Heat Waves: Perspectives from Observations, Reanalysis and Modeling

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

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 6552

Special Issue Editors


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Guest Editor
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519000, Guangdong, China
Interests: urban climate; boundary-layer meteorology; environmental fluid mechanics; pollutant dispersion; numerical weather prediction; large-scale scientific computation

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Guest Editor
Department of the Built Environment, College of Design & Engineering, National University of Singapore, 4 Architecture Drive, Singapore 117566, Singapore
Interests: urban climate; wind engineering; computational fluid dynamics; natural ventilation

Special Issue Information

Dear Colleagues,

With continuous urbanization and global climate change, the extreme weather and climate events have been occurring more frequently and causing more disastrous damages globally, as highlighted in the 6th IPCC report. One of such extremes is heat waves, which are usually defined as consecutive days of temperature exceeding prescribed thresholds. The hazards of heat waves span from human health to infrastructure and the economy. Heat waves can also have synergistic effects when co-occurring with other natural and societal phenomena, e.g., the urban heat island effect, drought, rainfall, and ozone episodes.

To better understand heat waves, better datasets and methodologies are needed. Recently, many heat wave studies have resorted to the re-analysis of data and high-resolution numerical models, in addition to observations. It is therefore our intention here to gather the current understanding of various aspects of heat waves from the perspective of observation, reanalysis, and modeling to form a Special Issue.

The topics of the Special Issue can include, but are not limited to, the following:

  • Heat wave trends derived from different datasets or model results, for the past or in the future;
  • Heat wave prediction in meteorology or climate models;
  • Synergistic effects of heat wave with urban heat island, drought, rainfall, air pollution or others;
  • Heat wave and thermal comfort;
  • Heat waves’ impact on health;
  • Heat waves’ impact on building energy consumption;
  • Mitigation of heat waves;
  • Other topics related to heat waves.

Dr. Xianxiang Li
Dr. Lup Wai Chew
Guest Editors

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Keywords

  • weather/climate extremes
  • heat wave trends
  • interaction of heat wave and UHI
  • future projections of heat wave
  • heat wave and pollution
  • heat wave and energy consumption
  • heat wave mitigation

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Published Papers (4 papers)

