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Abstract
In this study, a 10-yr (2008–17) radar-based mesoscale convective system (MCS) and derecho climatology for Poland is presented. This is one of the first attempts of a European country to investigate morphological and precipitation archetypes of MCSs as prior studies were mostly based on satellite data. Despite its ubiquity and significance for society, economy, agriculture, and water availability, little is known about the climatological aspects of MCSs over central Europe. Our results indicate that MCSs are not rare in Poland as an annual mean of 77 MCSs and 49 days with MCS can be depicted for Poland. Their lifetime ranges typically from 3 to 6 h, with initiation time around the afternoon hours (1200–1400 UTC) and dissipation stage in the evening (1900–2000 UTC). The most frequent morphological type of MCSs is a broken line (58% of cases), then areal/cluster (25%), and then quasi-linear convective systems (QLCS; 17%), which are usually associated with a bow echo (72% of QLCS). QLCS are the feature with the longest life cycle. Among precipitation archetypes of linear MCSs, trailing stratiform (73%) and parallel stratiform (25%) are the most common. MCSs are usually observed from April to September, with a peak in mid-July. A majority of MCSs travels from the west, southwest, and south sectors. A total of 16 derecho events were identified (1.5% of all MCS and 9.1% of all QLCS); the majority of them were produced by a warm-season QLCS, whereas only 4 were produced by cold-season narrow cold-frontal rainbands. Warm-season derechos produced a bigger impact than did cold-season events, even though their damage paths were shorter.
Abstract
In this study, a 10-yr (2008–17) radar-based mesoscale convective system (MCS) and derecho climatology for Poland is presented. This is one of the first attempts of a European country to investigate morphological and precipitation archetypes of MCSs as prior studies were mostly based on satellite data. Despite its ubiquity and significance for society, economy, agriculture, and water availability, little is known about the climatological aspects of MCSs over central Europe. Our results indicate that MCSs are not rare in Poland as an annual mean of 77 MCSs and 49 days with MCS can be depicted for Poland. Their lifetime ranges typically from 3 to 6 h, with initiation time around the afternoon hours (1200–1400 UTC) and dissipation stage in the evening (1900–2000 UTC). The most frequent morphological type of MCSs is a broken line (58% of cases), then areal/cluster (25%), and then quasi-linear convective systems (QLCS; 17%), which are usually associated with a bow echo (72% of QLCS). QLCS are the feature with the longest life cycle. Among precipitation archetypes of linear MCSs, trailing stratiform (73%) and parallel stratiform (25%) are the most common. MCSs are usually observed from April to September, with a peak in mid-July. A majority of MCSs travels from the west, southwest, and south sectors. A total of 16 derecho events were identified (1.5% of all MCS and 9.1% of all QLCS); the majority of them were produced by a warm-season QLCS, whereas only 4 were produced by cold-season narrow cold-frontal rainbands. Warm-season derechos produced a bigger impact than did cold-season events, even though their damage paths were shorter.
Abstract
Using historical sources derived from 12 Polish digital libraries, an investigation into killer tornado events was carried out. Although some of the cases took place more than 150 years ago, it was still possible to identify tornado phenomena and the course of events. This study has shown that historical sources contain dozens of tornado reports, sometimes with information precise enough to reconstruct the tornado damage paths. In total, 26 newly identified deadly tornado cases were derived from the historical sources and the information on 11 currently known was expanded. An average of 1–2 killer tornadoes with 5 fatalities may be depicted for each decade and this rate is decreasing over time. It was estimated that 5%–10% of significant tornadoes in Poland have caused fatalities and the average number of fatalities per significant tornado was roughly 0.27. Most of the cases were reported in late July and early August. The majority of deaths and injuries were associated with victims being lifted or crushed by buildings (usually a wooden barn). Most of these cases took place in rural areas but some tornadoes hit urban areas, causing a higher number of fatalities. The spatial distribution of cases included maxima in the central lowland and south-central upland of Poland. In a noticeable fraction of cases (38%), large hail occurred either before or after passage of the tornado.
