Interannual Temperature Variability Research Articles

Enhanced interannual variability of the terrestrial carbon sink in China under high emissions

Abstract Interannual variability (IAV) of terrestrial carbon uptake is a major contributor to the variation of atmospheric CO2. With the influence of the East Asian monsoon, future climate variability would significantly increase in China. However, how these future changes will modulate the IAV of China’s terrestrial carbon sinks remains unclear. Here, we analyzed the IAV of China’s terrestrial net ecosystem productivity (NEPIAV) and investigated the potential impacts of climate change under various scenarios during the 21st century using the outputs from nine Coupled Model Intercomparison Project Phase 6 models. The results reveal that China’s terrestrial NEPIAV would be enhanced under higher emissions scenarios from 2015 to 2100. The standard deviation of national NEPIAV under the SSP585 scenario rises by 12% compared with SSP126. The most prominent contribution to this enhancement in the total NEPIAV comes from a larger NEP IAV in summer (10%), particularly in the subtropical–tropical monsoonal climate zone in China. Moreover, the enhancement is largely attributed to the intensified IAV in temperature and precipitation in the monsoonal climate zones as well as the heightened sensitivity to them, especially in the ecosystems of the subtropical–tropical monsoonal zone. Compared with monsoonal precipitation, IAV of temperature in the subtropical–tropical monsoonal climate zone also plays an important role in NEPIAV under higher emissions scenarios. Our results highlight the crucial influence of future fluctuations in monsoon climate systems on terrestrial carbon sink IAV and the urgency of reducing the uncertainties of Earth system models in predicting both climate in monsoon regions and the responses of carbon cycling processes to temperature.

Long-Term Trends of Lake Surface Water Temperatures in Lowland Polish Temperate Lakes

In this study, long-term lake surface water temperature (LSWT) data were used to investigate the impact of climate change on thermal conditions in 25 Polish lowland lakes. The results show that the warming rate of the annual mean LSWT ranges from 0.14 °C per decade to 0.69 °C per decade with an average value of 0.44 °C per decade. The annual maximum LSWT presented the strongest warming trend, with the warming rate varying between 0.26 °C per decade and 1.06 °C per decade (average value of 0.65 °C per decade). Warming rates were observed in all seasons but with different intensities, with warming rates increasing from spring to autumn and then to summer. The warming rate of the summer LSWT varied between 0.29 °C per decade and 0.87 °C per decade with an average value of 0.56 °C per decade. Conversely, winter and annual minimum LSWTs did not present clear increasing trends. The increase in the annual maximum, annual average, and seasonal LSWTs correlated well with the inter-annual variability in air temperature. To understand the relationship between LSWT and air temperature, the non-linear regression model (S-curve) was used in this study. The results indicate that the non-linear regression model can help to present the relationship between LSWT and air temperature in the studied lakes (the average values of the root mean squared error (RMSE), the mean absolute error (MAE), and the Nash–Sutcliffe efficiency coefficient (NSE) are 1.68 °C, 1.28 °C, and 0.95, respectively). The warming trends of LSWTs observed for the studied lakes in Poland are coherent and in some cases larger than the data from other lakes worldwide, and should be seriously considered by policy makers.

Arctic sea ice melting has produced distinct sea ice-atmosphere coupled patterns

Abstract The possible influence of Arctic sea ice on weather events and climate variations has received considerable attention, while the evolution of its relationship with interannual variations of winter temperature across much of Eurasia remains poorly understood. This study quantitatively describes two distinct coupled patterns between autumn Arctic sea ice concentration (SIC) in the Barents-Kara Seas and the subsequent winter regional temperature over Eurasia. The leading coupled pattern dominantly depicts interannual variations of the cold Arctic – warm Eurasia or warm Arctic – cold Eurasia configuration, differing from the background warming pattern. While the second coupled pattern describes in-phase interannual variations of winter temperature over the Arctic and across much of Eurasia. This second pattern displayed an interdecadal transition in the early 2010s, from frequent occurrences of the cold Arctic – cold Eurasia pattern to the dominant warm Arctic – warm Eurasia configuration. Through this interdecadal transition, the warm Arctic – warm Eurasia configuration replaced the leading coupled pattern. The previously proposed the tropospheric and stratospheric processes cannot fully explain this Arctic-Eurasia temperature configuration. These findings underscore the pivotal role of Arctic sea ice melting in influencing the interannual and interdecadal variations of winter atmospheric circulation patterns and have significant implications for predicting short-term winter temperature trends over Eurasia.

