Ocean-atmosphere Interactions Research Articles

The first firn core from Peter I Island – capturing climate variability across the Bellingshausen Sea

Abstract. Peter I Island is situated in the Bellingshausen Sea, a region that has experienced considerable climate change in recent decades. Warming sea surface temperatures and reduced sea ice cover have been accompanied by warming surface air temperature, increased snowfall, and accelerated mass loss over the adjacent ice sheet. Here we present data from the first firn core drilled on Peter I Island, spanning the period 2001–2017 CE. The stable water isotope data capture regional changes in surface air temperature and precipitation (snow accumulation) at the site, which are highly correlated with the surrounding Amundsen–Bellingshausen seas and the adjacent Antarctic Peninsula (r > 0.6, p < 0.05). The firn core data, together with the unique in situ data from an automatic weather station, confirm the high skill of the ERA5 reanalysis in capturing daily mean temperature and inter-annual precipitation variability, even over a small sub-Antarctic island. This study demonstrates the suitability of Peter I Island for future deep-ice-core drilling, with the potential to provide a valuable archive to explore ice–ocean–atmosphere interactions over decadal to centennial timescales for this dynamic region.

A Model that Explains the Contrasting SST Trends in the Southern Pacific Ocean

Sea surface temperature (SST) of the southern Pacific Ocean plays an important role in ocean-atmospheric interactions, influencing both regional and global climate and ecosystems. The contrasting SST trends in the southern Pacific Ocean during 1993-2021 are noted by analyzing satellite and in-situ datasets, consisting of SST warming trend (0.05℃·yr−1) in the region of 80°W-180,30°S-50°S and cooling trend (−0.04℃·yr−1) in the area of 60°W-150°W, 55°S-70°S. A detailed trend analysis for the wind and sea ice concentration suggest that Ekman transport and sea ice radiative positive feedback are the two key contributors to the contrasting SST trends. The intensified downwelling (upwelling), induced by the Ekman transport and strengthened westerlies, gives rise to warm (cold) water swarming in (upturning) from lower latitudes (deeper ocean), which causes SST warming (cooling). Moreover, the sea ice increase at higher latitudes, due to both the cold water transport from deeper ocean layers and broken ice transport from polar regions, strengthens the cooling trend through sea ice positive radiative feedback. In conclusion, these findings underscore the complexity of SST trends in the southern Pacific Ocean, highlighting the critical roles of Ekman transport and sea ice radiative feedback in shaping regional climate dynamics.Plain Language Summary: The southern Pacific Ocean is an indispensable part in the climate system while it still remained poorly observed. The SST trend is regarded as a critical indicator of global climate change. Using the satellite and in-situ datasets, we find that the contrasting SST trends from 1993 to 2021, one area in this region is warmed by 0.3℃ per decade, while another area is cooled by -0.1℃ per decade. Considering impacts of various factors such as wind, sea ice and radiation, the primarily explanation is that wind-driven warm (cold) water from the subtropics (deeper ocean) flows in and goes downward (goes upward and flow away) in the warm (cold) area through oceanic circulation and leads to the SST warming (cooling). Additionally, the cooling trend is also related to the cold water that flows to higher latitudes and forms ice there and at the same time, trash ice from polar regions driven by enhanced south wind speed will be transported there. As a result, ice increases, reflects more shortwave radiation to space, and surface downward shortwave radiation decreases which contributes to SST decreases.

