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Precipitation Observations and Prediction (2nd Edition)
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Precipitation Observations and Prediction (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (28 December 2024) | Viewed by 10047

Special Issue Editors

Dr. Xiaoming Shi

E-Mail Website
Guest Editor
Division of Environment and Sustainability, Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology, Hong Kong, China
Interests: turbulence; convection; clouds; extreme weather; deep learning
Special Issues, Collections and Topics in MDPI journals
Dr. Berry Wen

E-Mail Website
Guest Editor
Department of Geography, University of Florida, Gainesville, FL 32611-7315, USA
Interests: synergy of ground weather radar and satellite products; applications of remote sensing data to monitor and forecast natural hazards; AI/ML
Special Issues, Collections and Topics in MDPI journals
Dr. Lisa Milani

E-Mail Website
Guest Editor
1. NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
2. Earth Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, MD 20740, USA
Interests: shallow convective snowfall; microwave sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are excited to present the second edition of our Special Issue on “Precipitation Observation and Prediction.” Riding on the momentum of our inaugural edition, we eagerly invite contributions to this pivotal domain of climate and atmospheric science.

Precipitation patterns, in both their variability and distribution, shape the hydrological cycle — a cycle that is integral to our human needs and the vitality of our ecosystems. More than ever, we are witnessing a rise in extreme precipitation events and associated flash floods due to global warming, leading to considerable societal impacts. Enhancing our ability to observe and forecast precipitation across various scales remains paramount for refining weather and climate services for communities worldwide.

Within this Special Issue, our mission is to showcase groundbreaking research articles and comprehensive review papers that shed light on the latest in observational datasets, innovative precipitation retrieval algorithms, analysis methodologies, forecasting techniques, and the underpinning theories of Earth’s precipitation processes. This Issue is particularly interested in, but not limited to:

  1. Advances in remote sensing for precipitation (both solid and liquid) spanning local, regional, and global scales.
  2. Novel methods in remote sensing precipitation retrievals.
  3. Insights from long-term observational studies on climate change impacts.
  4. Innovative techniques to identify and assess precipitation patterns influenced by global warming.
  5. In-depth explorations of cloud and precipitation microphysical processes.
  6. Rigorous ground validations of remote-sensed precipitation data.
  7. Breakthroughs in numerical modeling and parameterization to enhance precipitation prediction accuracy.
  8. Comprehensive studies on sub-seasonal to seasonal precipitation forecasting.
  9. Forward-looking assessments of rainfall and snowfall patterns, focusing on extreme events.
  10. Strategies for integrating data across diverse precipitation observation or prediction systems.
  11. AI/ML in precipitation observations and predictions.

Dr. Xiaoming Shi
Dr. Berry Wen
Dr. Lisa Milani
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 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind 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

  • precipitation
  • remote sensing
  • climate change detection and attribution
  • numerical weather forecast
  • climate projection
  • extreme precipitation
  • snow

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Related Special Issue

Published Papers (7 papers)

