The dynamics of the tropospheric polar jet stream are a key control of weather and climate in the mid-latitudes. These dynamics arise from the interplay of baroclinic instability and large-scale wave patterns known as Rossby waves . To zeroth order, these components are driven by meridional temperature gradients, the thermal wind relation and the Earth's rotation. In the North Atlantic region, the polar jet is often referred to as the North Atlantic jet.

The North Atlantic jet influences regional weather across Europe and the Baltic Sea region by modulating pressure systems, temperature advection, cloud cover, radiative processes and precipitation patterns . More specifically, jet variability in the North Atlantic can be organized by time scale. On synoptic time scales, it primarily reflects baroclinic wave growth and downstream development that is tightly coupled with the storm track. On longer intraseasonal time scales, the dominant variability is captured by persistent flow patterns (weather regimes) . On seasonal to interannual scales, anomalies in the jet latitude and strength project onto canonical modes of climate variability such as the NAO or the East Atlantic pattern . On decadal and longer time scales, coupled ocean-atmosphere variability in the North Atlantic can modulate the jet and storm track, providing a pathway for low-frequency variability to influence Northern Europe and the Baltic Sea region .

It should be noted that several localized processes further modulate this large-scale circulation and form the basis for typical synoptic-scale weather phenomena and dominant modes of climate variability affecting the Baltic Sea region. Factors such as orography, seasonal snow, ice cover, radiative processes, ocean heat transport and differences between land and ocean surfaces all contribute to a distinct thermal structure that drives a seasonal cycle. As a consequence, the jet stream follows a seasonally varying pattern with locally modified characteristics .

Because the jet's latitude and strength vary seasonally, upstream Pacific circulation anomalies as well as the state of the North Atlantic Ocean , affect the jet differently in different seasons. Consequently, their downstream impacts over Europe and the Baltic Sea region are also season-dependent .

Changes in the structure, latitude and strength of the North Atlantic jet not only drive extreme weather in the mid-latitudes, such as heat waves, cold-air outbreaks and droughts, but also regulate moisture and precipitation . Close to 90 % of the poleward moisture transport occurs within atmospheric rivers , long, narrow corridors in the atmosphere characterized by strong horizontal water vapor transport. Atmospheric rivers are typically in the warm conveyor belt ahead of extratropical cyclones. By influencing cyclone growth and storm tracks, the North Atlantic jet sets the preferred corridors and landfall latitudes. Accordingly, atmospheric river occurrence, intensity and associated precipitation patterns over the Baltic Sea region are sensitive to shifts in the North Atlantic jet as well.

Pattern-based dimensionality reduction approaches are commonly used to assess this complexity, including canonical large-scale circulation patterns such as the NAO or the Euro-Atlantic weather regimes , which collapse jet and storm-track variability, Rossby-wave dynamics, and related regional modulation into a small number of reference states and display a systematic connection to jet characteristics . These approaches provide an interpretable link between large-scale atmospheric circulation and its regional importance in the Baltic Sea region and allow a more detailed description of the local dynamics by describing their patterns and statistical properties. They are less suited to describe phenomena that are controlled by specific synoptic sequences rather than low-dimensional modes, such as MBIs, which depend on particular wind and pressure patterns e.g.,.

An atmospheric block is a long-lasting (days to a few weeks) weather pattern that occurs when persistent and quasi-stationary highs hinder the climatological westerly winds in the mid-latitudes . Dynamically, blocking is closely tied to the jet-stream and Rossby wave variability discussed in the previous section, as it reflects amplified planetary-wave patterns and is often accompanied by wave breaking and a deformation or splitting of the jet. This commonly leads to a deflected and strong zonal flow north and south of the blocking system and prevents the usual progression of synoptic weather systems across large areas . Blocking systems typically extend vertically across the whole troposphere and are associated with large high pressure systems at the surface. As a consequence of their tight coupling to the background flow, changes in the large-scale circulation states (and modes of climate variability) can modulate blocking statistics by shifting the jet and storm track and therefore also the region of dominant wave amplification and breaking.

In the mid-latitudes, blocking is frequently associated with extreme weather conditions, including heat waves , cold spells , heavy rainfall and compound weather events . The type of extreme event also depends on the exact location of the blocking pattern. Moreover, a single blocking event can cause different surface extremes at different locations (Fig. ). In general, blocking events are 7–10 d long and the most extreme events last 2–3 weeks. However, the societal relevance of these events is not solely defined by their persistence but also by the number of total blocking days and their seasonality .

Figure  illustrates the potential extreme surface weather conditions in the Baltic Sea region associated with the Omega pattern: a blocking high with two cutoff lows on either side, with a high-pressure system squeezed in between. Panels (a) and (b) separate the impacts between the cold season (October to March) and the warm season (April to September), respectively. During the colder months, the eastern side of the blocking system may exhibit low-temperature anomalies. In contrast, the warmer months are prone to heat waves beneath the blocking system, occasionally coinciding with drought conditions. Additionally, the probability of thunderstorms increases at both the eastern and western flanks of the blocking system. Regardless of the season, heavy rainfall events – potentially leading to floods and associated with high integrated water vapor concentrations – are observed at the edges and near the poleward boundary of the blocking ridge.

Atmospheric circulation variability over the Baltic Sea region spans a broad range of time scales, from synoptic to multidecadal, and reflects the interplay of atmospheric, oceanic, and terrestrial factors. At shorter time scales, departures from the climatological reference state often take the form of large-scale geopotential height anomalies that persist from several days to about two weeks .

These recurrent disturbances are modulated by variations in the Euro-Atlantic atmospheric circulation and are well classified by the Euro-Atlantic weather regimes . At their core, weather regimes represent a statistical description of persistent and recurrent circulation patterns, similar to attractors in non-linear dynamical systems that can be described in terms of their quasi-stationarity and frequency of occurrence. The regimes are identified objectively from daily large-scale circulation anomalies over the Euro-Atlantic sector: the seasonal cycle is removed and anomaly fields are normalized by their standard deviation, dimensionality is reduced using the leading EOFs (principal components), and k-means clustering is applied in this reduced phase space. This yields a daily sequence of regime occurrence, with some days assigned to one of the recurrent regimes and others classified as transition or “no regime” days . The regimes affect the Baltic Sea region by shaping the synoptic-scale pressure gradient over Northern Europe. They are closely linked to jet-stream variability and the associated characteristic flow patterns . As a result, they modulate the prevalence and intensity of westerly flow into the Baltic Sea catchment versus blocking situations, as well as the position and strength of the storm tracks affecting the region.