TEOS-10 and the climatic relevance of ocean–atmosphere interaction

Abstract. Unpredicted observations in the climate system, such as recent excessive ocean warming, are often lacking immediate causal explanations and are challenging numerical models. As a highly advanced mathematical tool, the Thermodynamic Equation of Seawater – 2010 (TEOS-10) was established by international bodies as an interdisciplinary standard and is recommended for use in geophysics, such as, and in particular, in climate research. From its very beginning, the development of TEOS-10 was supported by Ocean Science through publishing successive stages and results. Here, the history and properties of TEOS-10 are briefly reviewed. With focus on the air–sea interface, selected current problems of climate research are discussed, and tutorial examples for the possible use of TEOS-10 in the associated context are presented, such as topics related to ocean heat content, latent heat, and the rate of marine evaporation; properties of sea spray aerosol; or climatic effects of low-level clouds. Appended to this article, a list of publications and their metrics is provided for illustrating the uptake of TEOS-10 by the scientific community, along with some continued activities, addressing still pending, connected issues such as uniform standard definitions of uncertainties of relative humidity, seawater salinity, or pH. This article is dedicated to the jubilee celebrating 20 years of Ocean Science. This article is also dedicated to the memory of Wolfgang Wagner, who sadly and unexpectedly passed away on 12 August 2024. His contributions to TEOS-10 are truly indispensable constituents; Wolfgang was an essential co-author of various related documents and articles. He will be deeply missed. All the rivers run into the sea; yet the sea is not full; unto the place from whence the rivers come, thither they return again. The King James Bible: Ecclesiastes, 450–150 BCE He wraps up the waters in his clouds, yet the clouds do not burst under their weight. Holy Bible: New International Version, Job 26:8 Of the air, the part receiving heat is rising higher. So, evaporated water is lifted above the lower air. Leonardo da Vinci: Primo libro delle acque, Codex Arundel, ca. 1508 Two-thirds of the Sun's energy falling on the Earth's surface is needed to vaporize … water … as a heat source for a gigantic steam engine. Heinrich Hertz: Energiehaushalt der Erde, 1885 The sea-surface interaction is obviously a highly significant quantity in simulating climate. Andrew Gilchrist and Klaus Hasselmann: Climate Modelling, 1986 The climate of the Earth is ultimately determined by the temperatures of the oceans. Donald Rapp: Assessing Climate Change, 2014

Statistical seasonal prediction of Arctic sea ice concentration based on spatiotemporal anomaly persistent method

Abstract Accurate prediction of Arctic sea ice is crucial for high-latitude and even mid-latitude climate prediction. It significantly affects atmospheric circulation, the environment, ecology, and maritime transport. This study developed a statistical prediction model to predict monthly Arctic sea ice concentration (SIC) for up to one year based on the season-reliant empirical orthogonal functions (SEOFs) technique. Its prediction skill was compared with that of a dynamical prediction model. The spatiotemporal pattern of sea ice anomalies, which exhibit strong seasonality and are maintained for a significant period above the seasonal time scale by atmosphere-ocean interactions, was extracted using SEOFs. A prediction model was constructed by extrapolating from the recent anomalous state of sea ice to predict the future. Experimental retrospective predictions with monthly time resolution for 1982–2021 were performed to validate the prediction skill of Arctic SIC and areal extent. Statistically significant prediction skills were achieved over several months, even up to six months, exceeding the skill of the dynamical model.

Community structure of tropics emerging from spatio-temporal variations in the Intertropical Convergence Zone dynamics

The Intertropical Convergence Zone (ITCZ) is a narrow tropical belt of deep convective clouds, intense precipitation, and monsoon circulations encircling the Earth. Complex interactions between the ITCZ and local geophysical dynamics result in high climate variability, making weather forecasting and prediction of extreme rainfall or drought events challenging. We unravel the complex spatio-temporal dynamics of the ITCZ and the resulting teleconnection patterns via a novel tropical climate classification achieved using complex network analysis and community detection. We reduce the high-dimensional complex ITCZ dynamics into a simple yet insightful community structure that classifies the tropics into seven regions representing distinct ITCZ dynamics. The two largest communities, encompassing landmasses over the Northern and Southern hemispheres, are associated with coherent seasonal ITCZ dynamics and have significant long-range connections. Temporal analysis of the community structure highlights that the tropical Pacific and Atlantic Oceans communities exhibit substantial variation on multidecadal scales. Further, these communities exhibit incoherent dynamics due to atmosphere-ocean interactions driven by equatorial and coastal oceanic upwelling.

