Impact Of Sea Surface Temperature Research Articles

Impact of sea surface temperature in the Arabian Sea on the variability of Summer Monsoon Rainfall over Pakistan Region

The seas and oceans are essential in preserving energy in the Earth, Ocean, and atmosphere system. Assessing past trends and expected sea surface temperature (SST) shifts is critical for future climate scenarios within this framework. Previous studies have emphasized the importance of SST in the emergence and intensification of heavy rainfall events in the South Asian basin and the development of heat waves in the coastal regions of South Asia. This study has focused to investigate the relationship between SST of the Arabian Sea and mean rainfall in South Asia using Singular Value Decomposition Analysis (SVDA) for the July, August, and September (JAS) season, as most of the region's rainfall is in this season. The first mode accounts for 69 % of the covariance between Arabian Sea SST and regional JAS rainfall, with three dominant SVDA modes explaining 96 % of the total squared covariance. The degree to which the connected fields are correlated has been investigated using Root Mean Squared Covariance. By heterogeneous correlation maps, it is concluded how significant is the impact of one field (SST) on the other (rainfall), which validates our hypothesis that the SST of the Arabian Sea affects variation in precipitation. The empirical results from the SVDA are consistent with those of the composite diagrams. Dry and wet years have been defined and analyzed to examine the impact of SST on regional JAS rainfall further. Vertically integrated moisture transport reveals a significant difference in moisture transport over the Arabian Sea between wet and dry years during the JAS season. Water vapor transport is much stronger during wet years compared to dry years.

Dynamics of Noctiluca scintillans blooms: A 20-year study in Jangmok Bay, Korea

This 20-year study (2001–2020) conducted in Jangmok Bay, Korea, assessed the intricate relationships between environmental factors and Noctiluca scintillans blooms. Granger causality tests and PCA analysis were used to assess the impact of sea surface temperature (SST), salinity, dissolved oxygen (DO) concentration, wind patterns, rainfall, and chlorophyll-a (Chl-a) concentration on bloom dynamics. The results revealed significant, albeit delayed, influences of these variables on bloom occurrence, with SST exhibiting a notable 2-month lag and salinity a 1-month lag in their impact. Additionally, the analysis highlighted the significant roles of phosphate, ammonium, and silicate, which influenced N. scintillans blooms with lags of 1 to 3 months. The PCA demonstrates how SST and wind speed during spring and summer, along with wind direction and salinity in winter, significantly impact N. scintillans blooms. We noted not only an increase in large-scale N. scintillans blooms but also a cyclical pattern of occurrence every 3 years. These findings underscore the synergistic effects of environmental factors, highlighting the complex interplay between SST, salinity, DO concentration, and weather conditions to influence bloom patterns. This research enhances our understanding of harmful algal blooms (HABs), emphasizing the importance of a comprehensive approach that considers multiple interconnected environmental variables for predicting and managing N. scintillans blooms.

A sedimentary DNA record of the Atacama Trench reveals biodiversity changes in the most productive marine ecosystem.

The hadopelagic environment remains highly understudied due to the inherent difficulties in sampling at these depths. The use of sediment environmental DNA (eDNA) can overcome some of these restrictions as settled and preserved DNA represent an archive of the biological communities. We use sediment eDNA to assess changes in the community within one of the world's most productive open-ocean ecosystems: the Atacama Trench. The ecosystems around the Atacama Trench have been intensively fished and are affected by climate oscillations, but the understanding of potential impacts on the marine community is limited. We sampled five sites using sediment cores at water depths from 2400 to ~8000 m. The chronologies of the sedimentary record were determined using 210Pbex. Environmental DNA was extracted from core slices and metabarcoding was used to identify the eukaryote community using two separate primer pairs for different sections of the 18S rRNA gene (V9 and V7) effectively targeting pelagic taxa. The reconstructed communities were similar among markers and mainly composed of chordates and members of the Chromista kingdom. Alpha diversity was estimated for all sites in intervals of 15 years (from 1842 to 2018), showing a severe drop in biodiversity from 1970 to 1985 that aligns with one of the strongest known El Niño events and extensive fishing efforts during the time. We find a direct impact of sea surface temperature on the community composition over time. Fish and cnidarian read abundance was examined separately to determine whether fishing had a direct impact, but no direct relation was found. These results demonstrate that sediment eDNA can be a valuable emerging tool providing insight in historical perspectives on ecosystem developments. This study constitutes an important step toward an improved understanding of the importance of environmental and anthropogenic drivers in affecting open and deep ocean communities.

