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39 pages, 13007 KiB

Open AccessArticle

Changes in the Characteristics of Dry and Wet Periods in Europe (1851–2015)

by Stephanie Hänsel

Atmosphere 2020, 11(10), 1080; https://doi.org/10.3390/atmos11101080 - 10 Oct 2020

Cited by 11 | Viewed by 2519

This study spanning the period 1851–2015 explores the spatial and temporal characteristics of dry and wet periods in Europe as well as their variability and changes. It is based on up to 220 stations with monthly precipitation time series that have a varying [...] Read more.

This study spanning the period 1851–2015 explores the spatial and temporal characteristics of dry and wet periods in Europe as well as their variability and changes. It is based on up to 220 stations with monthly precipitation time series that have a varying data availability within the study period. The stations are classified into eight regions with similar climate characteristics. Dry and wet periods are analyzed using the decile method as well as the modified Rainfall Anomaly Index mRAI at the 3-month timescale. Spatial extent, duration, and frequency of dry and wet periods show a large multi-decadal variability resulting in comparatively small long-term trends over the entirety of Europe for the study periods 1901–2015 and 1951–2015. Nonetheless, several sub-regions show distinct changes—with opposite signals for northern and southern Europe. Spatial extent and duration of dry periods generally decreased, while wet periods show increases throughout the 20th century—particularly in Scandinavia. A simultaneous increase in the frequency of severely dry and wet years, respectively, is observed since the 1980s. This indicates that temperature increases across Europe may be connected with an increasing frequency of extremes at both sides of the probability density function of precipitation. Full article

(This article belongs to the Special Issue Climate Events and Extreme Weather)

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15 pages, 6044 KiB

Open AccessArticle

Evaluation of the Performance of CMIP6 HighResMIP on West African Precipitation

by Felix Olabamiji Ajibola, Botao Zhou, Gnim Tchalim Gnitou and Anselem Onyejuruwa

Atmosphere 2020, 11(10), 1053; https://doi.org/10.3390/atmos11101053 - 01 Oct 2020

Cited by 38 | Viewed by 5891

Abstract

This research focuses on evaluating the High-Resolution Model Intercomparison Project (HighResMIP) simulations within the framework of the Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6). We used seven of its consortiums to study how CMIP6 reproduced the West African precipitation features during the [...] Read more.

This research focuses on evaluating the High-Resolution Model Intercomparison Project (HighResMIP) simulations within the framework of the Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6). We used seven of its consortiums to study how CMIP6 reproduced the West African precipitation features during the 1950–2014 historical simulation periods. The rainfall event was studied for two sub-regions of West Africa, the Sahel and the Guinea Coast. Precipitation datasets from the Climate Research Unit (CRU) TS v4.03, University of Delaware (UDEL) v5.01, and Global Precipitation Climatology Centre (GPCC) were used as observational references with the aim of accounting for uncertainty. The observed annual peak during August, which is greater than 200, 25, and 100 mm/month in the Guinea Coast, the Sahel, and West Africa as a whole, respectively, appears to be slightly underestimated by some of the models and the ensemble mean, although all the models captured the general rainfall pattern. Global climate models (GCMs) and the ensemble mean reproduced the spatial daily pattern of precipitation in the monsoon season (from June to September) over West Africa, with a high correlation coefficient exceeding 0.8 for the mean field and a relatively lower correlation coefficient for extreme events. Individual models, such as IPSL and ECMWF, tend to show high performance, but the ensemble mean appears to outperform all other models in reproducing West African precipitation features. The result from this study shows that merely improving the horizontal resolution may not remove biases from CMIP6. Full article

(This article belongs to the Special Issue Climate Events and Extreme Weather)

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29 pages, 10290 KiB

Open AccessArticle

Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean Temperature over Pakistan during 1970–2014

by Rizwan Karim, Guirong Tan, Brian Ayugi, Hassen Babaousmail and Fei Liu

Atmosphere 2020, 11(9), 1005; https://doi.org/10.3390/atmos11091005 - 20 Sep 2020

Cited by 26 | Viewed by 4736

Abstract

This work employed recent model outputs from coupled model intercomparison project phase six to simulate surface mean temperature during the June–July–August (JJA) and December–January–February (DJF) seasons for 1970–2014 over Pakistan. The climatic research unit (CRU TS4.03) dataset was utilized as benchmark data to [...] Read more.

