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Atmosphere
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China Heatwaves
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China Heatwaves

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

Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 4531

Special Issue Editors

Dr. Guwei Zhang

E-Mail Website
Guest Editor
Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
Interests: heatwaves; regional climate modeling; climate change; land–sea–air interactions
Dr. Lin Pei

E-Mail Website
Guest Editor
Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
Interests: extreme weather; anthropogenic influence; regional climate modeling

Special Issue Information

Dear Colleagues,

Heatwaves are among the most dangerous climate extremes, with devastating effects on human and natural systems. In China, heatwaves have become more intense and frequent, posing a series of threats to public health, socio-economy, and outdoor activities. Since 1990, heatwave-related deaths in China have quadrupled and the number in 2019 reached 26,800, resulting in economic losses equivalent to the average annual income of 1.4 million Chinese people. As climate models indicated that future warming in China would exceed the global level, the intensity, frequency, and duration of China's heatwaves are expected to increase continually in this century. Meanwhile, considering the growth of the population, urbanization, and similar factors, China will face significant heat risks in the future. Moreover, global warming could also lead to changes in the possible mechanisms of heatwaves (e.g., atmospheric circulation anomalies, key thermal factors, etc.). Recent works have pointed out that the Tibetan Plateau snow cover, the Atlantic and Pacific sea surface temperature, and Arctic sea ice showed some connections with China's heatwaves. Furthermore, anthropogenic influences such as city expansion, the urban heat island, and carbon emissions have also been identified as contributing to the increasing heatwaves. Overall, a series of in-depth research studies on heatwaves in China are critical. In this Special Issue, we aim to publish innovative articles that investigate historical simulations and future projections of heatwaves (or extreme heat) in China, assess heat risks, and analyze the possible mechanisms.

Dr. Guwei Zhang
Dr. Lin Pei
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

  • heatwaves
  • global warming
  • variability
  • anthropogenic influences
  • mechanism
  • land–sea–air interactions
  • future projections
  • risk assessment

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Published Papers (2 papers)

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Research

11 pages, 1662 KiB  
Communication
The Dependence of Gales on Relevant Meteorological Elements in One of the Hottest Regions of China, the Turpan Basin
by Zhiqi Xu, Hao Tang, Xiya Zhang and Haibo Hu
Atmosphere 2023, 14(6), 1051; https://doi.org/10.3390/atmos14061051 - 19 Jun 2023
Viewed by 1631
Abstract
The Turpan Basin is one of the hottest regions in China, with high fire potential. The occurrence of gales could roll over trains as well as spread and expand the fire rapidly, posing adverse effects on traffic and fire protection. Therefore, it is [...] Read more.
The Turpan Basin is one of the hottest regions in China, with high fire potential. The occurrence of gales could roll over trains as well as spread and expand the fire rapidly, posing adverse effects on traffic and fire protection. Therefore, it is important to discuss the frequency and mechanism of gales in Turpan. Based on the observational data of seven stations and ERA5 reanalysis data from 2015 to 2021, this study uses the t-mode principal component analysis using the oblique rotation (T-PCA) method to explore the seasonal differences and related synoptic patterns of gales in the Turpan Basin. The synoptic circulations are divided into nine categories. In types 1, 2, 3, 5, 7 and 9, there are a high-pressure center to the west and a lower-pressure center to the south of Turpan, while in types 4, 6 and 8, there is a strong high-pressure center to the south or northeast of Turpan. When the high-pressure system is located to the west of Turpan, gales are prone to occur, while to the south or northeast, gales seem to be less likely to occur, which is closely related to synoptic patterns and terrain. To the best of our knowledge, this study pioneered the frequency and mechanism of gales in Turpan, which could facilitate gale prevention in the area. Full article
(This article belongs to the Special Issue China Heatwaves)
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15 pages, 6692 KiB  
Article
Multi-Model Ensemble Forecasts of Surface Air Temperatures in Henan Province Based on Machine Learning
by Tian Wang, Yutong Zhang, Xiefei Zhi and Yan Ji
Atmosphere 2023, 14(3), 520; https://doi.org/10.3390/atmos14030520 - 8 Mar 2023
Cited by 9 | Viewed by 2434
Abstract
Based on the China Meteorological Administration Land Data Assimilation System (CLDAS) reanalysis data and 12–72 h forecasts of the surface (2-m) air temperature (SAT) from the European Centre for Medium-Range Weather Forecasts (ECMWF) and three numerical weather prediction (NWP) models of the China [...] Read more.
Based on the China Meteorological Administration Land Data Assimilation System (CLDAS) reanalysis data and 12–72 h forecasts of the surface (2-m) air temperature (SAT) from the European Centre for Medium-Range Weather Forecasts (ECMWF) and three numerical weather prediction (NWP) models of the China Meteorological Administration (CMA-GFS, CMA-SH, and CMA-MESO), multi-model ensemble forecasts are conducted with a convolutional neural network (CNN) and a feed-forward neural network (FNN) to improve the SAT forecast in Henan Province, China. The results show that there are large errors in the 12–72 h forecasts of SAT from the CMA, while the ECMWF outperforms the other raw NWP models, especially in eastern and southern Henan. The CNN has the best short-term forecasting skills. The difference in the geographical distribution of the CNN forecast errors is small, without any apparent large-value areas. The CNN shows its advantages in its bias correction in the mountainous region (western Henan), indicating that the CNN can capture the spatial features of the atmospheric fields and is therefore more robust in regions with varied topography. In addition, the CNN can extract data features through the convolution kernel and focus on local features; it can assimilate the local features at a higher level and obtain global features. Therefore, the CNN takes advantage of the four models in the SAT forecast and further improves the forecast skill. Full article
(This article belongs to the Special Issue China Heatwaves)
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