Daily Circulation Patterns Research Articles

Prevalent atmospheric and oceanic signals of the unprecedented heatwaves over the Yangtze River Valley in July–August 2022

Unprecedented heatwaves attacked the Yangtze River valley (YRV) in July–August of 2022. The heatwave-favorable circulation pattern for the YRV is identified by using a self-organizing map. Result shows that the dominant daily circulation pattern driving heatwaves in the YRV is the East Asian anticyclonic pattern (EAAP), characterized by an anomalous deep anticyclone over the East Asian mid-latitudes. Remarkably, the unprecedented frequent occurrence of EAAP in 2022 contributes about 84.6% of the temperature anomalies in the 35 YRV hot days, which is the key dynamical factor for the heatwave in 2022. Physical mechanisms for the occurrence of EAAP are revealed on interannual and interdecadal time scales. On interannual time scale, the dipole sea surface temperature (SST) anomalies over the North Atlantic, characterized by warm and cold SST anomalies in the midlatitudes and subtropics, respectively, exert an important influence on the EAAP days. This dipole SST pattern is unprecedentedly strong in 2022. It facilitates the EAAP through the maintenance of the coupled British–Okhotsk Corridor pattern and the Silk Road pattern in the mid-latitudes. Additionally, the persistent cold SST anomalies in tropical Indian ocean and the central-eastern Pacific from the preceding spring to summer contribute to cooling of the tropical troposphere and induce easterly anomalies in the East Asian subtropics, thereby further promoting the occurrence of EAAP. On interdecadal time scale, the negative Pacific Decadal Oscillation may establish favorable circulation conditions for the occurrence of the EAAP through modulating the interdecadal Silk Road pattern. These findings improve our understanding of the physical mechanisms for driving extreme heatwaves in the YRV and have an implication for enhancing regional heatwave prediction.

Features and Evolution of Autumn Weather Regimes in the Southeast China

Autumn is the transitional season when the atmospheric circulation pattern changes from summer to winter. The temperature and precipitation in Southeastern China in autumn are significantly influenced by the change in circulation patterns, and both show significant uniqueness. The clustering method can be used to observe the changes of circulation patterns in detail and to observe and analyze the transition from warm to cold seasons from a detailed view of the daily circulation pattern perspective. This method may have important research implications on how to study the generation and dissipation of extreme weather events. The Self-Organizing Maps (SOM) method is used to a 500 hPa geopotential height and 850 hPa wind and sea level pressure for 1981–2020 to identify the characteristic weather patterns (WTs) in autumn (September–November) over Southeastern China. Characteristics of the captured WTs are also analyzed in terms of the distribution characteristics of weather patterns, occurrence frequency, typical progression, precipitation and extreme precipitation (EP), temperature and extreme high temperature (EHT), and the relationship with atmospheric teleconnection. Nine WTs were identified in autumn, which represents a series of weather situations consisting of troughs and ridges. On this basis, these WTs were used to carry out the differentiation of seasonal differences between early and late autumn. The maximum mean and extreme precipitation occur in several early season patterns (WT1, WT2, WT4, and WT7). It is highly likely that extremely high temperatures occur in the WT1 and WT2 patterns. The most common progression between WTs is WT7−WT1−WT2−WT4 in the early season. This seasonality allows us to distinguish between early and late seasons based on daily weather types. A preliminary trend analysis suggests that patterns in the early season occur more frequently and last longer in the early season, and patterns in the late season occur less frequently and later. That is, the longer cool season pattern is shifting to the shorter warm season pattern. In addition, the persistence of both cool and warm patterns increased during 2001–2020 relative to 1981–2000, and the risk of both flooding and drought occurrence is on the rise.

Spring Extreme Precipitation Days in North China and Their Reliance on Atmospheric Circulation Patterns during 1979–2019

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. Significance Statement Springtime extreme precipitation (SEP) has important social and economic impacts on North China (NC), but few studies have examined the variation of SEP in NC. We find that the number of SEP days has no significant trend but shows large interannual variability during 1979–2019. The interannual variation of SEP days is mainly determined by the total days of three frontal circulation patterns associated with strong southerly wind. Based on the daily circulation pattern, the West Pacific pattern is found to be one of the possible climate variability modes related to SEP days. These findings may shed light on the understanding of SEP in midlatitudes around the world.