Traditionally, the canonical Euro-Atlantic weather-regime classification refers to the four recurrent large-scale circulation regimes most robustly identified in boreal winter . In this manuscript, weather regimes refer to statistically identified, recurrent large-scale circulation states, rather than to individual synoptic weather patterns. The Zonal and Greenland-Blocking regimes are often described as NAO-like, in the sense that they project strongly onto the positive and negative phases of the NAO, respectively. Hence, the Zonal pattern (NAO+) corresponds to a central North Atlantic jet which brings mild and wet air masses as well as Atlantic cyclones into Northern Europe . In contrast, Greenland Blocking (NAO-) represents a more southerly jet position, weakening the westerlies, favoring colder, drier conditions. The Atlantic Ridge describes a high pressure system over the Atlantic with a northward shift of the jet, leading to stable weather and potentially blocking the eastward progression of wet and windy conditions. The Scandinavian Blocking is a high pressure system over Scandinavia featuring a jet structure that tilts from southwest to northeast (Fig. ).

A year-round classification adds three more regimes (Fig. ): the Scandinavian Trough, a low pressure system over Scandinavia, the Atlantic Trough, associated with a low pressure system over the North Atlantic, and European Blocking, marked by a high pressure system over western Europe that blocks the North Atlantic jet . In total, the seven weather regimes represent different types of zonal regimes (Atlantic Trough, Zonal, and Scandinavian Trough), responsible for the advection of warm (or cold) air masses from the North Atlantic region into the Baltic Sea region, as well as four regional blocking regimes (Atlantic Ridge, European Blocking, Scandinavian Blocking, and Greenland Blocking).

Depending on the season, zonal regimes are associated with wet and cool (warm) conditions in northern Europe during summer (winter). In contrast, the blocked regimes interrupt the mean flow and are often associated with hot and dry spells during summer and cold spells on their eastern flank during winter .

The seven regimes (Fig. ) occur with a similar frequency but have strong seasonal preferences. Zonal regimes (i.e. Atlantic Trough, Zonal/NAO+ and Scandinavian Trough) are more common in winter (November–March), with Zonal being particularly frequent. Summer (May–September) is dominated by blocked regimes (i.e. Atlantic Ridge, European Blocking, Scandinavian Blocking and Greenland Blocking), with Scandinavian Blocking occurring most often. Atlantic Trough occurs year round and European Blocking is the leading winter blocking pattern, while Scandinavian Blocking dominates summer .

Seasonal circulation variability over the Baltic Sea region differs markedly between winter and summer. Winter is dominated by zonal (NAO-like) patterns, enhanced baroclinicity and high internal variability. The latter is often weaker, with a poleward-shifted jet and a more barotropic background. Thermodynamic processes such as land-sea contrasts, soil-moisture feedbacks, and diabatic heating then play a larger role in shaping circulation variability and extremes . This suggests that large-scale atmospheric circulation variability exerts a stronger control on the Baltic Sea region in winter than in summer.

Interannual variability can be understood through the lens of the jet stream. Specifically, anomalies in the location and intensity of the jet stream during the winter season drive climate variability that can explain much of the observed interannual variability . Good examples are the winters of 2009/10 and 2011/12 (Fig. ), which exhibited opposite jet regimes: the former displayed an anomalously southerly, zonal jet, while the latter displayed an anomalously northerly jet . The first led to an anomalously cold winter in the Baltic Sea region, while the second led to an unusually warm winter.

The NAO reflects a leading mode of observed interannual wintertime variability in North Atlantic-European atmospheric circulation and is tightly coupled to the zonal jet. Notably, both the intensity (NAO+ or NAO-; Fig. ) and the geographic positioning of the NAO centers of action vary substantially year-to-year . These spatial shifts of the NAO modify how strongly the NAO affects the Baltic Sea region, as changes in the pressure gradient orientation alter prevailing wind patterns . This dynamic is likely linked to the interaction between the NAO and the jet stream , which due to the zonal shift of the Icelandic Low aligns the westerly winds directly toward the Baltic Sea.

To relate this interannual perspective to the synoptic-to-intraseasonal weather-regime framework introduced above, we compare the characteristic circulation patterns associated with the main interannual climate-variability indices to the circulation patterns of the weather regimes. The positive East Atlantic pattern corresponds to a quasi-stationary ridge over the North Atlantic aligning with the Atlantic Ridge regime, while the negative East Atlantic pattern corresponds to the Atlantic Trough . Together with the NAO, the East Atlantic pattern can be used as a combined framework describing both climatological changes and interannual and multidecadal variability in the North Atlantic jet . However, the NAO primarily describes shifts in the jet latitude, which tends to be more relevant for interannual time scales . For the Baltic Sea region, this distinction implies that NAO-driven jet-latitude shifts dominate year-to-year variability in winter temperature, sea-ice and storminess, whereas changes linked with the East Atlantic pattern modulate multidecadal variability.

While the positive phase of the Scandinavian pattern e.g., resembles Scandinavian Blocking, its negative phase aligns with the Scandinavian Trough. After the NAO and East Atlantic pattern, it is the third most important winter sea level pressure pattern over the North Atlantic domain and in the Baltic Sea region, specifically, it is considered the second most important pattern .

Since the Scandinavian pattern resembles the positive Scandinavian Blocking regime , the question arises how it might be connected to the interannual variability of blocking occurrences. According to , the anticyclonic center of the Scandinavian pattern lies in a region where the potential vorticity gradients are generally very low during the winter months, possibly favoring the development of a block. However, found that the dominant winter blocking patterns are connected to different large-scale circulation patterns, the Scandinavian pattern only being one of them. This could be different in the summer season where Scandinavian Blocking occurs more often. However, studies on summer modes of interannual variability are still scarce.

In summary, these interannual modes systematically alter the direction and strength of the flow over Northern Europe/Scandinavia, modulating winter advection, storminess, temperature, and sea-ice. Multiple other interannual circulation patterns in the Euro-Atlantic sector have been identified, for example the East Atlantic/West Russia pattern or the Barents Sea Oscillation . They all represent a statistical description of characteristic jet features. However, there is little literature specifically addressing their role in modulating the climate of the Baltic Sea region on interannual time scales.

On decadal time scales, atmospheric variability in Northern Europe is modulated by an interplay of the aforementioned atmospheric modes with the North Atlantic Ocean, shaping the statistics of local climate in the Baltic Sea region. The ocean's memory, especially through the Atlantic Meridional Overturning Circulation (AMOC), drives much of this decadal variability as it transports heat into higher latitudes, altering sea surface temperature (SST) patterns e.g.,.

One central component of this variability is the AMV, which refers to basin-wide fluctuations in the North Atlantic SSTs over multidecadal periods e.g.,. The main driver of these fluctuations is likely a combination of internal variability that is coupled to AMOC variability and a response to external forcing . For the Baltic Sea region, large ensembles of global climate simulations suggest that the response to external forcing is more relevant than internal variability .