Abstract
Using historical sources derived from 12 Polish digital libraries, an investigation into killer tornado events was carried out. Although some of the cases took place more than 150 years ago, it was still possible to identify tornado phenomena and the course of events. This study has shown that historical sources contain dozens of tornado reports, sometimes with information precise enough to reconstruct the tornado damage paths. In total, 26 newly identified deadly tornado cases were derived from the historical sources and the information on 11 currently known was expanded. An average of 1–2 killer tornadoes with 5 fatalities may be depicted for each decade and this rate is decreasing over time. It was estimated that 5%–10% of significant tornadoes in Poland have caused fatalities and the average number of fatalities per significant tornado was roughly 0.27. Most of the cases were reported in late July and early August. The majority of deaths and injuries were associated with victims being lifted or crushed by buildings (usually a wooden barn). Most of these cases took place in rural areas but some tornadoes hit urban areas, causing a higher number of fatalities. The spatial distribution of cases included maxima in the central lowland and south-central upland of Poland. In a noticeable fraction of cases (38%), large hail occurred either before or after passage of the tornado.
Abstract
Very few studies on the occurrence of tornadoes in Poland have been performed and, therefore, their temporal and spatial variability have not been well understood. This article describes an updated climatology of tornadoes in Poland and the major problems related to the database. In this study, the results of an investigation of tornado occurrence in a 100-yr historical record (1899–1998) and a more recent 15-yr observational dataset (1999–2013) are presented. A total of 269 tornado cases derived from the European Severe Weather Database are used in the analysis. The cases are divided according to their strength on the F scale with weak tornadoes (unrated/F0/F1; 169 cases), significant tornadoes (F2/F3/F4; 66 cases), and waterspouts (34 cases). The tornado season extends from May to September (84% of all cases) with the seasonal peak for tornadoes occurring over land in July (23% of all land cases) and waterspouts in August (50% of all waterspouts). On average 8–14 tornadoes (including 2–3 waterspouts) with 2 strong tornadoes occur each year and 1 violent one occurs every 12–19 years. The maximum daily probability for weak and significant tornadoes occurs between 1500 and 1800 UTC while it occurs between 0900 and 1200 UTC for waterspouts. Tornadoes over land are most likely to occur in the south-central part of the country known as the “Polish Tornado Alley.” Cases of strong, and even violent, tornadoes that caused deaths indicate that the possibility of a large-fatality tornado in Poland cannot be ignored.
Abstract
Very few studies on the occurrence of tornadoes in Poland have been performed and, therefore, their temporal and spatial variability have not been well understood. This article describes an updated climatology of tornadoes in Poland and the major problems related to the database. In this study, the results of an investigation of tornado occurrence in a 100-yr historical record (1899–1998) and a more recent 15-yr observational dataset (1999–2013) are presented. A total of 269 tornado cases derived from the European Severe Weather Database are used in the analysis. The cases are divided according to their strength on the F scale with weak tornadoes (unrated/F0/F1; 169 cases), significant tornadoes (F2/F3/F4; 66 cases), and waterspouts (34 cases). The tornado season extends from May to September (84% of all cases) with the seasonal peak for tornadoes occurring over land in July (23% of all land cases) and waterspouts in August (50% of all waterspouts). On average 8–14 tornadoes (including 2–3 waterspouts) with 2 strong tornadoes occur each year and 1 violent one occurs every 12–19 years. The maximum daily probability for weak and significant tornadoes occurs between 1500 and 1800 UTC while it occurs between 0900 and 1200 UTC for waterspouts. Tornadoes over land are most likely to occur in the south-central part of the country known as the “Polish Tornado Alley.” Cases of strong, and even violent, tornadoes that caused deaths indicate that the possibility of a large-fatality tornado in Poland cannot be ignored.
