Tropical Pacific Region Research Articles

Exploring the Relationship Between Upper Ocean States and the Falling Ice Radiative Effects using ECCO Product and Global Climate Models

Abstract This study seeks to explore the relationship between upper ocean current (UOC) anomalies (above 200 meters) and surface wind stress (TAU), focusing on the influence of falling ice (snow) radiative effects (FIREs) over the tropical and subtropical Pacific regions. To achieve this, we conducted sensitivity experiments with the CESM1-CAM5 model, using the Coupled Model Intercomparison Project phase 5 (CMIP5) historical run setting, with FIREs turned off (NOS) and on (SON). The monthly ocean current and temperature of the ocean reanalysis from the NASA Estimating the Circulation and Climate of the Ocean (ECCO) project, which assimilates satellite and in situ measurements, serve as a reference for this study. The spatial patterns of the horizontal UOC anomaly (UOCA) differences between the NOS and SON experiments show a strong correlation with the TAU patterns across the studied domain. When compared to the experiments with NOS, the experiments with SON demonstrate an improvement in the annual mean UOC. The improvement in UOC can be attributed to the enhancements in TAU, specifically in the trade-wind regions. The enhancements in TAU play a significant role in influencing the UOCA patterns and contribute to the overall improvement observed in the experiments with SON. In SON, the average absolute bias of simulated UOCA over the study area is reduced by up to 30% compared to NOS against ECCO. 
Although biases in UOC are present over the southern and northern flanks of the equator in SON, the improvements in annual mean ocean currents are closely related to enhancements in TAU driven by the inclusion of FIREs. Notably, stronger ocean current magnitudes correspond to more significant changes in TAU due to Coriolis forces. When evaluating the ensemble mean absolute biases of UOC from the CMIP5 models, similarities to NOS, however, are limited over the South Pacific region.

Parasalinivibrio latis gen. nov., sp. nov., isolated from the distal gut of healthy farmed Asian Seabass (Lates calcarifer).

Asian Seabass (Lates calcarifer) is widely farmed as a sustainable source of protein for countries in the tropical Indo-West Pacific region. However, microbial species of the gut microbiome of healthy Asian Seabass remain largely uncharacterized and uncultured. Here, we analysed the microbial composition along the gastrointestinal tract of a farmed healthy Asian Seabass. We used different cultivation approaches to obtain isolates from the seabass intestinal tract and describe the isolation and characterization of a novel strain, TLL-SE01T. Analysis of the strain's 16S rRNA gene indicates that the strain belongs to the family Vibrionaceae with Photobacterium damselae as its closest relative, albeit sharing only 94.8% (aligned region 1553bp) nucleotide identity. Comparative genomic analysis with all validly published Vibrionaceae species with available genomes revealed average nucleotide identity (ANI) and DNA-DNA hybridisation (DDH) values of around 70% and 24% respectively to strain TLL-SE01T, which are well below proposed thresholds for species delineation (ANI, 95-96%; DDH, 70%). The alignment fraction and ANI genus demarcation boundaries for all genera in the Vibrionaceae family were determined for which strain TLL-SE01T is well below the calculated values, indicating that it belongs to a novel genus. Single- and core-gene phylogenetic analysis places strain TLL-SE01T in a monophyletic clade, further supporting its designation to a novel genus. Phenotypic comparison between strain TLL-SE01T and its close relatives indicated additional differences, such as growth response at different salt concentrations and different metabolic capabilities. Based on genotypic, phylogenetic and phenotypic differences to other Vibrionaceae species, we propose a novel species in a new genus, Parasalinivibrio latis gen. nov. sp. nov. and strain TLL-SE01T (= BCRC 81435T = JCM 36283T) as the type strain.

Megabenthic Diversity Patterns on a Seamount in the Philippine Sea: Implications for Conservation Planning on the Kyushu-Palau Ridge.

