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Advances in Understanding, Simulating and Predicting Extreme Climates in Northern...
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Advances in Understanding, Simulating and Predicting Extreme Climates in Northern Hemisphere

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

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 9084

Special Issue Editors

Dr. Bo Sun

E-Mail Website
Guest Editor
School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: climate variability; air-sea interaction; hydrological cycle
Dr. Helene R. Langehaug

E-Mail Website
Guest Editor
Nansen Environmental and Remote Sensing Center & Bjerknes Centre, Thormøhlens gate 47N-5006, Bergen, Norway
Interests: oceanic variability; climate prediction

Special Issue Information

Dear Colleagues,

In recent decades, extreme climate events (e.g., drought, floods, heat waves, heavy rainfall and snowfall, extreme high/low temperatures) have led to enormous economic losses and a vast amount of casualties and hunger around the world. As global warming continues, more frequent and more intense extreme climate events have been observed, which bring huge threats to the human community. Hence, it is very important to improve our understanding of the simulation and prediction of extreme climates.

For the simulation of extreme climates, we expect to know how well numerical models can simulate extreme climates in different areas such as Asia and Europe, the multi-time scale variability of extreme climates, and the driving factors in numerical simulations. In particular, we expect to better understand the links/teleconnections between tropical air–sea interaction, Arctic sea ice, snow cover, and the extreme climates in numerical simulations. For the prediction of extreme climates, we expect to know the predictability of extreme climates based on dynamic models, physical–empirical models, statistical models, dynamic–statistical models, and deep learning approaches. Particularly, it is essential to unveil the sources of the predictability of extreme climates and the key factors that affect the prediction of extreme climates.

In this context, for this Special Issue of Atmosphere, we are calling for submissions related but not limited to the above questions. Articles that may make a contribution to a better understanding of the simulation and prediction of extreme climates are invited. 

Dr. Bo Sun
Dr. Helene R. Langehaug
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

  • extreme climates
  • prediction
  • numerical simulation
  • multi-time scale variability
  • Arctic sea ice
  • air–sea interaction
  • dynamic process
  • dynamic–statistical model
  • sources of predictability
  • teleconnections

Published Papers (4 papers)