Abstract
This research focuses on the climatology of cloud-to-ground (CG) lightning flashes based on PERUN lightning detection network data from 2002 to 2013. To present various CG lightning flash characteristics, 10 km × 10 km grid cells are used, while for estimating thunderstorm days, circles with radii of 17.5 km in the 1 km × 1 km grid cells are used. A total of 4 328 892 CG lightning flashes are used to analyze counts, density, polarity, peak current, and thunderstorm days. An average of 151 days with thunderstorm (appearing anywhere in Poland) occurs each year. The annual number of days with thunderstorms increases southeasterly from the coast of the Baltic Sea (15–20 days) to the Carpathian Mountains (30–35 days). The mean CG lightning flash density varies from 0.2 to 3.1 flashes km−2 yr−1 with the highest values in the southwest–northeast belt from Kraków-Częstochowa Upland to the Masurian Lake District. The maximum daily CG lightning flash density in this region amounted to 9.1 km−2 day−1 (3 July 2012). The monthly variation shows a well-defined thunderstorm season extending from May to August with July as the peak month. The vast majority of CG lightning flashes were detected during the daytime (85%) with a peak at 1400 UTC and a minimum at 0700 UTC. Almost 97% of all CG lightning flashes in the present study had a negative current, reaching the highest average monthly values in February (55 kA) and the lowest in July (24 kA). The percentage of positive CG lightning flashes was the lowest during the summer (2%–3%) and the highest during the winter (10%–20%).
Abstract
This research focuses on the climatology of cloud-to-ground (CG) lightning flashes based on PERUN lightning detection network data from 2002 to 2013. To present various CG lightning flash characteristics, 10 km × 10 km grid cells are used, while for estimating thunderstorm days, circles with radii of 17.5 km in the 1 km × 1 km grid cells are used. A total of 4 328 892 CG lightning flashes are used to analyze counts, density, polarity, peak current, and thunderstorm days. An average of 151 days with thunderstorm (appearing anywhere in Poland) occurs each year. The annual number of days with thunderstorms increases southeasterly from the coast of the Baltic Sea (15–20 days) to the Carpathian Mountains (30–35 days). The mean CG lightning flash density varies from 0.2 to 3.1 flashes km−2 yr−1 with the highest values in the southwest–northeast belt from Kraków-Częstochowa Upland to the Masurian Lake District. The maximum daily CG lightning flash density in this region amounted to 9.1 km−2 day−1 (3 July 2012). The monthly variation shows a well-defined thunderstorm season extending from May to August with July as the peak month. The vast majority of CG lightning flashes were detected during the daytime (85%) with a peak at 1400 UTC and a minimum at 0700 UTC. Almost 97% of all CG lightning flashes in the present study had a negative current, reaching the highest average monthly values in February (55 kA) and the lowest in July (24 kA). The percentage of positive CG lightning flashes was the lowest during the summer (2%–3%) and the highest during the winter (10%–20%).
Abstract
The relationship between convective parameters derived from ERA5 and cloud-to-ground (CG) lightning flashes from the PERUN network in Poland was evaluated. All flashes detected between 2002 and 2019 were divided into intensity categories based on a peak 1-min CG lightning flash rate and were collocated with proximal profiles from ERA5 to assess their climatological variability. Thunderstorms in Poland are the most frequent in July, between 1400 and 1600 UTC and over the southeastern parts of the country. The highest median of most unstable convective available potential energy (MUCAPE) for CG lightning flash events is from June to August, between 1400 and 1600 UTC (around 900 J kg−1), whereas patterns in 0–6-km wind shear [deep-layer shear (DLS)] are reversed, with the highest median values during winter and night (around 25 m s−1). The best overlap of MUCAPE and DLS (MUWMAXSHEAR parameter) is in July–August, typically between 1400 and 2000 UTC with median values of around 850 m2 s−2. Thunderstorms in Poland are the most frequent in MUCAPE below 1000 J kg−1, and DLS between 8 and 15 m s−1. Along with increasing MUCAPE and DLS, peak CG lightning flash rates increase as well. Compared to DLS, MUCAPE is a more important parameter in forecasting any lightning activity, but when these two are combined together (MUWMAXSHEAR) they are more reliable in distinguishing between thunderstorms producing small and high CG lightning flash rates. Our results also indicate that higher CG lightning flash rates result in thunderstorms more frequently associated with severe weather reports (hail, tornado, wind).