The oligotrophic tropical western Pacific region is characterized by a high density of seamounts, with the Kyushu-Palau Ridge (KPR) being the longest seamount chain here. Effective spatial management plans for seamount ecosystems necessitate an understanding of distribution patterns and key environmental factors influencing benthic communities. However, knowledge regarding deep-sea biodiversity patterns over intricate topography remains limited. In this study, we investigated a seamount with a water depth of 522 m at the summit located in the southern section of KPR. Survey transects were conducted from 522 m to 4059 m. By analyzing video-recorded data obtained by a human-occupied vehicle (HOV) during dives and environmental variables derived from bathymetry, distinct assemblages were identified through noise clustering. α- and β-diversity patterns within the seamount megabenthic community were analyzed across the depth gradient, along with investigation of their environmental drivers. A total of 10,596 megafauna individuals were documented, categorized into 88 morphospecies and statistically separated into six distinct community clusters using noise clustering analysis. Species abundance and richness were highest within the 700-800 m water depth range, declining notably beyond 2100 m, indicating a critical threshold for habitat classification in this region. The β-diversity of megabenthic communities was high (0.836). Although β-diversity patterns along the depth gradient were mostly dominated by differences in species richness, the contribution of species replacement increased with depth, becoming dominant at depths greater than 3000 m. Depth emerged as the primary driver of spatial variation in community structure, while near-bottom current velocity, topographic parameters (bathymetric position index, slope), and substrate type also influenced the formation of microhabitats. The study highlights the depth gradients, thresholds, and other intricate environmental factors shaping the spatial heterogeneity of these communities. It provides valuable insights for the future development of effective survey and conservation strategies for benthic biodiversity on the KPR.

Vegetation, temperature, and Indian Summer Monsoon evolution over the past 4400 years revealed by a pollen record from Drigo Co on the southern Qinghai-Tibet Plateau

Understanding the changes in temperature and precipitation on the southern Qinghai-Tibet Plateau (QTP), which is influenced by the Indian Summer Monsoon (ISM), is crucial for predicting possible future changes in the regional ecological environment under ongoing climate change. However, due to the lack of well-dated, high-resolution paleoclimate records, the trends of temperature and ISM precipitation on the southern QTP since the mid-Holocene are poorly understood. We present a high-resolution pollen record from Dirgo Co, on the southern QTP, spanning the past 4400 years. The decrease in the pollen ratio of Artemisia to Cyperaceae (A/Cy) indicates a downward shift of altitudinal vegetation belts in the Drigo Co area over the past 4400 years, suggesting falling temperatures; and decreases in tree pollen percentages indicate the gradual weakening of the ISM. Our pollen record also indicates five cold phases with the near-simultaneous weakening of the monsoon, during: 4300–4100 cal yr BP, 3600–3400 cal yr BP, 2800–2600 cal yr BP, 1600–1400 cal yr BP, and 700–100 cal yr BP, and these climate anomalies were also recorded elsewhere on the QTP. We suggest that the changes in temperature and ISM intensity on the southern QTP over the past 4400 years were modulated by changes in summer insolation and solar activity. These changes affected the sea surface temperature (SST) over the tropical Pacific and Indian Ocean regions, and they were linked to a positive phase of the El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), which weakened the ISM intensity in the Drigo Co area. Additionally, due to increased evaporation related to high temperatures, combined with intensified grazing activities over the past ∼200 years, the lake level has fallen, and the vegetation cover has decreased. As global temperatures continue to rise, the alpine steppe in the Drigo Co area may increase and the vegetation density may gradually decrease, and at the same time the regional ecological environment may gradually deteriorate.

