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Atmosphere
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Storms, Jets and Other Meteorological Phenomena in Coastal Seas
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Storms, Jets and Other Meteorological Phenomena in Coastal Seas

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

Deadline for manuscript submissions: closed (15 June 2018) | Viewed by 55711

Special Issue Editors

Prof. Dr. Hans von Storch

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Guest Editor
Institute for Coastal Research, Helmholtz-Zentrum Geesthacht, 21502 Geesthacht, Germany
Interests: climate; climate change; climate statistics; detection and attribtion; adaptation; coastal seas and regions; marine risks; climate policy; climate communication; climate knowledge
Dr. Delei Li

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Guest Editor
Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China
Interests: extreme wind and wave; regional climate change; climate project; compound extremes
Special Issues, Collections and Topics in MDPI journals
Dr. Leone Cavicchia

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Guest Editor
School of Earth Sciences, University of Melbourne, Melbourne, VIC 3010, Australia
Interests: east coast lows; tropical cyclones; Mediterranean cyclones; regional climate modelling; extreme events; Mediterranean climate
Dr. Oliver Krueger

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Guest Editor
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Max-Planck-Str. 1, 21502 Geesthacht, Germany
Interests: long-term mid-latitude storminess; climate and weather extreme events; feedback mechanisms between the ocean; waves and atmosphere

Special Issue Information

Dear Colleagues,

Coastal regions are featured by high population densities and high levels of development, especially in the 21st century. However, properties, life and environment in coastal regions are greatly threatened by coastal hazards, which is, in most cases, caused by coastal meteorological events. This Special Issue aims to collect current state-of-the-art studies on the statistics and the changes of hazardous regional meteorological events in coastal regions, in particular meso-scale and synoptic scale storms (polar lows, Mediterranean cyclones including medicanes, Australian east coast lows, tropical and midlattude baroclinic storms) and coastal low-level jets.

Topics of interest include, but are not limited to:

  1. Analyses of the frequency and characteristics of regional meteorological events based on observation data, re-analyses and simulations, both regionally and globally;
  2. Identification of links between low-frequency large-scale atmospheric configurations and the tendency for generating such regional phenomena;
  3. Historical and future climate changes in coastal meteorological events;
  4. Changes in ocean states, such as waves and storm surges related to coastal meteorological events;
  5. Risks and impact assessment of such phenomena for human activities and coastal environment.
Prof. Hans von Storch
Dr. Delei Li
Dr. Leone Cavicchia
Dr. Oliver Krueger
Guest Editors

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Published Papers (10 papers)

