Special Issue "Climate Events and Extreme Weather"

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

Deadline for manuscript submissions: 31 July 2020.

Special Issue Editor

Prof. Dr. Zbigniew Ustrnul
Website
Guest Editor
1 Department of Climatology, Jagiellonian University, Gronostajowa 7, 30-387 Krakow, Poland
2 Institute of Meteorology and Water Management (IMGW-PIB), 01-673 Warszawa, Poland
Interests: synoptic climatology; extreme weather events; atmosphere circulation; climate spatial analyses; climate change in recent centuries

Special Issue Information

Dear Colleagues,

Extreme weather events become one of the most important topics in meteorology and climatology in recent years. This is related, beyond any doubt, to their frequent disastrous effects, both environmentally and socioeconomically. Regarding current possibilities for their detection, with remote sensing techniques and systems above all, meteorological extremes have been permanently monitored and have become a bit easier to forecast. This monitoring should also contribute to early warning systems.

Regardless, the nature of weather extremes seems to be fascinating, including the scale, plot, and their atmospheric and environmental origins. It usually refers to extremes of different spatial and temporal scale, especially thermal, precipitation or anemological events. In many areas, it could also be limited to the others like fog, deposits, thunderstorms, snow cover, etc.

The following topics concerning weather and climate extremes are preferable, but other related problems are also welcome:

(1) Criteria and indices of meteorological extremes and their evaluation in different spatial and temporal scales;

(2) Circulation and other determinants of events;

(3) Long-term variability and changes;

(4) Challenges in forecasting;

(5) Social and economic impacts.

Prof. Dr. Zbigniew Ustrnul
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 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

  • weather and climate extremes
  • detection systems
  • circulation determinants
  • spatial scales
  • long term variability and changes
  • forecasting methods and warning tools

Published Papers (7 papers)