Dakar Niño under global warming investigated by a high-resolution regionally coupled model

Abstract. In this study, we investigated interannual variability in sea surface temperature (SST) along the northwestern African coast, focusing on strong Dakar Niño and Niña events and their potential alterations under the RCP8.5 emission scenario for global warming, using a high-resolution regional coupled model. Our model accurately reproduces the SST seasonal cycle along the northwestern African coast, including its interannual variability in terms of amplitude, timing, and the position of maximum variability. Comparing Dakar Niño variability between the 1980–2010 and 2069–2099 periods, we found that it intensifies under a warmer climate without changing its location and timing. The intensification is more pronounced during Dakar Niñas (cold SST events) than during Dakar Niños (warm SST events). In the future, SST variability will be correlated with ocean temperature and vertical motion at deeper layers. The increase in Dakar Niño variability can be explained by the larger variability in meridional wind stresses, which is likely to be amplified in the future by enhanced land–sea thermal contrast and associated sea-level-pressure anomalies extending from the Iberian Mediterranean area. A heat budget analysis of the mixed layer suggests that surface heat flux and horizontal-advection anomalies are comparably important for Dakar Niño and Niña events in the present climate. However, the future intensification of Dakar Niños and Niñas is likely to be driven by surface heat flux (latent heat flux and shortwave radiation). While horizontal- and vertical-advection anomalies also contribute to the intensification, their roles are secondary.

Long-Term Teleconnections Between Global Circulation Patterns and Interannual Variability of Surface Air Temperature over Kingdom of Saudi Arabia

Surface air temperature (SAT) variability is investigated for advancing our understanding of the climate patterns over the Kingdom of Saudi Arabia (KSA). SAT variability reveals significant warming trends, particularly from 1994 onward, as demonstrated by nonlinear and linear trend analysis. This warming is linked to global climate patterns, which serve as significant indicators for studying the effects of climate change on surface air temperature patterns across the KSA. The empirical orthogonal function (EOF) method is employed for analyzing SAT due to its effectiveness in extracting dominant patterns of variability during the winter (DJF) and summer (JJA) seasons. The first mode (EOF1) for both seasons shows positive variability across the KSA, explaining more than 45% of the variance. The second mode (EOF2) indicates negative variability in central and northern regions. The third mode (EOF3) describes positive variability but with lower variance over time. PC1 is used to describe the physical mechanism of SAT variability and correlations with global sea surface temperature (SST). The physical mechanism shows that the variability in Mediterranean troughs during the winter season and high pressure over the Indian Ocean and central Asia controls SAT variability over the KSA. The correlation coefficients (CCs) were calculated during the winter and summer season between the SAT of the KSA and six teleconnection indices, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Atlantic Meridional Mode (AMM), Pacific Warm Pool (PWP), North Atlantic Oscillation (NAO), and Tropical North Atlantic (TNA) SST for the period from 1994 to 2022. ENSO shifts from positive to negative correlations with SAT from winter to summer. IOD shows a diminished correlation with SAT due to the absence of upper air dynamics. PWP consistently enhances surface warming in both seasons through upper air convergence during both seasons. AMM and NAO have a non-significant impact on SAT; however, TNA contributes warming over central and northern parts during winter and summer seasons. The seasonal SAT variations emphasize the significant role of ENSO, PWP, and TNA across the seasons. The findings of this study can be helpful for seasonal predictability in the KSA.

Cross-continental comparison of plant reproductive phenology shows high intraspecific variation in temperature sensitivity.