Significance Statement
Each year severe thunderstorms produce considerable material losses and lead to deaths across central Europe; thus, a better understanding of local storm climatologies and their accompanying environments is important for operational forecasters, emergency managers, and risk estimation. In this research we address this issue by analyzing 18 years of lightning intensity data and collocated atmospheric environments. Thunderstorms in Poland are the most frequent in July between 1400 and 1600 UTC and form typically in environments with low atmospheric instability and moderate vertical shear of the horizontal wind. The probability for storms producing intense lightning increases when both of these environmental parameters reach higher values.
Abstract
The relationship between convective parameters derived from ERA5 and cloud-to-ground (CG) lightning flashes from the PERUN network in Poland was evaluated. All flashes detected between 2002 and 2019 were divided into intensity categories based on a peak 1-min CG lightning flash rate and were collocated with proximal profiles from ERA5 to assess their climatological variability. Thunderstorms in Poland are the most frequent in July, between 1400 and 1600 UTC and over the southeastern parts of the country. The highest median of most unstable convective available potential energy (MUCAPE) for CG lightning flash events is from June to August, between 1400 and 1600 UTC (around 900 J kg−1), whereas patterns in 0–6-km wind shear [deep-layer shear (DLS)] are reversed, with the highest median values during winter and night (around 25 m s−1). The best overlap of MUCAPE and DLS (MUWMAXSHEAR parameter) is in July–August, typically between 1400 and 2000 UTC with median values of around 850 m2 s−2. Thunderstorms in Poland are the most frequent in MUCAPE below 1000 J kg−1, and DLS between 8 and 15 m s−1. Along with increasing MUCAPE and DLS, peak CG lightning flash rates increase as well. Compared to DLS, MUCAPE is a more important parameter in forecasting any lightning activity, but when these two are combined together (MUWMAXSHEAR) they are more reliable in distinguishing between thunderstorms producing small and high CG lightning flash rates. Our results also indicate that higher CG lightning flash rates result in thunderstorms more frequently associated with severe weather reports (hail, tornado, wind).
Significance Statement
Each year severe thunderstorms produce considerable material losses and lead to deaths across central Europe; thus, a better understanding of local storm climatologies and their accompanying environments is important for operational forecasters, emergency managers, and risk estimation. In this research we address this issue by analyzing 18 years of lightning intensity data and collocated atmospheric environments. Thunderstorms in Poland are the most frequent in July between 1400 and 1600 UTC and form typically in environments with low atmospheric instability and moderate vertical shear of the horizontal wind. The probability for storms producing intense lightning increases when both of these environmental parameters reach higher values.
Abstract
Observed proximity soundings from Europe are used to highlight how well environmental parameters discriminate different kind of severe thunderstorm hazards. In addition, the skill of parameters in predicting lightning and waterspouts is also tested. The research area concentrates on central and western European countries and the years 2009–15. In total, 45 677 soundings are analyzed including 169 associated with extremely severe thunderstorms, 1754 with severe thunderstorms, 8361 with nonsevere thunderstorms, and 35 393 cases with nonzero convective available potential energy (CAPE) that had no thunderstorms. Results indicate that the occurrence of lightning is mainly a function of CAPE and is more likely when the temperature of the equilibrium level drops below −10°C. The probability for large hail is maximized with high values of boundary layer moisture, steep mid- and low-level lapse rates, and high lifting condensation level. The size of hail is mainly dependent on the deep layer shear (DLS) in a moderate to high CAPE environment. The likelihood of tornadoes increases along with increasing CAPE, DLS, and 0–1-km storm-relative helicity. Severe wind events are the most common in high vertical wind shear and steep low-level lapse rates. The probability for waterspouts is maximized in weak vertical wind shear and steep low-level lapse rates. Wind shear in the 0–3-km layer is the best at distinguishing between severe and extremely severe thunderstorms producing tornadoes and convective wind gusts. A parameter WMAXSHEAR multiplying square root of 2 times CAPE (WMAX) and DLS turned out to be the best in distinguishing between nonsevere and severe thunderstorms, and for assessing the severity of convective phenomena.