Impact of Cloud Vertical Overlap on Cloud Radiative Effect in the Korean Integrated Model (KIM) Seasonal Simulations during Boreal Summer and Winter

Exponential-random vertical overlap of clouds is applied for radiative processes in a research version of the Korean Integrated Model (KIM) to replace the maximum-random vertical overlap of clouds. The cloud radiative effect (CRE) increases overall when the exponential-random overlap is used. This is because vertically continuous clouds, which are assumed to overlap maximally under the maximum-random overlap assumption, can be relaxed to random overlap depending on the vertical distance between cloud layers and the specified decorrelation length of clouds. CRE is more enhanced by considering the latitudinal dependency of cloud decorrelation length based on previous observational studies. This alleviates biases in CRE, which is underestimated overall, except in the low latitudes where the CRE is overestimated in the present simulations. The interaction between radiative and convective processes plays a role in decreasing CRE over the tropical western Pacific region, where strong convections develop, although the direct impact of applying the exponential-random overlap is to decrease the vertical overlap between ice clouds. The simulation of temperature in the lower troposphere is improved owing to the changes in cloud overlap. The warm bias over the Eurasian continent, in particular, is alleviated as more shortwave fluxes are reflected due to increased CRE.

Generation of state‐dependent ensemble perturbations based on time‐varying seawater density for GloSea5 initialization

AbstractIn this study, we developed a flow‐dependent oceanic initialization system for initializing the oceanic temperature and salinity in the Global Seasonal forecast system version 5 (GloSea5). Our algorithm overcomes the limitation of stationary perturbations for Ensemble Optimal Interpolation (EnOI) by spreading observed information along isopycnal lines to create three‐dimensional snapshot density states. The proposed algorithm, which we call state‐dependent ensemble‐based EnOI (SD‐EnOI), takes into account changes in the background error covariance over time without relying on ensemble model simulations. To evaluate the quality of the oceanic initial conditions (ICs) produced by SD‐EnOI, we compared them with those generated by the Global Ocean Data Assimilation and Prediction System version 1 (GODAPS1) operated by the Korea Meteorological Agency (KMA) throughout January 2017 to December 2017. Our findings show that the thermal construction of the SD‐EnOI ICs is more realistic than that of GODAPS1, particularly in the tropical Pacific region. The strong warm bias in sea surface temperature (SST) and the shallow mixed‐layer depth bias observed in the GODAPS1 ICs are not shown in SD‐EnOI. Due to the more realistic oceanic thermal structure present in the SD‐EnOI ICs, their use in retrospective forecast experiments resulted in a systematic reduction in climatological SST drift in the central‐eastern Pacific for forecasts up to four lead months compared to using GODAPS1 ICs. This demonstrates the significant impact of the initialization process on the quality of dynamical seasonal forecasts.

Improving the Predictability of the US Seasonal Surface Temperature With Convolutional Neural Networks Trained on CESM2 LENS

AbstractTo better understand and improve the prediction of the seasonal surface temperature (TS) across the United States, we employed convolutional neural network (CNN) models trained on the Community Earth System Model Version 2 Large Ensemble (CESM2 LENS). We used lagged sea surface temperatures (SST) over the tropical Pacific region, containing the information of the El Niño Southern Oscillation (ENSO), as input for the CNN models. ENSO is the principal driver of variability in seasonal US surface temperatures (TSUS) and employing CNN models allows for spatiotemporal aspects of ENSO to be analyzed to make seasonal TSUS predictions. For predicting TSUS, the CNN models exhibited significantly improved skill over standard statistical multilinear regression (MLR) models and dynamical forecasts across most regions in the US, for lead times ranging from 1 to 6 months. Furthermore, we employed the CNN models to predict seasonal TSUS during extreme ENSO events. For these events, the CNN models outperformed the MLR models in predicting the effects on seasonal TSUS, suggesting that the CNN models are able to capture the ENSO‐TSUS teleconnection more effectively. Results from a heatmap analysis demonstrate that the CNN models utilize spatial features of ENSO rather than solely the magnitude of the ENSO events, indicating that the improved skill of seasonal TSUS is due to analyzing spatial variation in ENSO events. The proposed CNN model demonstrates a promising improvement in prediction skill compared to existing methods, suggesting a potential path forward for enhancing TSUS forecast skill from subseasonal to seasonal timescales.