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Research

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23 pages, 5507 KiB  
Article
Deep Convolutional Neural Networks Capabilities for Binary Classification of Polar Mesocyclones in Satellite Mosaics
by Mikhail Krinitskiy, Polina Verezemskaya, Kirill Grashchenkov, Natalia Tilinina, Sergey Gulev and Matthew Lazzara
Atmosphere 2018, 9(11), 426; https://doi.org/10.3390/atmos9110426 - 31 Oct 2018
Cited by 24 | Viewed by 5073
Abstract
Polar mesocyclones (MCs) are small marine atmospheric vortices. The class of intense MCs, called polar lows, are accompanied by extremely strong surface winds and heat fluxes and thus largely influencing deep ocean water formation in the polar regions. Accurate detection of polar mesocyclones [...] Read more.
Polar mesocyclones (MCs) are small marine atmospheric vortices. The class of intense MCs, called polar lows, are accompanied by extremely strong surface winds and heat fluxes and thus largely influencing deep ocean water formation in the polar regions. Accurate detection of polar mesocyclones in high-resolution satellite data, while challenging, is a time-consuming task, when performed manually. Existing algorithms for the automatic detection of polar mesocyclones are based on the conventional analysis of patterns of cloudiness and they involve different empirically defined thresholds of geophysical variables. As a result, various detection methods typically reveal very different results when applied to a single dataset. We develop a conceptually novel approach for the detection of MCs based on the use of deep convolutional neural networks (DCNNs). As a first step, we demonstrate that DCNN model is capable of performing binary classification of 500 × 500 km patches of satellite images regarding MC patterns presence in it. The training dataset is based on the reference database of MCs manually tracked in the Southern Hemisphere from satellite mosaics. We use a subset of this database with MC diameters falling in the range of 200–400 km. This dataset is further used for testing several different DCNN setups, specifically, DCNN built “from scratch”, DCNN based on VGG16 pre-trained weights also engaging the Transfer Learning technique, and DCNN based on VGG16 with Fine Tuning technique. Each of these networks is further applied to both infrared (IR) and a combination of infrared and water vapor (IR + WV) satellite imagery. The best skills (97% in terms of the binary classification accuracy score) is achieved with the model that averages the estimates of the ensemble of different DCNNs. The algorithm can be further extended to the automatic identification and tracking numerical scheme and applied to other atmospheric phenomena that are characterized by a distinct signature in satellite imagery. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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16 pages, 7532 KiB  
Article
PAN–Precursor Relationship and Process Analysis of PAN Variations in the Pearl River Delta Region
by Jun Yuan, Zhenhao Ling, Zhe Wang, Xi Lu, Shaojia Fan, Zhuoran He, Hai Guo, Xuemei Wang and Nan Wang
Atmosphere 2018, 9(10), 372; https://doi.org/10.3390/atmos9100372 - 25 Sep 2018
Cited by 20 | Viewed by 4573
Abstract
Peroxy acetyl nitrate (PAN) is an important photochemical product formed from the reactions between volatile organic compounds (VOCs) and nitrogen oxides (NOx) under sunlight. In this study, a field measurement was conducted at a rural site (the backgarden site, or BGS) [...] Read more.
Peroxy acetyl nitrate (PAN) is an important photochemical product formed from the reactions between volatile organic compounds (VOCs) and nitrogen oxides (NOx) under sunlight. In this study, a field measurement was conducted at a rural site (the backgarden site, or BGS) of the Pearl River Delta (PRD) region in 2006, with the 10 min maximum PAN mixing ratios of 3.9 ppbv observed. The factors influencing the abundance of PAN at the BGS site was evaluated by the process analysis through the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model. The results suggested that the increase of PAN abundance at the BGS site was mainly controlled by the gas-phase chemistry, followed by vertical transport, while its loss was modulated mainly by dry deposition and horizontal transport. As the dominant important role of gas-phase chemistry, to provide detailed information on the photochemical formation of PAN, a photochemical box model with near-explicit chemical mechanism (i.e., the master chemical mechanism, MCM) was used to explore the relationship of photochemical PAN formation with its precursors based on the measured data at the BGS site. It was found that PAN formation was VOC-limited at the BGS site, with the oxidation of acetaldehyde the most important pathway for photochemical PAN production, followed by the oxidation and photolysis of methylglyoxal (MGLY). Among all the primary VOC precursors, isoprene and xylenes were the main contributors to PAN formation. Overall, our study provides new insights into the PAN photochemical formation and its controlling factors, and highlighted the importance of gas chemistry on the PAN abundance in the PRD region. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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30 pages, 8604 KiB  
Article
A Comparison between 3DVAR and EnKF for Data Assimilation Effects on the Yellow Sea Fog Forecast
by Xiaoyu Gao, Shanhong Gao and Yue Yang
Atmosphere 2018, 9(9), 346; https://doi.org/10.3390/atmos9090346 - 3 Sep 2018
Cited by 15 | Viewed by 6659
Abstract