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Research

19 pages, 19605 KiB  
Article
Skill Validation of High-Impact Rainfall Forecasts over Vietnam Using the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) and Dynamical Downscaling with the Weather Research and Forecasting Model
by Tran Anh Duc, Mai Van Khiem, Mai Khanh Hung, Dang Dinh Quan, Do Thuy Trang, Hoang Gia Nam, Lars R. Hole and Du Duc Tien
Atmosphere 2025, 16(2), 224; https://doi.org/10.3390/atmos16020224 - 16 Feb 2025
Viewed by 740
Abstract
This research evaluates the quality of high-impact rainfall forecasts across Vietnam and its sub-climate regions. The 3-day rainfall forecast products evaluated include the European Centre for Medium-Range Weather Forecasts (ECMWF) High-Resolution Integrated Forecasting System (IFS) and its downscaled outputs using the Weather Research [...] Read more.
This research evaluates the quality of high-impact rainfall forecasts across Vietnam and its sub-climate regions. The 3-day rainfall forecast products evaluated include the European Centre for Medium-Range Weather Forecasts (ECMWF) High-Resolution Integrated Forecasting System (IFS) and its downscaled outputs using the Weather Research and Forecasting (WRF) model with the Advanced Research WRF core (WRF-ARW): direct downscaling and downscaling with data assimilation. A full 5-year validation period from 2019 to 2025 was processed. The validation focused on basic rainfall thresholds and also considered the distribution of skill scores for intense events and extreme events. The validations revealed systematic errors (bias) in the models at low rainfall thresholds. The forecast skill was the lowest for northern regions, while the central regions exhibited the highest. For regions strongly affected by terrain, high-resolution downscaling with local observation data assimilation is necessary to improve the detectability of extreme events. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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31 pages, 3113 KiB  
Article
Automatic Threshold Selection for Generalized Pareto and Pareto–Poisson Distributions in Rainfall Analysis: A Case Study Using the NOAA NCDC Daily Rainfall Database
by Roberto Mínguez
Atmosphere 2025, 16(1), 61; https://doi.org/10.3390/atmos16010061 - 8 Jan 2025
Viewed by 893
Abstract
Both extreme-excess modeling and extreme-value analysis of precipitation events frequently utilize the Generalized Pareto (GP) distribution to model peaks above a selected threshold. However, selecting an appropriate threshold remains a complex and challenging task, which has discouraged many practitioners from employing Pareto or [...] Read more.
Both extreme-excess modeling and extreme-value analysis of precipitation events frequently utilize the Generalized Pareto (GP) distribution to model peaks above a selected threshold. However, selecting an appropriate threshold remains a complex and challenging task, which has discouraged many practitioners from employing Pareto or Pareto–Poisson distributions for extreme-value analysis. Recent analyses of threshold selection methods proposed in the technical literature, particularly when applied to rainfall records with high quantization levels, have shown that nonparametric methods are often unreliable. Additionally, methods relying on the asymptotic properties of the GP distribution tend to produce unrealistically high threshold estimates. In contrast, graphical methods and goodness-of-fit (GoF) metrics that account for the pre-asymptotic behavior of the GP distribution have demonstrated better performance. Despite these improvements, there remains no automatic and statistically robust methodology for threshold selection. This study develops an automatic, statistically sound procedure for optimal threshold selection, leveraging weighted mean square errors and internally studentized residuals. The proposed method outperforms existing approaches in terms of accuracy, as demonstrated through numerical experiments and its application to real-world data from the NOAA NCDC Daily Rainfall Database. Results indicate that the method not only improves threshold estimation precision but also enhances the reliability of extreme-value analysis for precipitation records, making it a valuable tool for hydrological applications. The findings emphasize the practical implications of the method for analyzing extreme rainfall events and its potential for broader climatological studies. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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30 pages, 7742 KiB  
Article
Rainfall Enhancement Downwind of Hills Due to Stationary Waves on the Melting Level and the Extreme Rainfall of December 2015 in the Lake District of Northwest England
by Edward Carroll
Atmosphere 2024, 15(10), 1252; https://doi.org/10.3390/atmos15101252 - 19 Oct 2024
Viewed by 1055
Abstract
This paper investigates how stationary gravity waves generated by flow over orography enhance rainfall, with particular attention to the role of induced waves in the melting level. The findings reveal a new mechanism by which gravity wave flow focuses precipitation, amplifying rainfall intensity [...] Read more.