Abstract
Observed proximity soundings from Europe are used to highlight how well environmental parameters discriminate different kind of severe thunderstorm hazards. In addition, the skill of parameters in predicting lightning and waterspouts is also tested. The research area concentrates on central and western European countries and the years 2009–15. In total, 45 677 soundings are analyzed including 169 associated with extremely severe thunderstorms, 1754 with severe thunderstorms, 8361 with nonsevere thunderstorms, and 35 393 cases with nonzero convective available potential energy (CAPE) that had no thunderstorms. Results indicate that the occurrence of lightning is mainly a function of CAPE and is more likely when the temperature of the equilibrium level drops below −10°C. The probability for large hail is maximized with high values of boundary layer moisture, steep mid- and low-level lapse rates, and high lifting condensation level. The size of hail is mainly dependent on the deep layer shear (DLS) in a moderate to high CAPE environment. The likelihood of tornadoes increases along with increasing CAPE, DLS, and 0–1-km storm-relative helicity. Severe wind events are the most common in high vertical wind shear and steep low-level lapse rates. The probability for waterspouts is maximized in weak vertical wind shear and steep low-level lapse rates. Wind shear in the 0–3-km layer is the best at distinguishing between severe and extremely severe thunderstorms producing tornadoes and convective wind gusts. A parameter WMAXSHEAR multiplying square root of 2 times CAPE (WMAX) and DLS turned out to be the best in distinguishing between nonsevere and severe thunderstorms, and for assessing the severity of convective phenomena.
Abstract
The near-ground wind profile exhibits significant control over the organization, intensity, and steadiness of low-level updrafts and mesocyclones in severe thunderstorms, and thus their probability of being associated with tornadogenesis. The present work builds upon recent improvements in supercell tornado forecasting by examining the possibility that storm-relative helicity (SRH) integrated over progressively shallower layers has increased skill in differentiating between significantly tornadic and nontornadic severe thunderstorms. For a population of severe thunderstorms in the United States and Europe, sounding-derived parameters are computed from the ERA5 reanalysis, which has significantly enhanced vertical resolution compared to prior analyses. The ERA5 is shown to represent U.S. convective environments similarly to the Storm Prediction Center’s mesoscale surface objective analysis, but its greater number of vertical levels in the lower troposphere permits calculations to be performed over shallower layers. In the ERA5, progressively shallower layers of SRH provide greater discrimination between nontornadic and significantly tornadic thunderstorms in both the United States and Europe. In the United States, the 0–100 m AGL layer has the highest forecast skill of any SRH layer tested, although gains are comparatively modest for layers shallower than 0–500 m AGL. In Europe, the benefit from using shallower layers of SRH is even greater; the lower-tropospheric SRH is by far the most skillful ingredient there, far exceeding related composite parameters like the significant tornado parameter (which has negligible skill in Europe).
Abstract
The near-ground wind profile exhibits significant control over the organization, intensity, and steadiness of low-level updrafts and mesocyclones in severe thunderstorms, and thus their probability of being associated with tornadogenesis. The present work builds upon recent improvements in supercell tornado forecasting by examining the possibility that storm-relative helicity (SRH) integrated over progressively shallower layers has increased skill in differentiating between significantly tornadic and nontornadic severe thunderstorms. For a population of severe thunderstorms in the United States and Europe, sounding-derived parameters are computed from the ERA5 reanalysis, which has significantly enhanced vertical resolution compared to prior analyses. The ERA5 is shown to represent U.S. convective environments similarly to the Storm Prediction Center’s mesoscale surface objective analysis, but its greater number of vertical levels in the lower troposphere permits calculations to be performed over shallower layers. In the ERA5, progressively shallower layers of SRH provide greater discrimination between nontornadic and significantly tornadic thunderstorms in both the United States and Europe. In the United States, the 0–100 m AGL layer has the highest forecast skill of any SRH layer tested, although gains are comparatively modest for layers shallower than 0–500 m AGL. In Europe, the benefit from using shallower layers of SRH is even greater; the lower-tropospheric SRH is by far the most skillful ingredient there, far exceeding related composite parameters like the significant tornado parameter (which has negligible skill in Europe).