Characterising a diversity of coastal community fisheries in Kiribati and Vanuatu

AbstractUnderstanding what diversity of small‐scale fisheries translates to in practice, and what this means for management regimes seeking sustainability, continues to be a challenging undertaking. This is particularly so in the tropical Pacific Islands region, where small‐scale coastal fisheries play a significant role in domestic food and livelihood systems. A renewed regional policy focus on supporting coastal fisheries, combined with momentum built from a decades‐long ‘Pacific renaissance’ in community‐based fisheries management approaches, has increased resourcing and support for coastal fishery data collection and knowledge production. In this context, there is growing demand to explicitly characterise diversity and complexity of community‐based coastal fisheries to inform how national co‐management programs can adequately support the many communities within national constituencies. This study presents findings from a community‐based coastal fisheries monitoring programme implemented in ten communities across Kiribati and Vanuatu between 2019 and 2021. Findings illustrate the intra‐ and inter‐country diversity of contextual drivers, fishing practices, and fisher participation. We discuss the implications of this enhanced understanding of community‐based fisheries for applied co‐management practice in these two countries. In doing so, we add to a growing knowledge base about fishing practices in Pacific Island coastal communities and elucidate avenues through which to incorporate this knowledge into adaptive co‐management practice.

Anomalously weak intensity of tropical cyclones striking eastern China over the past two millennia

Anthropogenic climate warming is predicted to increase the intensity of global tropical cyclones (TCs) on decadal timescales, known as the ‘temperature-TC intensity’ paradigm. However, no proxy is currently available to directly quantify TC intensity in the northwestern Pacific region over centennial to millennial timescales. Here, we reconstruct the intensity of past TCs inferred from event-beds detected in two sedimentary systems in eastern China spanning approximately 1910 to 645 yr BP using an instrumental-calibrated technique, thereby encompassing a sufficiently wide range of temperatures to test the paradigm in the time domain. Intriguingly, our two intensity indices, based on flooding depth and wind speed, provide the initial quantitative evidence that TC intensity in eastern China has been anomalously weak since around 1485 ± 45 yr BP, with a reduction of approximately 30 ± 8% in intensity, despite no concurrent temperature shift. This reduction appears to have been pre-conditioned by a combined influence of a weaker El Niño-Southern Oscillation, a stronger Atlantic Meridional Overturning Circulation, and an increased level of Saharan dust. We suggest that the magnitudes of these factors may have crossed a tipping point and have not reverted to their pre-shift levels since that time, resulting in their impact on TC intensity exceeding that of temperature by triggering changes in the oceanic and atmospheric state within the tropical Pacific region where TCs originate.

Properties of Cirrus Cloud Observed over Koror, Palau (7.3°N, 134.5°E), in Tropical Western Pacific Region

This study presented an analysis of the geometric and optical properties of cirrus clouds with data produced by Compact Cloud-Aerosol Lidar (ComCAL) over Koror, Palau (7.3°N, 134.5°E), in the Tropical Western Pacific region. The lidar measurement dataset covers April 2018 to May 2019 and includes data collected during March, July and August 2022. The results show that cirrus clouds occur approximately 47.9% of the lidar sampling time, predominantly between altitudes of 15 and 18 km. Seasonal variations in cirrus top height closely align with those of the cold point tropopause. Most cirrus clouds exhibit low cloud optical depth (COD < 0.1), with an annual mean depolarization ratio of 31 ± 19%. Convective-forming cirrus clouds during the summer monsoon season exhibit a larger size by notably lower values in terms of color ratio. Extremely thin cirrus clouds (COD < 0.005) constituting 1.6% of total cirrus occurrences are frequently observed at 1–2 km above the cold point, particularly during winter and summer, suggesting significant stratosphere–troposphere exchange. The coldest and highest tropopause over Palau is persistent during winter, and related to the pathway of tropospheric air entering the stratosphere through the cold trap. In summer, the extremely thin cirrus above the cold point is likely correlated with equatorial Kelvin waves induced by western Pacific monsoon convection.