The data assimilation method to improve the sea fog forecast over the Yellow Sea is usually three-dimensional variational assimilation (3DVAR), whereas ensemble Kalman filter (EnKF) has not yet been applied to this weather phenomenon. In this paper, two sea fog cases over the [...] Read more.
The data assimilation method to improve the sea fog forecast over the Yellow Sea is usually three-dimensional variational assimilation (3DVAR), whereas ensemble Kalman filter (EnKF) has not yet been applied to this weather phenomenon. In this paper, two sea fog cases over the Yellow sea, one spread widely and the other spread narrowly along the coastal area, are studied in detail by a series of numerical experiments with 3DVAR and EnKF based on the Grid-point Statistical Interpolation (GSI) system and the Weather Research and Forecasting (WRF) model. The results show that the assimilation effect of EnKF outperforms that of 3DVAR: for the widespread-fog case, the probability of detection and equitable threat scores of the forecasted sea fog area are improved respectively by ~57.9% and ~55.5%; the sea fog formation of the other case completely mis-forecasted by 3DVAR was produced successfully by EnKF. These improvements of EnKF relative to 3DVAR benefit from its flow-dependent background error covariances, resulting in more realistic depiction of sea surface wind for the widespread-fog case and better moisture distribution for the other case in the initial conditions. More importantly, the correlation between temperature and humidity in the background error covariances of EnKF plays a vital role in the response of moisture to the assimilation of temperature, which leads to a great improvement in the initial moisture conditions for sea fog forecast. Extra sensitivity experiments of EnKF indicate that the forecast result is sensitive to ensemble inflation and localization factors, in particular, highly sensitive to the latter. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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18 pages, 8960 KiB  
Article
How Sea Fog Influences Inland Visibility on the Southern China Coast
by Jianxiang Sun, Huijun Huang, Suping Zhang and Weikang Mao
Atmosphere 2018, 9(9), 344; https://doi.org/10.3390/atmos9090344 - 3 Sep 2018
Cited by 7 | Viewed by 6591
Abstract
Sea fog can lead to inland fog on the southern China coast, affecting visibility on land. To better understand how such fog influences inland visibility, we observed two sea-fog cases at three sites (over sea, at coast, and inland) and analyzed the results [...] Read more.
Sea fog can lead to inland fog on the southern China coast, affecting visibility on land. To better understand how such fog influences inland visibility, we observed two sea-fog cases at three sites (over sea, at coast, and inland) and analyzed the results here. Our analysis suggests four factors may be key: (1) The synoptic pattern is the decisive factor determining whether fog forms inland. First, sea fog and low clouds form when the synoptic pattern involves warm, moist air moving from a warmer sea-surface temperature (SST) region to a colder SST region near the coast. Then, inland fog tends to occur under this low-cloud background with relatively large horizontal-vapor transport. A greater horizontal-vapor transport results in denser fog with higher liquid-water content. Conversely, a strong horizontal advection of temperature with less horizontal-vapor transport can hinder inland-fog formation. (2) Local cooling (including ground radiative cooling) helps promote inland fog formation. (3) Fog formation requires low wind speed and small turbulent kinetic energy (TKE). The small TKE helps the vapor accumulate close to the surface and maintain the local cooling effect. (4) Fog formation is promoted by having the energy flux downward at night with the land surface cooling the atmosphere as well as having lower soil temperature and higher soil humidity. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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14 pages, 7673 KiB  
Article
Tracking Jianghuai Cyclones in China and Their Climate Characteristics
by Lan Xia and Yue Zhou
Atmosphere 2018, 9(9), 341; https://doi.org/10.3390/atmos9090341 - 30 Aug 2018
Cited by 2 | Viewed by 3605
Abstract
A Jianghuai cyclone is an extratropical cyclone, which influences the middle and lower reaches of the Yangtze River and Huai River basins in China. According to the definition of Jianghuai cyclones, statistics of their climate characteristics from 1979 to 2010 are obtained by [...] Read more.
A Jianghuai cyclone is an extratropical cyclone, which influences the middle and lower reaches of the Yangtze River and Huai River basins in China. According to the definition of Jianghuai cyclones, statistics of their climate characteristics from 1979 to 2010 are obtained by an objective detection and tracking algorithm using ERA-Interim reanalysis data. The results show that the frequency of Jianghuai cyclones has a strong year-to-year variability but no obvious trend. Jianghuai cyclones are most frequent in May but fewest in December. As the cold air is active in spring, which interacts with the warm air from the southwest of the subtropical high at the Yangtze-Huai River region, it makes Jianghuai cyclones occur more frequently in this season. The main origins of Jianghuai cyclones are located in the Poyang Lake region, Dongting Lake region, and Dabie Mountain area. The maximum deepening rate of 0–2 hPa/6h is featured in 66.4% of Jianghuai cyclones. Over 40% of Jianghuai cyclones have a mean deepening rate of 0–1 hPa/6h. The lifetime of Jianghuai cyclones is short, mainly lasting for one to two days. In addition, background characteristics are compared between the formation, climax, and decaying periods of Jianghuai cyclones. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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17 pages, 6525 KiB  