Synoptic circulation changes over Central Europe from 1900 to 2100: Reanalyses and Coupled Model Intercomparison Project phase 6

AbstractWhile the evidence for anthropogenic climate change continues to strengthen, and concerns about severe weather events are increasing, global projections of regional climate change are still uncertain due to model‐dependent changes in large‐scale atmospheric circulation, including over North Atlantic and Europe. Here, the Jenkinson–Collison classification of daily circulation patterns is used to evaluate past and future changes in their seasonal frequencies over Central Europe for the 1900–2100 period. Three reanalyses and eight global climate models from the Coupled Model Intercomparison Project phase 6, were used based on daily mean sea‐level pressure data. Best agreement in deriving relative frequencies of the synoptic types was found between the reanalyses. Global models can generally capture the interannual variability of circulation patterns and their climatological state, especially for the less frequent synoptic types. Based on historical data and the shared socioeconomic pathway 5 scenario, the evaluated trends show more robust signals during summer, given their lesser internal variability. Increasing frequencies were found for circulation types characterized by weak pressure gradients, mainly at the expense of decreasing frequencies of westerlies. Our findings indicate that given a high‐emission scenario, these signals will likely emerge from past climate variability towards the mid‐21st century for most altered circulation patterns.

Detectable anthropogenic changes in daily-scale circulations driving summer rainfall shifts over eastern China

Wetting in the south while drying in the north during the last few decades constitutes the well-known ‘southern flood–northern drought’ (SFND) precipitation pattern over eastern China. The fingerprint of anthropogenic influence on this dipole pattern of regional precipitation trends has not been confirmed, especially for forced changes in relevant dynamics at the synoptic scale. Using a process-based approach involving model experiments both with and without anthropogenic inputs, it is demonstrated that the occurrences of daily circulation patterns (CPs) governing precipitation over eastern China during 1961–2013 have been altered by human influence. Due to anthropogenic forcing, CPs favoring SFND have become more likely to occur at the expense of CPs unfavorable to SFND. Regression analysis shows that changes recorded in the occurrence of CPs from the factual simulations could explain a large part of the precipitation trends over eastern China. CP frequencies driven by purely natural forcing do not reproduce this dipole pattern nor the inferred magnitude of precipitation trends over eastern China. These results suggest that human influence has played a critical role in shaping the contrasting north–south precipitation trends.

Precipitation projections for Spain by means of a weather typing statistical method

This study develops a weather typing stochastic method for the climatic prediction of rainfall in Peninsular Spain and the Balearic Islands during the 21st century. Cluster analysis is applied to the geopotential height fields with the purpose of classifying the atmospheric states into distinct daily circulation patterns. The same kind of analysis is performed on the rainfall distributions, obtaining the corresponding daily rainfall patterns. It is possible to establish a suitable association between each of the circulation types and the rainfall patterns. This circulation–rainfall link becomes the essence of our downscaling method, which will allow the “reconstruction” of the accumulated rainfall field from a generated sequence of daily rainfall patterns. This is done with the support of a statistical weather generator using the daily patterns of atmospheric circulation provided by different GCMs as input. The weather typing approach and the weather generator strategy interrelate in a novel and unique way different from any previous method. The downscaling method is first subjected to calibration, using reanalysis circulation as input, from which the optimal number of atmospheric and rainfall patterns to perform the projection is found. Later on the method is subjected to validation, using GCMs' daily atmospheric circulation as input, in order to test its robustness. The final part of the study focuses on the analysis and intercomparison of future precipitation projections for the 21st century under the A1B emission scenario from five different GCMs. A substantial drying of about 30% is foreseen at the end of the century in Spain compared to present, although with a nonuniform pattern in space and time as the century progresses.