The success of plant species under climate change will be determined, in part, by their phenological responses to temperature. Despite the growing need to forecast such outcomes across entire species ranges, it remains unclear how phenological sensitivity to temperature might vary across individuals of the same species. In this study, we harnessed community science data to document intraspecific patterns in phenological temperature sensitivity across the multicontinental range of six herbaceous plant species. Using linear models, we correlated georeferenced temperature data with 23 220 plant phenological records from iNaturalist to generate spatially explicit estimates of phenological temperature sensitivity across the shared range of species. We additionally evaluated the geographic association between local historic climate conditions (i.e. mean annual temperature [MAT] and interannual variability in temperature) and the temperature sensitivity of plants. We found that plant temperature sensitivity varied substantially at both the interspecific and intraspecific levels, demonstrating that phenological responses to climate change have the potential to vary both within and among species. Additionally, we provide evidence for a strong geographic association between plant temperature sensitivity and local historic climate conditions. Plants were more sensitive to temperature in hotter climates (i.e. regions with high MAT), but only in regions with high interannual temperature variability. In regions with low interannual temperature variability, plants displayed universally weak sensitivity to temperature, regardless of baseline annual temperature. This evidence suggests that pheno-climatic forecasts may be improved by accounting for intraspecific variation in phenological temperature sensitivity. Broad climatic factors such as MAT and interannual temperature variability likely serve as useful predictors for estimating temperature sensitivity across species' ranges.

Increasing Optimum Temperature of Vegetation Activity Over the Past Four Decades

AbstractOver the past four decades, global temperatures have increased more rapidly than before, potentially reducing vegetation activity if temperatures exceed the optimum temperature (Topt). However, plants have the capacity to acclimate to rising temperatures by adjusting Topt, thereby maintaining or even enhancing photosynthesis and carbon uptake. Despite this, it remains unclear how Topt of vegetation activity changes over time and to what extent global vegetation can acclimate to current temperature changes. In this study, we evaluated the temporal trends of Topt of vegetation activity and the thermal acclimation magnitudes globally using three remote‐sensed vegetation indices and eddy‐covariance observations of gross primary productivity from 1982 to 2020. We found that the global Topt of vegetation activity has increased at an average rate of 0.63°C per decade over the past four decades. The increase in Topt closely tracked the rise in annual maximum daily mean temperature (Tmax), indicating that thermal acclimation has occurred widely across the globe. Globally, we found an average thermal acclimation magnitude of 0.38°C per 1°C increase in Tmax. Notably, polar and continental regions exhibited the highest thermal acclimation magnitudes, while arid areas showed the lowest. Additionally, the thermal acclimation magnitude was positively affected by interannual temperature variability and negatively affected by soil moisture and vapor pressure deficits. Our findings indicate that terrestrial ecosystems have acclimated to current climate warming trends with varying degrees, suggesting a greater potential for land carbon uptake. Moreover, these results highlight the necessity for earth system models to integrate the thermal acclimation of Topt to better forecast the global carbon cycle.

Long-term interannual temperature variability across the KwaZulu-Natal Bight as a technique for monitoring the complex uThukela Marine Protected Area, South Africa

The uThukela Marine Protected Area (MPA), situated on the continental shelf of the KwaZulu-Natal (KZN) Bight on the northeastern coast of South Africa, has been identified as a vital ecological region. Knowledge of the oceanographic dynamics in the region is essential for understanding the functioning of the ecosystem and the effectiveness of the MPA. This study analysed ocean temperature variability at 20 sites across the KZN Bight, between 1980 and 2021, using in situ and satellite data. Significant warming of an average of 0.03 °C y−1 across the period occurred at sites within and around the MPA. Coastal sea surface temperatures warmed by an average of 0.02 °C y−1, during both summer and winter. However, a persistent decrease in temperatures along the length of the KZN Bight during the summer of 2017/2018 could have significant consequences for temperature-sensitive species. Significant coastal temperature variability during the period 1980–2021 was not reflected in a data subset covering 2013–2021, highlighting the importance of long-term spatially extensive monitoring when investigating climate change within MPAs. Warming biases of up to 2 °C and an underestimation of the warming rates observed in satellite-derived temperatures highlight the limitations of using remotely sensed observations to assess changes. These findings can help assess the success of MPAs and guide monitoring and research activities within the region.