Abstract
Previous studies have identified environmental characteristics that skillfully discriminate between severe and significant-severe weather events, but they have largely been limited by sample size and/or population of predictor variables. Given the heightened societal impacts of significant-severe weather, this topic was revisited using over 150 000 ERA5 reanalysis-derived vertical profiles extracted at the grid point nearest—and just prior to—tornado and hail reports during the period 1996–2019. Profiles were quality controlled and used to calculate 84 variables. Several machine learning classification algorithms were trained, tested, and cross validated on these data to assess skill in predicting severe or significant-severe reports for tornadoes and hail. Random forest classification outperformed all tested methods as measured by cross-validated critical success index scores and area under the receiver operating characteristic curve values. In addition, random forest classification was found to be more reliable than other methods and exhibited negligible frequency bias. The top three most important random forest classification variables for tornadoes were wind speed at 500 hPa, wind speed at 850 hPa, and 0–500-m storm-relative helicity. For hail, storm-relative helicity in the 3–6 km and −10° to −30°C layers, along with 0–6-km bulk wind shear, were found to be most important. A game theoretic approach was used to help explain the output of the random forest classifiers and establish critical feature thresholds for operational nowcasting and forecasting. A use case of spatial applicability of the random forest model is also presented, demonstrating the potential utility for operational forecasting. Overall, this research supports a growing number of weather and climate studies finding admirable skill in random forest classification applications.
Abstract
Previous studies have identified environmental characteristics that skillfully discriminate between severe and significant-severe weather events, but they have largely been limited by sample size and/or population of predictor variables. Given the heightened societal impacts of significant-severe weather, this topic was revisited using over 150 000 ERA5 reanalysis-derived vertical profiles extracted at the grid point nearest—and just prior to—tornado and hail reports during the period 1996–2019. Profiles were quality controlled and used to calculate 84 variables. Several machine learning classification algorithms were trained, tested, and cross validated on these data to assess skill in predicting severe or significant-severe reports for tornadoes and hail. Random forest classification outperformed all tested methods as measured by cross-validated critical success index scores and area under the receiver operating characteristic curve values. In addition, random forest classification was found to be more reliable than other methods and exhibited negligible frequency bias. The top three most important random forest classification variables for tornadoes were wind speed at 500 hPa, wind speed at 850 hPa, and 0–500-m storm-relative helicity. For hail, storm-relative helicity in the 3–6 km and −10° to −30°C layers, along with 0–6-km bulk wind shear, were found to be most important. A game theoretic approach was used to help explain the output of the random forest classifiers and establish critical feature thresholds for operational nowcasting and forecasting. A use case of spatial applicability of the random forest model is also presented, demonstrating the potential utility for operational forecasting. Overall, this research supports a growing number of weather and climate studies finding admirable skill in random forest classification applications.
Abstract
In this work, long-term trends in convective parameters are compared between ERA5, MERRA-2, and observed rawinsonde profiles over Europe and the United States including surrounding areas. A 39-yr record (1980–2018) with 2.07 million quality-controlled measurements from 84 stations at 0000 and 1200 UTC is used for the comparison, along with collocated reanalysis profiles. Overall, reanalyses provide signals that are similar to observations, but ERA5 features lower biases. Over Europe, agreement in the trend signal between rawinsondes and the reanalyses is better, particularly with respect to instability (lifted index), low-level moisture (mixing ratio), and 0–3-km lapse rates as compared with mixed trends in the United States. However, consistent signals for all three datasets and both domains are found for robust increases in convective inhibition (CIN), downdraft CAPE (DCAPE), and decreases in mean 0–4-km relative humidity. Despite differing trends between continents, the reanalyses capture well changes in 0–6-km wind shear and 1–3-km mean wind with modest increases in the United States and decreases in Europe. However, these changes are mostly insignificant. All datasets indicate consistent warming of almost the entire tropospheric profile, which over Europe is the fastest near ground whereas across the Great Plains it is generally between 2 and 3 km above ground level, thus contributing to increases in CIN. Results of this work show the importance of intercomparing trends between various datasets, as the limitations associated with one reanalysis or observations may lead to uncertainties and lower our confidence in how parameters are changing over time.