Plastic pollution transcends marine protected area boundaries in the eastern tropical and south-eastern Pacific

The Eastern Tropical and South-Eastern Pacific region is of global biodiversity importance. At COP26, the governments of Costa Rica, Panama, Colombia, and Ecuador committed to the expansion of existing MPAs to create a new Mega MPA, safeguarding the Eastern Tropical Pacific Marine Corridor. It offers a profound step forward in conservation efforts but is not specifically designed to protect against the more diffuse anthropogenic threats, such as plastic pollution. We combine published data with our own unpublished records to assess the abundance and distribution of plastic pollution in the region. Macro- and microplastic concentrations varied markedly and were not significantly different when comparing areas inside and outside existing MPA boundaries. These findings highlight the diffuse and complex nature of plastic pollution and its ubiquitous presence across MPA boundaries. Understanding the sources and drivers of plastic pollution in the region is key to developing effective solutions.

Decoding low-frequency climate variations: A case study on ENSO and ocean surface warming

Current perspectives on lower frequency variations and secular warming have predominantly been shaped by traditional anomalies that assume an annual cycle (AC) with a time-invariant amplitude. However, this anomaly framework falls short in capturing the complexity of multiple periodic modes with intricate waveforms and time dependent amplitude—the traits, in general, shared by externally forced responses of complex dynamical systems. By allowing interannual amplitude modulation of ACs, we show that the monotonic amplitude increases of the first AC of Sea Surface Temperature (SST) are manifested as the basin-wide secular warming of the ocean surface. Notably, the first SST-AC exhibits significant interannual variances and the largest linear warming rates in the Pacific Warm Pool. While the linear warming pattern mirrors that of a long-term mean SST, it depicts an entirely different warming pattern on the surface of the tropical Pacific Ocean compared to those reported so far. Moreover, all interannual warm (El Niño) and cold (La Niña) events in tropical Pacific regions are abnormal interannual modulations in the third and fourth ACs of SST, respectively. Specifically, a strong El Niño event occurs when a positive amplitude modulation leads to the overlap of two consecutive positive phases of the third AC of SST. Conversely, the absence of such overlaps during negative amplitude modulations significantly contributes to the positive skewness of SST anomalies. No systematic decadal changes in the zonal propagation characteristics of SST in the eastern Pacific (EP) and central Pacific (CP) regions were detected. These findings underscore that the secular warming and low-frequency events in EP and CP are intrinsic to three distinct ACs.

Comparison of two filter approaches for characterizing boreal summer intraseasonal oscillation

Two commonly used filter approaches for boreal summer intraseasonal oscillation (BSISO) are investigated with the observations during 1979–2021. One is the real-time BSISO index and the other is based on 20–80-day Lanczos bandpass filter. Both two filter approaches are able to isolate spatial structure and life cycle of BSISO realistically in the Indo-NWP region. But the BSISO phase pattern match does not guarantee consistent propagation characteristics and phase occurrence frequency. The real-time monitoring methods such as real-time BSISO index does not use future information beyond the current date, so it is influenced by seasonal mean anomalies induced by El Niño on the interannual timescale over the Indo-NWP region. During post-El Niño summers, the real-time BSISO index shows a weaker northward propagation than bandpass filter approach. Phases 2–4 of BSISO show relatively higher occurrence frequency than other phases during post-El Niño summers in real-time BSISO index, resulting in the seasonal mean of active eight BSISO phases largely resembling the El Niño induced mean state anomaly pattern with depressed convection and low-level anomalous anticyclone in the tropical northwest Pacific region. Bandpass filter approach exhibits a more uniform phase occurrence frequency for both normal and post-El Niño summers, which is consistent with the random nature of BSISO as one of atmospheric internal variability. Bandpass filter approach is recommended for studies of BSISO northward propagation and its relationship with low-frequency variability such as ENSO.

