Atmospheric Circulation Regimes Research Articles

A Bayesian Approach to Atmospheric Circulation Regime Assignment

Abstract The standard approach when studying atmospheric circulation regimes and their dynamics is to use a hard regime assignment, where each atmospheric state is assigned to the regime it is closest to in distance. However, this may not always be the most appropriate approach as the regime assignment may be affected by small deviations in the distance to the regimes due to noise. To mitigate this we develop a sequential probabilistic regime assignment using Bayes’s theorem, which can be applied to previously defined regimes and implemented in real time as new data become available. Bayes’s theorem tells us that the probability of being in a regime given the data can be determined by combining climatological likelihood with prior information. The regime probabilities at time t can be used to inform the prior probabilities at time t + 1, which are then used to sequentially update the regime probabilities. We apply this approach to both reanalysis data and a seasonal hindcast ensemble incorporating knowledge of the transition probabilities between regimes. Furthermore, making use of the signal present within the ensemble to better inform the prior probabilities allows for identifying more pronounced interannual variability. The signal within the interannual variability of wintertime North Atlantic circulation regimes is assessed using both a categorical and regression approach, with the strongest signals found during very strong El Niño years. Significance Statement Atmospheric circulation regimes are recurrent and persistent patterns that characterize the atmospheric circulation on time scales of 1–3 weeks. They are relevant for predictability on these time scales as mediators of weather. In this study we propose a novel approach to assigning atmospheric states to six predefined wintertime circulation regimes over the North Atlantic and Europe, which can be applied in real time. This approach introduces a probabilistic, instead of deterministic, regime assignment and uses prior knowledge on the regime dynamics. It allows us to better identify the regime persistence and indicates when a state does not clearly belong to one regime. Making use of an ensemble of model simulations, we can identify more pronounced interannual variability by using the full ensemble to inform prior knowledge on the regimes.

Occurrence of Winter Atmospheric Circulation Regimes in Euro-Atlantic Region and Associated Extreme Weather Anomalies in the Northern Hemisphere

Occurrence of Winter Atmospheric Circulation Regimes in Euro-Atlantic Region and Associated Extreme Weather Anomalies in the Northern Hemisphere

Changes in the Atmospheric Circulation Regime in the Context of Global Climate Trends in the Atlantic-Eurasian Sector of the Northern Hemisphere

Changes in the Atmospheric Circulation Regime in the Context of Global Climate Trends in the Atlantic-Eurasian Sector of the Northern Hemisphere

Shallow-water modelling of the atmospheric circulation regimes of brown dwarfs and their observable features

ABSTRACTObservations of time-varying thermal emission from brown dwarfs suggest that they have large-scale atmospheric circulation. The magnitude of this variability ranges from a few per cent to tens of per cent, implying a range of sizes of atmospheric perturbations. Periodograms of phase curves of the thermal emission reveal a range of peaks with different periods and widths, suggesting different atmospheric flow speeds and directions. This implies a variety of atmospheric circulations in the different brown dwarfs observed to date, but there is no general theoretical understanding of the circulation regimes these objects can support, and the resulting sizes and velocities of their atmospheric features. We therefore use an idealized 2D shallow-water model of a brown dwarf atmosphere to understand their potential large-scale circulation regimes. We non-dimensionalize the model to reduce the number of input parameters to two non-dimensional numbers: the thermal Rossby number and the non-dimensional radiative time-scale. This allows us to define a parameter space that bounds the entire range of brown dwarf behaviour possible in our model. We analyse the resulting height, velocity, and potential vorticity fields in this parameter space, and simulate observed phase curve and periodograms for comparison with real observations. We use our results to qualitatively define four circulation regimes, which we hope will be useful for interpreting observations and for guiding simulations with more detailed physical models.