Sea surface temperature anomalies that are advected along the North Atlantic current influence temperature variations in the Norwegian Sea and over Norway . These anomalies can often be traced back to oceanic advection of signals from the North Atlantic subpolar gyre (SPG) , which is one of the most predictable regions in the world on decadal to multidecadal time scales . This connection indicates a potential for successful near-term predictions of decadal climate variability in the Baltic Sea region.

Multidecadal SST variations in the North Atlantic have been shown to alter the atmospheric circulation in the North Atlantic and climate variability across Europe with further impacts on the Nordic Seas and the Baltic Sea . One example of this influence is the modulation of a subpolar wave train, a large-scale atmospheric pattern that responds to SST anomalies and projects onto the European climate . This wave train is often centered over Northern Europe and transports oceanic signals from the North Atlantic into the Baltic Sea region.

Similar to the interannual time scale, in Northern Europe, decadal atmospheric variability in wintertime over the North Atlantic is dominated by the NAO e.g.,. More specifically, the decadal to multidecadal SST anomalies, linked to the AMV, influence both the position and strength of the NAO and the jet stream . Hence, during wintertime, the AMV influences the advection of air masses from the North Atlantic, weakening the westerlies during its positive states. Negative AMV states are associated with increased westerlies, transporting moist air masses into the Baltic Sea region . This coupling between the ocean and the atmosphere has been linked to the relative importance of the NAO for the Baltic Sea region on multidecadal time scales . During summer, subtropical North Atlantic SSTs excite an atmospheric Rossby wave which connects to decadal surface air temperature fluctuations in Europe, with an imprint on the Baltic Sea region e.g.,.

On decadal to multidecadal time scales, the relevance of modes of climate variability such as the NAO arises from changes in the frequency and persistence of large-scale circulation states and from their coupling to slowly varying boundary conditions, especially North Atlantic SSTs and ocean circulation, rather than from direct analogies with individual synoptic systems . For example, besides its interplay with the AMV, one key feedback loop involves the NAO and the North Atlantic SST tripole pattern . The direction of this interaction is still under debate with studies illustrating an SST influence on the NAO and some showing NAO influence on SST . It was also shown that the location of the Gulf Stream front may imprint onto NAO on these time scales . Recent research proposes a negative feedback loop: NAO-induced SST anomalies affect the AMOC, which in turn alters the SSTs which influence the NAO in the opposite direction . Some studies also indicate that a vertical component in the atmosphere is included in this feedback loop . This feedback loop acts on decadal-to-multidecadal time scales and may give rise to important variability in Northern Europe as well .

In this context, the representation of coupled North Atlantic ocean-atmosphere variability in global climate models has recently been questioned. In particular, showed that the observed link between spring North Atlantic SST variability and summer Euro-Atlantic circulation is temporally non-stationary and is generally not reproduced, or is too weakly reproduced, in the evaluated global model. More broadly, persistent deficiencies in the simulation of Euro-Atlantic jet and regime dynamics, including blocking, further limit the realism of atmosphere-ocean coupling pathways in models. This is also relevant for the Baltic Sea region, because many regional Baltic Sea models are still forced by prescribed atmospheric boundary conditions and therefore inherit biases in the large-scale circulation from their driving models.

Freshwater anomalies in the subpolar North Atlantic (SPG) may also influence European, and potentially Baltic Sea, climate through downstream circulation anomalies. linked such anomalies – likely related to anomalous Arctic/sub-Arctic runoff and meltwater input – to a sharper winter SST front between the subpolar and subtropical North Atlantic and to associated large-scale atmospheric circulation anomalies. Overall, these hydrographic anomalies, modulated by SPG variability, contribute to multiyear predictability in both oceanic and atmospheric conditions .

Longer-range teleconnections which can modulate the North Atlantic climate, particularly from the Indian and Pacific Oceans, add further complexity to European climate variability . One notable mode of Pacific variability is the Pacific Decadal Oscillation (PDO), the leading mode of North Pacific SST variability (EOF1 of SSTs over 20–70° N) . While direct studies on the PDO's influence on the Baltic climate remain limited, its impact on the region is often mediated through its interactions with other modes of climate variability such as the NAO, El Niño-Southern Oscillation (ENSO) and Arctic sea ice variability. For instance, report PDO-related anomalies over the Baltic region, though they emphasize its modulation of broader sea ice effects. Additionally, the PDO has been shown to modulate ENSO's influence on the North Atlantic , further underscoring its indirect role in shaping atmospheric circulation patterns that can affect Northern Europe. This is because PDO-related shifts in the Aleutian Low and North Pacific jet reshape the North Pacific waveguide, steering ENSO-forced Rossby waves and altering their downstream projection into the North Atlantic . More broadly, such extratropical teleconnections are dependent on the climatological background flow . This interconnectedness highlights the PDO's potential contribution to (multi)decadal variability in European climate.

Precipitation in the Baltic Sea region varies across time scales, with different mechanisms dominating at each scale. The best-established link is for wintertime variability, when large-scale North Atlantic circulation exerts a strong control on moisture transport and cyclone pathways into Northern Europe. On synoptic and intraseasonal time scales, precipitation anomalies are primarily associated with variations in the latitude and strength of the North Atlantic jet and the resulting shifts in storm-track activity, rather than with any specific weather regime. When the jet is stronger and displaced northward, cyclones and moisture transport more frequently reach Northern Europe and parts of the Baltic Sea catchment, favoring wetter conditions. In contrast, a more southerly jet or blocked circulation over Scandinavia tends to suppress precipitation over large parts of the region, while enhancing it along the flanks and poleward side of the block, where moisture transport and warm conveyor belts are concentrated . On interannual time scales, the NAO is the most widely used index for precipitation variability in the Baltic Sea region, especially in winter, but its influence is not spatially uniform across the region . Positive NAO conditions are generally associated with strong westerly flow and wetter-than-average conditions over the northern and western parts of the Baltic Sea region, whereas negative NAO conditions tend to favor reduced precipitation there. However, the strength and even the sign of the precipitation response can vary within the Baltic catchment depending on the longitudinal position of the NAO centers of action and on the state of other circulation patterns . In particular, the East Atlantic and Scandinavian patterns modulate both the spatial structure and the magnitude of precipitation anomalies over the Baltic Sea region . On multidecadal time scales, the influence is more indirect. North Atlantic sea-surface temperature variability can alter the mean position of the jet and the associated sea-level pressure patterns, thereby changing the background likelihood of wet and dry conditions in the Baltic Sea region. Available evidence suggests relatively drier conditions during positive AMV phases and wetter conditions during negative AMV phases, although these relationships are less robust and more weakly constrained than the wintertime interannual links associated with the NAO . Potential influences from Arctic or Pacific sea-ice variability on Baltic precipitation remain uncertain, and their net effect on the region has not yet been robustly established .

