Pluvial conditions in the eastern Sahara following the penultimate deglaciation: implications for changes in atmospheric circulation patterns with global warming

1993 ◽  
Vol 103 (1-2) ◽  
pp. 95-105 ◽  
Author(s):  
Judith A. McKenzie
2020 ◽  
Author(s):  
Kathrin Wehrli ◽  
Mathias Hauser ◽  
Sonia I. Seneviratne

Abstract. Extreme temperatures were experienced over a large part of the Northern Hemisphere during the 2018 boreal summer (hereafter referred to as NH2018 event), leading to major impacts to agriculture and society in the affected countries. Previous studies highlighted both the anomalous atmospheric circulation patterns during the event and the background warming due to human greenhouse gas emissions as main drivers for the event. In this study, we present Earth System Model experiments investigating different storylines of the NH2018 event given the same atmospheric circulation and alternative background global warming for: no human imprint, the 2018 conditions, and different mean global warming levels (1.5 °C, 2 °C, 3 °C, and 4 °C). The results reveal that the human-induced background warming was a strong contributor to the intensity of the NH2018 event, and that resulting extremes under similar atmospheric circulation conditions at higher levels of global warming would reach very dangerous levels. About 32 % (61 %) of the inhabited or agricultural area in the investigated region would reach maximum temperatures over 40 °C under 2 °C (4 °C) of global warming and similar atmospheric circulation conditions.


2020 ◽  
Vol 11 (4) ◽  
pp. 855-873
Author(s):  
Kathrin Wehrli ◽  
Mathias Hauser ◽  
Sonia I. Seneviratne

Abstract. Extreme temperatures were experienced over a large part of the Northern Hemisphere during the 2018 boreal summer (hereafter referred to as “NH2018 event”), leading to major impacts on agriculture and society in the affected countries. Previous studies highlighted both the anomalous atmospheric circulation patterns during the event and the background warming due to human greenhouse gas emissions as main drivers of the event. In this study, we present Earth system model experiments investigating different storylines of the NH2018 event given the same atmospheric circulation and alternative background global warming for no human imprint, the 2018 conditions, and different mean global warming levels 1.5, 2, 3 and 4 ∘C. The results reveal that the human-induced background warming was a strong contributor to the intensity of the NH2018 event, and that resulting extremes under similar atmospheric circulation conditions at higher levels of global warming would reach dangerous levels. Compared to 9 % during the NH2018 event, about 13 % (34 %) of the inhabited or agricultural area in the investigated region would reach daily maximum temperatures over 40 ∘C under 2 ∘C (4 ∘C) of global warming and similar atmospheric circulation conditions.


2014 ◽  
Vol 14 (8) ◽  
pp. 2145-2155 ◽  
Author(s):  
J. Pringle ◽  
D. D. Stretch ◽  
A. Bárdossy

Abstract. Wave climates are fundamental drivers of coastal vulnerability; changing trends in wave heights, periods and directions can severely impact a coastline. In a diverse storm environment, the changes in these parameters are difficult to detect and quantify. Since wave climates are linked to atmospheric circulation patterns, an automated and objective classification scheme was developed to explore links between synoptic-scale circulation patterns and wave climate variables, specifically wave heights. The algorithm uses a set of objective functions based on wave heights to guide the classification and find atmospheric classes with strong links to wave behaviour. Spatially distributed fuzzy numbers define the classes and are used to detect locally high- and low-pressure anomalies. Classes are derived through a process of simulated annealing. The optimized classification focuses on extreme wave events. The east coast of South Africa was used as a case study. The results show that three dominant patterns drive extreme wave events. The circulation patterns exhibit some seasonality with one pattern present throughout the year. Some 50–80% of the extreme wave events are explained by these three patterns. It is evident that strong low-pressure anomalies east of the country drive a wind towards the KwaZulu-Natal coastline which results in extreme wave conditions. We conclude that the methodology can be used to link circulation patterns to wave heights within a diverse storm environment. The circulation patterns agree with qualitative observations of wave climate drivers. There are applications to the assessment of coastal vulnerability and the management of coastlines worldwide.


2022 ◽  
pp. 1-41

Abstract The interannual variation of springtime extreme precipitation (SEP) days in North China (NC) and their reliance on atmospheric circulation patterns are studied by using the continuous daily record of 396 rain gauges and the fifth generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis during 1979–2019. The SEP days are defined as the days when at least 10% of rain gauges in NC record daily precipitation no less than 10.5 mm. Results show that the number of SEP days shows large interannual variability but no significant trend in the study period. Using the objective classification method of the obliquely rotated principal analysis in T-mode, we classify the atmospheric circulation into five different patterns based on the geopotential height at 700 hPa. Three circulation patterns all have fronts and are associated with strong southerly wind, leading to 88% of SEP days in NC. The strong southerly wind may provide moisture and dynamic forcing for the frontal precipitation. The interannual variation of SEP days is related with the number of the three above-mentioned dominant circulation patterns. Further analysis shows that the West Pacific pattern could be one of the possible climate variability modes related to SEP days. This study reveals that the daily circulation pattern may be the linkage between SEP days and climate variability modes in NC.


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