An automated classification method of daily circulation patterns for surface climate data downscaling based on optimized fuzzy rules

A method for automated circulation patterns (CPs) definition and classification is presented, based on optimized fuzzy rules. The target of the method is to provide a basis (daily classified CPs) for downscaling of the most common climate data, i.e. precipitation and temperature. Therefore the presented classification method is objective providing CPs that explain the dependency between the large-scale atmospheric circulation and the surface climate. Thus the downscaling can be done by means of downscaling models with parameters depending on the CPs. The CPs are defined using 700 hPa geo-potential field anomalies. Fuzzy rules are described by the position of high- and low-pressure anomalies. The fuzzy rules are obtained automatically, using an optimization for the performance of the classification. For the precipitation, the performance of the classification is measured by rainfall frequencies and rainfall amounts conditioned on the CPs. Thus, the task is to define wet or dry CPs. For the temperature, the deviation from the average long-term annual cycle is used. In this way, warm or cold CPs are identified. The presented method produces physically realistic CP definitions. With the help of these definitions, the observed (historical) pressure fields can be classified for twelve precipitation stations and four temperature stations inside and around the Mesochora catchment in Greece.

Nonlinear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates

AbstractA statistical framework based on nonlinear dynamics theory and recurrence quantification analysis of dynamical systems is proposed to quantitatively identify the temporal characteristics of extreme (maximum) daily precipitation series. The methodology focuses on both observed and general circulation model (GCM) generated climates for present (1961–2000) and future (2061–2100) periods which correspond to 1xCO2 and 2xCO2 simulations. The daily precipitation has been modelled as a stochastic process coupled with atmospheric circulation. An automated and objective classification of daily circulation patterns (CPs) based on optimized fuzzy rules was used to classify both observed CPs and ECHAM4 GCM‐generated CPs for 1xCO2 and 2xCO2 climate simulations (scenarios). The coupled model ‘CP‐precipitation’ was suitable for precipitation downscaling. The overall methodology was applied to the medium‐sized mountainous Mesochora catchment in Central‐Western Greece. Results reveal substantial differences between the observed maximum daily precipitation statistical patterns and those produced by the two climate scenarios. A variable nonlinear deterministic behaviour characterizes all climate scenarios examined. Transitions’ patterns differ in terms of duration and intensity. The 2xCO2 scenario contains the strongest transitions highlighting an unusual shift between floods and droughts. The implications of the results to the predictability of the phenomenon are also discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Estimation of the dispersion of an accidental release of radionuclides and toxic materials based on weather type classification

We investigate the influence of the regional-scale weather types on the atmospheric dispersion processes of the air pollutants originated from point sources. Hypothetical accidents were simulated with two different dispersion models. During a year’s test period, the 6-h emission of a radionuclide from the Paks Nuclear Power Plant (Paks NPP, Hungary) was assumed every day and the transport and deposition of the radionuclide was simulated by the Eulerian TREX dispersion model over the Central European region. In addition, the ALOHA Gaussian air dispersion model was also used for the local environment of the Paks NPP to simulate hypothetical hourly releases of ammonia during a 10-year period. During both types of model simulations, the dispersion of the plume for each time was analysed and tested with consideration of 13 circulation types corresponding to daily weather patterns over the Carpathian Basin. There are significant correlations between circulation types and plume directions and structures both in local and regional scales. The daily circulation pattern can be easily obtained from weather analyses; the expected size and direction of polluted area after an accidental release can be quickly estimated even before an accident occurs. However, this fast method cannot replace or neglect dispersion model simulations. It gives a ‘first guess’ and a fast estimation on the direction of the plume and can provide sufficient information for decision-making strategies.