Variability in storminess in the Baltic Sea region is closely connected to the location and strength of the North Atlantic storm track, but the relative importance of associated large-scale circulation and locally driven dynamics depends on the time scale. On synoptic to intraseasonal time scales, the NAO and jet-stream configuration provide a useful framework for describing the regional likelihood, pathways, and clustering of storms reaching the Baltic Sea region . In this sense, large-scale circulation exerts a strong control on the statistics of storminess, especially in winter, whereas the realized near-surface winds and local impacts of individual events remain strongly shaped by local factors such as coastline orientation, basin geometry, bathymetry, and land-sea contrasts. Generally, a stronger and northward-shifted jet – such as during NAO+ or a positive East Atlantic pattern – favors enhanced storm-track activity and increased storminess over the Baltic Sea region. In contrast, blocked regimes (Atlantic Ridge and European/Scandinavian Blocking) tend to suppress storms locally beneath the ridge, while enhancing activity along the flanks. A positive NAO also increases extreme wind return levels along the southern Baltic Sea and downstream, indicating an elevated risk of storm surges .

On interannual time scales, the influence of large-scale atmospheric variability is spatially heterogeneous across the Baltic region. The Scandinavian Pattern appears to be the strongest modulator of winter storm activity in the Baltic region, followed by the NAO and the Polar/Eurasian pattern – a pattern projecting onto a zonal/NAO+ regime during its positive phase, while the negative phase projects onto blocked regimes, mainly Greenland Blocking (NAO-) and sometimes Scandinavian Blocking. The East Atlantic pattern also plays an important role, especially for the forecasting skill of storm tracks into the Baltic Sea region . Moreover, the positioning of the jet stream and the strength of the meridional pressure gradient in the North Atlantic can explain a large part of the decadal changes in 10 m wind speeds in northern Europe, with low windiness in winters of the 1980s and 2010s and high windiness in the 1990s . On multidecadal time scales, the warm phase of the AMV corresponds to an equatorward-shifted jet and a storm track that is less extended poleward compared to the AMV cold phase , favoring reduced storminess in the Baltic region.

Sea level variability in the Baltic Sea is predominantly driven by the large-scale atmospheric circulation owing to small tidal amplitudes. On synoptic time scales, the Baltic Sea sea level is mainly driven by wind stress inside the basin, whereas on seasonal to multidecadal time scales the controlling signal originates from the adjacent basin Kattegat and thus ultimately from the North Atlantic . This is because the Danish straits separating the Baltic Sea from the Kattegat act as a physical low-pass filter, essentially damping synoptic scale variability, while allowing seasonal and longer time scales to pass .

Sea level in the Baltic Sea exhibits a seasonal cycle, with higher levels in autumn and winter than in spring and summer . Against this seasonal background, interannual sea-level variability has been found to correlate with the NAO, especially in winter, although the strength of the relationship varies in time and across the Baltic Sea region. For example, reported a correlation of r=0.63 between the winter (JFM) NAO index and the winter mean Baltic Sea level over 1825–1997, increasing to r=0.74 for 1902–1997. Westerly winds over the area are typically stronger during the positive phase of the NAO which pushes water into the Baltic and raises the sea level . The strength of the correlation between the NAO and mean sea level, however, varies between different basins and in time. The temporal variability can partly be explained by the interplay between the NAO, the East Atlantic and the Scandinavian patterns .

An index based on the sea level pressure difference between the Bay of Biscay and Tromsø has also been suggested as an alternative to the NAO . This Baltic Sea and North Sea Oscillation (BANOS) index was introduced because the NAO–Baltic sea-level relationship is non-stationary in time and spatially heterogeneous, whereas BANOS is more stably linked to Baltic and North Sea sea-level variability. showed that it explained locally up to 90 % of interannual sea-level variance in winter and up to 79 % in summer during 1993–2013. Decadal and multidecadal sea level variability is much less explored than interannual variability. reported statistically significant links between decadal sea level variability and variations in sea level pressure and precipitation. In contrast, they found no robust connection to the AMV, as the strongest correlation reported for any season was only 0.2.

Not only mean sea level, but also sea level extremes in the Baltic Sea are correlated to the NAO e.g.,. However, this relationship is regionally heterogeneous and generally weaker than for mean sea level. In part, the relationship can be explained as a preconditioning, where storm surges occur from a higher baseline during positive NAO phases owing to its effect on the mean sea level, but there is likely an effect also on the surges themselves . Yet, the magnitude of individual storm-surge events depends strongly on regional and event-specific wind forcing, coastline orientation, fetch, and basin geometry. This indicates that multiple time scales from synoptic to at least interannual could be contributing to this effect. Moreover, NAO variability extends to other flooding-relevant drivers. For example, along the southern coast of Sweden, total annual wave energy is positively correlated with the winter NAO (r=0.51) offshore, and this relationship is even stronger closer to the coast . Runoff has likewise been reported to show seasonally significant NAO correlations in parts of the Baltic catchment, although these relationships are more regionally heterogeneous than for mean sea level . Together, these links suggest that the risk of compound flooding may also be modulated by the NAO e.g.,.

Surface air temperature (SAT) and sea-surface temperature (SST) in the Baltic Sea are tightly coupled. In summer, the surface mixed layer is typically 15–20 m deep, while in autumn-winter it often reaches the seabed in shallow areas or deepens to the halocline (40–80 m) in deeper basins. Consequently, daily SAT anomalies are reflected in SST with a lag of only a few days; in summer the lag rarely exceeds two weeks. Hence, more than 80 % of the monthly SST variance is explained by the combined sensible and latent heat fluxes that depend on SAT and incoming shortwave radiation .

Anomalously low winter SSTs in the Baltic Sea are associated with negative NAO phases and severe winters, whereas anomalously high SSTs are linked to positive NAO phases and mild winters , closely following the winter NAO-SAT relationship . Most of the interannual winter SAT variability (87 % at Stockholm) is explained by the NAO .

The properties of the cold intermediate layer are established during winter mixing, and this water mass persists in the water column until the following winter. Consequently, the interannual variability of cold intermediate layer temperature is strongly correlated with the severity of the preceding winter, which is largely determined by the winter NAO .