Occurrence and Distribution of Long-Term Variability in Precipitation Classes in the Source Region of the Yangtze River

Various precipitation-related studies have been conducted on the Yangtze River. However, the topography and atmospheric circulation regime of the Source Region of the Yangtze River (SRYZ) differ from other basin parts. Along with natural uniqueness, precipitation constitutes over 60% of the direct discharge in the SRYZ, which depicts the decisive role of precipitation and a necessary study on the verge of climate change. The study evaluates the event distribution of long-term variability in precipitation classes in the SRYZ. The precipitation was classified into three precipitation classes: light precipitation (0–5 mm, 5–10 mm), moderate precipitation (10–15 mm, 15–20 mm, 20–25 mm), and heavy precipitation (>25 mm). The year 1998 was detected as a changing year using the Pettitt test in the precipitation time series; therefore, the time series was divided into three scenarios: Scenario-R (1961–2016), the pre-change point (Scenario-I; 1961–1998), and the post-change point (Scenario-II; 1999–2016). Observed annual precipitation amounts in the SRYZ during Scenario-R and Scenario-I significantly increased by 13.63 mm/decade and 48.8 mm/decade, respectively. The same increasing trend was evident in seasonal periods. On a daily scale, light precipitation (0–5 mm) covered most of the days during the entire period, with rainy days accounting for 83.50%, 84.5%, and 81.30%. These rainy days received up to 40%, 41%, and 38% of the annual precipitation during Scenario-R, Scenario-I, and Scenario-II, respectively. Consequently, these key findings of the study will be helpful in basin-scale water resources management.

Occurrence of winter atmospheric circulation regimes in Euro-Atlantic region and associated extreme weather anomalies in the Northern Hemisphere

Occurrence of winter atmospheric circulation regimes in Euro-Atlantic region and associated extreme weather anomalies in the Northern Hemisphere

Changes in volume and geometry of the Austre Dahlfonna glacier (Spitsbergen island) in 2008–2019

Previously published geodetic mass balance data indicate glacier shrinkage in the Barentsburg area of Svalbard since the beginning of the 20th century on the decadal time scale. However, observations for shorter time spans allowing one to compute the inter-annual variability of the mass balance are scarce. The study presents results of ground-based GNSS and the GPR surveys of the Austre Dahlfonna glacier (2 sq km) located on Spitsbergen island, south of the town of Barentsburg. According to the GPR survey of spring 2019 at 50 MHz frequency, the area-averaged ice thickness was equal to 82 m, while the maximum was 170 m. The results confirm the polythermal structure of the glacier, with a layer of underlying temperate ice. Since the end of the Little Ice Age, the area of Austre Dahlfonna has halved. By comparing the GNSS survey results (the end of the melt season of 2019) with the co-registered archived remote sensing data (ArcticDEM strip of 2013 and S0 Terrengmodell of 2008), it was computed that, within the last 12 years (2008–2019), Austre Dahlfonna lost 16 % of its volume, which corresponds to a geodetic mass balance of –12.05 ± 0.85 m w. e. The mass loss in 2008–2013 (5.22 ± 0.37 m w. e.) was lower than in 2013–2019 (6.83 ± 0.48 m w. e.), which is in agreement with the ongoing direct measurements on the neighboring Austre Grønfjordbreen glacier and with the archipelago-wide mass-balance patterns. We demonstrate that the less intensive glacier mass loss, which occurred in 2005–2012 and was detected previously for the whole archipelago, definitely took place in the Barentsburg area as well. This time interval is characterized by the prevalence of a negative NAO phase (65 % of recurrence), which may indicate more frequent intrusions of colder Arctic air masses. This fact proves that the mass-balance variability of the Barentsburg area glaciers is governed in time spans of 5–10 years by regional-scale factors, presumably by shifts in the atmospheric circulation regimes.

Revealing recurrent regimes of mid-latitude atmospheric variability using novel machine learning method.

The low-frequency variability of the extratropical atmosphere involves hemispheric-scale recurring, often persistent, states known as teleconnection patterns or regimes, which can have a profound impact on predictability on intra-seasonal and longer timescales. However, reliable data-driven identification and dynamical representation of such states are still challenging problems in modeling the dynamics of the atmosphere. We present a new method, which allows us both to detect recurring regimes of atmospheric variability and to obtain dynamical variables serving as an embedding for these regimes. The method combines two approaches from nonlinear data analysis: partitioning a network of recurrent states with studying its properties by the recurrence quantification analysis and the kernel principal component analysis. We apply the method to study teleconnection patterns in a quasi-geostrophical model of atmospheric circulation over the extratropical hemisphere as well as to reanalysis data of geopotential height anomalies in the mid-latitudes of the Northern Hemisphere atmosphere in the winter seasons from 1981 to the present. It is shown that the detected regimes as well as the obtained set of dynamical variables explain large-scale weather patterns, which are associated, in particular, with severe winters over Eurasia and North America. The method presented opens prospects for improving empirical modeling and long-term forecasting of large-scale atmospheric circulation regimes.