Influence of Spatial Heterogeneity in Sea Surface Temperature on Tropical Cyclone Intensity Over the Western North Pacific

AbstractThis study explores the impact of sea surface temperature (SST) spatial heterogeneity on tropical cyclone (TC) intensity through a combination of observations and simulations, aiming to provide a reference for further improving TC intensity forecasting skills. Two distinct patterns of SST spatial heterogeneity are identified based on a statistical analysis of observational data, when the SST at the TC center is above and below 29.3°C, respectively. One is a warm‐core pattern (WCP) with a warm peak SST at the TC center decreasing centrifugally which favors TC development, and the other one is a poleward‐decreasing pattern (PDP) with a warm SST at the south decreasing poleward which suppresses TC development. The numerical simulations confirm the opposite influence of the WCP and the PDP on TC intensity. The WCP intensifies TC intensity by strengthening TC secondary circulation, increasing the conversion from ocean heat energy to TC kinetic energy, and compacting TC structure. In contrast, the PDP weakens TC intensity by inducing opposing responses of these processes. The magnitude of TC intensity change caused by SST spatial heterogeneity is comparable to those caused by a 1°C change in SST at the TC center. These findings offer valuable insights into the role of SST spatial heterogeneity in TC development and provide a new perspective to improve TC intensity forecasting by incorporating SST spatial heterogeneity into statistical‐dynamic models.

Exploring the impact of sea surface temperature and salinity on SMAP excess surface emissivity

Exploring the impact of sea surface temperature and salinity on SMAP excess surface emissivity

Daily-Scale Prediction of Arctic Sea Ice Concentration Based on Recurrent Neural Network Models

Arctic sea ice prediction is of great practical significance in facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice prediction, they predominantly operate at the seasonal or sub-seasonal scale, often focusing on localized areas, and few cater to full-region daily-scale prediction. This study introduces the use of spatiotemporal sequence data prediction models, namely, the convolutional LSTM (ConvLSTM) and predictive recurrent neural network (PredRNN), for the prediction of sea ice concentration (SIC). Our analysis reveals that, when solely utilizing SIC historical data as the input, the ConvLSTM model outperforms the PredRNN model in SIC prediction. To enhance the models’ capacity to capture spatiotemporal relationships between multiple variables, we expanded the range of input data types to form the ConvLSTM-multi and PredRNN-multi models. Experimental findings demonstrate that the prediction accuracy of the four models significantly surpasses the CMIP6 model in three prospective climate scenarios (SSP126, SSP245, and SSP585). Of the four models, the ConvLSTM-multi model excels in assimilating the influence of reanalysis data on sea ice within the sea ice edge region, thus exhibiting superior performance than the PredRNN-multi model in predicting daily Arctic SIC over the subsequent 10 days. Furthermore, sensitivity tests on various model parameters highlight the substantial impact of sea surface temperature and prediction date on the accuracy of daily sea ice prediction, and meteorological and oceanographic parameters primarily affect the prediction accuracy of the thin-ice region at the edge of the sea ice.