On decadal and longer time scales, positive AMV phases are associated with higher Baltic Sea SSTs, but this response is strongly seasonal and spatially heterogeneous rather than uniform throughout the year. Previous work estimated that about 58 % of the decadal Baltic SST variability can be linked to the AMV after removing the global warming signal . More recent work further showed that the linear annual-mean SST response to the AMV is relatively weak, on the order of 0.2 °C, whereas the influence is strongest in winter, when up to 40 % of regional SST variability can be associated with multidecadal variability closely linked to the AMV, corresponding locally to about 1.2 °C per standard deviation of the AMV. This influence is thought to be mediated partly through the NAO and partly through a subpolar atmospheric wave train that links North Atlantic SST anomalies to Northern European climate . In the Baltic Sea region, this influence appears to be expressed primarily through changes in large-scale pressure patterns, westerly flow, and oceanic inertia and aerosol forcing .

Temperature variability on all time scales provides the baseline for marine heat waves (MHWs) in the Baltic Sea, which are predominantly linked to atmospheric modes . These MHWs very likely coincide with atmospheric heat waves although a dedicated comparison is missing. identified the dominant preconditions for MHWs on seasonal time scales. During summer, a prevailing stable high pressure system over Scandinavia supports anomalously high shortwave absorption and thus heat uptake in the upper water layer. The associated weak-wind regime further delimits mixing of heated surface waters with colder water from below resulting in a stable and shallow thermocline. Winter MHWs are mainly caused by external warm and humid air masses advected from the North Atlantic via the westerly wind regime . Consequently, atmospheric conditions resembling the positive phase of the NAO elevate the risk for winter MHWs in the Baltic Sea. The local processes are characterized by an anomalously low heat flux out of the sea. Here, reduced latent heat fluxes (due to the humid air masses) and reduced sensible heat fluxes (due to anomalously warm air) play the dominant roles.

Sea ice in the Baltic Sea shows pronounced interannual variability . Over the past century, a shift toward milder ice winters has been observed, with reductions in both ice extent and thickness expected to continue in the present century .

The variability is influenced by the NAO and the Arctic Oscillation . Statistical modelling shows that zonal flow is the dominant circulation control on Baltic Sea ice extent, with the winter NAO accounting for about 29 % of the year-to-year variance in annual maximum ice extent, while meridional flow also contributes, particularly in November and January . Winters dominated by strong westerlies (NAO+) are typically associated with reduced sea ice cover in the Baltic Sea. Between January and March, negative NAO phases (NAO<-0.5) are linked to substantially larger mean annual ice extent (259 000 km2), while positive phases (NAO>+0.5) are associated with reduced ice extent 121 000 km2,. The relationship between NAO and annual maximum ice extent is non-stationary and can vary across different time periods , possibly linked to shifts in the NAO centers of action .

In addition to the NAO and Arctic Oscillation, interannual variations in Baltic Sea ice parameters have also been found to correlate with the PDO . The physical mechanisms underlying this connection remain unclear, but correlations can be of comparable magnitude to those of the North Atlantic Oscillation, although they are not temporally persistent .

Salinity variations in the Baltic Sea are controlled by the interplay of freshwater input, mainly through river runoff and irregular saltwater inflows from the North Sea. The river runoff lowers the salinity in the surface layer of the Baltic Sea via direct dilution, accounting for 27 % of the salinity variations . Consequently, the outflowing water through the Danish straits becomes fresher. This water partly mixes with the underlying saltier layer which decreases the salinity of subsequent saltwater inflows .

Saltwater inflows that shape the salinity of the deeper parts in the Baltic Sea occur under specific synoptic wind conditions and are connected to the passage of deep cyclones over the region e.g.,. Wind variations on synoptic time scales are reflected in salinity fluctuations in the rather shallow western Baltic Sea whereas the deeper basins of the central Baltic Sea act as a low-pass filter e.g.,. Depending on their density, inflows spread at intermediate depths or form a deep layer that propagates along the bottom. Only large inflows (MBIs) can reach the deep basins of the Baltic Proper and settle at the bottom. While MBIs occur mainly in winter and only roughly a few times per decade, smaller inflows can happen throughout the year . MBIs are modulated by the accumulated freshwater supply over multidecadal time scales , whereas smaller inflows show a strong dependence on interannual atmospheric forcing.

Directly linking NAO and salinity variations is challenging due to their differing dominant time scales: the NAO fluctuates mainly on 4–10 year periods , while the water balance of the Baltic Sea is characterized by multidecadal 30 year fluctuations e.g.,. Longer periods with predominant NAO+ (i.e., persistent strong westerlies) elevate the mean sea level in the Baltic Sea, suppressing saltwater inflows and lowering bottom salinities .

On a multidecadal scale, the salinity of the Baltic Sea is correlated with the AMV. During the course of the last millennium, the dominant time scales were above 120 and 60–90 years during the Little Ice Age their Fig. 2 and were linked to salinity changes of about 0.7 gkg-1. For the 20th century, common spectral power was also found between 20 and 30 years , resulting in changes of about 0.2 gkg-1. The dominance of 30 year fluctuations in the water cycle of the Baltic Sea has been a matter of discussion for a long time, given that neither the NAO nor the AMV have high spectral power in that period band. Recently, argued that the superposition of 60 year temperature fluctuations in the North Atlantic related to the AMV and the 60 year periodicity in the displacement of the NAO's centers of action evoked by, again, the AMV causes the 30 year variability in the water balance of the Baltic Sea.

Changes in solar radiation, more specifically, shortwave irradiance, are affected by atmospheric processes altering the amount of sunlight which can be absorbed, reflected or scattered by atmospheric transparency, water vapour, cloud cover and albedo. In the 1950s to 1980s a decrease in shortwave irradiance (dimming) has been detected in many regions in Europe, followed by an increase (brightening) until present .

Several studies attribute brightening in Europe to a decline in aerosols . However, a recent investigation found a more subtle shift in attribution over the last four decades supporting earlier results . While the aerosol effect was primarily responsible for brightening between 1983 and 2002, variability in cloud cover emerged as the predominant driver of observed brightening between 2001 and 2020. found a significant increase in solar radiation accompanied by a decrease in cloud cover in the Baltic Sea during the past half-century. They show that while anticyclonic (clear) circulation patterns have become more frequent, zonal (overcast) patterns are occurring less often with a significant negative trend. This can be partially explained by variations in the synoptic patterns over Scandinavia (Sect. ) likely linked to a northward shift in the North Atlantic storm tracks which enter the Arctic, without passing Scandinavia, and promote the blocking over northwestern Europe .

The increase in surface solar radiation may also explain shifts in seasonality, especially to longer and earlier summers in the Baltic Sea . detected important seasonal shifts in a variety of physical and biological parameters, with e.g. the cumulative sum of 30 000 Wm-2 of surface incoming shortwave irradiance being reached 23 d earlier in 2013 compared to 1983. The shift is highly correlated with earlier warming and later cooling of SST, which in turn also affects the availability of light in the water column (see also Sect. ).

