex terrain. Full article
(This article belongs to the Special Issue Meteorological Models: Recent Trends, Current Progress and Future Directions (2nd Edition))
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