Impact of Sea Surface Temperature in the Extratropical Southern Indian Ocean on Antarctic Sea Ice in Austral Spring

Abstract The relationship between the seasonal Antarctic sea ice concentration (SIC) variability and the extratropical southern Indian Ocean (SIO) sea surface temperature (SST) is explored in this study. It is found that the Antarctic SIC in a wide band of the SIO, Ross Sea, and Weddell Sea is significantly related to an SIO dipole (SIOD) SST anomaly on the interannual time scale during austral spring. This relationship is linearly independent of the effects of El Niño–Southern Oscillation, the Indian Ocean dipole, and the Southern Hemisphere annular mode. The positive phase of the SIOD, with warm SST anomalies off of western Australia and cold SST anomalies centered around 60°E in high latitudes, stimulates a downstream wave train that induces large-scale cyclonic circulations over the SIO and the Ross and Weddell Seas. Subsequently, anomalous horizontal moisture advection causes water vapor divergence, changes the surface energy budget, and cools the underlying ocean, which leads to the increased SIC over the region in the SIO, Ross Sea, and Weddell Sea. This SIOD SST anomaly reached a record low during the austral spring of 2016 and promoted the prominent wave pattern at high latitudes, contributing to the dramatic decline of sea ice in the 2016 spring. In addition, the proportion of the SIC trend that is linearly congruent with the SIOD SST trend during austral spring is quantified. The results indicate that the trend in the SIOD SST may account for a significant component of the 1979–2014 SIC trend in the Ross Sea with the congruency peaking at 60%.

Warming trends of southwestern Atlantic SST and the summer's warmest SST's impact on South American climate

AbstractSeveral atmospheric variables are directly influenced by oceanic conditions, mainly the sea surface temperature (SST). SST trends and variability over the southwestern Atlantic (SWA) have affected the South American climate, principally the monsoonal period (austral summer). This study analysed the SST trends over the SWA for all seasons. In addition, possible large‐scale triggers of the austral summer's warmest SST over the SWA and the straight impacts of these warmest SSTs on the South American climate were investigated. The results showed a significant positive SST trend of approximately 0.02°C·year−1 over the SWA for all seasons. Since 2000, positive SST anomalies have increased in frequency in all seasons, with the seven warmest summers occurring during the 2010s. The highest SST summers over the SWA have been related to four leading causes: (i) planetary waves triggered by warm anomalies over the subtropical South Pacific; (ii) an omega‐type blocking configuration over the South Atlantic; (iii) a Southern Annular Mode positive phase; and (iv) a strengthening of the Hadley Cell, responding to warm SST over tropical North Atlantic. They all reflected on intensification of the South Atlantic Subtropical High and the western boundary current, heating the SWA. The summer's warmest SST led to positive air temperature anomalies extending in almost all of eastern South America, with significantly highest temperatures over southeastern Brazil, northern Argentina and western Paraguay. Clouds decrease strengthen the incident shortwave in southeastern Brazil, warming the region. Significant reduction of cloudiness and precipitation indicate a low performance of the South Atlantic Convergence Zone. The comparison of the warmest summers in 1980s–1990s in the SWA ratified the role of SST intensification. In conclusion, the positive SST trends over the SWA are related to the summer's warmest SST after 2000s, causing heating and dryness in eastern South America, mainly over southeastern Brazil.

Investigating the impact of sea surface temperature on the development of the Mediterranean tropical-like cyclone “Ianos” in 2020

This study aims to unravel and quantify the impact of sea surface temperature (SST) on the formation, intensity, structure and track of the Mediterranean tropical-like cyclone (medicane) Ianos occurred on 15–20 September 2020 at the central Mediterranean. This study, thus, demonstrates how Ianos would be in past and future climate conditions, assuming that SST changes over the years, but preserving the same atmospheric conditions. To investigate the SST impact, the medicane was simulated using the Advanced Weather and Research Forecasting (WRF-ARW) model. The numerical experiments were initialized either with SST analysis data (control experiment) or applying a uniform decrease and increase to SST analysis by 1 °C and 2 °C (four sensitivity experiments). In this way, the past and future climatic SSTs were concisely approximated. Analysis of various thermodynamic parameters in combination with phase space diagrams, revealing the thermal symmetry and the warm core structure of the cyclone, indicated that Ianos was very sensitive on SST. Thus, SST changes especially by ±2 °C had significant impact on its intensity, changing the period of tropical features while also determining the track and the landfall location. Overall, the average enthalpy flux (i.e., the sum of sensible and latent heat fluxes) in Ianos changed by approximately −39% and + 50% when SST changed by −2 °C and + 2 °C, respectively. This, in turn, affected the characteristics of Ianos causing changes for example in the average wind speed (approximately −15% and + 15%) and the average precipitation (approximately −56% and + 44%). This study quantifies the impacts of SST on Ianos medicane that have important research and socioeconomic implications with a view to a changing future. Therefore, it could support scientists, decision-makers and civil protection in the adaptation to extreme weather phenomena by building climate resilience and sustainability.