This work employed recent model outputs from coupled model intercomparison project phase six to simulate surface mean temperature during the June–July–August (JJA) and December–January–February (DJF) seasons for 1970–2014 over Pakistan. The climatic research unit (CRU TS4.03) dataset was utilized as benchmark data to analyze models’ performance. The JJA season exhibited the highest mean temperature, whilst DJF displayed the lowest mean temperature in the whole study period. The JJA monthly empirical cumulative distribution frequency (ECDF) range (26 to 28 °C) was less than that of DJF (7 to 10 °C) since JJA matched closely to CRU. The JJA and DJF seasons are warming, with higher warming trends in winters than in summers. On temporal scale, models performed better in JJA with overall low bias, low RMSE (root mean square error), and higher positive CC (correlation coefficient) values. DJF performance was undermined with higher bias and RMSE with weak positive correlation estimates. Overall, CanESM5, CESM2, CESM2-WACCM, GFDL-CM4, HadGEM-GC31-LL, MPI-ESM1-2-LR, MPI-ESM1-2-HR, and MRI-ESM-0 performed better for JJA and DJF. Full article

(This article belongs to the Special Issue Climate Events and Extreme Weather)

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40 pages, 65362 KiB

Open AccessArticle

Future Projections for Wind, Wind Shear and Helicity in the Iberian Peninsula

by Joana Martins, Alfredo Rocha, Carolina Viceto, Susana Cardoso Pereira and João A. Santos

Atmosphere 2020, 11(9), 1001; https://doi.org/10.3390/atmos11091001 - 18 Sep 2020

Cited by 8 | Viewed by 3469

Abstract

Wind is among the most important climatic elements. Its characteristics are determinant for a wide range of natural processes and human activities. However, ongoing climate change is modifying these characteristics, which may have important implications. Climatic changes on wind speed and direction, wind [...] Read more.

Wind is among the most important climatic elements. Its characteristics are determinant for a wide range of natural processes and human activities. However, ongoing climate change is modifying these characteristics, which may have important implications. Climatic changes on wind speed and direction, wind shear intensity, and helicity, over the 21st century and for 26 cities in the Iberian Peninsula, under the Representative Concentration Pathway (RCP) 8.5 anthropogenic forcing scenario, are assessed. For this purpose, the Weather Research and Forecasting (WRF) model was used, with initial and boundary conditions being obtained from simulations with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM-LR) climate model and ERA-Interim reanalysis. Quantile-quantile bias correction was applied to the simulated data prior to subsequent analysis. Overall, the results hint at a reduction in the intensity of both near-surface and 850 hPa (approx. 5%) wind in the future. Nevertheless, for the 300 hPa level, a decrease in summertime wind speed is accompanied by a slight increase in the remaining months. Furthermore, significant increases in the number of occurrences of extreme wind events were also identified, mainly in northwestern Iberia. For wind shear, an intensity increase is projected throughout most of the year (approx. 5% in the upper quantiles), mainly in southwestern Iberia. Helicity is also projected to undergo a strengthening, mostly in summer months and over southwestern Iberia, with greater emphasis on events of longer duration and intensity. This study highlights some important projected changes in the wind structure and profile under future anthropogenic forcing. This knowledge may support decisions on climate change adaptation options and risk reduction of several major sectors, such as energy and aviation, thus deserving further research. Full article

(This article belongs to the Special Issue Climate Events and Extreme Weather)

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17 pages, 5216 KiB

Open AccessArticle

Characterization of Spatio-Temporal Trends and Periodicity of Precipitation over Malawi during 1979–2015

by Edwin Tadeyo, Dan Chen, Brian Ayugi and Chunzhen Yao

Atmosphere 2020, 11(9), 891; https://doi.org/10.3390/atmos11090891 - 23 Aug 2020

Cited by 22 | Viewed by 3682

Abstract

Precipitation remains the key climatic parameter in sub-Saharan Africa, as it drives the economy through rain-fed agricultural production. Malawi is one of the countries most susceptible to the impacts of climate change and variability. This paper presents the characteristics of spatio-temporal trends and [...] Read more.