Abstract
In this work, long-term trends in convective parameters are compared between ERA5, MERRA-2, and observed rawinsonde profiles over Europe and the United States including surrounding areas. A 39-yr record (1980–2018) with 2.07 million quality-controlled measurements from 84 stations at 0000 and 1200 UTC is used for the comparison, along with collocated reanalysis profiles. Overall, reanalyses provide signals that are similar to observations, but ERA5 features lower biases. Over Europe, agreement in the trend signal between rawinsondes and the reanalyses is better, particularly with respect to instability (lifted index), low-level moisture (mixing ratio), and 0–3-km lapse rates as compared with mixed trends in the United States. However, consistent signals for all three datasets and both domains are found for robust increases in convective inhibition (CIN), downdraft CAPE (DCAPE), and decreases in mean 0–4-km relative humidity. Despite differing trends between continents, the reanalyses capture well changes in 0–6-km wind shear and 1–3-km mean wind with modest increases in the United States and decreases in Europe. However, these changes are mostly insignificant. All datasets indicate consistent warming of almost the entire tropospheric profile, which over Europe is the fastest near ground whereas across the Great Plains it is generally between 2 and 3 km above ground level, thus contributing to increases in CIN. Results of this work show the importance of intercomparing trends between various datasets, as the limitations associated with one reanalysis or observations may lead to uncertainties and lower our confidence in how parameters are changing over time.
Abstract
Long-term trends in the historical frequency of environments supportive of atmospheric convection are unclear, and only partially follow the expectations of a warming climate. This uncertainty is driven by the lack of unequivocal changes in the ingredients for severe thunderstorms (i.e., conditional instability, sufficient low-level moisture, initiation mechanism, and vertical wind shear). ERA5 hybrid-sigma data allow for superior characterization of thermodynamic parameters including convective inhibition, which is very sensitive to the number of levels in the lower troposphere. Using hourly data we demonstrate that long-term decreases in instability and stronger convective inhibition cause a decline in the frequency of thunderstorm environments over the southern United States, particularly during summer. Conversely, increasingly favorable conditions for tornadoes are observed during winter across the Southeast. Over Europe, a pronounced multidecadal increase in low-level moisture has provided positive trends in thunderstorm environments over the south, central, and north, with decreases over the east due to strengthening convective inhibition. Modest increases in vertical wind shear and storm-relative helicity have been observed over northwestern Europe and the Great Plains. Both continents exhibit negative trends in the fraction of environments with likely convective initiation. This suggests that despite increasing instability, thunderstorms in a warming climate may be less likely to develop due to stronger convective inhibition and lower relative humidity. Decreases in convective initiation and resulting precipitation may have long-term implications for agriculture, water availability, and the frequency of severe weather such as large hail and tornadoes. Our results also indicate that trends observed over the United States cannot be assumed to be representative of other continents.
Abstract
Long-term trends in the historical frequency of environments supportive of atmospheric convection are unclear, and only partially follow the expectations of a warming climate. This uncertainty is driven by the lack of unequivocal changes in the ingredients for severe thunderstorms (i.e., conditional instability, sufficient low-level moisture, initiation mechanism, and vertical wind shear). ERA5 hybrid-sigma data allow for superior characterization of thermodynamic parameters including convective inhibition, which is very sensitive to the number of levels in the lower troposphere. Using hourly data we demonstrate that long-term decreases in instability and stronger convective inhibition cause a decline in the frequency of thunderstorm environments over the southern United States, particularly during summer. Conversely, increasingly favorable conditions for tornadoes are observed during winter across the Southeast. Over Europe, a pronounced multidecadal increase in low-level moisture has provided positive trends in thunderstorm environments over the south, central, and north, with decreases over the east due to strengthening convective inhibition. Modest increases in vertical wind shear and storm-relative helicity have been observed over northwestern Europe and the Great Plains. Both continents exhibit negative trends in the fraction of environments with likely convective initiation. This suggests that despite increasing instability, thunderstorms in a warming climate may be less likely to develop due to stronger convective inhibition and lower relative humidity. Decreases in convective initiation and resulting precipitation may have long-term implications for agriculture, water availability, and the frequency of severe weather such as large hail and tornadoes. Our results also indicate that trends observed over the United States cannot be assumed to be representative of other continents.