Monitoring and Quantification of Carbon Dioxide Emissions and Impact of Sea Surface Temperature on Marine Ecosystems as Climate Change Indicators in the Niger Delta Using Geospatial Technology

The Niger Delta marine environment has experienced a series of environmental disasters since the inception of oil and gas exploration, which can be attributed to climate change. Carbon dioxide (CO2) emissions and sea surface temperature (T) ties associated with burning fossil fuels, such as gas flaring, vehicular traffic, and marine vessel movement along the sea, are increasing. Using data extracted from the NASA Giovanni satellite’s Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), this study mapped the carbon footprint and T along the coastline into the deep sea from 2003 to 2011, using ArcGIS software. The spatial distribution of CO2 and T concentrations determined by the inverse distance weighting (IDW) method reveals variations in the study area. The results show an increase in the quantity of the mean tropospheric CO2 from July 2003 to December 2011, from 374.5129 ppm to 390.7831 ppm annual CO2 emissions, which also reflects a continuous increase. The average Monthly sea surface temperature had a general increasing trend from 25.79 °C in July 2003 to 27.8 °C in December, with the Pearson correlation coefficient between CO2 and T indicating 50% strongly positive, 20% strongly negative, 20% weakly positive,and 10% weakly negative. CO2 levels, like temperature, follow a seasonal cycle, with a decrease during the wet season due to precipitation dissolving and plant uptake during the growing season, and then a rise during the dry season. Carbon capture and storage technologies must be implemented to benefit the marine ecosystem and human well-being.

The Impact of Madden - Julian Oscillation and Sea Surface Temperature Process Interaction on Rainfall Variability During Rainy Season: A Case Study in East Nusa Tenggara, Indonesia

Most studies of the impact of sea surface temperature (SST) have explored rainfall in a part of Indonesia. This paper takes a different approach and explores the impact of air-sea coupling interaction between Madden-Julian Oscillation (MJO) and SST on rainfall variability in East Nusa Tenggara (NTT). This study uses daily rainfall observation from some of the NTT seasonal zone (ZOM) from 1991to 2016. Meanwhile, the gridded data of SST around NTT was obtained from Japan Meteorological Agency (JMA). For the amplitude of MJO, the data was downloaded from the Bureau of Meteorology (BOM)’s website. This study used a statistical approach of conditional probability and gamma correlation to identify the impact of MJO-SST coupling interaction on rainfall variability in NTT. The results of this study showed that during rainy seasons and MJO located in phase 5, they are still a high probability of rainfall appearing in most NTT regions, even though SST is in cooling condition. The evidence shows that the result provides insights into the adequacy of MJO caused high rainfall variability in almost NTT regions in all of SST condition.