Atmospheric bias teleconnections in boreal winter associated with systematic sea surface temperature errors in the tropical Indian Ocean

Abstract. Coupled climate models suffer from significant sea surface temperature (SST) biases in the tropical Indian Ocean (TIO), leading to errors in global climate predictions. In this study, we investigate the local and remote effects of the TIO SST bias on the simulated atmospheric circulation and spatio-temporal variability – bias teleconnections. A set of century-long simulations forced by idealized SST perturbations, which resemble various (monopolar or dipolar, positive or negative) TIO SST biases in coupled climate models, are conducted with an intermediate-complexity atmospheric model. Bias teleconnections with a focus on boreal wintertime are analysed using the normal-mode function (NMF) decomposition, which can differentiate between balanced and unbalanced flows across spatial scales. The results show that the atmospheric circulation biases caused by the TIO SST bias have the Gill–Matsuno-type pattern in the tropics and Rossby-wave-train structure in the extratropics, similar to the steady-state response to tropical heating perturbations. The teleconnections between the tropical and extratropical biases are set up by Rossby wave activity flux emanating from the subtropics. Over 90 % of the bias variance (i.e. the square of the bias amplitude) is contained in zonal wavenumbers k≤5. The northward shift of the SST bias away from the Equator weakens the amplitude but does not change the spatial structure of the atmospheric response. Besides, the positive SST bias produces stronger bias teleconnections than the negative one of the same size and magnitude. In the NMF framework, the change in the spatial variance of the time-mean state (i.e. energy) is equal to the sum of the bias variance and the covariance between the circulation bias and the reference state (i.e. bias covariance). Due to the TIO SST biases, the global unbalanced zonal-mean (k=0) flow energy decreases, whereas its balanced counterpart increases. These changes primarily arise from the strong bias covariance. For k>0, both the global unbalanced and the tropical balanced energies increase in the case of a monopolar SST bias and decrease in the case of a dipolar SST bias. The increase appears mainly as the bias variance, whereas the decrease is associated with a strong negative bias covariance at k=1 and 2. In contrast, the extratropical balanced wave energy decreases (increases) when the TIO SST bias is positive (negative), which is mainly associated with the bias covariance at k=1. The change in the interannual variance (IAV) is contingent upon the sign of the TIO SST bias. A positive bias reduces, whereas a negative one increases, the IAV in both balanced and unbalanced flows. Geographically, large IAV changes are observed in the tropical Indo-West Pacific region, Australia, South and Northeast Asia, the Pacific-North America region, and Europe, where the background IAVs are strong.

Tropical Cyclones and Equatorial Waves in a Convection‐Permitting Aquaplanet Simulation With Off‐Equatorial SST Maximum

AbstractTropical weather phenomena—including tropical cyclones (TCs) and equatorial waves—are influenced by planetary‐to‐convective‐scale processes; yet, existing data sets and tools can only capture a subset of those processes. This study introduces a convection‐permitting aquaplanet simulation that can be used as a laboratory to study TCs, equatorial waves, and their interactions. The simulation was produced with the Model for Prediction Across Scales‐Atmosphere (MPAS‐A) using a variable resolution mesh with convection‐permitting resolution (i.e., 3‐km cell spacing) between 10°S and 30°N. The underlying sea‐surface temperature is given by a zonally symmetric profile with a peak at 10°N, which allows for the formation of TCs. A comparison between the simulation and satellite, reanalysis, and airborne dropsonde data is presented to determine the realism of the simulated phenomena. The simulation captures a realistic TC intensity distribution, including major hurricanes, but their lifetime maximum intensities may be limited by the stronger vertical wind shear in the simulation compared to the observed tropical Pacific region. The simulation also captures convectively coupled equatorial waves, including Kelvin waves and easterly waves. Despite the idealization of the aquaplanet setup, the simulated three‐dimensional structure of both groups of waves is consistent with their observed structure as deduced from satellite and reanalysis data. Easterly waves, however, have peak rotation and meridional winds at a slightly higher altitude than in the reanalysis. Future studies may use this simulation to understand how convectively coupled equatorial waves influence the multi‐scale processes leading to tropical cyclogenesis.