A recent modeling study suggested that the PDO accounts for about 20 %–40 % of the unforced year-to-year shortwave-flux variability in Northern Hemisphere continental averages, mainly through cloud redistribution. For Europe, the modeled response is weaker, with anomalies of about ±2 Wm-2, and negative PDO phases are associated with reduced atmospheric shortwave reflectivity. However, the signal is strongest in spatially aggregated averages and is difficult to distinguish from atmospheric noise over most of Europe, so its relevance for the Baltic Sea region remains uncertain .

Oxygen concentrations in surface waters are determined by the exchange with the atmosphere, oxygen production during photosynthesis, sea surface temperatures, sea surface salinity and the supply of oxygen through vertical and lateral transport. Surface oxygen is then distributed to the rest of the water column. In the Baltic Sea, mechanisms controlling oxygenation in the interior differ per subbasin (hereafter following the subbasin names of Savchuk, 2018), largely depending on the presence/absence of a permanent halocline.

In the central and western Baltic Proper, below its permanent halocline, oxygen levels are controlled by MBIs, smaller inflows (both are often referred to as “intrusions” of oxygen-rich waters) e.g.,, vertical mixing e.g.,, and oxygen consumption due to organic matter degradation. The latter is related to the temperature-dependent remineralization in both the water column and the sediments, and the supply of degradable organic matter e.g.,. Only large MBIs can ventilate the deeper parts of the central and western Baltic Proper . These subbasins are therefore prone to develop permanent bottom anoxia which has spread due to the rise of anthropogenic nutrient loads in the 1960s (Fig. ).

The basins without permanent halocline, such as the eastern Gulf of Finland, Gulf of Bothnia, and Gulf of Riga, are largely impacted by atmospheric conditions which control the local stratification/mixing regime . These basins are generally more oxygenated, but are not exempt from developing prolonged periods of deoxygenation and bottom anoxia.

Coastal deoxygenation in the Baltic Sea is also affected by additional processes, such as marine heat waves (MHWs; Sect. ) . The gradual decline of oxygen, the expansion (both vertically and horizontally) of oxygen deficit, and the increasing hydrogen sulfide inventory adding to the “oxygen debt” in the Baltic Proper (Fig. ) increase the risk of exporting hypoxic waters to the Bothnian Sea and shallow coastal areas .

Primary productivity – the rate at which marine autotrophs, mainly phytoplankton, convert inorganic carbon (CO2) into organic matter through photosynthesis – is heterogeneous in space and consistently enhanced by nutrient inputs in the Baltic Sea (Fig. ). The high nutrient concentrations result from human-induced nutrient enrichment, long water residence times due to limited exchange with the North Sea, vertical mixing, and efficient benthic nutrient recycling e.g.,.

Natural fluctuations in nutrient and organic matter supply, closely linked to the hydrological cycle, regulate primary productivity. Other physical factors, such as the availability of incoming surface solar radiation, the penetration of light into the water column, the spectral quality of light in the euphotic zone, changes in freshwater supply, ocean mixing, sea surface temperature, and winds, likewise play a role in primary production. While the averaged primary productivity shows consistent patterns (an example for the period 2010–2019 is shown in Fig. a), significant differences can be found from year-to-year and from region to region. For example, anomaly analysis shows considerably elevated productivity in relation to the 10 year average in the Baltic Proper in 2019 Fig. b;.

Since phytoplankton forms the dominant group of primary producers in the Baltic Sea, its growth directly reflects the combined effects of the aforementioned drivers. Light availability, which is further decreased by the presence of organic particles in the water column, is the main limiting factor for phytoplankton growth during autumn in the Baltic Sea . In contrast, during spring and summer, light is not a limiting factor and allows phytoplankton growth, leading to seasonal peaks in primary production. While yearly primary production in the Baltic Sea shows a general slight increasing trend due to the response of phytoplankton to local drivers, primary productivity trends differ per basin Fig. c and d;.

In winter, both temperature and light limit phytoplankton growth. In summer, thermal stratification is an additional factor regulating production dynamics as it forms a stable upper mixed layer that is shallower than the euphotic zone. Phytoplankton is then confined within this lighted surface layer allowing blooms to develop. However, stratification also suppresses mixing with deeper layers, gradually limiting the upward transport of nutrients to the surface and thus phytoplankton growth. Nitrate is usually fully depleted down to the halocline after the spring bloom period . A second bloom of nitrogen-fixing primary producers (cyanobacteria) develops in summer, with timing of the onset and intensity subject to large interannual variability .

In early spring, diatoms – a major group of phytoplankton characterized by their capacity of building silica-based cell walls – are the first to bloom, particularly in the southern Baltic Sea. In the central Baltic Sea (Baltic Proper, Gulf of Finland and Gulf of Riga), cold-water dinoflagellates may be dominant, especially after warmer winters, while mixotrophic dinoflagellates and occasionally ciliates are dominant in summer e.g.,. Cyanobacteria in the Baltic Sea, which grow in low salinity (<10 gkg-1; ) and are capable of fixing atmospheric nitrogen, form blooms in summer after nitrogen depletion in surface waters . However, phytoplankton dynamics in the Baltic Sea are changing, potentially due to changing seasonality of the cumulative surface incoming solar radiation , reduced light penetration in the water column (so-called darkening), water temperatures and stratification .

Ocean acidification is a core indicator of the Global Climate Observing System, as rising surface-ocean CO2 partial pressure (pCO2) levels closely track rising atmospheric pCO2. When CO2 dissolves in seawater, it forms carbonic acid, releases hydrogen ions (H+), and lowers pH e.g.,. In the open ocean, ocean acidification is traceable as a decreasing long-term pH trend since at least the 1980s (i.e., since observations have been available), clearly revealing against the background of seasonal pH variability related to photosynthesis and respiration . In the Baltic Sea (similar to most coastal and shelf waters), ocean acidification trends are less clear (Fig. ), mainly due to changes related to eutrophication and variable total alkalinity which, next to CO2 dynamics, is a key driver for seawater pH .

Total alkalinity is defined as an excess of proton acceptors over proton donors (or bases over acids) and is a measure of buffer capacity against ocean acidification . Although total alkalinity is a conservative salinity-dependent parameter, its surface distribution in the Baltic Sea is complex. This is due to significant differences in the total alkalinity concentrations in river water across the Baltic Sea catchment, a phenomenon closely linked to variations in the geological structure of the surrounding land . Generally, the Scandinavian rivers drain catchments underlain by granite bedrock and therefore have low total alkalinity concentrations. Rivers entering the Baltic Sea from the south and south-east flow through a catchment area rich in limestone and heavily agriculturally transformed, which makes these rivers an important net source of total alkalinity. Finally, the Baltic Proper acts as a mixing chamber where these various freshwater types mix with the salty (and therefore alkalinity-rich) water flowing into the Baltic from the North Sea .