Impacts of Sea Surface Temperature on the Interannual Variability of Winter Haze Days in Guangdong Province

Impacts of Sea Surface Temperature on the Interannual Variability of Winter Haze Days in Guangdong Province

Sea Surface Temperature Impact on Diurnal Cycle and Seasonal Evolution of the Guinea Coast Rainfall in Boreal Spring and Summer

Abstract ERA5 reanalyses and observations of convective clouds and precipitation are used over the northern Gulf of Guinea between 7°W and 3°E to study the influence of ocean surface temperature and the land–sea temperature gradient on Guinea Coast rainfall (GCR) in boreal spring and summer. Seasonal composites are calculated around two dates indexing the onset (Tref) and demise (Tend) of the GCR. The Tref date corresponds to the emergence of the equatorial upwelling in boreal spring, which “pushes” the zonal precipitation belt northward against the Guinea coast. The Tend date characterizes the emergence of the coastal upwelling in July, which is known to coincide with the beginning of the “Little Dry Season” that lasts until September. Along the Guinea Coast, the diurnal cycle of the air–sea temperature gradient controls precipitation through the land–sea breeze, which explains why precipitation reaches its maximum around noon over the ocean, and in the late afternoon over the continent. The emergence of the Guinea Coast upwelling in July induces a weakening of southerlies on a seasonal scale, and a weaker land breeze on a diurnal scale. It induces a decrease in the convergence of humidity transport across the coast and in coastal oceanic precipitation. Therefore, the GCR is seasonally controlled by the latitude of the maximum tropospheric water vapor content and the annual cycle of the West African monsoon, but the ocean surface temperature is responsible for the abruptness of its onset via the intensification of the equatorial upwelling around the end of May, and possibly of its demise as well via the emergence of the coastal upwelling by early July.

Influence of tropical Atlantic meridional dipole of sea surface temperature anomalies on Antarctic autumn sea ice

Antarctic sea ice plays an important role in polar ecosystems and global climate, while its variability is affected by many factors. Teleconnections between the tropical and high latitudes have profound impacts on Antarctic climate changes through the stationary Rossby wave mechanism. Recent studies have connected long-term Antarctic sea ice changes to multidecadal variabilities of the tropical ocean, including the Atlantic Multidecadal Oscillation and the Interdecadal Pacific Oscillation. On interannual timescales, whether an impact exists from teleconnection of the tropical Atlantic is not clear. Here we find an impact of sea surface temperature (SST) variability of the tropical Atlantic meridional dipole mode on Antarctic sea ice that is most prominent in austral autumn. The meridional dipole SST anomalies in the tropical Atlantic force deep convection anomalies locally and over the tropical Pacific, generating stationary Rossby wave trains propagating eastward and poleward, which induce atmospheric circulation anomalies affecting sea ice. Specifically, convective anomalies over the equatorial Atlantic and Pacific are opposite-signed, accompanied by anomalous wave sources over the subtropical Southern Hemisphere. The planetary-scale atmospheric response has significant impacts on sea ice concentration anomalies in the Ross Sea, near the Antarctic Peninsula, and east of the Weddell Sea.

Impact of SST on Present and Future Extreme Precipitation in Hokkaido Investigated Considering Weather Patterns

AbstractThis study investigated the impact of sea surface temperature (SST) on extreme precipitation events in North Japan and its relation to synoptic weather patterns using large‐ensemble climate simulations. Eight weather patterns were identified by applying cluster analysis to sea level pressure anomalies for selected days with extreme precipitation derived from a 3000‐year historical climate experiment. Interannual variability of extreme precipitation days associated with two specific weather patterns, characterized by a weak low‐pressure system and an atmospheric river (AR), significantly correlated with that of SST over the Sea of Japan, with a correlation coefficient of 0.37 and 0.53, respectively. In higher SST years, the increased atmospheric moisture can increase the extreme precipitation in the inland area of Hokkaido for the weather pattern associated with a weak low‐pressure system, whereas it appears to enhance orographic precipitation along the western slopes of mountains for the pattern resembling AR. These results indicate that the effect of local SST on extreme precipitation strongly depends on the weather patterns. In the future projection, the two weather patterns that are sensitive to SST over the Sea of Japan show a sharp increase of more than 4 times under the 4 K warming climate. Moreover, the magnitude of extreme precipitation was also found to increase with SST, broadly following the Clausius–Clapeyron relation in both historical and warmed climates. These results suggest increased risk of heavy precipitation associated with such weather patterns over North Japan in the future.