Precipitation remains the key climatic parameter in sub-Saharan Africa, as it drives the economy through rain-fed agricultural production. Malawi is one of the countries most susceptible to the impacts of climate change and variability. This paper presents the characteristics of spatio-temporal trends and periodicity of precipitation in Malawi in the period from 1979 to 2015. The analysis was based on recent rain ground gauge data. In total, 31 out of 36 rainfall stations, which include some key stations from the southeast of Malawi, were selected for the study after robust homogeneity tests were applied to the datasets. Spatial distribution of annual mean precipitation showed that high amounts of rainfall are located in areas along the lake and the southeast part of Malawi. The spatial distribution of the wet season (November to April) precipitation from EOF (Empirical Orthogonal Function) analysis revealed ten wet years (1985, 1986, 1989, 1996, 1997, 1999, 2001, 2006, 2007, and 2015) and ten dry years (1981, 1983, 1987, 1990, 1992, 1994, 1995, 2005, 2011, and 2014). In general, the temporal trends analyses of seasonal (wet season) and annual precipitations both displayed slight decreasing slopes during the 37 years. The trend of precipitation per decade displayed an increase in precipitation during 1980s and 1990s, followed by a decrease in the 21st century. Furthermore, the analysis of the spatial and temporal variability and trends of rainfall showed that northern and central Malawi displayed a clearer variability than southern Malawi. Although the trends of most of the stations are not significant at 95% confidence level, the decreasing rates of rainfall in the last decade and the decreasing trends on wet season and annual scale detected by Mann–Kendall tests require closer monitoring of rainfall changes in the near future. The stations which exhibited significant trends (Naminjiwa and Dedza stations) also call for closer monitoring, since the area relies heavily on rain-fed agriculture for economic sustenance. Full article

(This article belongs to the Special Issue Climate Events and Extreme Weather)

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18 pages, 8417 KiB

Open AccessArticle

Heatwaves in the Future Warmer Climate of South Africa

by Innocent Mbokodo, Mary-Jane Bopape, Hector Chikoore, Francois Engelbrecht and Nthaduleni Nethengwe

Atmosphere 2020, 11(7), 712; https://doi.org/10.3390/atmos11070712 - 03 Jul 2020

Cited by 51 | Viewed by 9126

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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20 pages, 9610 KiB

Open AccessArticle

How Unusual Were June 2019 Temperatures in the Context of European Climatology?

by Agnieszka Sulikowska and Agnieszka Wypych

Atmosphere 2020, 11(7), 697; https://doi.org/10.3390/atmos11070697 - 30 Jun 2020

Cited by 16 | Viewed by 2786

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)

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16 pages, 2244 KiB

Open AccessArticle

Possible Increase of Vegetation Exposure to Spring Frost under Climate Change in Switzerland

by Ondřej Lhotka and Stefan Brönnimann

Atmosphere 2020, 11(4), 391; https://doi.org/10.3390/atmos11040391 - 15 Apr 2020

Cited by 10 | Viewed by 4129

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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22 pages, 1284 KiB

Open AccessArticle

An Alternative to PCA for Estimating Dominant Patterns of Climate Variability and Extremes, with Application to U.S. and China Seasonal Rainfall

by Stephen Jewson

Atmosphere 2020, 11(4), 354; https://doi.org/10.3390/atmos11040354 - 07 Apr 2020

Cited by 5 | Viewed by 3662

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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20 pages, 2988 KiB

Open AccessArticle

Evaluation of Meteorological Drought and Flood Scenarios over Kenya, East Africa

by Brian Ayugi, Guirong Tan, Rouyun Niu, Zeyao Dong, Moses Ojara, Lucia Mumo, Hassen Babaousmail and Victor Ongoma

Atmosphere 2020, 11(3), 307; https://doi.org/10.3390/atmos11030307 - 21 Mar 2020

Cited by 73 | Viewed by 8100

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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15 pages, 4493 KiB

Open AccessArticle

An Integrated Wind Risk Warning Model for Urban Rail Transport in Shanghai, China

by Zhihui Han, Jianguo Tan, C. S. B. Grimmond, Bingxin Ma, Tongxiao Yang and Chunhui Weng

Atmosphere 2020, 11(1), 53; https://doi.org/10.3390/atmos11010053 - 01 Jan 2020

Cited by 3 | Viewed by 2652

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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17 pages, 3262 KiB

Open AccessArticle

Observed Multi-Timescale Differences between Summertime Near-Surface Equivalent Temperature and Temperature for China and Their Linkage with Global Sea Surface Temperatures

by Jingping Li, Xiao Li, Xing Li, Lian Chen and Likun Jin

Atmosphere 2019, 10(8), 447; https://doi.org/10.3390/atmos10080447 - 03 Aug 2019

Cited by 2 | Viewed by 2776

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 (T_e) 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 (T_e) 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 T_e 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 T_e are generally larger than that of T. Meanwhile, both T and T_e are dominated by their inter-annual, multi-decadal variations and the non-linear trend. High correlations of T and T_e 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 T_e 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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