Linking maize yields in Veneto Italy, to large-scale atmospheric variability, circulation regimes and weather types

AbstractThis paper describes the relationships between large-scale modes of climate variability and its related weather types with the fluctuations in the yield of maize crops in Veneto, Italy. The teleconnections analysed in this work are the winter North Atlantic Oscillation (NAO) and the summer North Atlantic Oscillation (SNAO); the West African monsoon (WAM) and the Intertropical Front (ITF). Despite that these indices are not rigorously linked to one another, they result in being considerably related to atmospheric circulation regimes and associated weather types. They have an impact on temperature and precipitation patterns in Italy and on yields of maize crops in Veneto, a region located in northeast Italy. Yields are strongly affected by large-scale temperate and tropical variability directly through three main circulation regimes. Troughing weather regimes that produced below average temperatures depress yields over the entire Veneto region, as does the zonal regime that affects rainfall. Results confirm the relevance of large-scale modes and associated weather regimes and types on maize crop yields fluctuations in Veneto.

Changes in temperature–precipitation correlations over Europe: are climate models reliable?

Inter-variable correlations (e.g., between daily temperature and precipitation) are key statistical properties to characterise probabilities of simultaneous climate events and compound events. Their correct simulations from climate models, both in values and in changes over time, is then a prerequisite to investigate their future changes and associated impacts. Therefore, this study first evaluates the capabilities of one 11-single run multi-model ensemble (CMIP6) and one 40-member single model initial-condition large ensemble (CESM) over Europe to reproduce the characteristics of a reanalysis dataset (ERA5) in terms of temperature–precipitation correlations and their historical changes. Next, the ensembles’ correlations for the end of the 21st century are compared. Over the historical period, both CMIP6 and CESM ensembles have season-dependent and spatially structured biases. Moreover, the inter-variable correlations from both ensembles mostly appear stationary. Thus, although reanalysis displays significant correlation changes, none of the ensembles can reproduce them, with internal variability representing only 30% on the inter-model variability. However, future correlations show significant changes over large spatial patterns. Yet, those patterns are rather different for CMIP6 and CESM, reflecting a large uncertainty in changes. In addition, for historical and future projections, an analysis conditional on atmospheric circulation regimes is performed. The conditional correlations given the regimes are found to be the main contributor to the biases in correlation over the historical period, and to the past and future changes of correlation. These results highlight the importance of the large-scale circulation regimes and the need to understand their physical relationships with local-scale phenomena associated to specific inter-variable correlations.

Winter wet–dry weather patterns driving atmospheric rivers and Santa Ana winds provide evidence for increasing wildfire hazard in California

Floods caused by atmospheric rivers and wildfires fanned by Santa Ana winds are common occurrences in California with devastating societal impacts. In this work, we show that winter weather variability in California, including the occurrence of extreme and impactful events, is linked to four atmospheric circulation regimes over the North Pacific Ocean previously named and identified as the “NP4 modes”. These modes come in and out of phase with each other during the season, resulting in distinct weather patterns that recur throughout the historical record. Some phase combinations favor atmospheric river landfalls and extreme daily or multi-day precipitation, while other phase combinations favor anomalously hot weather and drying Santa Ana wind conditions over Southern California. This historical perspective of atmospheric circulation and impacts over 70 years reveals that weather patterns are changing in a way that enhances wildfire hazard in California, while the frequency of weather patterns linked to historical floods is not diminishing. These changes highlight the rising hazards of cascading weather extremes in California’s present and future.