Analysis and prediction of mesoscale eddy kinetic energy variations in the Kuroshio extension

The Kuroshio Extension (KE) region, a crucial area in the Northwest Pacific Ocean, exhibits eddy kinetic energy with various scales of periodicity. Understanding how to extract its characteristic features and analyze and predict their periodic correlations has become vital for studying the regulatory mechanisms of eddy kinetic energy in the KE region. This paper first introduces a mesoscale eddy hybrid identification algorithm based on the flow field vector and the closed flow field. Using this algorithm, we gather mesoscale eddy identification data from the KE region to extract the monthly average series of five typical features of the KE region. Subsequently, wavelet theory is applied to analyze the cycles of these main features, identifying the common cycles of the KE region as the primary focus for analyzing the vorticity kinetic energy. This analysis includes cycle correlations with globally recognized indices, and it predicts these correlations. Further analysis of the main characteristic cycles through wavelet theory reveals that the KE region's eddy kinetic energy is significantly influenced by solar activity over long periods and by the North Pacific ocean-atmosphere interaction over shorter, interannual periods. Finally, this paper introduces a W-LSTM (Wavelet Decomposition based Long Short-term Memory Networks) prediction model based on wavelet decomposition for the KE region, covering January 2023–December 2023. The model demonstrates its effectiveness, achieving a Root Mean Square Error (RMSE) of 0.2530 and a correlation coefficient of 0.8259 between the predicted data and the actual observations.

The LGM termination in the southeastern Tibetan plateau: View from high-frequency LGM glacier fluctuations in the Boshula mountain range

Climate processes that operated during the end of the Last Glacial Maximum (LGM) are remarkable for its global synchroneity. Atmospheric CO2 concentrations have been widely seen as its cause. However, the stepwise LGM deglaciation of mountain glaciers in both hemispheres complicates this view, and signifies additional factors that likely prompted the onset of LGM termination. Here, we examine LGM climate change in the Hengduan Mountains (HDM), southeastern Tibetan Plateau (TP), based on 10Be surface exposure dating of moraine boulders (n = 51). The timing of four moraine-building events is constrained to 22.8 ± 1.0 ka, 21.2 ± 0.6 ka, 20.4 ± 0.6 ka, and 19.2 ± 0.6 ka. These precisely-dated events provide convincing evidence of millennial-to centennial-scale glacial activities in the TP during the LGM. We show that these high-frequency glacier fluctuations likely reacted to a combination of changes in regional summer temperature related to sea surface temperatures as well as monsoon precipitation. The pronounced glacial retreat is dated at 19.2 ± 0.6 ka, representing the end of the LGM in the HDM. That is, the onset of LGM termination preceded the rapid CO2 rise at ∼18 ka. We suggest that the LGM termination in the southeastern TP was initiated by ice-sheet shrinkage, which induced changes in summer temperature and monsoon precipitation via ocean-atmosphere interactions.

Characterizing the local and global climatic factors associated with vegetation dynamics in the karst region of southwest China

Understanding the relationship between vegetation and climatic drivers is essential for assessing terrestrial ecosystem patterns and managing future vegetation dynamics. This study examines the effects of local climatic factors and remote large-scale ocean–atmosphere circulations from the Pacific, Atlantic, and Arctic Oceans, as well as the East Asian and Indian summer monsoons, on the spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) in the karst region of southwest China (KRSC) using Mann-Kendall test, Sen’s slope, cross-correlation, and wavelet analysis. We observed a significant increase in NDVI over karst and non-karst regions from 1981 to 2019, with a notable abrupt shift from 2001 onwards, underscoring the importance of understanding the underlying drivers. The significant correlation and coherence of surface air (TMP) and soil temperatures (ST) with NDVI, especially when analyzed using wavelet methods, indicate their crucial role in vegetation dynamics. Additionally, the broad coherence patterns of AMO and WHWP with NDVI at annual and decadal cycles suggest that ocean–atmosphere interactions also play a significant part. At interannual periodicities, most large-scale indices displayed significant coherence with NDVI. These findings highlight the complexity of NDVI variability, which is better explained by the integration of multiple local and global factors rather than by single variables. The integrated local–global drivers, particularly TMP-ST-AMO-NP-WHWP and PCP-SM-AMO-NP-WHWP with mean coherence of 0.90 and 0.89, respectively, showed the highest mean coherence, emphasizing the need for a multifaceted approach in understanding vegetation changes rather than a single local variable or atmospheric circulation index. These findings have significant implications for policymakers, aiding in better planning and policy formulations considering climate change and atmospheric variability.