Impacts of Sea Temperature Rise on Rastrelliger kanagurta Potential Fishing Grounds in the Exclusive Economic Zone (EEZ) Off South China Sea

The Indian mackerel (Rastrelliger kanagurta) is one of the most commercially crucial epipelagic scombrid where it is caught in the Exclusive Economic Zone (EEZ) off the South China Sea (SCS). High demand for fisheries resources is a challenge for fishers to achieve optimal fish landing targets. By using R. kanagurta catch data, and high resolution satellite data of chl-a and SST (MODIS-Aqua) and SSH (AVISO) from 2018 together with boosted regression tree (BRT) model, this study aims to determine the impact of sea surface temperature (SST) increase on the potential catch of R. kanagurta based on temperature projection of IPCC-AR5-RCPs scenarios. BRT modelling result indicated that during the northeast monsoon (NEM), at elevated temperature of 1.80 and 2.60 ℃ showed that the potential fishing grounds of R. kanagurta increase in the area especially in the northern part of the EEZ. However, at elevated temperature of 3.30 ℃, the potential fishing areas was found to decrease along the coast of Peninsular Malaysia. Meanwhile, during southwest monsoon (SWM) and inter-monsoon transition, at temperature rise of 1.80, 2.60 and 3.30 °C showed a significant reduction in the potential fishing area of the R. kanagurta potential fishing grounds especially along the coast of the EEZ off SCS. Results indicated that changes in SST influenced suitability of habitat which affected the distribution of R. kanagurta. Understanding the impacts of temperature increase would contribute towards future sustainable fisheries resource management strategies.

Impact of SST and Surface Waves on Hurricane Florence (2018): A Coupled Modeling Investigation

AbstractHurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir–Simpson category 4 to category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. In addition to experiments using a fully coupled atmosphere–ocean–wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by ocean waves through data from an uncoupled wave model. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity (r = 0.89) and strength (r = 0.95) coming from the fully coupled simulations. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. Adding ocean and wave features to the model further modified the fluxes due to more realistic cooling beneath the storm, which in turn modified the precipitation field. Our experiments highlight significant differences in how air–sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes.

Sensitivity of WRF-derived hydrometeorological extremes to sea surface temperatures in regions with complex topography and diverse climate

This study investigates the impact of sea surface temperature (SST) describing the lower boundary of Weather Research and Forecasting (WRF) model on the extreme weather events that occurred on the Mediterranean (MED) and the Eastern Black Sea (EBS) regions of Turkey. For each region, one extreme event case is selected and characterized as a summer convective system in EBS and as a winter synoptic system in MED region. The SST impact on the WRF model forecasts of these events is accomplished in two ways. First, the SST analysis is conducted by making a 10-days simulation for each event with and without activating the SST options (update and skin options) available in the model configuration. In these runs, the selected initial and boundary condition datasets, Global Forecasting System (GFS) for the MED region and the ERA5 for the EBS regions, provide corresponding internal SST data. Second, the prediction performance of the model is evaluated among the simulations of non-external, time-varying (GFS and ERA5 SST) and external, time–varying, high-resolution SST products (The Group for High Resolution Sea Surface Temperature; GHRSST, Medspiration, and NCEP) for each event. The results show that the WRF model simulations, even for short-term event predictions, are highly sensitive to time-variant SST options. The overestimation and high spreading feature of maximum and total precipitation are realistically reduced by time-variant SST products. The Medspiration and the NCEP sources for the MED region and the GHRSST and the Medspiration sources for the EBS region yielded warmer SSTs among the simulations. By establishing the amplified air-sea interactions, these sources provide more appropriate peak precipitation distributions in both regions. Furthermore, based on this study, the effect of using high-resolution SST (GHRSST and Medspiration) is more prominent in predicting convective event developed over complex topography of the EBS while the resolution effect is not much critical for synoptic system simulation even under the complex topography in MED. Lastly, the highest mean correlation of conditional hourly rain is calculated as 0.65 with the Medspiration product on MED and 0.48 with the GHRSST product on the EBS region.