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Research

Open AccessArticle
Heatwaves in the Future Warmer Climate of South Africa
Atmosphere 2020, 11(7), 712; https://doi.org/10.3390/atmos11070712 - 03 Jul 2020
Abstract
Weather and climate extremes, such as heat waves (HWs), have become more frequent due to climate change, resulting in negative environmental and socioeconomic impacts in many regions of the world. The high vulnerability of South African society to the impacts of warm extreme [...] Read more.
Weather and climate extremes, such as heat waves (HWs), have become more frequent due to climate change, resulting in negative environmental and socioeconomic impacts in many regions of the world. The high vulnerability of South African society to the impacts of warm extreme temperatures makes the study of the effect of climate change on future HWs necessary across the country. We investigated the projected effect of climate change on future of South Africa with a focus on HWs using an ensemble of regional climate model downscalings obtained from the Conformal Cubic Atmospheric Model (CCAM) for the periods 2010–2039, 2040–2069, and 2070–2099, with 1983–2012 as the historical baseline. Simulations were performed under the Representative Concentration Pathway (RCP) 4.5 (moderate greenhouse gas (GHG) concentration) and 8.5 (high GHG concentration) greenhouse gas emission scenarios. We found that the 30-year period average maximum temperatures may rise by up to 6 °C across much of the interior of South Africa by 2070–2099 with respect to 1983–2012, under a high GHG concentration. Simulated HW thresholds for all ensemble members were similar and spatially consistent with observed HW thresholds. Under a high GHG concentration, short lasting HWs (average of 3–4 days) along the coastal areas are expected to increase in frequency in the future climate, however the coasts will continue to experience HWs of relatively shorter duration compared to the interior regions. HWs lasting for shorter duration are expected to be more frequent when compared to HWs of longer durations (over two weeks). The north-western part of South Africa is expected to have the most drastic increase in HWs occurrences across the country. Whilst the central interior is not projected to experience pronounced increases in HW frequency, HWs across this region are expected to last longer under future climate change. Consistent patterns of change are projected for HWs under moderate GHG concentrations, but the changes are smaller in amplitude. Increases in HW frequency and duration across South Africa may have significant impacts on human health, economic activities, and livelihoods in vulnerable communities. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
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Open AccessArticle
How Unusual were June 2019 Temperatures in the Context of European Climatology?
Atmosphere 2020, 11(7), 697; https://doi.org/10.3390/atmos11070697 - 30 Jun 2020
Abstract
The aims of the study were to assess the severity of temperature conditions in Europe, in June 2019, using a newly developed extremes index, as well as to evaluate circulation conditions that favored the occurrence of extremely hot days in June 2019, as [...] Read more.
The aims of the study were to assess the severity of temperature conditions in Europe, in June 2019, using a newly developed extremes index, as well as to evaluate circulation conditions that favored the occurrence of extremely hot days in June 2019, as seen over the long term. The main focus of this work was on two European regions particularly affected by high temperatures in June 2019, namely Central Europe and Iberia. To comprehensively characterize heat events in terms of their spatial extent and intensity, we proposed the extremity index (EI) and used it to compare hot days occurring in areas of different sizes and with different climatic conditions. The role of atmospheric circulation in the occurrence of hot days was evaluated using the Grosswetterlagen (GWL) circulation types catalog, as well as composite maps created with the bootstrap resampling technique. Our results reveal that June 2019 was unusually hot, and in terms of the magnitude of the anomaly, it has no analogue in the 70-year-long temperature record for Europe. However, the properties of heat events in the two considered regions were substantially different. The occurrence of hot days in June 2019, in Europe, was mainly associated with the GWL types forcing advection from the southern sector and co-occurrence of high-pressure systems which was significantly proven by the results of bootstrap resampling. In terms of the applicability of the new approach, the EI proved to be a useful tool for the analysis and evaluation of the severity of hot days based on their intensity and spatial range. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
Open AccessArticle
Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland
Atmosphere 2020, 11(4), 391; https://doi.org/10.3390/atmos11040391 - 15 Apr 2020
Abstract
We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the [...] Read more.
We assessed future changes in spring frost risk for the Aare river catchment that comprises the Swiss Plateau, the most important agricultural region of Switzerland. An ensemble of 15 bias-corrected regional climate model (RCM) simulations from the EXAR data set forced by the RCP 4.5 and RCP 8.5 concentration pathways were analysed for two future periods. Correlating actual meteorological observations and Swiss phenological spring index, we proposed and tested an RCM-compatible methodology (based on temperature data only) for estimating a start of spring and severity of frost events. In the historical climate, a significant advancement in start of spring was observed and frost events were more frequent in those years in which spring started sooner. In 2021–2050, spring is projected to start eight (twelve) days earlier, considering the RCP 4.5 (8.5) scenario. Substantial changes were simulated for the 2070–2099 period under RCP 8.5, when the total severity of frost events was projected to be increased by a factor of 2.1 compared to the historical climate. The study revealed the possible future increase of vegetation exposure to spring frost in Switzerland and that this phenomenon is noticeable even in the near future under the ‘low concentration’ RCP 4.5 scenario. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
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Open AccessArticle
An Alternative to PCA for Estimating Dominant Patterns of Climate Variability and Extremes, with Application to U.S. and China Seasonal Rainfall
Atmosphere 2020, 11(4), 354; https://doi.org/10.3390/atmos11040354 - 07 Apr 2020
Abstract
Floods and droughts are driven, in part, by spatial patterns of extreme rainfall. Heat waves are driven by spatial patterns of extreme temperature. It is therefore of interest to design statistical methodologies that allow the rapid identification of likely patterns of extreme rain [...] Read more.