Predicting fish spawning phenology for adaptive management: Integrating thermal drivers and fishery constraints

Climate warming is causing shifts in reproductive phenology, a crucial life history trait determining offspring survival and population productivity. Evaluating these impacts on exploited marine resources is essential for implementing adaptive measures from an ecosystemic approach. This study introduces a statistical model designed to predict fish spawning phenology from sea surface temperature profiles, integrating mortality-corrected hatch-date distributions inferred from fishery-dependent samplings, along with the gonadosomatic index of adult individuals. When applied to different dolphinfish (Coryphaena hippurus) populations across a broad latitudinal range, the model reasonably predicts the spawning phenology across its extensive thermal ranges, elucidating a direct relationship between mean annual temperature and the breadth of the spawning season. Despite the varying thermal profiles, results show a consistent timing of spawning peaks approximately 49 days before the peak in temperature. Importantly, these findings account for the impact of fishery constraints, such as seasonal closures or different sampling schedules, offering a robust tool for adjusting management practices in response to inter-annual temperature variations. These insights are critical for both short-term fishery management, including the strategic planning of seasonal closures, and long-term projections of spawning phenology shifts under changing thermal regimes. By enhancing our ability to predict spawning times, this research contributes significantly to the sustainable management of fish populations and the adaptive response to environmental changes.

Role of atmospheric and oceanic processes on interannual summertime (2016–2017) decrease of sea ice in the Antarctic regions of the Southern Ocean

In this article, the interannual variability of sea ice in the Antarctic sea ice regions between 2013–2018 is studied using a global ocean sea ice coupled model and satellite observation. The numerical model reasonably well simulates satellite observed interannual variability of sea ice concentration (SIC) and sea surface temperature (SST) in the Antarctic regions of Southern Ocean during all four austral seasons; summer (December–February), autumn (March–May), winter (June–August), and spring (September–November).A comparison of satellite and model shows that, during last two decades between 2001–2020, summertime of 2016–2017 had the lowest (highest) SIC (SST) across the Antarctic sea ice regions. Mixed layer heat budget analysis has been performed to comprehend how thermodynamic processes affect changes in SIC and SST in the Antarctic sea ice regions. The strong positive net atmospheric heat flux and the negative ocean vertical entrainment during summertime of 2016–2017 resulted in increased SST compared to other years, which lead to decreased SIC during above years. Also, loss of sea ice during summertime of 2016–2017 in the Antarctic sea ice regions are linked with significant decrease of wind stress magnitude and increase of wind stress curl.

Dynamical downscaling CMIP6 models over New Zealand: added value of climatology and extremes

Dynamical downscaling provides physics-based high-resolution climate change projections across regional and local scales. This is particularly important for island nations characterized by complex terrain, where the coarse resolution of global climate model (GCM) output often prohibits direct use. One of the main motivations for dynamical downscaling is to reduce biases relative to the host GCM at the local scale, which can be quantified through assessing ‘added value’. However, added value from downscaling is not guaranteed; quantifying this can help users make informed decisions about how best to use available climate projection data. Here we describe the experiment design of the updated national climate projections for New Zealand based on dynamical downscaling. The global non-hydrostatic Conformal Cubic Atmospheric Model (CCAM) is primarily used for downscaling, with a global stretched grid targeting high resolution over New Zealand (12-km) and the wider South Pacific region (12–35-km). Focusing on the historical simulations, we assess added value for a range of metrics, climatological fields, extreme indices, and tropical cyclones. The main strengths of the downscaling include generally large improvements relative to the host GCM for temperature and orographic precipitation. Inter-annual variability in temperature is well captured across New Zealand, and several temperature and precipitation-based extreme indices show large improvements. The representation of tropical cyclones reaching at least category 2 intensity is generally improved relative to the large consistent under-representation in the host GCMs. The remaining biases are explored and discussed forming the basis for ongoing bias-correction work.