Predictability and prediction skill of summertime East/Japan Sea surface temperature events

The East/Japan Sea (EJS), a marginal sea of the Northwestern Pacific, is one of the ocean regions showing the most rapid warming and greatest increases in ocean heatwaves over the last several decades. Predictability and skillful prediction of the summer season EJS variability are crucial, given the increasing severity of ocean temperature events impacting fisheries and reinforcing climate conditions like the East Asian rainy season, which in turn affects adjacent high-population density areas over East Asia. We use observations and the Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system to investigate the summertime EJS Sea Surface Temperature (SST) predictability and prediction skill. The observations and seasonal prediction system show that the summer season EJS SST can be closely linked to the previous winter air-sea coupling and predictable 8–9 months in advance. The SPEAR seasonal prediction system demonstrates skillful forecast of EJS SST events from summer to late fall, with added skill for long-lead forecasts initialized in winter. We find that winter large-scale atmospheric circulations linked to Barents Sea variability can induce persistent surface wind anomalies and corresponding northward Ekman heat transport over the East China Sea. The ocean advection anomalies that enter the EJS in prior seasons appear to play a role in developing anomalous SST during summer, along with instantaneous atmospheric forcing, as the source of long-lead predictability. Our findings provide potential applications of large-scale ocean-atmosphere interactions in understanding and predicting seasonal variability of East Asian marginal seas.

Analysis of oceanic suspended particulate matter in the western North Pacific using the complex amplitude sensor

Oceanic suspended particulate matter (SPM) plays important roles in the coupling of climate and biogeochemical cycles via ocean–atmosphere interactions. However, methods for quantifying the properties of SPM in seawater have not yet been well established. Here we present the application of the recently developed complex amplitude sensor (CAS) for analyzing the complex forward-scattering amplitude of individual SPM (0.2–5.0 µm in diameter) obtained at depths of 0–100 m during a research cruise in the western North Pacific. The measured distribution of the complex amplitude indicated that the CAS-derived SPM data could be roughly classified into five major types. Comparison with reference sample’s complex amplitude data and scanning electron microscopy analysis suggested that these types could be attributed mainly to diatom fragments, carbonaceous materials (likely organic matter), mineral dusts, iron oxides, or black carbon. Depth profiles revealed that relatively high concentrations of SPM, presumably dominated by diatom fragments and carbonaceous materials with peak diameters of 0.7–1.0 µm, were typically associated with elevated turbidities and chlorophyll a concentrations. Based on this case study, we discuss the practical advantages and limitations of using the CAS to measure size-resolved concentrations of SPM in seawater and to characterize its composition.

Conceptual Models for Exploring Sea-Surface Temperature Variability Vis-à Long-Range Weather Forecasting

This paper analyzes the ability of three conceptual stochastic models (one-box, two-box, and diffusion models) to reproduce essential features of sea surface temperature variability on intra-annual time scales. The variability of sea surface temperature, which is particularly influenced by feedback mechanisms in ocean surface–atmosphere coupling processes, is characterized by power spectral density, commonly used to analyze the response of dynamical systems to random forcing. The models are aimed at studying local effects of ocean–atmosphere interactions. Comparing observed and theoretical power spectra shows that in dynamically inactive ocean regions (e.g., north-eastern part of the Pacific Ocean), sea surface temperature variability can be described by linear stochastic models such as one-box and two-box models. In regions of the world ocean (e.g., north-western Pacific Ocean, subtropics of the North Atlantic, the Southern Ocean), in which the observed sea surface temperature spectra on the intra-annual time scales do not obey the ν−2 law (where ν is a regular frequency), the formation mechanisms of sea surface anomalies are mainly determined by ocean circulation rather than by local ocean–atmosphere interactions. The diffusion model can be used for simulating sea surface temperature anomalies in such areas of the global ocean. The models examined are not able to reproduce the variability of sea surface temperature over the entire frequency range for two primary reasons; first, because the object of study, the ocean surface mixed layer, changes during the year, and second, due to the difference in the physics of processes involved at different time scales.