Exploring the Effects of Active Magnetic Drag in a General Circulation Model of the Ultrahot Jupiter WASP-76b

Ultrahot Jupiters represent an exciting avenue for testing extreme physics and observing atmospheric circulation regimes not found in our solar system. Their high temperatures result in thermally ionized particles embedded in atmospheric winds interacting with the planet’s interior magnetic field by generating current and experiencing bulk Lorentz force drag. Previous treatments of magnetic drag in 3D general circulation models (GCMs) of ultrahot Jupiters have mostly been uniform drag timescales applied evenly throughout the planet, which neglects the strong spatial dependence of these magnetic effects. In this work, we apply our locally calculated active magnetic drag treatment in a GCM of the planet WASP-76b. We find the effects of this treatment to be most pronounced in the planet’s upper atmosphere, where strong differences between the day and night side circulation are present. These circulation effects alter the resulting phase curves by reducing the hot spot offset and increasing the day–night flux contrast. We compare our models to Spitzer phase curves, which imply a magnetic field of at least 3 G for the planet. We additionally contrast our results to uniform drag timescale models. This work highlights the need for more careful treatment of magnetic effects in atmospheric models of hot gas giants.

Detection of interannual ensemble forecast signals over the North Atlantic and Europe using atmospheric circulation regimes

AbstractTo study the forced variability of atmospheric circulation regimes, the use of model ensembles is often necessary for identifying statistically significant signals as the observed data constitute a small sample and are thus strongly affected by the noise associated with sampling uncertainty. However, the regime representation is itself affected by noise within the atmosphere, which can make it difficult to detect robust signals. To this end we employ a regularised k‐means clustering algorithm to better identify the signal in a model ensemble. The approach allows for the identification of six regimes for the wintertime Euro‐Atlantic sector and leads to more pronounced regime dynamics, compared to results without regularisation, both overall and on sub‐seasonal and interannual time‐scales. We find that sub‐seasonal variability in the regime occurrence rates is mainly explained by changes in the seasonal cycle of the mean climatology. On interannual time‐scales relations between the occurrence rates of the regimes and the El Niño Southern Oscillation (ENSO) are identified. The use of six regimes captures a more detailed response of the circulation to ENSO compared to the common use of four regimes. Predictable signals in occurrence rate on interannual time‐scales are found for the two zonal flow regimes, namely a regime consisting of a negative geopotential height anomaly over the Norwegian Sea and Scandinavia, and the positive phase of the NAO. The signal strength for these regimes is comparable between observations and model, in contrast to that of the NAO‐index where the signal strength in the observations is underestimated by a factor of 2 in the model. Our regime analysis suggests that this signal‐to‐noise problem for the NAO‐index is primarily related to those atmospheric flow patterns associated with the negative NAO‐index as we find poor predictability for the corresponding NAO regime.

General Circulation Model Errors Are Variable across Exoclimate Parameter Spaces

Abstract General circulation models (GCMs) are often used to explore exoclimate parameter spaces and classify atmospheric circulation regimes. Models are tuned to give reasonable climate states for standard test cases, such as the Held–Suarez test, and then used to simulate diverse exoclimates by varying input parameters such as rotation rates, instellation, atmospheric optical properties, frictional timescales, and so on. In such studies, there is an implicit assumption that the model works reasonably well for the standard test case will be credible at all points in an arbitrarily wide parameter space. Here, we test this assumption using the open-source GCM THOR to simulate atmospheric circulation on tidally locked Earth-like planets with rotation periods of 0.1–100 days. We find that the model error, as quantified by the ratio between physical and spurious numerical contributions to the angular momentum balance, is extremely variable across this range of rotation periods with some cases where numerical errors are the dominant component. Increasing model grid resolution does improve errors, but using a higher-order numerical diffusion scheme can sometimes magnify errors for finite-volume dynamical solvers. We further show that to minimize error and make the angular momentum balance more physical within our model, the surface friction timescale must be smaller than the rotational timescale.