The overall low alkalinity suggests that the Baltic Sea is prone to ocean acidification. However, total alkalinity in the Baltic Sea has shown an increase over the past three decades . The most recent data analysis by shows that this increase is between 3.2 µmolkg-1yr-1 in the Gulf of Bothnia and 5.3 µmolkg-1yr-1 in the Bornholm Basin, which partially mitigates the pH drop in the Baltic Sea due to increasing pCO2 (Fig. b). The source of this increase remains unclear, but it is likely the result of a combination of different processes, such as a rise in total alkalinity loads from rivers, enhanced erosion, dissolution of carbonate deposits, and total alkalinity input due to the expansion of bottom anoxia and low redox conditions .

Because both pCO2 and total alkalinity are key parameters to understand pH variability and ocean acidification, any processes and mechanisms affecting either of them should be considered in the context of teleconnections. This makes correlations between acidification and natural variability, large-scale atmospheric, and oceanic patterns difficult to detect in the Baltic Sea, leaving the response to changes across different time scales poorly understood.

Most of the available biogeochemical observational data do not cover long-term periods with the time resolution to capture synoptic (1–7 d) and intraseasonal (10–90 d) time scales. In addition, atmospheric or oceanic data do not always have the same period, the same frequency or spatial coverage. Only due to the recent availability of satellite observations together with improved measurement techniques and numerical modeling has it become possible to obtain biogeochemical data with higher spatiotemporal resolution. Therefore, it is not surprising that biogeochemical parameters are not typically linked to weather systems on synoptic or intraseasonal time scales. However, the need for early warnings and short-term predictions for biogeochemical parameters (e.g., for risk assessments) demands more studies on the biogeochemistry responses to weather regimes or short-term events like storms.

A study by Post and Aun (2024) about solar radiation on synoptic time scales (Sect. ) potentially explains the observed earlier onset of phytoplankton growth reported for the Baltic Sea (see Sect. 3.1.2). recently suggested that the main controlling factors for the initiation of cyanobacteria blooms are the rate of change in SST due to surface irradiance and reduced vertical mixing due to lower wind speed, while SST itself was not correlated with bloom initiation. Similarly, observed the vertical carbon removal from the surface layer during a cyanobacterial event, and related the integrated cyanobacterial production to the heat uptake in the surface layer. Increased wind speed and resulting mixed layer deepening ended this productive episode. These findings link both the onset of cyanobacterial blooms and integrated production of individual bloom events to meteorological conditions with persistent low wind speed and reduced cloud cover. This parallels conditions fostering summer heat waves, with an apparent link to blocking regimes (Sect. ). Yet, for the most part, a clear correlation between phytoplankton variability and weather regimes is still missing.

The shallow and brackish Baltic Sea is affected by marine heat waves (MHWs) on synoptic time scales (Sect. ). Their impact can last from a couple of days to a few months and can reach the seabed at water depths of less than 20 m , which has been shown to have led to a significant decrease in oxygen concentration during summer . As MHWs are projected to increase in intensity, duration and frequency in the future , the risk of hypoxic events in Baltic coastal waters is of growing concern . suggested that MHWs can trigger extreme surface accumulations of cyanobacteria which, in turn, will further increase heating in the uppermost water layer due to increased light absorption and thus modulated air-sea heat fluxes. studied the effect of MHWs on benthic ecosystems in the Baltic Sea and found that the seafloor functioning responds differently depending on the intensity of the heatwave. They suggest that a prolonged, moderate MHW enhances nutrient recycling by boosting benthic activity, while a strong heatwave reduces organic matter degradation and the nutrient cycling. Over time, both can lead to a build-up of organic matter on the seafloor and cause oxygen depletion . As bioturbation and related benthic fluxes alter the nutrient recycling and organic matter remineralization, benthic processes can also alter primary productivity.

Most physical parameters in the Baltic Sea, such as temperature, wind speed, cloudiness, runoff, evaporation, and precipitation have pronounced intraseasonal/seasonal variations, whose influence decreases with depth according to the bathymetry of each basin. Consequently, such signals are also reflected in most biogeochemical processes, but can be mitigated by other regional effects. For example, while intraseasonal/seasonal variations in oxygen are weak in most of the stratified areas of the Baltic Sea , in the Gulf of Finland, bottom water conditions are dominated by seasonal variability as seasonal westerly winds can reverse the estuarine circulation, which deepens the halocline and increases the oxygen content in the near-bottom layer .

Primary productivity in the entire Baltic Sea has a clear seasonal cycle mainly driven by temperature, light and nutrient availability (Sect. ). Following changes in pCO2 caused by seasonal changes in the production and remineralization of organic matter, the pH of the Baltic surface waters also changes seasonally, with higher values observed in summer than in winter. Thus, natural variability of ocean acidification is closely related to that of primary production, but also to the buffering capacity, given by the total alkalinity. In addition, the CO2 flux at the air-sea interface is largely controlled by temperature, salinity and winds , which are directly impacted by the large-scale atmospheric variability across different time scales (Sect. ). In deeper waters, the seasonal influence of teleconnections is less evident but may follow that of deoxygenation (Fig. ), since pH is primarily controlled by CO2 accumulation and alkalinity release during redox processes . In the end, all of these processes are linked to seasonally affected physical parameters. The relative roles of such parameters in controlling the intraseasonal to seasonal variability of primary production and ocean acidification remain unclear and likely vary regionally.

Interannual variability (1–9 years) in Baltic Sea oxygen deficiency is strongly driven by atmospheric forcing through its effects on circulation, stratification, and vertical exchange, leading to changes in oxygen content.

Interannual variability below the halocline in the western and southern Baltic depends largely on the inflow of oxygenated water from the North Sea . In between MBI events, oxygen concentrations in the near bottom layer decline continuously although the frequent smaller inflows oxygenate the subhalocline layer (≈100 m depth) at an interannual time scale. Consequently, year-to-year variability in the subhalocline layer is more closely linked to the large-scale atmospheric circulation than the deeper bottom layers in the central Baltic Sea.

The influence of atmospheric variability is particularly pronounced in the shallower basins of the Baltic Sea. A positive NAO with accompanying winds from southwest can alter or even reverse the advection of oxygen-depleted saline waters from the Baltic Proper to the Gulf of Finland and remove hypoxia in the whole gulf . A negative NAO, on the other hand, supports estuarine circulation and stronger oxygen deficiency. and showed that oxygen depletion in the case of a warmer upper layer is not only intensified due to stronger stratification, but that enhanced oxygen consumption in higher temperatures also contributes to the interannual variability of deoxygenation in the shallow southern Baltic Sea.