Anthropogenic Changes in Interannual-to-Decadal Climate Variability in CMIP6 Multiensemble Simulations

Abstract As well as having an impact on the background state of the climate, global warming due to human activities could affect its natural oscillations and internal variability. In this study, we use four initial-condition ensembles from the CMIP6 framework to investigate the potential evolution of internal climate variability under different warming pathways for the twenty-first century. Our results suggest significant changes in natural climate variability and point to two distinct regimes driving these changes. The first is a decrease in internal variability of surface air temperature at high latitudes and all frequencies, associated with a poleward shift and the gradual disappearance of sea ice edges, which we show to be an important component of internal variability. The second is an intensification of the interannual variability of surface air temperature and precipitation at low latitudes, which appears to be associated with El Niño–Southern Oscillation (ENSO). This second regime is particularly alarming because it may contribute to making the climate more unstable and less predictable, with a significant impact on human societies and ecosystems.

How Much Does Land–Atmosphere Coupling Influence Summertime Temperature Variability in the Western United States?

Abstract Interannual fluctuations in average summertime temperatures across the western United States are captured by a leading empirical orthogonal function that explains over 50% of the total observed variance. In this paper, we explain the origins of this pattern of interannual temperature variability by examining soil moisture–temperature coupling that acts across seasons in observations and climate models. We find that a characteristic pattern of coupled temperature–soil moisture climate variability accounts for 34% of the total observed variance in summertime temperature across the region. This pattern is reproduced in state-of-the-art global climate models, where experiments that eliminate soil moisture variability reduce summertime average temperature variance by a factor of 3 on average. We use an idealized model of the coupled atmospheric boundary layer and underlying land surface to demonstrate that feedbacks between soil moisture, boundary layer relative humidity, and precipitation can explain the observed relations between springtime soil moisture and summertime temperature. Our results suggest that antecedent soil moisture conditions and subsequent land–atmosphere interactions play an important role in interannual summertime temperature variability in the western United States; soil moisture variations cause distal temperature anomalies and impart predictability at time scales longer than one season. Our results indicate that 40% of the observed warming trend across the western United States since 1981 has been driven by wintertime precipitation trends in the U.S. southwest. Significance Statement Year-to-year fluctuations in summertime temperatures have a large impact on drought, wildfire, and extreme heat across the Western United States. We find strong evidence that soil moisture deficits in the preceding spring may be the primary driver of higher-than-average summer temperatures in this region. Our results suggest that memory in the water cycle may lead to greater predictability in the climate system from season to season and that trends in southwest precipitation have exerted a considerable influence on observed warming over the past 40 years.

Influence of ENSO and the urban heat island on climate variation in a growing city of the western Mexico

To understand climate change in the local context, it is necessary to analyse three factors in the territories; 1) how temperature and precipitation have varied over time, 2) if there is an association with the natural variation of the planet, for example with the El Niño-Southern Oscillation (ENSO) phenomenon, and 3) if the variations could be related to human actions that directly alter the climate, such as gas emissions into the atmosphere and deforestation. Understanding how these three factors interact, what impacts they have caused on the territory and how they will behave in future scenarios, allows us to think about development planning strategies that seek to adapt human communities to future climate conditions. This study addresses climate change in the City of Tepic, analysing the interannual variation of temperature and precipitation, its association with the ENSO phenomenon and the possible relationship with the urban heat island, contrasting two time periods; 1980-1999 and 2000-2018. The results showed a generalised increase of +1 ºC between periods, decrease of precipitation up to -6% the summer months and increase up to +20% the autumn months. The influence of ENSO on temperature variation increased from 10% to 20% in the most recent period, and its influence on precipitation variation decreased from 17% to 8%, respectively. On the other hand, the heat island increased its extension by more than 60% and its intensity by about 8 degrees between the periods analysed. The differences between periods are discussed descriptively in relation to the doubling of the area of urban use, population, atmospheric emissions and the loss of 30% of the forests in the areas adjacent to the city.