This paper investigates how stationary gravity waves generated by flow over orography enhance rainfall, with particular attention to the role of induced waves in the melting level. The findings reveal a new mechanism by which gravity wave flow focuses precipitation, amplifying rainfall intensity downwind of hills. This mechanism, which depends on the differential velocities of rain and snow, offers fresh insights into how orographic effects can intensify rainfall. A two-dimensional diagnostic model based on linear gravity wave theory is used to investigate the record-breaking rainfall of December 2015 in the Lake District of northwest England. The pattern of ascent is shown to have a qualitatively good fit to that of the Met Office’s operational high-resolution UKV model averaged over 24 h, suggesting that orographically excited stationary waves were the principal cause of the rain. Precipitation trajectories imply that a persistent downstream elevated wave caused by the Isle of Man supported a spray of seeding ice particles directed towards the Lake District, and that these grew whilst suspended in strong upslope flow before being focused by the undulating melting-level into intense shafts of rain. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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18 pages, 11141 KiB  
Article
Inter-Model Spread in Representing the Impacts of ENSO on the South China Spring Rainfall in CMIP6 Models
by Xin Yin, Xiaofei Wu, Hailin Niu, Kaiqing Yang and Linglong Yu
Atmosphere 2024, 15(10), 1199; https://doi.org/10.3390/atmos15101199 - 8 Oct 2024
Viewed by 1023
Abstract
A major challenge for climate system models in simulating the impacts of El Niño–Southern Oscillation (ENSO) on the interannual variations of East Asian rainfall anomalies is the wide inter-model spread of outputs, which causes considerable uncertainty in physical mechanism understanding and short-term climate [...] Read more.
A major challenge for climate system models in simulating the impacts of El Niño–Southern Oscillation (ENSO) on the interannual variations of East Asian rainfall anomalies is the wide inter-model spread of outputs, which causes considerable uncertainty in physical mechanism understanding and short-term climate prediction. This study investigates the fidelity of 40 models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) in representing the impacts of ENSO on South China Spring Rainfall (SCSR) during the ENSO decaying spring. The response of SCSR to ENSO, as well as the sea surface temperature anomalies (SSTAs) over the tropical Indian Ocean (TIO), is quite different among the models; some models even simulate opposite SCSR anomalies compared to the observations. However, the models capturing the ENSO-related warm SSTAs over TIO tend to simulate a better SCSR-ENSO relationship, which is much closer to observation. Therefore, models are grouped based on the simulated TIO SSTAs to explore the modulating processes of the TIO SSTAs in ENSO affecting SCSR anomalies. Comparing analysis suggests that the warm TIO SSTA can force the equatorial north–south antisymmetric circulation in the lower troposphere, which is conducive to the westward extension and maintenance of the western North Pacific anticyclone (WNPAC). In addition, the TIO SSTA enhances the upper tropospheric East Asian subtropical westerly jet, leading to anomalous divergence over South China. Thus, the westward extension and strengthening of WNPAC can transport sufficient water vapor for South China, which is associated with the ascending motion caused by the upper tropospheric divergence, leading to the abnormal SCSR. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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16 pages, 9124 KiB  
Article
Changes in Convective Precipitation Reflectivity over the CONUS Revealed by High-Resolution Radar Observations from 2015 to 2021
by Haotong Jing, Zhi Li, Yixin Wen, Shang Gao, Yueya Wang, Weikang Qian and Jesse Kisembe
Atmosphere 2024, 15(6), 627; https://doi.org/10.3390/atmos15060627 - 24 May 2024
Viewed by 1260
Abstract
The change in extreme precipitation events in the conterminous United States (CONUS) has been of interest to the research communities in recent years for its intensification under environmental and climate change. Previous studies have not yet used sub-hourly precipitation observations to examine convective [...] Read more.