Article
Analysis on the Extreme Sea Levels Changes along the Coastline of Bohai Sea, China
by Jianlong Feng, Delei Li, Hui Wang, Qiulin Liu, Jianli Zhang, Yan Li and Kexiu Liu
Atmosphere 2018, 9(8), 324; https://doi.org/10.3390/atmos9080324 - 20 Aug 2018
Cited by 11 | Viewed by 4149
Abstract
Using hourly sea level data from four tide gauges, the changes of the extreme sea level in the Bohai Sea were analyzed in this work. Three components (i.e., mean sea level, tide and surge) as well as the tide–surge interaction were studied to [...] Read more.
Using hourly sea level data from four tide gauges, the changes of the extreme sea level in the Bohai Sea were analyzed in this work. Three components (i.e., mean sea level, tide and surge) as well as the tide–surge interaction were studied to find which component was important in the changes of extreme sea levels. Significant increasing trends exist in the mean sea level at four tide gauges from 1980 to 2016, and the increase rate ranges from 0.2 to 0.5 cm/year. The mean high tide levels show positive trends at four tide gauges, and the increasing rate (0.1 to 0.3 cm/year) is not small compared with the long-term trends of the mean sea levels. However, the mean tidal ranges show negative trends at Longkou, Qinhuangdao and Tanggu, with the rate from about −0.7 to −0.2 cm/year. At Qinhuangdao and Tanggu, the annual surge intensity shows explicit long-term decreasing trend. At all four tide gauges, the storm surge intensity shows distinct inter-annual variability and decadal variability. All four tide gauges show significant tide–surge interaction, the characteristics of the tide–surge interaction differ due to their locations, and no clear long-term change was found. Convincing evidence implies that the extreme sea levels increase during the past decades from 1980 to 2016 at all tide gauges, with the increasing rate differing at different percentile levels. The extreme sea level changes in the Bohai Sea are highly affected by the changes of mean sea level and high tide level, especially the latter. The surge variation contributes to the changes of extreme sea level at locations where the tide–surge interaction is relatively weak. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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15 pages, 3391 KiB  
Article
Extreme Wave Storms and Atmospheric Variability at the Spanish Coast of the Bay of Biscay
by Domingo Rasilla, Juan Carlos García-Codron, Carolina Garmendia, Sixto Herrera and Victoria Rivas
Atmosphere 2018, 9(8), 316; https://doi.org/10.3390/atmos9080316 - 13 Aug 2018
Cited by 6 | Viewed by 4297
Abstract
This paper examines the characteristics and long-term variability of storminess for the Spanish coast of the Bay of Biscay for the period 1948 to 2015, by coupling wave (observed and modelled) and atmospheric datasets. The diversity of atmospheric mechanisms that are responsible for [...] Read more.
This paper examines the characteristics and long-term variability of storminess for the Spanish coast of the Bay of Biscay for the period 1948 to 2015, by coupling wave (observed and modelled) and atmospheric datasets. The diversity of atmospheric mechanisms that are responsible for wave storms are highlighted at different spatial and temporal scales: synoptic (cyclone) and low frequency (teleconnection patterns) time scales. Two types of storms, defined mostly by wave period and storm energy, are distinguished, resulting from the distance to the forcing cyclones, and the length of the fetch area. No statistically significant trends were found for storminess and the associated atmospheric indices over the period of interest. Storminess reached a maximum around the decade of the 1980s, while less activity occurred at the beginning and end of the period of study. In addition, the results reveal that only the WEPI (West Europe Pressure Anomaly Index), EA (Eastern Atlantic), and EA/WR (Eastern Atlantic/Western Russia) teleconnection patterns are able to explain a substantial percentage of the variability in storm climate, suggesting the importance of local factors (W-E exposition of the coast) in controlling storminess in this region. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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19 pages, 7831 KiB  
Article
Analysis of Wave Distribution Simulated by WAVEWATCH-III Model in Typhoons Passing Beibu Gulf, China
by Weizeng Shao, Yexin Sheng, Huan Li, Jian Shi, Qiyan Ji, Wei Tan and Juncheng Zuo
Atmosphere 2018, 9(7), 265; https://doi.org/10.3390/atmos9070265 - 15 Jul 2018
Cited by 34 | Viewed by 5656
Abstract
The Beibu Gulf is an important offshore region in the South China Sea for the fishing industry and other human activities. In 2017, typhoons Doksuri and Khanun passed the Beibu Gulf in two paths, at maximum wind speeds of up to 50 m/s. [...] Read more.