Wind patterns and heat fluxes associated with high pressure systems during the European Blocking regime support the seasonal oxygen depletion occurring from year-to-year in the Gulf of Riga . North-easterly winds cause dense water transport from the Baltic Proper to the Gulf of Riga. Although this water is oxygenated, it also causes strong stratification and reduces oxygen transport by vertical mixing in the gulf. Strong heat fluxes during the prevailing European Blocking regime cause higher sea surface temperature and stratification, which could reduce downward oxygen transport and enhance deoxygenation of the deep layer .

Besides low oxygen concentrations, seasonally increasing near-bottom water temperature seems to be the main factor controlling denitrification rates . In turn, intensive denitrification and organic matter degradation under anoxic conditions are an important source of alkalinity and thus can affect the year-to-year acid-base system of the Baltic Proper . Although the effect is usually reversed upon re-oxygenation, denitrification and the formation of vivianite and pyrite are permanent sources of alkalinity , potentially acting on longer time scales.

During 1860–1880 and 1980–2000, negative wavelet coherence between surface and bottom salinity at Gotland Deep and the NAO index is found in the period band between 5 and 10 years , very likely affecting bottom oxygen concentration dynamics e.g.,. found strong correlation between the positive phase of winter NAO and negative salinity and positive oxygen anomalies in the Baltic Proper during the period 1983 to 1990. This suggest that the positive phase of winter NAO (west wind anomaly) causes a salinity decline in the Gotland Basin and improved oxygen conditions. The mechanism is explained by and confirmed by dynamic modeling and statistics (Zorita and Laine, 2000). Correlations between the NAO and the main factors controlling primary productivity, such as air/sea surface temperature, light and sea ice at interannual time scales are large (Sect. ; ). Therefore, strong interannual signals are expected to modulate primary productivity in the Baltic Sea. Indeed, a study on primary productivity in the northeastern Baltic Sea and large-scale atmospheric variability found significant correlations between chlorophyll and the winter values of NAO, Scandinavian pattern and the annual Polar/Eurasian index, which suggests a potential effect on primary productivity . Solar radiation has been shown to affect cyanobacteria on interannual time scales rather than on decadal time scales. Wind conditions did not show a strong relationship with how often cyanobacteria blooms occurred, although winds mainly influenced variations from year-to-year their Fig. .

The Baltic Sea exhibits complex decadal to multidecadal-scale variability in oxygen dynamics, primary productivity and ocean acidification. By examining paleoenvironmental archives from sediment records, we can better understand shifts in core biogeochemical processes under conditions of no or minimal anthropogenic influence. Past widespread hypoxia in the Baltic Sea has occurred during the Holocene Thermal Maximum (8000–4800 years before present) and the Medieval Climate Anomaly (1000–700 years before present) . These past hypoxic intervals generally coincided with warmer climatic conditions and elevated salinity, both of which favored higher primary productivity and increased organic matter flux to the seafloor. Sediment record studies show that, before major human influence, hypoxia in the Baltic Sea was largely a natural response to climate variability and changes in water exchange with the North Sea .

Proxy records of hypoxia showed strong multidecadal oscillations likely driven by both the internal iron-phosphorus cycling and the Atlantic Multidecadal Variability (AMV) , in which temperature and salinity played a major role in modulating the remineralization of organic matter and the timing of massive blooms . In addition, oxygen concentration variations at multidecadal time scales have been identified to be negatively correlated with salinity in the major part of the water column, indicating improved ventilation during a fresher state of the Baltic Sea e.g.,. Reduced salinity and consequent improved oxygen conditions have been linked to stronger zonal atmospheric circulation .

Modern bottom oxygen concentrations in both the Baltic Proper and the western Gulf of Finland show strong decadal signals, mainly controlled by runoff and zonal wind stress . Similarly, reported an increase in oxygen concentrations in the late 1980s and early 1990s which they attributed to a decrease in salinity due to high runoff and a loss of stratification, thus related to more humid weather conditions.

Primary production has fluctuated over a range of spatial and temporal scales, increasing approximately 2–3-fold since the early-to-mid 20th century as a direct result of nutrient enrichment . However, multidecadal variability persists, superimposed on the anthropogenic trend. Model and field data show that wind forcing and shifts in atmospheric circulation play a crucial role in regulating primary production and biogeochemical regimes in the Baltic Sea . For example, the AMV has been shown to account for a significant fraction (over 50 %) of decadal-scale variability in sea surface temperature in the Baltic Sea, indirectly influencing primary productivity through impacts on thermal stratification and nutrient availability .

Paleoceanographic evidence demonstrates that during the Medieval Climate Anomaly, periods of warmer temperatures promoted abundant cyanobacteria blooms in the Baltic Sea and increased diatom production, boosting organic matter export and contributing to hypoxia in deep basins . Furthermore, significant changes have occurred in net primary productivity from 1993 to the present (Fig. ), which cannot solely be explained by nutrient distribution . Still, nutrient loads from rivers, especially after industrialization, and nutrient recycling from sediments have become the dominant control on primary productivity , amplifying and modulating its magnitude rather than overriding its natural, climate-driven variability.

Long-term trends and variations of primary productivity in the Baltic Sea are difficult to study due to the lack of observations in both space and time, especially before the year 1996 . Nevertheless, long seasonal trends in primary productivity have been identified in the Baltic Sea, especially in the Gulf of Gdansk e.g.,. As large-scale temperature, shortwave radiation, and cloudiness changes have been shown to affect phytoplankton growth, large-scale circulation variability on multidecadal time scales likely impacts primary productivity.

showed that the frequency of cyanobacteria in the Baltic Proper at decadal time scales is primarily correlated with phosphorus abundance and bottom-water anoxia (Fig. ). However, sea surface temperature and wind speed also play a significant role in modulating decadal cyanobacteria blooms and their initiation . Yet, in the Baltic Sea, the links between large-scale circulation patterns and primary productivity remain poorly understood and largely unquantified; consequently, the relative importance of these links and the future response of productivity to accelerated warming are even less certain.

The recent multidecadal increase in total alkalinity has also been partially explained by changes in precipitation patterns and continental weathering driven by acidic rain which are closely linked to the NAO and AMV (Sect. ). The latter are expected to change by the end of the 21st century, likely leading to wetter conditions in the northern part of the Baltic Sea, mostly composed of granite, and drier conditions in the southern, limestone-rich Baltic Sea . The sources of the alkalinity increase are neither well understood nor quantified and are also highly linked to eutrophication and alkalinity production from anaerobic processes . The teleconnections for total alkalinity production through anaerobic processes, though not yet directly investigated, should be similar to those for primary production and hypoxia/anoxia.