The change in extreme precipitation events in the conterminous United States (CONUS) has been of interest to the research communities in recent years for its intensification under environmental and climate change. Previous studies have not yet used sub-hourly precipitation observations to examine convective precipitation change over the CONUS. This study aims to fill the gap by examining convective precipitation, identified by radar reflectivity, in the CONUS using the state-of-the-art Multi-radar Multi-sensor data, operated at the NOAA/National Severe Storms Laboratory, with an unprecedentedly high spatial (1 km) and temporal (2 min) resolutions. These high-resolution data are expected to better capture the precipitation peak and the precipitation pattern. The results showed that in CONUS, precipitation reflectivity increased both in magnitude and the number of convective days from 2015 to 2021. For example, in 2019, 60% of areas showed an increase in the magnitude of precipitation, and the average number of convective days over CONUS has increased by 19%. Changes in precipitation also vary by season and region. This study highlights the need for continued monitoring and understanding of the evolving pattern of extreme precipitation in the CONUS, especially at sub-hourly frequency, as it exposes significant impacts on various sectors, including agriculture, infrastructure, and human health. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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22 pages, 8435 KiB  
Article
Evaluating the Effects of Raindrop Motion on the Accuracy of the Precipitation Inversion Algorithm by X-SAR
by Xueying Yu, Yanan Xie and Rui Wang
Atmosphere 2024, 15(3), 265; https://doi.org/10.3390/atmos15030265 - 22 Feb 2024
Viewed by 1138
Abstract
Precipitation has a profound impact on both human life and the natural environment. X-band synthetic aperture radar (X-SAR) utilizes high-resolution microwave remote-sensing technology, providing opportunities for global precipitation measurements. The current precipitation inversion algorithms from X-SAR measurements assume that precipitation particles remain relatively [...] Read more.
Precipitation has a profound impact on both human life and the natural environment. X-band synthetic aperture radar (X-SAR) utilizes high-resolution microwave remote-sensing technology, providing opportunities for global precipitation measurements. The current precipitation inversion algorithms from X-SAR measurements assume that precipitation particles remain relatively stationary with the ground. However, the motion of raindrops could potentially reduce the accuracy of these algorithms. In this study, we first established a functional relationship between raindrop motion and SAR echoes based on the standard deviation of the raindrop Doppler velocity spectrum. Secondly, an exploratory algorithm was proposed to retrieve rainfall distribution under the raindrop motion error model (RMM) and quantitatively calculate the precipitation inversion error caused by raindrop motion. In comparison to conditions where the atmosphere is stationary, when the standard deviation of the Doppler velocity spectrum of raindrops is 1.1 m/s, the relative error of the retrieved surface rain rate increases from 2.1% to 35.8%. Numerical simulations show that SAR echoes are sensitive to changes in the standard deviation of the Doppler velocity spectrum, and the impact of raindrop motion on the accuracy of X-SAR precipitation measurements cannot be neglected. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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23 pages, 14850 KiB  
Article
Analysis of Precipitation and Drought in the Main Southeastern Iberian River Headwaters (1952–2021)
by María José Estrela, David Corell, Juan Javier Miró and Raquel Niclós
Atmosphere 2024, 15(2), 166; https://doi.org/10.3390/atmos15020166 - 27 Jan 2024
Cited by 6 | Viewed by 2783
Abstract
This study evaluated the long-term changes in precipitation patterns and drought conditions in one of the key recharge areas of the hydrological system of southern and southeastern Spain, namely, the Sierra de Cazorla y Segura, which contains the headwater sectors of the catchment [...] Read more.
This study evaluated the long-term changes in precipitation patterns and drought conditions in one of the key recharge areas of the hydrological system of southern and southeastern Spain, namely, the Sierra de Cazorla y Segura, which contains the headwater sectors of the catchment basins of two important rivers, namely, the Guadalquivir and the Segura. The research covered a period of 70 years (1952–2021) and undertook an exhaustive analysis of data from 348 pluviometric stations. The most relevant results are as follows: (1) most areas experienced a decrease in the precipitation volume and number of rainy days during the study period; (2) summer and winter showed the most significant decreases; (3) weak and moderate precipitation (<40 mm/d) showed significant decreases in both volume and frequency, while heavy precipitation (≥40 mm/d) showed the opposite behavior; (4) the durations of dry periods increased, while the durations of wet periods decreased in most areas; and (5) the SPEI showed an increase under drought conditions. This research underscores the need for water resource management and resilience strategies with interdisciplinary relevance in the face of changing hydrological patterns. Full article
(This article belongs to the Special Issue Precipitation Observations and Prediction (2nd Edition))
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