Seasonal Predictability of North American Surface Temperature Arises from SST Propagation over the Western Pacific

Abstract The predictability of temperatures in North America is of great importance for local agriculture and human health. In autumn (SON), the temperature in North America is correlated with ENSO, but its predictive skill is limited. Here, we show that spring (MAM) sea surface temperature (SST) anomalies in the southwest Pacific (SWP) exhibit a higher correlation with autumn temperature in North America (r = 0.73) than ENSO. This cross-seasonal and cross-hemispheric relationship is established via the western tropical Pacific (WTP) region. The spring SWP SST anomalies show a cross-hemispheric propagation embedded in the southerly monsoonal flow through the wind–evaporation–SST feedback, which sustains the progression of SST anomalies toward the WTP in autumn. The AGCM simulations from multimodels show that active convection in the WTP caused by SST warming stimulate a Rossby wave train propagating downward to North America, where it is governed by an anomalous high with increased atmospheric thickness and tropospheric temperature. Consequently, the longwave radiative heating over North America is enhanced, raising the surface air temperature. These results indicate that the SWP SST is a useful predictor of North American temperature 6 months in advance through the cross-hemispheric influence. A model based on the spring SWP SST and preceding winter ENSO (Niño-3.4) shows a high predictive skill for the autumn temperature anomalies in North America. Significance Statement Seasonal predictions of surface temperature are important for agricultural decision-making, disaster prevention, and mitigation. Over the western Pacific, associated with the seasonal evolution of ITCZ, there is a strong northward progression of SST anomaly signals generated in the southwest Pacific. This study finds that this cross-hemispheric SST propagation can significantly impact the autumn surface temperature over central North America through the atmospheric bridge. A statistical model incorporating southwest Pacific SST for spring is constructed to predict the North American autumn surface temperature and exhibits high consistency with observations. This improves our understanding of the interhemispheric interactions at seasonal time scales and the seasonal predictability of the North American climate.

Wind and Heat Forcings of the Seasonal and Interannual Sea Level Variabilities in the Southwest Pacific

Abstract Sea level variabilities in the southwest Pacific contribute to the variations of equatorial current bifurcation and the Indonesian Throughflow transport. These processes are closely related to the recharge/discharge of equatorial heat content and dynamic distribution of anthropogenic ocean heating over the Indo-Pacific basin, thus being of profound significance for climate variability and change. Here we identify the major features of seasonal and interannual sea level variabilities in this region, confirming the dominance of the first baroclinic mode in the tropics (contributing 60%–80% of the variances) and higher baroclinic modes in the extratropics (40%–60% of the seasonal variance). Seasonally, except in the western Coral Sea where the Ekman pumping is significant, the wind-driven first-mode baroclinic Rossby waves originating to the east of the date line control the sea level variations over most tropical Pacific regions. In the domain where the 1.5-layer reduced gravity model becomes deficient, the surface heat fluxes dominate, explaining ∼40%–80% of sea level variance. For interannual variability, ∼40%–60% of the variance are El Niño–Southern Oscillation (ENSO) related. The wind-driven Rossby and Kelvin waves east of the date line explain ∼40%–78% of the interannual variance in the tropical Pacific. Outside the tropics, small-scale diffusive processes are presumed critical for interannual variability according to a thermodynamic analysis using an eddy-permitting ocean model simulation. Further process and predictive understandings can be achieved with the coupled climate models properly parameterizing the subgrid-scale processes.

Anthropogenic fingerprints in daily precipitation revealed by deep learning

According to twenty-first century climate-model projections, greenhouse warming will intensify rainfall variability and extremes across the globe1–4. However, verifying this prediction using observations has remained a substantial challenge owing to large natural rainfall fluctuations at regional scales3,4. Here we show that deep learning successfully detects the emerging climate-change signals in daily precipitation fields during the observed record. We trained a convolutional neural network (CNN)5 with daily precipitation fields and annual global mean surface air temperature data obtained from an ensemble of present-day and future climate-model simulations6. After applying the algorithm to the observational record, we found that the daily precipitation data represented an excellent predictor for the observed planetary warming, as they showed a clear deviation from natural variability since the mid-2010s. Furthermore, we analysed the deep-learning model with an explainable framework and observed that the precipitation variability of the weather timescale (period less than 10 days) over the tropical eastern Pacific and mid-latitude storm-track regions was most sensitive to anthropogenic warming. Our results highlight that, although the long-term shifts in annual mean precipitation remain indiscernible from the natural background variability, the impact of global warming on daily hydrological fluctuations has already emerged.