Atmospheric circulation regimes for prescribed burns along the U.S. Gulf of Mexico coast

The regional-to-synoptic-scale steering atmospheric circulation is important for advecting energy, mass, and momentum across space, with the near-surface wind being the local manifestation of this circulation. The local winds can affect phenomena of economic, ecological, and/or aesthetic values, such as bird migrations and prescribed burns to restore bird habitats. The purpose of this research is to classify the days from 1979 to 2018 based on circulation patterns near the surface (i.e., 1000-hPa) and at the highest level of airflow affecting bird migration (i.e., 700-hPa), across the Gulf Coast region of the United States. The resulting patterns, derived from Ward's clustering method on rotated principal component scores, are used as input in a fire management plan to restore niches for bird species such as black and yellow rails and mottled ducks. Results suggest that for the (near-surface) 1000-hPa level, a classification system consisting of eight circulation types maximizes the between-group variability while minimizing the within-group variability, with a total of 95.8 percent of the dataset variance explained, and reasonable correspondence with existing manual, subjective and semi-automated techniques. At the 700-hPa level, a system of eight circulation types was derived, explaining 95.05 percent of the dataset variance. In general, the western U.S. Gulf of Mexico arc is more likely than the eastern to respond to synoptic control in the form of weather types, while the eastern region may have more influence from local-to-meso-scale land and sea breezes. These results will assist in optimizing the success of controlled burn conditions while enhancing efforts to minimize advection to populated areas.

Sensitivity of near-surface meteorology to PBL schemes in WRF simulations in a port-industrial area with complex terrain

Parameterizations of the Planetary Boundary Layer (PBL) embedded in numerical weather prediction models are crucial in the simulation of local meteorology and require a special investigation. In this study we evaluate simulations at 1 km horizontal resolution using six PBL schemes of the Weather Research and Forecasting model (WRF) by comparison to observations performed in a coastal port-industrial area (Civitavecchia) on the Tyrrhenian coast of Central Italy. During the measurement campaign (April 2016) three types of atmospheric circulation regimes were identified: “breeze”, “jet” and “synoptic”. Some generalizations can be inferred from the results, despite the variety of settings analyzed (two sites, three regimes in both day and night conditions). Our results show that the temperature simulation is much more sensitive to the configuration at night than during the day, especially on breeze days, when the occurrence of stable boundary layer is favored. For wind speed, non-local schemes are very similar to each other, unlike the local closure schemes.The use of the urban Building Environment Parameterization (BEP) significantly improves the simulation of the 2 m temperature during the “jet” evenings and nights, while it entails a further overestimation of the temperature during the “breeze” days leading to a reduction of the bias.

Circulation Pathways and Exports of Arctic River Runoff Influenced by Atmospheric Circulation Regimes

River runoff supplies the Arctic Ocean with a large amount of freshwater and land-derived material, so it is important for both the physical and biogeochemical marine environment. In this study, we used wind perturbation simulations to elucidate the response of the circulation pathways and exports of Arctic river runoff to different atmospheric circulation regimes. Specifically, wind perturbations representing the negative and positive phases of the Arctic Oscillation and Beaufort High modes were imposed over the Arctic Ocean separately in different sensitivity experiments. In addition, some combinations of the two modes were also considered in sensitivity experiments. By comparing these experiments with a control simulation, we revealed the impact of different wind perturbations. The atmospheric circulation regimes influence the Arctic surface geostrophic currents through changing the halosteric height, which is associated with the changes in spatial distribution of surface freshwater. The circulation pathways of river runoff, and Pacific and Atlantic derived surface waters are mainly determined by the surface geostrophic currents. The positive (negative) Arctic Oscillation reduces (increases) freshwater storage and sea surface height in the Makarov and Eurasian basins, thus strengthening (weakening) the cyclonic circulation and weakening (strengthening) the anticyclonic circulation; Accordingly, the Eurasian runoff leaves the Siberian shelf at more eastern (western) locations, and has an enhanced export through the Fram Strait (Canadian Arctic Archipelago). The positive (negative) Beaufort High increases (reduces) freshwater storage and sea surface height in the Amerasian Basin, thus strengthening (weakening) the anticyclonic circulation; Accordingly, the Eurasian runoff export through the Fram Strait and the Mackenzie River runoff export through the Canadian Arctic Archipelago are reduced (increased). The positive Arctic Oscillation increases freshwater available to the Beaufort Gyre, which can be efficiently accumulated there in the presence of a positive Beaufort High forcing. The impact of the Beaufort High mode on the location of the Transpolar Drift Stream and runoff circulation pathways is stronger with a positive Arctic Oscillation than with a neutral Arctic Oscillation state. Our results also showed that Eurasian runoff can only have a relatively small contribution to freshwater accumulation in the Beaufort Gyre region.