Decadal Variability in a Central Greenland High-Resolution Deuterium Isotope Record and Its Relationship to the Frequency of Daily Atmospheric Circulation Patterns from the North Atlantic Region

Abstract The variability of an annual resolution deuterium time series from central Greenland is investigated in connection with the variability in the frequency of daily atmospheric circulation patterns in the North Atlantic region. Statistical analysis reveals that a large part of the decadal variability of the deuterium isotope record is related to decadal variability in the frequency of several identified daily circulation patterns. The study shows that these circulation patterns induce variations in the deuterium record by altering where isotopic fractionation occurs, mainly during the passage of the associated air masses over continental areas. The study identifies three significant periodic components in the deuterium isotope record at ∼12, ∼20, and ∼30 yr. It also shows that the ∼20-yr signal in the deuterium isotope record is related to the variability in the frequency of a winter circulation type. An analysis of six oxygen isotope records from central Greenland reveals decadal variations similar to the deuterium isotope record. The authors argue that high-resolution stable isotope records from Greenland ice cores can be used to obtain information about the frequency of certain daily circulation patterns during past periods.

Spatial modelling of air temperature and precipitation for Andorra (Pyrenees) from daily circulation patterns

Based on the daily sea level pressure (SLP) circulation catalogue obtained by Esteban, Martin-Vide and Mases, Int J Climatol 26:1501–1515, (2006) for Western Europe, high-resolution maps of daily maximum and minimum temperature, mean daily precipitation and daily precipitation probability have been obtained for Andorra (Pyrenees). The 20 daily-circulation patterns cover the period 1960–2001 and were generated using new approaches based on the rotated principal component analysis (PCA) and clustering technique. The final maps of Andorra associated with each circulation pattern have been constructed using altitude, latitude, continentality and solar radiation as multiple regression predictors (Ninyerola, Pons and Roure, Int J Climatol 20:1823–1841, 2000). The daily temperature and rainfall series used from Andorran, French and Catalan/Spanish weather stations have been checked for data quality. The results confirm the complexity of the spatial distribution of meteorological phenomena over mountainous areas such as in Andorra, and show the importance of the Mediterranean and Atlantic influence upon the climate of this country of the Pyrenees. On the other hand, different tests have been made showing that the classification results could improve the resulting interpolated climate maps by the use of the circulation-pattern frequencies.

Synoptic conditions of snow occurrence in Budapest

Daily circulation patterns responsible for snow occurrence in Budapest were analysed. Three types of circulation patterns were distinguished, using a Principal Component Analysis and clustering technique, for days with snowfalls and snow cover persistence. Low pressure systems located over the Italian Peninsula (south-west of Budapest) are characteristic for days with snowfalls. Such lows coming from the west generate warm fronts and are a source of humidity necessary for the snowfalls. At the same time, higher pressure extends north or east of the Carpathian Basin and brings polar continental air masses and consequently low temperature. Snow persistence also requires temperature below zero. This condition is fulfilled at the airflow direction from the east (or south east) which brings frosty air from the interior of the continent. A winter high pressure system extending over the Carpathian Basin also generates low temperature, mainly due to the nocturnal radiation conditioned by a clear sky.

Long-Term Variability of Daily North Atlantic–European Pressure Patterns since 1850 Classified by Simulated Annealing Clustering

AbstractReconstructed daily mean sea level pressure patterns of the North Atlantic–European region are classified for the period 1850 to 2003 to explore long-term changes of the atmospheric circulation and its impact on long-term temperature variability in the central European region. Commonly used k-means clustering algorithms resulted in classifications of low quality because of methodological deficiencies leading to local optima by chance for complex datasets. In contrast, a newly implemented clustering scheme combining the concepts of simulated annealing and diversified randomization (SANDRA) is able to reduce substantially the influence of chance in the cluster assignment, leading to partitions that are noticeably nearer to the global optimum and more stable. The differences between conventional cluster analysis and the SANDRA scheme are significant for subsequent analyses of single clusters—in particular, for trend analysis. Conventional indices used to determine the appropriate number of clusters failed to provide clear guidance, indicating that no distinct separation between clusters of circulation types exists in the dataset. Therefore, the number of clusters is determined by an external indicator, the so-called dominance criteria for t-mode principal component analysis. Nevertheless, the resulting partitions are stable for certain numbers of clusters and provide meaningful and reproducible clusters. The resulting types of pressure patterns reveal pronounced long-term variability and various significant trends of the time series of seasonal cluster frequency. Tentative estimations of central European temperature changes based solely on seasonal cluster frequencies can explain between 33.9% (summer) and 59.0% (winter) of temperature variance on the seasonal time scale. However, the signs of long-term changes in temperature are correctly reproduced even on multidecadal–centennial time scales. Moreover, linear warming trends are reproduced, implying from one-third up to one-half of the observed temperature increase between 1851/52 and 2003 (except for summer, but with significant trends for spring and autumn), indicating that changes in daily circulation patterns contribute to the observed overall long-term warming in the central European region.