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Research

14 pages, 3036 KiB  
Article
Comparison of Atmospheric Circulation Anomalies between Dry and Wet Extreme High-Temperature Days in the Middle and Lower Reaches of the Yellow River
by Hangcheng Ge, Gang Zeng, Vedaste Iyakaremye, Xiaoye Yang and Zongming Wang
Atmosphere 2021, 12(10), 1265; https://doi.org/10.3390/atmos12101265 - 28 Sep 2021
Cited by 10 | Viewed by 1873
Abstract
Many previous studies have reported that atmospheric circulation anomalies are generally the direct cause of extreme high-temperature (EHT). However, the atmospheric circulation anomalies of EHT days with different humidity and the differences between them are less often discussed, while humidity plays an important [...] Read more.
Many previous studies have reported that atmospheric circulation anomalies are generally the direct cause of extreme high-temperature (EHT). However, the atmospheric circulation anomalies of EHT days with different humidity and the differences between them are less often discussed, while humidity plays an important role in how people feel in a high-temperature environment. Therefore, this study uses 1961–2016 CN05.1 daily observational data and NCEP/NCAR reanalysis data to classify summer EHT days in China into dry and wet. Furthermore, we investigate the atmospheric circulation anomalies associated with the dry and wet EHT days in the middle and lower reaches of the Yellow River (MLRYR). The results reveal that dry EHT days are likely to be caused by adiabatic heating from anomalous subsidence, while wet EHT days are more likely caused by the low-latitude water vapor and heat anomalies brought by the Western Pacific Subtropical High (WPSH). This may be due to a remarkable westward/southward/narrowed extension of the Continental High (CH)/WPSH/South Asian High (SAH) accompanied by an occurrence of dry EHT day. The opposite pattern is observed for wet EHT days. Moreover, a wave train like the Silk Road pattern from the midlatitudes could affect the dry EHT days, while wet EHT days are more likely to be affected by a wave train from high latitudes. Knowing the specific characteristics of dry and wet EHT days and their associated atmospheric circulations could offer new insights into disaster risk prevention and reduction. Full article
(This article belongs to the Special Issue Advances in Understanding, Simulating and Predicting Extreme Climates in Northern Hemisphere)
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15 pages, 4958 KiB  
Article
Evaluation and Projection of Near-Surface Wind Speed over China Based on CMIP6 Models
by Hao Deng, Wei Hua and Guangzhou Fan
Atmosphere 2021, 12(8), 1062; https://doi.org/10.3390/atmos12081062 - 18 Aug 2021
Cited by 14 | Viewed by 2820
Abstract
The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison [...] Read more.
The characteristics of near-surface wind speed (NWS) are important to the study of dust storms, evapotranspiration, heavy rainfall, air pollution, and wind energy development. This study evaluated the performance of 30 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) through comparison with observational NWS data acquired in China during a historical period (1975–2014), and projected future changes in NWS under three scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) based on an optimal multi-model ensemble. Results showed that most models reproduced the spatial pattern of NWS for all seasons and the annual mean, although the models generally overestimated NWS magnitude. All models tended to underestimate the trends of decline of NWS for all seasons and the annual mean. On the basis of a comprehensive ranking index, the KIOST-ESM, CNRM-ESM2-1, HadGEM3-GC31-LL, CMCC-CM2-SR5, and KACE-1-0-G models were ranked as the five best-performing models. In the projections of future change, nationally averaged NWS for all months was weaker than in the historical period, and the trends decreased markedly under all the different scenarios except the winter time series under SSP2-4.5. Additionally, the projected NWS over most regions of China weakened in both the early period (2021–2060) and the later period (2061–2100). Full article
(This article belongs to the Special Issue Advances in Understanding, Simulating and Predicting Extreme Climates in Northern Hemisphere)
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15 pages, 3080 KiB  
Article
The Influence of Instrumental Line Shape Degradation on Gas Retrievals and Observation of Greenhouse Gases in Maoming, China
by Dandan Liu, Yinbo Huang, Zhensong Cao, Xingji Lu and Xiangyuan Liu
Atmosphere 2021, 12(7), 863; https://doi.org/10.3390/atmos12070863 - 02 Jul 2021
Cited by 1 | Viewed by 1548
Abstract
The instrument line shape (ILS), as a very important parameter, has a significant influence on the inversion of trace gas concentration. Different levels of ILS degradation for H2O, CO2, CH4, and CO gases were investigated, and the influence [...] Read more.
The instrument line shape (ILS), as a very important parameter, has a significant influence on the inversion of trace gas concentration. Different levels of ILS degradation for H2O, CO2, CH4, and CO gases were investigated, and the influence of ILS on the inversion of column-averaged dry air mole fractions (DMFs) was assessed. Our results indicate that the averages of XH2O, XCH4, and XCO with modulation efficiency (ME) amplitude values have a positive correlation, the correlation coefficients are 0.9925, 0.9968, and 0.9981 respectively, whereas the relationship between the average of XCO2 and ME is a negative correlation with 0.986 correlation coefficient. For a typical ILS degradation, a decrease of 5% in the modulation efficiency amplitude value results in the average of XCO2 changing by 0.744%, XCH4 and XH2O are less sensitive species, with average values of −0.206% and −0.464%, whereas XCO shows the strongest intraday variability with an average value of −0.238%. However, with a decrease of 2‰ in the phase error (PE) value, the average of XCO changed by −0.150%, XCO2 and XH2O almost coincided with the same average value of −0.141%, whereas XCH4 was the least sensitive species with an average value of −0.133%. At the same time, we measured the ILS for EM27/SUN spectrometers—the mean values of modulation efficiency amplitudes and phase errors were 0.9611 and 0.00593. Compared with standard values, the modulation efficiency amplitudes and the phase error deviations were 2.450% and 0.433%. During the observation period, the daily average of XCO2 ranged from 415.09 to 421.78 ppm. XCH4 ranged from 1.96 to 2.02 ppm with a mean of 1.982 ppm, and the daily average of XCO ranged from 0.118 to 0.157 ppm with a mean of 0.137 ppm. For the relationship between XCO2 and XCH4, the linear regression line shows a good correlation with the correlation coefficient R2 ≥ 0.5. Especially, for the correlation coefficient R2 = 0.82 on 8 October, our studies found a weak correlation in the variation of CO2 and CO during the observations. The correlation coefficient R2 ≥ 0.5 was only found on 30 September and 3 October. The trajectories dram at a height of 10 km give a hint of trace gas transport from the bay of western India, Bengal, and the Arabian Sea, whereas for the trajectories dram boundary layer height, trace gases were transported from southwest and east of China. These results provide a theoretical basis to understand the time and space distribution and the changes of greenhouse gas in the atmosphere as well as providing a theoretical basis for calculations of atmospheric radiation transmission. Full article
(This article belongs to the Special Issue Advances in Understanding, Simulating and Predicting Extreme Climates in Northern Hemisphere)
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15 pages, 25476 KiB  
Article
Winter Persistent Extreme Cold Events in Xinjiang Region and Their Associations with the Quasi-Biweekly Oscillation of the Polar Front Jet
by Jie Jiang and Suxiang Yao
Atmosphere 2021, 12(5), 597; https://doi.org/10.3390/atmos12050597 - 05 May 2021
Viewed by 2294
Abstract
Winter persistent extreme cold events (WPECEs) often cause great damage to the development of economies and people’s lives. The sub-seasonal variation of the atmospheric circulation is regarded as one of important causes of extreme weather, and is key to propel the extended period [...] Read more.
Winter persistent extreme cold events (WPECEs) often cause great damage to the development of economies and people’s lives. The sub-seasonal variation of the atmospheric circulation is regarded as one of important causes of extreme weather, and is key to propel the extended period prediction. In this paper, we mainly analyze the WPECEs in Xinjiang region and their relationship with the sub-seasonal variation of the East Asian polar front jet (PFJ). The results suggest the persistent extreme cold event (equal or greater than 7 days) occurs most frequently in Xinhe County of Xinjiang region, with obvious inter-annual and inter-decadal variations. Further analysis shows that the variation of the mean temperature in the key area has characteristics of intra-seasonal variation when the WPECE occurs. The result of composite analysis shows that this intra-seasonal variation is related to the sub-seasonal variation of atmospheric circulation, especially the PFJ anomalous activity near Lake Balkhash. By using the power spectrum analysis method, note that the PFJ activity has the characteristics of quasi-biweekly oscillation (QBWO) in WPECEs. On quasi-biweekly scale (10–20-day filtered), the weakening of PFJ, the intensification of the zonal easterly wind in the upper troposphere, the accumulation of the strong cold air, and the intensification of the meridional northerly wind in the lower troposphere enhance the occurrence of WPECEs in Xinjiang. Further investigation indicates that the quasi-biweekly PFJ mainly propagates eastward and southward before the WPECE occurs in Xinjiang, China. Full article
(This article belongs to the Special Issue Advances in Understanding, Simulating and Predicting Extreme Climates in Northern Hemisphere)
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