Effect of species-independent conspecific and heterospecific density dependence is contingent on seedling growth stage, season, and climate conditions

Conspecific negative density dependence (CNDD) and its extension heterospecific positive density dependence (HPDD) are the two most prominent mechanisms used to explain the maintenance of species diversity in forest communities. However, the impact of species identity, growth stage, seasonal and inter-annual variation in precipitation and temperature on conspecific and heterospecific density dependence remains poorly understood. Based on a decade of seedling (dbh < 1 cm) and tree (dbh ≥ 1 cm) census data from a 5-ha subtropical evergreen broad-leaved forest in eastern China, we used generalized linear mixed models with crossed random effects to test whether seedling survival was density dependent and varied by growth stage, species identity, season or interacted with inter-annual variation in seasonal precipitation and temperature. In addition to conspecific and heterospecific seedling and tree density, the height (or age) of the seedlings, habitat variables, seasonal precipitation and temperature and the interactions between conspecific and heterospecific seedling and tree density and seasonal precipitation and temperature were also used as predictors. The results of our long-term, spatially, and temporally explicit study showed that the strength of CNDD and enemy induced HPDD was stronger in summer and at early seedling stages, whereas interspecific facilitation induced HPDD mainly in winter for early and late seedling stages. Additionally, the effects of seasonal temperature and precipitation, and the soil PC1 axis (which correlated positively with soil nutrients and negatively with soil moisture) on seedling survival varied with season, seedling stage, and focal species identity, indicating the potential for niche partitioning among species in this community. However, neither conspecific nor heterospecific neighbor effects varied among focal seedling species, which resulted in a community compensatory trend in young seedlings. Variation in the effect of CNDD and HPDD across seedling stages, seasons, and inter-annual fluctuations of climate conditions highlights the necessity of long-term monitoring of the dynamics of CNDD in tree communities.

Ice phenology interactions with water and air temperatures in high mountain lakes

Ice phenology is of great importance for the thermal structure of lakes and ponds and the biology of lake species. Under the current climate change conditions, ice-cover duration has been reduced by an advance in ice-off, and a delay in ice-on, and future projections foresee this trend as continuing. Here, we describe the current ice phenology of Pyrenean high mountain lakes and ponds, including ice-cover duration and ice-on and ice-off dates. We used mixed models to identify the variables that explained the observed patterns, extrapolated them across all water bodies in the mountain range, and related the seasonality of air and water temperatures with ice phenology using structural equation models. Ice phenology was obtained from the temperature series of 85 lakes and ponds for fourteen years, including 2001 to 2004 and 2009 to 2019. We discovered that high autumn precipitation was related to earlier ice-on dates, and that earlier ice-off dates were associated with higher following-summer water temperatures. We found a greater predictability of ice-off dates and ice-cover duration than ice-on dates. Altitude was the most important variable explaining the variation in ice phenology, followed by latitude, which was related to climatic differences among the northern and southern slopes of the mountain range. The lake area was significant for ice-on dates and ice-cover duration. The interannual variability in air temperature and radiation was remarkable for the ice-off date and ice-cover duration but not for the ice-on date. In contrast, wind speed was related to an earlier ice-off date and shorter ice-cover duration. All the measured lakes and ponds froze in winter during the studied period, a feature maintained in the extrapolation to the whole set of water bodies.

Interdecadal shift of the North Pacific Oscillation and its nonstationary relationship with East Asian climate

A pronounced shift of the North Pacific Oscillation (NPO), including its teleconnection with the East Asian winter monsoon, has been observed in recent decades, but the underlying mechanism remains unclear. In this study, we found that interannual variation of the NPO and its relationship with the dominant modes of winter mean and extreme temperatures over East Asia (EA) experienced a significant interdecadal shift in the mid-1980s. Before the shift (during 1950–1985), the NPO emerged and was maintained as a strong regional north-south dipole, manifesting a remarkable tropical-extratropical teleconnection. It significantly modulated the second mode of air temperature over EA (depicted by a north-south dipole) and extreme temperature events over southern EA, mainly through horizontal advection and adiabatic heating induced by the anomalous circulation in the southern lobe of the NPO. After the shift (during 1986–2021), the NPO was characterized by an intensified northern lobe and a weakened and northwestward shifted southern lobe, and by a close teleconnection with the Rossby wave trains at the mid-higher latitudes. In the meantime, tropical-extratropical teleconnections became apparently weak. Correspondingly, the NPO was mainly linked to the interannual variation of air temperature and extreme events over northern EA via horizontal advection. Importantly, the decadal shift of the relationships of the NPO with the Arctic Oscillation and El Niño–Southern Oscillation played an apparent role in modulating EA climate.