Synoptic reasons for heavy snowfalls in the Polish – German lowlands

Daily circulation patterns responsible for heavy snowfalls in the Polish – German lowlands were analysed. Composite maps of sea level pressure (SLP) and 500 hPa geopotential height means and anomalies were constructed for the days with an increase in snow cover depth by ≥5 cm. Contour maps show negative anomalies of SLP and 500 hPa level over central Europe, indicating a low pressure system. Strong positive anomalies of SLP appear over Scandinavia and the northern Atlantic with the centre of positive anomalies located over Iceland. Weaker negative anomalies are observed in the Azores region. This confirms the strong negative correlation between snow cover appearance and the North Atlantic Oscillation index in Europe. The days with heavy snowfalls were clustered using the Ward’s method. Three types of circulation patterns were distinguished, each of them characterised by a low pressure system over central Europe. Type 3 represents the northern position of the low with its centre over the Baltic Sea, Type 2 shows the southern position of the low with its centre over the Adriatic and the Ionic Sea and Type 1 represents the low location between the two previous patterns with a wide meridional trough over the Atlantic.

Developing daily precipitation scenarios for climate change impact studies in the Guadiana and the Tejo basins

Abstract. Hydrological models to evaluate the impacts of climate change in the water resources sector require spatially correlated daily precipitation scenarios as model inputs. This paper presents a practical procedure for developing such precipitation scenarios using multisite stochastic weather models or generators conditional on large-scale daily circulation patterns, based on GCM-simulated future mean sea level pressure (MSLP) fields. The procedure is demonstrated on the basis of HadCM3 and HadAM3H simulations with an example for two river basins in the Iberian Peninsula. Changes in daily precipitation scenarios for the region generated by stochastic models are consistent with large-scale precipitation scenarios from direct GCM outputs; however, more localised characteristics have to be found from downscaled precipitation scenarios rather than from direct GCM outputs. This may imply that possible changes in downscaled precipitation reflect the underlying physics in GCMs, so that downscaled daily precipitation scenarios may be more suitable for impact models than the coarse GCM outputs.

Comprehensive analysis of the climate variability in the eastern Mediterranean. Part I: map‐pattern classification

AbstractThis paper provides an extended study of the dominant daily circulation patterns governing the climate variability in the eastern Mediterranean. The methodology adopted to determine the circulation patterns is based on combined analysis of the spatial and temporal variation of rotated principal components of sea‐level pressure. A catalogue of characteristic seasonal composites is presented and discussed. It is found that, during winter and spring, large scale features situated in northern Europe affect the atmospheric circulation over the domain of study, whereas the Atlantic (Azores) anticyclone and the Asian Thermal Low define most of the observed circulation types in summer. In autumn, the area exhibits a rapid transition from the warm to cold season showing climatic features from both extreme seasons. Similarities between winter and spring/autumn patterns are detected and correlation analyses are employed between their spatial patterns to reveal that similar circulation patterns occur amongst the three seasons, which usually appear more pronounced during winter. Frequencies and trends of the proposed circulation types are examined for each season. A linear trend analysis for the overall period (1958–2000) exhibits a significant increase in the anticyclonic types particularly in winter. With respect to the cyclonic types, statistically significant negative trends have been found in all seasons especially for types associated with depressional activity in central the Mediterranean. Copyright © 2007 Royal Meteorological Society