Impacts of Sea Surface Temperature and Atmospheric Teleconnection Patterns in the Northern Mid-Latitudes on Winter Extremely Cold Events in North China

The frequency distribution of winter extreme cold events (ECEs) in North China and the influences of mid-latitude sea surface temperature anomalies (SSTAs) in the Northern Hemisphere are studied. The results show that (1) the frequency of single station ECEs (SSECEs) in winter increases from southeast to northwest, with a decrease before 2008 and then a significant increase. This trend abrupt change occurs in late winter. (2) When the SST in the North Pacific shows an “El-Niño-like” anomaly in winter, it triggers the negative Arctic Oscillation (−AO), positive Pacific North America (+PNA), and positive Eurasia Pacific (+EUP) atmospheric teleconnection patterns in the mid-lower troposphere. As a result, the ridge to south of Lake Baikal becomes stronger. Meanwhile, SST in the North Atlantic shows a “reversed C” negative anomaly with North Atlantic Oscillation (+NAO), (+PNA)-like and (+EUP)-like patterns, and the ridge to southwest of Lake Baikal becomes stronger. Furthermore, both cause the Siberian High to become weaker in the north and stronger in the south. With the weaker East Asia subtropical jet and stronger East Asia winter monsoon, these factors lead to a significant increase of SSECE frequency in North China. (3) When the SSTA shows an “El Niño-like” developing pattern from summer to autumn in the North Pacific, the winter SSECE frequency will be higher. (4) The purported mechanism between the mid-latitude SSTA and the winter SSECE frequency in North China is the following: the SSTA in the North Pacific in summer and autumn excites atmospheric teleconnection wave trains, and the Atlantic stores these anomaly signals. In winter, the interaction between the SSTAs in the North Pacific and the North Atlantic enhances the Eurasian teleconnection wave train. With the upstream fluctuation energy dispersing downstream, the wave train centers move eastward with the season, resulting in an increase in the frequency of the SSECEs.

Using a larval growth index to detect the environment-recruitment relationships and its linkage with basin-scale climate variability: A case study for Japanese anchovy (Engraulis japonicus) in the Yellow Sea

Increasing evidence has suggested that climate variability has a vital impact on the stock fluctuation of many small pelagic fishes by regulating their recruitment. However, most recruitment-related studies have focused on large spawning/nursing grounds at annual or seasonal scales, while few have considered the impact of short-term environmental variations during the vulnerable passive-transport period. In this study, a larval growth index based on a Lagrangian particle-tracking model coupled with a hydrodynamic model that focused on the early growth and passive transport of the SPF was developed to identify the key spawning/nursing period and grounds accommodating fish recruitment. Taking Japanese anchovy (Engraulis japonicus) in the Yellow Sea as an example, the key spawning grounds and time for its recruitment was identified and the impact of sea-surface temperature (SST) and climate variability on its recruitment was then investigated and discussed. Significant positive (negative) correlations were identified between the recruitment index and the mean growth index (mean water temperature) along the tracking path of eggs or larvae released in the Bohai Sea and the southwestern Yellow Sea during July (1987–2004), implying that these were the key spawning grounds and period for recruitment success. The multi-year tracking path of released particles indicated that both the southwestern Yellow Sea and the central Bohai Sea may be the key nursing grounds. Meanwhile, the SST in July was found to be associated with basin-scale atmosphere–ocean interactions. A potential “atmosphere–ocean-recruitment” influence pattern for Japanese anchovy in the Yellow and Bohai Seas was thus proposed, in which higher (lower) temperature during the key spawning/nursing period induced by atmospheric variation might diminish (promote) recruitment success by limiting the growth and survival of anchovy larvae. The larval growth index developed in this study can be widely applied to other small pelagic fishes in other waters and provide implications for climate-induced recruitment studies.