On the Estimation of the Interannual Variability of the Ocean Surface Temperature in the Area of the Peruvian Upwelling

The interannual variability of the ocean surface temperature in the area of the Peruvian upwelling for the period 1980–2022 is considered according to the satellite archive GODAS (Global Ocean Data Assimilation System) using the methods of multivariate statistical analysis. Local foci of significant trends, for average annual Sea Surface Temperature (SST) values, were identified near the Peruvian offshore. Four regions (clusters) were obtained, which describe the variability of SST in front off Peru, which could be used to pretend to develop a prognostic oceanographic model. Furthermore, coincidences of temperature fluctuations were found between the first cluster and the region N3+4

Drivers of Laptev Sea interannual variability in salinity and temperature

Abstract. Eurasian rivers provide a quarter of total fresh water to the Arctic, maintaining a persistent fresh layer that covers the surface Arctic Ocean. This freshwater export controls Arctic Ocean stratification, circulation, and basin-wide sea ice concentration. The Lena River supplies the largest volume of runoff and plays a key role in this system, as runoff outflows into the Laptev Sea as a particularly shallow plume. Previous in situ and modelling studies suggest that local wind forcing is a driver of variability in Laptev sea surface salinity (SSS) but there is no consensus on the roles of Lena River discharge and sea ice cover in contributing to this variability or on the dominant driver of variability. Until recently, satellite SSS retrievals were insufficiently accurate for use in the Arctic. However, retreating sea ice cover and continuous progress in satellite product development have significantly improved SSS retrievals, giving satellite SSS data true potential in the Arctic. In this region, satellite-based SSS is found to agree well with in situ data (r&gt;0.8) and provides notable improvements compared to the reanalysis product used in this study (r&gt;0.7) in capturing patterns and variability observed in in situ data. This study demonstrates a novel method of identifying the dominant drivers of interannual variability in Laptev Sea dynamics within reanalysis products and testing if these relationships appear to hold in satellite-based SSS, sea surface temperature (SST) data, and in situ observations. The satellite SSS data firmly establish what is suggested by reanalysis products and what has previously been subject to debate due to the limited years and locations analysed with in situ data; the zonal wind is the dominant driver of offshore or onshore Lena River plume transport. The eastward wind confines the plume to the southern Laptev Sea and drives alongshore transport into the East Siberian Sea, and westward wind drives offshore plume transport into the northern Laptev Sea. This finding is affirmed by the strong agreement in SSS pattern under eastward and westward wind regimes in all reanalyses and satellite products used in this study, as well as with in situ data. The pattern of SST also varies with the zonal wind component and drives spatial variability in sea ice concentration.

Mesoscale mosaics of interannual variations in surface temperature, chlorophyll a concentration, and their relation in a coastal fishing ground

AbstractTo test the potential of high‐resolution satellite image analysis for assessing and predicting the mesoscale (&lt;10 km in this study) effects of climate and environmental change on temperature and primary productivity in fishing grounds, we conducted satellite image analysis around an island in a coastal strait west of Japan from 2018 to 2023. We observed a distinct north–south gradient in sea surface temperature (SST) and chlorophyll a concentration (CHL) over approximately 20 km of the transect, which was likely affected by the current system. The model configuration suggests that the frequency of southward currents during winter–spring can control the magnitude of spring phytoplankton blooms. In the study region, an increase in SST at a rate of 0.06–0.13°C y−1 occurred during the study period, accompanied by a decrease in CHL. The north–south gradient in the rate of change suggests that the variation in the temperature and flow rate of the Kuroshio Current into the study area was due to these abrupt changes. The relationship between the annual mean SST and CHL was also spatially heterogeneous, showing a higher sensitivity of CHL to SST in the southwest of the island than in the north. In addition to the intrusion of warm and oligotrophic Kuroshio waters, the spread of less saline and more eutrophic coastal waters likely influenced this spatial heterogeneity. The satellite image analysis in the present study successfully revealed mesoscale mosaics of environmental conditions in coastal fishery grounds.