Weather regimes and their connection to the winter rainfall in Portugal

AbstractWintertime rainfall over Portugal is strongly coupled with the large‐scale atmospheric flow in the Euro‐Atlantic sector. A K‐means cluster analysis, on the space spanned by a subset of the empirical orthogonal functions of the daily mean sea‐level pressure fields, is performed aiming to isolate the weather regimes responsible for the interannual variability of the winter precipitation. Each daily circulation pattern is keyed to a set of five weather regimes (C, W, NAO−, NAO+ and E). The dynamical structure of each regime substantiates the statistical properties of the respective rainfall distribution and validates the clustering technique. The C regime is related to low‐pressure systems over the North Atlantic that induce southwesterly and westerly moist winds over the country. The W regime is characterized by westerly disturbed weather associated with low‐pressure systems mainly located over northern Europe. The NAO− regime is manifested by weak low‐pressure systems near Portugal. The NAO+ regime corresponds to a well‐developed Azores high with generally settled and dry weather conditions. Finally, the E regime is related to anomalous strong easterly winds and rather dry conditions. Although the variability in the frequencies of occurrence of the C and NAO− regimes is largely dominant in the interannual variability of the winter rainfall throughout Portugal, the C regime is particularly meaningful over northern Portugal and the NAO− regime acquires higher relevance over southern Portugal. The inclusion of the W regime improves the description of the variability over northern and central Portugal. Dry weather conditions prevail in both the NAO+ and E regimes, with hardly any exceptions. The occurrence of the NAO+ and the NAO− regimes is also strongly coupled with the North Atlantic oscillation. Copyright © 2005 Royal Meteorological Society

Multisite stochastic weather models for impact studies

AbstractStochastic weather models have been developed for simultaneous simulations of daily precipitation, and daily maximum and minimum temperatures at multiple sites in a river basin in order to reproduce the interstation correlations and self‐consistency in weather series. The basic structure of the stochastic weather models was adopted from Wilks (1999. Agricultural and Forest Meteorology 96: 85–101), but an extension was made to condition the model parameters on daily circulation patterns. Model parameters were also estimated without conditioning on daily circulation patterns, so that both conditional and unconditional simulations were conducted and compared. Statistical analyses on the synthetic weather data imply a better performance of the conditional simulations, on most aspects of the required statistics. In addition, the conditional weather models on daily circulation patterns can be applied directly in impact studies, for the purpose of downscaling climate scenarios from climate model simulations, and some related aspects are also discussed. Copyright © 2002 Royal Meteorological Society.

Automated objective classification of daily circulation patterns for precipitation and temperature downscaling based on optimized fuzzy rules

A methodology for automated objective circulation pattern (CP) definition and classifi- cation is presented based on optimized fuzzy rules. The main goal of the method is to provide a basis (daily classified CPs) for downscaling of precipitation and temperature, which can be done by means of downscaling models with parameters depending on the CP. The CPs are defined using 500 or 700 hPa geopotential height anomalies. Fuzzy rules are defined by the position of high- and low- pressure anomalies. The fuzzy rules are obtained automatically using an optimization of the perfor- mance of the classification. For precipitation, the performance of the classification is measured by rainfall frequencies and rainfall amounts conditioned on the CP. So the task is to define wet or dry CPs. For temperature, the deviation from the average long-term annual cycle is used. In this way warm or cold CPs are identified. The performance of the CPs is validated using a split-sampling approach. The presented method produces physically realistic CP definitions. With the help of these definitions the observed (historical) pressure fields can be classified as shown in 2 case studies for regions with different climate conditions: Central Europe (Germany) and the Eastern Mediterranean (Greece).

A circulation classification scheme applicable in GCM studies

The goal of the paper is to present and examine the method of classification of daily circulation patterns that allows (i) a fair comparison of groupings among different datasets (typically representing the observed climate and that simulated by a general circulation model, GCM) and (ii) huge datasets, common in GCM studies based on daily values, to be classified. The circulation classification method is shown to be a useful tool in GCM validation and analysis of climate change response, particularly in comparisons of (i) shapes of the mean type patterns, (ii) the frequency and persistence of the types, (iii) the probability of transitions from one type to another, and (iv) conditional surface temperature distributions. It is also shown that a simultaneous examination of multiple classifications is beneficial in eliminating subjectivity of any single classification and allowing a detailed inspection of differences between climates.