Effect of waves on the magnitude and direction of wind stress over the Ocean

Correctly estimating the wind stress at the sea surface is of the utmost importance in models for climate studies, weather forecasting, and ocean–atmosphere interaction. The wind stress is mainly obtained by drag coefficient parameterizations, which always consider the wind stress to be aligned with the wind, but this is sometimes the case. Also, during moderate to weak wind conditions, these parameterizations may lead to high estimation errors due to the presence of swell. This study measured the wind stress with a high-rate (100 Hz) sonic anemometer mounted on a spar buoy. The sea state was also characterized by obtaining the directional spectrum of the waves by six wave-staff arrays sensing the free surface level at 10 Hz. Bouy’s movement was corrected by employing an inertial motion unit. The turbulent and wave-coherent wind stress components were also estimated and analyzed. It was observed that during swell conditions with wind traveling in the same direction, the wave-coherent wind stress component has an opposite direction to the wind and dampens the total wind stress magnitude. During counter-directional wind relative to swell events, the wave boundary layer is modified; swell produces a wave-coherent wind stress in the same direction as the wind, resulting in an enhanced total wind stress magnitude. The wave age, significant wave height, and the traveling direction of the swell relative to the wind are essential to correctly estimating the wind stress in swell-dominant conditions. A set of empirical parameterizations for each wind stress component is proposed.

Impact of Enso on Indian Monsoon and Food Production

El Nino is a big ocean-atmosphere climate interaction It happens when Sea Temperatures (SST) warm up in central and eastern parts of the Equatorial Pacific. Whereas La Nina is the opposite event of it, when ocean SST cools down in those same areas. Together, El Nino and La Nina are known as the El Nino Southern Oscillation Index (O). Usually, El Nino brings warm and dry weather to southern & eastern inland regions of India, Australia, Indonesia, Philippines, Malaysia, and the central Pacific islands. The variations of Indian summer monsoon Rainfall (ISMR) are linked to changes in sea surface temperatures over the equatorial Pacific & Indian Oceans. ENSO events really affect summer rainfall in India and major droughts have faced during El Nino events. When El Nino kicks in, it often leads to weak monsoons & higher temperatures in India. This raises the chances of droughts, which could upset crop production & water supply in India. The lack of rain because of El Nino causes crop production to drop, especially short-duration Kharif crops. This situation can lead to higher inflation rates & slower GDP growth, since agriculture is such a huge part of India’s economy. Therefore, this paper provide information about how El Nino affects climate throughout various regions of India, especially regarding monsoons and growing food.

Role of ocean-atmosphere interaction in intraseasonal variability of summer rainfall over the Indo–Northwest Pacific

Role of ocean-atmosphere interaction in intraseasonal variability of summer rainfall over the Indo–Northwest Pacific

50-year seasonal variability in East African droughts and floods recorded in central Afar lake sediments (Ethiopia) and their connections with the El Niño–Southern Oscillation

Abstract. Understanding past and present hydrosystem feedbacks to global ocean–atmospheric interactions represents one of the main challenges to preventing droughts, extreme events, and related human catastrophes in the face of global warming, especially in arid and semiarid environments. In eastern Africa, the El Niño–Southern Oscillation (ENSO) was identified as one of the primary drivers of precipitation variability affecting water availability. However, the northern East African Rift System (EARS) still suffers from the underrepresentation of predictive and ENSO teleconnection models because of the scarcity of local to regional historical or palaeo-data. In this paper, we provide a 50-year seasonal flood and drought chronicle of the Awash River catchment from the study of laminated sediment from Gemeri and Afambo lakes (central Afar region, Ethiopia) with the aim of reconstructing the magnitude of regional hydroclimatic events. Pluricentimetric micro-laminated lithogenic facies alternating with plurimillimetric carbonate-enriched facies are investigated in both lakes. We couple dating methods including radiocarbon, short-lived radionuclides, palaeomagnetic field variations, and varve counting on both lake deposits to build a high-resolution age model and to discuss the regional hydrosedimentary dynamics of the Awash River over the last ∼ 700 years with a focus on the last 50 years. Using a multiproxy approach, we observe that following a multicentennial enhanced hydrological period, the two lakes have experienced a gradual decrease in river load inflow since 1979 CE, attaining extreme drought and high evaporative conditions between 1991 and 1997 CE. In 2014, the construction of a dam and increased agricultural water management in the lower Awash River plain impacted the erodibility of local soils and the hydrosedimentary balance of the lake basins, as evidenced by a disproportionate sediment accumulation rate. Comparison of our quantitative reconstruction with (i) lake water surface evolution, (ii) the interannual Awash River flow rates, and (iii) the El Niño 3.4 model highlights the intermittent connections between ENSO sea surface temperature anomalies, regional droughts, and hydrological conditions in the northern EARS.