Floods and droughts are driven, in part, by spatial patterns of extreme rainfall. Heat waves are driven by spatial patterns of extreme temperature. It is therefore of interest to design statistical methodologies that allow the rapid identification of likely patterns of extreme rain or temperature from observed historical data. The standard work-horse for the rapid identification of patterns of climate variability in historical data is Principal Component Analysis (PCA) and its variants. But PCA optimizes for variance not spatial extremes, and so there is no particular reason why the first PCA spatial pattern should identify, or even approximate, the types of patterns that may drive floods, droughts or heatwaves, even if the linear assumptions underlying PCA are correct. We present an alternative pattern identification algorithm that makes the same linear assumptions as PCA, but which can be used to explicitly optimize for spatial extremes. We call the method Directional Component Analysis (DCA), since it involves introducing a preferred direction, or metric, such as “sum of all points in the spatial field”. We compare the first PCA and DCA spatial patterns for U.S. and China winter and summer rainfall anomalies, using the sum metric for the definition of DCA in order to focus on total rainfall anomaly over the domain. In three out of four of the examples the first DCA spatial pattern is more uniform over a wide area than the first PCA spatial pattern and as a result is more obviously relevant to large-scale flooding or drought. Also, in all cases the definitions of PCA and DCA result in the first PCA spatial pattern having the larger explained variance of the two patterns, while the first DCA spatial pattern, when scaled appropriately, has a higher likelihood and greater total rainfall anomaly, and indeed is the pattern with the highest total rainfall anomaly for a given likelihood. The first DCA spatial pattern is arguably the best answer to the question: what single spatial pattern is most likely to drive large total rainfall anomalies in the future? It is also simpler to calculate than PCA. In combination PCA and DCA patterns yield more insight into rainfall variability and extremes than either pattern on its own. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
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Open AccessArticle
Evaluation of Meteorological Drought and Flood Scenarios over Kenya, East Africa
Atmosphere 2020, 11(3), 307; https://doi.org/10.3390/atmos11030307 - 21 Mar 2020
Cited by 1
Abstract
This work examines drought and flood events over Kenya from 1981 to 2016 using the Standardized Precipitation–Evapotranspiration Index (SPEI). The spatiotemporal analysis of dry and wet events was conducted for 3 and 12 months. Extreme drought incidences were observed in the years 1987, [...] Read more.
This work examines drought and flood events over Kenya from 1981 to 2016 using the Standardized Precipitation–Evapotranspiration Index (SPEI). The spatiotemporal analysis of dry and wet events was conducted for 3 and 12 months. Extreme drought incidences were observed in the years 1987, 2000, 2006, and 2009 for SPEI-3, whilst the SPEI-12 demonstrated the manifestation of drought during the years 2000 and 2006. The SPEI showed that the wettest periods, 1997 and 1998, coincided with the El Nino event for both time steps. SPEI-3 showed a reduction in moderate drought events, while severe and extreme cases were on the increase tendencies towards the end of the twentieth century. Conversely, SPEI-12 depicted an overall increase in severe drought occurrence over the study location with ab observed intensity of −1.54 and a cumulative frequency of 64 months during the study period. Wet events showed an upward trend in the western and central highlands, while the rest of the regions showed an increase in dry events during the study period. Moreover, moderate dry/wet events predominated, whilst extreme events occurred least frequently across all grid cells. It is apparent that the study area experienced mild extreme dry events in both categories, although moderately severe dry events dominated most parts of the study area. A high intensity and frequency of drought was noted in SPEI-3, while the least occurrences of extreme events were recorded in SPEI-12. Though drought event prevailed across the study area, there was evidence of extreme flood conditions over the recent decades. These findings form a good basis for next step of research that will look at the projection of droughts over the study area based on regional climate models. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
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Open AccessArticle
An Integrated Wind Risk Warning Model for Urban Rail Transport in Shanghai, China
Atmosphere 2020, 11(1), 53; https://doi.org/10.3390/atmos11010053 - 01 Jan 2020
Cited by 1
Abstract
The integrated wind risk warning model for rail transport presented has four elements: Background wind data, a wind field model, a vulnerability model, and a risk model. Background wind data uses observations in this study. Using the wind field model with effective surface [...] Read more.
The integrated wind risk warning model for rail transport presented has four elements: Background wind data, a wind field model, a vulnerability model, and a risk model. Background wind data uses observations in this study. Using the wind field model with effective surface roughness lengths, the background wind data are interpolated to a 30-m resolution grid. In the vulnerability model, the aerodynamic characteristics of railway vehicles are analyzed with CFD (Computational Fluid Dynamics) modelling. In the risk model, the maximum value of three aerodynamic forces is used as the criteria to evaluate rail safety and to quantify the risk level under extremely windy weather. The full model is tested for the Shanghai Metro Line 16 using wind conditions during Typhoon Chan-hom. The proposed approach enables quick quantification of real-time safety risk levels during typhoon landfall, providing sophisticated warning information for rail vehicle operation safety. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
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Open AccessArticle
Observed Multi-Timescale Differences between Summertime Near-Surface Equivalent Temperature and Temperature for China and Their Linkage with Global Sea Surface Temperatures
Atmosphere 2019, 10(8), 447; https://doi.org/10.3390/atmos10080447 - 03 Aug 2019
Abstract
Based on the ensemble empirical mode decomposition method, this study explores the differences and similarities in multiple time-scale characteristics of summer air temperature (T) and equivalent temperature (Te) over China during 1961–2017, using daily meteorological observations collected at [...] Read more.
Based on the ensemble empirical mode decomposition method, this study explores the differences and similarities in multiple time-scale characteristics of summer air temperature (T) and equivalent temperature (Te) over China during 1961–2017, using daily meteorological observations collected at 412 stations in China. Their relationships to global sea surface temperature variations is also discussed. Results show that both T and Te can be decomposed into five components, which includes multiple timescales, from interannual to long-term trends. The spatial patterns of each timescale’s leading mode show that the variations of Te are generally larger than that of T. Meanwhile, both T and Te are dominated by their inter-annual, multi-decadal variations and the non-linear trend. High correlations of T and Te can also be found in these major scales. The related sea surface temperature variations in these major scales also show consistent patterns, which correspond to El Niño–Southern Oscillation, Atlantic Multidecadal Oscillation and the global warming trend in the sea, respectively. In other scales, both spatial patterns of T and Te and the corresponding correlation patterns with sea surface temperature are distinguishable. The current results explore the compound changes of surface temperature-humidity during the past five decades from a new perspective, which provides some insights for a better understanding of the possible causes of climate change over China. Full article
(This article belongs to the Special Issue Climate Events and Extreme Weather)
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