The Beibu Gulf is an important offshore region in the South China Sea for the fishing industry and other human activities. In 2017, typhoons Doksuri and Khanun passed the Beibu Gulf in two paths, at maximum wind speeds of up to 50 m/s. Typhoon Doksuri passed the Beibu Gulf through the open waters of the South China Sea and Typhoon Khanun moved towards the Beibu Gulf through the narrow Qiongzhou Strait. The aim of this study is to analyze the typhoon-induced wave distribution in the Beibu Gulf. WAVEWATCH-III (WW3) is a third-generation numeric wave model developed by the National Oceanic and Atmospheric Administration (NOAA), which has been widely used for sea wave research. The latest version of the WW3 (5.16) model provides three packages of nonlinear term for four wave components (quadruplets) wave–wave interactions, including Discrete Interaction Approximation (DIA), Full Boltzmann Integral (WRT), and Generalized Multiple DIA (GMD) with two kinds of coefficients, herein called GMD1 and GMD2. These four packages have been conveniently implemented for simulating wave fields in two typhoons after taking winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) at 0.125° grids as the forcing fields. It was found that the GMD2 package was the recommended option of the nonlinear term for quadruplets wave–wave interactions due to the minimum error when comparing a number of simulated results from the WW3 model with significant wave height (SWH) from ECMWF and altimeter Jason-2. Then the wave distribution simulated by the WW3 model employing the GMD2 package was analyzed. In the case of Typhoon Doksuri, wind-sea dominated in the early and middle stages while swell dominated at the later stage. However, during Typhoon Khanun, wind-sea dominated throughout and swell distributed outside the bay around the east of Hainan Island, because the typhoon-induced swell at mesoscale was difficult to propagate into the Beibu Gulf through the narrow Qiongzhou Strait. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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20 pages, 7463 KiB  
Article
Detecting Coastline Change with All Available Landsat Data over 1986–2015: A Case Study for the State of Texas, USA
by Nan Xu
Atmosphere 2018, 9(3), 107; https://doi.org/10.3390/atmos9030107 - 14 Mar 2018
Cited by 78 | Viewed by 8378
Abstract
Coastline change often results from social and natural factors, such as human activities in the coastal zone, long-term and short-term sea level change, hurricane occurrences, subsequent recovery, and so on. Tracking coastline change is essential to deepen our understanding of coastal responses to [...] Read more.
Coastline change often results from social and natural factors, such as human activities in the coastal zone, long-term and short-term sea level change, hurricane occurrences, subsequent recovery, and so on. Tracking coastline change is essential to deepen our understanding of coastal responses to these factors. Such information is also required for land use planning and sustainable development of coastal zones. In this context, we aimed to collect all available Landsat data (TM: Thematic Mapper, ETM+: Enhanced Thematic Mapper Plus and OLI: Operational Land Imager) over 1986–2015 for tracking the coastline dynamic and estimating its change rate in the State of Texas, USA. First, the land vs. water maps at an annual scale were derived from the satellite images. The border between land and water represents the coastline in this study. Second, the annual land area was obtained to characterize the coastline dynamic and a linear regression model was used for estimating the change rate. We also analyzed the potential driving factors of the observed coastline change. The results reveal that the coastline in the State of Texas changed at a rate of −0.154 ± 0.063 km2/year from 1986 to 2015, which indicates that the coastline has mainly experienced an erosion over the past three decades. Specifically, 52.58% of the entire coastline retreated to the land while a 47.42% portion advanced to the ocean. Long-term sea level rise can result in the erosion of coastline. Hurricane occurrences can explain the relatively strong coastline erosion. Besides, significant difference between the coastline change rate with a higher curvature and a lower curvature was observed. This study establishes a general method for detecting coastline change at large spatial and long-term temporal scales, by using remote sensing that can give fundamental information on coastline change. This is important for making scientific and reasonable policies of sustainable development of coastal zones. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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Review

Jump to: Research

16 pages, 5607 KiB  
Review
The Concept of Large-Scale Conditioning of Climate Model Simulations of Atmospheric Coastal Dynamics: Current State and Perspectives
by Hans Von Storch, Leone Cavicchia, Frauke Feser and Delei Li
Atmosphere 2018, 9(9), 337; https://doi.org/10.3390/atmos9090337 - 27 Aug 2018
Cited by 3 | Viewed by 5391
Abstract
We review the state of dynamical downscaling with scale-constrained regional and global models. The methodology, in particular spectral nudging, has become a routine and well-researched tool for hindcasting climatologies of sub-synoptic atmospheric disturbances in coastal regions. At present, the spectrum of applications is [...] Read more.
We review the state of dynamical downscaling with scale-constrained regional and global models. The methodology, in particular spectral nudging, has become a routine and well-researched tool for hindcasting climatologies of sub-synoptic atmospheric disturbances in coastal regions. At present, the spectrum of applications is expanding to other phenomena, but also to ocean dynamics and to extended forecasting. Additionally, new diagnostic challenges are appearing such as spatial characteristics of small-scale phenomena such as Low Level Jets. Full article
(This article belongs to the Special Issue Storms, Jets and Other Meteorological Phenomena in Coastal Seas)
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