The relationship between the South China Sea summer monsoon onset and North Pacific meridional sea surface temperature anomalies

AbstractThis study investigates the connection between significant sea surface temperature (SST) anomalies in the North Pacific during boreal spring (February–April, FMA) and the subsequent South China Sea (SCS) summer monsoon (SCSSM) onset. The SST anomalies, similar to the Pacific meridional mode (PMM), referred to as the PMM+ mode, are defined to examine the new influencing factor on the SCSSM onset. Our findings reveal that the (February–March–April, FMA) PMM+ has a noteworthy positive correlation with the subsequent May SCSSM onset date, with this correlation being minimally affected by the El Niño–Southern Oscillation (ENSO) during preceding winter. A robust positive PMM+ in boreal spring can be persist until May via atmosphere–ocean interaction. The cooling area over Western North Pacific would reduce precipitation heating, thereby generating Rossby waves that reinforce the formation of the anomalous anticyclone over the SCS. As a result, easterly winds and suppressed convection prevail over the SCS, making the SCSSM break out later than normal. Furthermore, the amplification of anticyclonic vorticity anomalies also strengthens the western North Pacific subtropical high (WNPSH) stronger and shifts its position further westward compared to normal years, thereby blocking active convection to the west of the SCS. Given the weakened relationship between El Niño–Southern Oscillation (ENSO) and the SCSSM onset in recent years, the PMM+ could be considered as a promising preceding signal for the SCSSM onset, thus holding significant implications for the SCSSM prediction efforts.

Impact of a fresh-core mesoscale eddy in modulating oceanic response to a Madden-Julian Oscillation

Theories of ocean–atmosphere interaction during a Madden–Julian Oscillation (MJO) are generally based on a thermodynamic model with surface fluxes dictating changes in sea surface temperature. Evidence from a two month ocean glider deployment in early 2019 in the southeast Indian Ocean suggests the impact of mesoscale dynamics on upper-ocean stratification likely affects ocean–atmosphere interaction at MJO scales. Until mid-February, local surface fluxes consistent with a convectively suppressed MJO phase drove near-surface ocean evolution. With the advection of a fresh-core eddy to the glider location in late February, ocean dynamics then becomes an additional driver of this evolution by modulating local stratification and generating a barrier layer of ≈12 m thickness for 10 days. One-dimensional modelling experiments based on the ocean and atmospheric conditions experienced during our sampling period show that the ocean subsurface structure within the eddy induce changes in SST of physical significance for ocean-atmosphere interaction. Moreover, results also suggest that the presence of a thick eddy-induced barrier layer during the MJO suppressed phase modulates the magnitude of temperature anomalies forced by surface fluxes during the following enhanced MJO phase. As eddies are abundant in this area, their dynamics must be considered to correctly represent SST variability for MJO modelling.

An in-depth investigation of global sea surface temperature behavior utilizing chaotic modeling.

Sea surface temperature (SST), with its complex and dynamic behavior, is a major driver of ocean-atmosphere interactions. The purpose of this study is to investigate the behavior of SST and its prediction using a chaotic approach. Average mutual information (AMI) and Cao methods were used to reconstruct the phase space. The Lyapunov exponent and correlation dimension were used to investigate chaos. The Lyapunov exponent index was used to predict SST with a 5-year average prediction horizon using the local prediction method between 2023 and 2027. The results showed a 3-month delay time for the Pacific and Antarctic Oceans, and a 2-month delay time for the Atlantic, Indian, and Arctic Oceans. The optimal embedding dimension for all oceans is between 6 and 7. Our analysis reveals that the dynamics of SST in all oceans exhibit varying degrees of chaos, as indicated by the correlation dimension. The local prediction method achieves relatively accurate short-term SST predictions due to the clustering of SST points around specific attractors in the phase space. However, in the long term, the accuracy of this method decreases as the points in the phase space of SST can spread randomly. The model performance ranking with a Percent Mean Relative Absolute Error shows that the Indian Ocean has the best performance compared to other oceans, while the Atlantic, Pacific, and Antarctic and Arctic Oceans are in the next ranks. This study contributes to understanding the dynamics of SST and has practical value for use in the development of climate models.