Contrasting northern and southern European winter climate trends during the Last Interglacial

Abstract The Last Interglacial (LIG; 130–115 ka) is an important test bed for climate science as an instance of significantly warmer than preindustrial global temperatures. However, LIG climate patterns remain poorly resolved, especially for winter, affected by a suite of strong feedbacks such as changes in sea-ice cover in the high latitudes. We present a synthesis of winter temperature and precipitation proxy data from the Atlantic seaboard of Europe, spanning from southern Iberia to the Arctic. Our data reveal distinct, opposite latitudinal climate trends, including warming winters seen in the European Arctic while cooling and drying occurred in southwest Europe over the LIG. Climate model simulations for 130 and 120 ka suggest these contrasting climate patterns were affected by a shift toward an atmospheric circulation regime with an enhanced meridional pressure gradient and strengthened midlatitude westerlies, leading to a strong reduction in precipitation across southern Europe.

Variability of the low-level circulation of the South American Monsoon analysed with complex networks

Understanding the variability of low-level atmospheric circulation regimes is key for understanding the dynamics of monsoon systems. The South American Monsoon is characterized by strong year-long trade winds that are channeled southward into the South American Low-Level Jet after crossing the Amazon basin, which in turn is elementary for the moisture transport to Southern South America. In this study, we utilize streamflow wind networks, a type of climate networks that tracks the local flow of the wind field, together with the analysis of composites of wind, precipitation, and geopotential height fields, to investigate the variability of the South American low-level circulation. The streamflow wind networks are used here as they are able to directly track the wind flow and encode its spatiotemporal characteristics in their topology. We focus on intraseasonal variations in terms of active and break monsoon phases on the one hand, and on the interannual variability in terms of the impacts of the El Niño-Southern Oscillation on the other hand. Our findings highlight the importance of the South American Low-Level Jet, its spatial position and variability. Our study reveals the relation of the active and break regimes to anomalous high- and low-pressure systems over the southern Atlantic that are connected to Rossby wave trains from the southern Pacific, as well as the impact of these regimes on the cross-equatorial low-level flow. In addition, the streamflow networks that we use demonstrate significant shifts of the dominant wind flow pattern during El Niño and La Niña episodes.

Control Mechanisms of Primary Productivity Revealed by Calcareous Nannoplankton From Marine Isotope Stages 12 to 9 at the Shackleton Site (IODP Site U1385)

AbstractNowadays, primary productivity variations at the SW Iberian Margin (IbM) are primarily controlled by wind‐driven upwelling. Thus, major changes in atmospheric circulation and wind regimes between the Marine Isotope Stages (MIS) 12 and 9 could have driven substantial changes in phytoplankton productivity which remains poorly understood. We present a high‐resolution calcareous nannofossil record from the Shackleton Site Integrated Ocean Discovery Program Site U1385 that allow the assessment of primary productivity and changing surface conditions on orbital and suborbital timescales over the SW IbM. These records are directly compared and integrated with terrestrial – Mediterranean forest pollen – and marine – benthic and planktic oxygen stable isotopes (δ18O), alkenone concentration [C37], Uk´37‐Sea Surface Temperature and % C37:4 – proxy records from Site U1385. Our results indicate intra‐interglacial increase in primary productivity together with intensification of the Azores anticyclonic high‐pressure cell beyond the summer that suggests a two‐phase upwelling behavior during the full interglacial MIS 11c (∼420–397 ka), potentially drived by atmospheric NAO‐like variability. Primary productivity is largely enhanced during the inception of glacial MIS 10 and the early MIS 10 (∼392–356 ka), linked to intensified upwelling and associated processes during a period of strengthened atmospheric circulation. In agreement with the conditions observed during Heinrich events of the last glacial cycle, primary productivity reductions during abrupt cold episodes, including the Heinrich‐type (Ht) events 4 to 1 (∼436, 392, 384 and 339 ka) and the Terminations V and IV, seems to be the result of halocline formation induced by meltwater arrival, reducing the regional upward nutrient transference.