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Atmosphere

Atmosphere is an international, peer-reviewed, open access journal of scientific studies related to the atmosphere published monthly online by MDPI.
The Italian Aerosol Society (IAS) and Working Group of Air Quality in European Citizen Science Association (ECSA) are affiliated with Atmosphere and their members receive a discount on the article processing charges.
Quartile Ranking JCR - Q3 (Meteorology and Atmospheric Sciences | Environmental Sciences)

All Articles (11,873)

Air Sensor Network Analysis Tool: R-Shiny Application

  • Karoline K. Barkjohn,
  • Todd Plessel and
  • Jiacheng Yang
  • + 8 authors

Poor air quality can harm human health and the environment. Air quality data are needed to understand and reduce exposure to air pollution. Air sensor data can supplement national air monitoring data, allowing for a better understanding of localized air quality and trends. However, these sensors can have limitations, biases, and inaccuracies that must first be controlled to generate data of adequate quality, and analyzing sensor data often requires extensive data analysis. To address these issues, an R-Shiny application has been developed to assist air quality professionals in (1) understanding air sensor data quality through comparison with nearby ambient air reference monitors, (2) applying basic quality assurance and quality control, and (3) understanding local air quality conditions. This tool provides agencies with the ability to more quickly analyze and utilize air sensor data for a variety of purposes while increasing the reproducibility of analyses. While more in-depth custom analysis may still be needed for some sensor types (e.g., advanced correction methods), this tool provides an easy starting place for analysis. This paper highlights two case studies using the tool to explore PM2.5 sensor performance under the conditions of wildfire smoke impacts in the Midwestern United States and the performance of O3 sensors for a year.

8 November 2025

A screenshot of ASNAT, showing data selection on the left and loaded data displayed on the map on the right. The display includes AQS and corrected PurpleAir sensor data across the Midwestern U.S. and has multiple tabs to further quality-assure, summarize, and visualize the data.

Urban flooding poses an escalating threat to riverine cities in Southern Asia’s tropical regions, primarily driven by rapid urban expansion. This study develops future projections of Intensity–Duration–Frequency (IDF) curves for major urban centers in Punjab, Pakistan, utilizing downscaled satellite-derived precipitation data. Baseline IDF curves were established using historical rainfall records from multiple meteorological stations. Among eight General Circulation Models (GCMs) assessed, EC-Earth3-Veg-LR demonstrated the highest skill in capturing extreme rainfall patterns relevant to the region. Future precipitation projections from this model were downscaled using the Equidistant Quantile Matching (EQM) technique and applied to generate IDF curves under two CMIP6 scenarios: SSP2-4.5 and SSP5-8.5. The results reveal a substantial increase in extreme rainfall intensities, particularly under the SSP5-8.5 scenario, with projected 100-year return period rainfall intensities rising by approximately 30–55% across key cities. The downscaled projections reveal more pronounced variations than the raw GCM outputs, emphasizing the importance of high-resolution climate data for accurate regional hydrological risk evaluation and effective urban flood resilience planning.

8 November 2025

Thermokarst lakes play a crucial role in regulating hydrological, ecological, and biogeochemical processes in permafrost regions. However, due to the limited spatial resolution of earlier satellite imagery, small thermokarst lakes—highly sensitive to climate change and permafrost degradation—have often been overlooked, hindering accurate spatiotemporal analyses. To address this limitation, five water indices—Modified Normalized Difference Water Index (MNDWI), Multi-Band Water Index (MBWI), Automated Water Extraction Index (AWEIsh and AWEInsh), and Red Edge Water Index (RWI)—were employed based on Sentinel-2 imagery from 2021 to extract thermokarst lakes in the Qinghai–Tibet Highway (QTH) region, China. Visual validation indicated that the Red Edge Water Index (RWI) yielded the best performance, with an error of only 10.21%, significantly lower than other indices (e.g., MNDWI: 41.36%; MBWI: 38.80%). Seasonal comparisons revealed that the applicability of different water indices varies, with autumn months (September to October) being the optimal period for lake extraction due to stable and unfrozen surface conditions. Using the RWI, 56 thermokarst lake drainage events were identified in the study area from 2016 to 2025 (as of September 2025), most occurring after 2019—likely associated with climatic factors—and small lakes were found to be more prone to drainage, accompanied by notable surface subsidence in drained regions. These findings are applicable across the Qinghai–Tibet Plateau (QTP) and provide a scientific basis for monitoring thermokarst lakes, delineating accurate lake boundaries, and exploring drainage mechanisms.

8 November 2025

Generalized frosts have a significant impact on the Pampa Húmeda of Argentina, particularly those without persistence (0DP), defined as events that do not last more than one day, and are the most frequent generalized frosts. This study investigates the dynamical and physical mechanisms that sustain these events, emphasizing the nonlinear interactions represented by the Rossby Wave Source (RWS) equation. Composite analysis of pressure, temperature, wind and geopotential height fields were performed, showing that 0DP events are related to abrupt cold air intrusion linked to the enhancement of upper levels troughs over the eastern Pacific Ocean and transient surface anticyclones over South America. This linear analysis only showed a lack of persistent upper-level maintenance and did not explain the dynamics of the rapid weakening of the circulation. For this reason, a nonlinear analysis based on the decomposition of the RWS equation into its advective and divergent terms is performed. The advective term only acts as an initial trigger, deepening troughs and favoring meridional cold air advection, while the divergent term dominates the events, representing 63–67% of the affected area. This term reinforces ridges, promotes subsidence and favors clear sky conditions that enhance nocturnal radiative cooling and frost formation. Positive anomalies of the divergent RWS term strengthen the ridge and advect cold air over the Pampa Húmeda, whereas subsequent negative anomalies over the southwestern Atlantic act as sinks of wave activity, leading to the rapid dissipation of the synoptic configuration. Consequently, the same mechanism that generates favorable conditions for frost development also determines their lack of persistence. These findings demonstrate that the short-lived nature of 0DP frosts is not due to the absence of dynamical forcing, but rather to nonlinear processes that both enable and constrain frost occurrence. This highlights the importance of incorporating nonlinear diagnostics, such as the RWS, to improve the understanding of short-lived atmospheric extremes.

7 November 2025

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Atmosphere - ISSN 2073-4433