Asian monsoonal temperature and environmental changes since the penultimate deglaciation as revealed by alkenones and alkanes in sediments from the northern South China Sea

A new alkenone sea surface temperature (SST) record from the South China Sea (SCS) over the last 170 ka has been reported here. Our analysis of magnetic susceptibility and AMS 14C dating on the top portion of the core suggests that this record dates to the Marine Isotope Stage (MIS) 6. As indicated in Termination I and II, SST changes are correlated with clear glacial/interglacial cycles and likely dominated by atmospheric CO2 and Western Pacific Warm Pool temperature changes. But the two Terminations were different in magnitude. In Termination I, the minimum and maximum SSTs are 24.5 °C and 27.5 °C, respectively, showing a smaller rise (3 °C) than in Termination II (24–28.3 °C). The n-alkane indices, such as average chain length (ACL) and carbon preference index (CPI), exhibited high/low values during glacial/interglacial periods, and possible more arid climate during MIS 6 than MIS 2. During Termination II, the maximum surface warming in the SCS is accompanied by a progressive lag of approximately 7000 years in relation to maximum summer insolation until Termination I, when they are nearly synchronous. According to the study, SSTs are continuously changing and are influenced by solar insolation, global ice volume changes, and ocean–atmosphere interactions across hemispheres.

Statistical Predictability of Euro-Mediterranean Subseasonal Anomalies: The TeWA Approach

Abstract It is widely known from energy balances that global oceans play a fundamental role in atmospheric seasonal anomalies via coupling mechanisms. However, numerical weather prediction models still have limitations in long-term forecasting due to their nonlinear sensitivity to initial deep oceanic conditions. As the Mediterranean climate has highly unpredictable seasonal variability, we designed a complementary method by supposing that 1) delayed teleconnection patterns provide information about ocean–atmosphere coupling on subseasonal time scales through the lens of 2) partially predictable quasi-periodic oscillations since 3) forecast signals can be extracted by smoothing noise in a continuous lead-time horizon. To validate these hypotheses, the subseasonal predictability of temperature and precipitation was analyzed at 11 reference stations in the Mediterranean area in the 1993–2021 period. The novel method, presented here, consists of combining lag-correlated teleconnections (15 indices) with self-predictability techniques of residual quasi-oscillation based on wavelet (cyclic) and autoregressive integrated moving average (ARIMA) (linear) analyses. The prediction skill of this teleconnection–wavelet–ARIMA (TeWA) combination was cross-validated and compared to that of the ECMWF’s Seasonal Forecast System 5 (SEAS5)–ECMWF model (3 months ahead). Results show that the proposed TeWA approach improves the predictability of first-month temperature and precipitation anomalies by 50%–70% compared with the forecast of SEAS5. On a moving-averaged daily scale, the optimum prediction window is 30 days for temperature and 16 days for precipitation. The predictable ranges are consistent with atmospheric bridges in teleconnection patterns [e.g., Upper-Level Mediterranean Oscillation (ULMO)] and are reflected by spatial correlation with sea surface temperature (SST). Our results suggest that combinations of the TeWA approach and numerical models could boost new research lines in subseasonal-to-seasonal forecasting. Significance Statement The Mediterranean climate presents a high natural variability that makes skillful seasonal forecasts very difficult to achieve. We propose to complement the current forecasting methods with a statistical approach that combines two conceptual models: First, climate anomalies (cold/warm or dry/wet periods) are considered as smooth waves (with slow changes); and second, atmospheric and oceanic indices perform the role of atmosphere–ocean interactions, which impact Mediterranean climate variability in a delayed way. The key findings are that combining both sides, a better predictability of climate variability is provided, which is an opportunity to improve natural resource management and planning.