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Research

25 pages, 7431 KiB  
Article
Hybrid Post-Processing on GEFSv12 Reforecast for Summer Maximum Temperature Ensemble Forecasts with an Extended-Range Time Scale over Taiwan
by Malasala Murali Nageswararao, Yuejian Zhu, Vijay Tallapragada and Meng-Shih Chen
Atmosphere 2023, 14(11), 1620; https://doi.org/10.3390/atmos14111620 - 29 Oct 2023
Viewed by 1123
Abstract
Taiwan is highly susceptible to global warming, experiencing a 1.4 °C increase in air temperature from 1911 to 2005, which is twice the average for the Northern Hemisphere. This has potentially led to higher rates of respiratory and cardiovascular mortality. Accurately predicting maximum [...] Read more.
Taiwan is highly susceptible to global warming, experiencing a 1.4 °C increase in air temperature from 1911 to 2005, which is twice the average for the Northern Hemisphere. This has potentially led to higher rates of respiratory and cardiovascular mortality. Accurately predicting maximum temperatures during the summer season is crucial, but numerical weather models become less accurate and more uncertain beyond five days. To enhance the reliability of a forecast, post-processing techniques are essential for addressing systematic errors. In September 2020, the NOAA NCEP implemented the Global Ensemble Forecast System version 12 (GEFSv12) to help manage climate risks. This study developed a Hybrid statistical post-processing method that combines Artificial Neural Networks (ANN) and quantile mapping (QQ) approaches to predict daily maximum temperatures (Tmax) and their extremes in Taiwan during the summer season. The Hybrid technique, utilizing deep learning techniques, was applied to the GEFSv12 reforecast data and evaluated against ERA5 reanalysis. The Hybrid technique was the most effective among the three techniques tested. It had the lowest bias and RMSE and the highest correlation coefficient and Index of Agreement. It successfully reduced the warm bias and overestimation of Tmax extreme days. This led to improved prediction skills for all forecast lead times. Compared to ANN and QQ, the Hybrid method proved to be more effective in predicting daily Tmax, including extreme Tmax during summer, on extended-range time-scale deterministic and ensemble probabilistic forecasts over Taiwan. Full article
(This article belongs to the Special Issue Heat Waves: Perspectives from Observations, Reanalysis and Modeling)
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21 pages, 8157 KiB  
Article
Changes in the Seasonal Cycle of Heatwaves, Dry and Wet Spells over West Africa Using CORDEX Simulations
by Assi Louis Martial Yapo, Benjamin Komenan Kouassi, Adama Diawara, Fidèle Yoroba, Adjoua Moise Landry Famien, Pêlèmayo Raoul Touré, Kouakou Kouadio, Dro Touré Tiemoko, Mouhamadou Bamba Sylla and Arona Diedhiou
Atmosphere 2023, 14(10), 1582; https://doi.org/10.3390/atmos14101582 - 19 Oct 2023
Viewed by 1187
Abstract
This study analyzes the potential response of the seasonal cycle of heatwaves (HWDI) and dry (CDD) and wet (CWD) spell indices over West Africa for the near- (2031–2060) and the far-future periods (2071–2100) under RCP4.5 and RCP8.5 scenarios using Coordinated Regional Climate Downscaling [...] Read more.
This study analyzes the potential response of the seasonal cycle of heatwaves (HWDI) and dry (CDD) and wet (CWD) spell indices over West Africa for the near- (2031–2060) and the far-future periods (2071–2100) under RCP4.5 and RCP8.5 scenarios using Coordinated Regional Climate Downscaling Experiment (CORDEX) simulations. Despite the fact that some relative biases (an underestimation of 30% for CDD, an overestimation of about 60% for CWD, and an overestimation of about 50% for HWDI) exist, during the historical period (1976–2005) in general, the CORDEX simulations and their ensemble mean outperform the seasonal variability in the above-mentioned indices over three defined subregions of West Africa (i.e., the Gulf of Guinea and Western and Eastern Sahel). They show high correlation coefficients (0.9 in general) and less RMSE. They project an increase (about 10 and 20 days) in heatwave days for both the near- and far-future periods over the whole West African region under both RCP scenarios. In addition, projections indicate that the Sahel regions will experience a decrease (about 5 days) in wet spell days from March to November, while in the Gulf of Guinea, a decrease (about 3 days) is projected throughout the year, except in the CCCLM simulation, which indicates an increase (about 5 days) during the retreat phase of the monsoon (October to December). Our results also highlight an increase (about 80%) in dry spells over the Sahel regions that are more pronounced during the March–November period, while over the Gulf of Guinea, an increase (about 40%) is projected over the entire year. Moreover, the months of increasing dry spells and decreasing wet spells coincide, suggesting that countries in these regions could be simultaneously exposed to dry seasons associated with a high risk of drought and heatwaves under future climate conditions. Full article
(This article belongs to the Special Issue Heat Waves: Perspectives from Observations, Reanalysis and Modeling)
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18 pages, 6148 KiB  
Article
Impact of Anthropogenic Heat on Urban Environment: A Case Study of Singapore with High-Resolution Gridded Data
by Ao Wang, Xian-Xiang Li, Rui Xin and Lup Wai Chew
Atmosphere 2023, 14(10), 1499; https://doi.org/10.3390/atmos14101499 - 28 Sep 2023
Cited by 3 | Viewed by 1699
Abstract
Anthropogenic heat (AH) emissions have great impacts on urban climate. AH is usually spatially heterogeneous and depends on the urban land use type. Studies using high-resolution gridded data that can resolve spatially heterogeneous AH are still scarce. The present study uses AH data [...] Read more.
Anthropogenic heat (AH) emissions have great impacts on urban climate. AH is usually spatially heterogeneous and depends on the urban land use type. Studies using high-resolution gridded data that can resolve spatially heterogeneous AH are still scarce. The present study uses AH data of a high spatial resolution of 200 m by 200 m and a temporal resolution of 1 h to investigate the impact of AH in Singapore in April 2016, particularly regarding the relative contribution of individual AH components. The WRF model coupled with a single-layer urban canopy model is employed. The WRF model can predict the 2-m air temperature and 2-m relative humidity with good agreement with the observation data, while the simulated 10-m wind speed has relatively large deviation from the observation data. The largest spatially averaged temperature increases caused by total AH (QF), AH from buildings (QB) and AH from traffic (QV) are 1.44 °C, 1.44 °C and 1.35 °C, respectively. The effects of AH on sensible heat flux and boundary layer height are largely consistent, with both QF and QB exhibiting significant effects at night, while the effects of QV are small. The effect of AH on the local circulations (sea and land breezes) in Singapore is small, while its effect on the urban heat island (UHI) circulations is more pronounced. Due to the UHI circulations, the sum of the effects on local temperatures caused by QB and QV may exceed that by QF in some areas. This finding can guide comprehensive mitigation measures of AH by not only focusing on land use type but also on the contribution of individual AH components, in order to ameliorate the impacts of urban overheating. Full article
(This article belongs to the Special Issue Heat Waves: Perspectives from Observations, Reanalysis and Modeling)
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15 pages, 5381 KiB  
Article
Intraseasonal Oscillation Features of the Two Types of Persistent High Temperature Events over Jiangnan Region
by Yan Li, Qingjiu Gao, Qi You and Yuanbo Yue
Atmosphere 2023, 14(1), 185; https://doi.org/10.3390/atmos14010185 - 15 Jan 2023
Cited by 1 | Viewed by 1572
Abstract
In order to find potential low-frequency signals and provide new ideas for extended-range forecasting, the intraseasonal oscillation (ISO) characteristics of persistent high temperature events (PHTEs) in the extended summer in Jiangnan area are explored by using daily maximum air temperature (Tmax) data from [...] Read more.
In order to find potential low-frequency signals and provide new ideas for extended-range forecasting, the intraseasonal oscillation (ISO) characteristics of persistent high temperature events (PHTEs) in the extended summer in Jiangnan area are explored by using daily maximum air temperature (Tmax) data from the China Meteorological Data Network and daily reanalysis data provided by NCEP/DOE. The results show that the low-frequency PHTEs can be classified into three types according to the position variation of the Western Pacific subtropical high (WPSH). For the first two types of PHTEs, a southwestward migrating mid-latitude wave train from the North American coast to the central and eastern China can be clearly seen in the whole troposphere. Whereas the two types of PHTEs show different features in the low-latitude. It is found that a significantly westward extension of the WPSH during the first type of PHTEs, with the low-frequency anticyclone moving westward in the mid-lower troposphere. For the second type of PHTEs, the WPSH is mainly located in the southeastern China with slightly movement. Analysis of the low-frequency vertical circulation and the thermodynamic equation further reveal that the increase of temperature in Jiangnan region is primarily attributed to the descending airflow. Full article
(This article belongs to the Special Issue Heat Waves: Perspectives from Observations, Reanalysis and Modeling)
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