Quantifying the contribution of temperature, salinity, and climate change to sea level rise in the Pacific Ocean: 2005-2019

In recent decades, Pacific Ocean’s steric sea level anomaly (SSLA) has shown prominent patterns among global sea level variations. With ongoing global warming, the frequency and intensity of climate and sea level changes have increased, particularly in the tropical Pacific region. Therefore, it is crucial to comprehend the overall trends and mechanisms governing volumetric sea level changes in the Pacific. To accurately quantify the spatiotemporal evolution characteristics of density-driven sea level change in the Pacific Ocean (PO) from 2005 to 2019, we decomposed temperature and salinity into linear trends, interannual variations, seasonal variations, and residual terms using the STL (seasonal-trend decomposition based on loess) method. To evaluate the influence of ocean temperature, salinity, and climate change on density-driven sea level change and its underlying mechanisms, we decompose temperature as well as salinity changes through into the Heaving (vertical displacements of isopycnal surfaces) and Spicing (density-compensated temperature and salinity change) modes. The findings reveal an average steric sea level rise rate of 0.34 ± 0.16 mm/yr in the PO from 2005 to 2019. Thermosteric sea-level accounts for 82% of this rise, primarily due to seawater temperature rise at depths of 0-700 m caused by Heaving mode changes. Accelerated SSLA increase via the thermosteric effect has been connected to interactions between greater Ekman downwelling from surface winds, radiation forcing linked to global greenhouse gases, and changes in the Pacific warm currents triggered by El Niño-Southern Oscillation (ENSO) episodes. Although salinity is affected by the Subantarctic Mode Water (SAMW) and the Antarctic Intermediate Water (AAIW) in the southern Indian Ocean, however the significance of salinity in sea level change is little compared to the role played by thermocline shift. This study offers a substantial contribution to the field, providing robust data and technical support, and facilitating a deeper understanding of the mechanisms underlying the effects of temperature and salinity on sea level changes during periods of rapid climate change, thus enhancing the accuracy of future predictions regarding sea level rise.

Morphological and molecular analysis of the tropical hermit crab Calcinus vachoni (Decapoda, Diogenidae) and its potential association with colonial anemone.

Calcinus is the colorful hermit crab genus belonging to the family Diogenidae and is often found in coral reefs of the tropical Indo-West Pacific region, including southern Honshu, Japan, which is the northern limit of their occurrence. In the present study, we found C. vachoni for the first time in the intertidal zone of Jeju Island-the southernmost island of South Korea. We examined their morphology and provided a diagnosis of their morphological details with illustrations. In addition, the Korean Calcinus population was genetically characterized using mtDNA cox1 sequences and by placing them into three previously reported regional haplogroups. The phylogenetic tree from maximum likelihood analysis revealed that Korean C. vachoni is assigned to the C. vachoni haplogroups exclusively, one of the three well-supported mitochondrial haplogroups with distinct geographic ranges (i.e., C. vachoni, C. aff. vachoni Cooks, and C. aff. vachoni Mascarenes). This result provides new information on the species distribution of C.vachoni, extending their geographic range further north into the southern coast of Korea. In this study, we also first report the potential association of C. vachoni with their co-occurring colonial anemone species Palythoa aff. mutuki and dead coral head of Pocillopora species based on our on-site observation and a public coral collection database of Calcinus species. However, their ecological association with co-occurring coral species is putatively assumed for now and therefore has to be validated by compelling evidence from further field observation and experimental studies (i.e., whether the presence/absence of colonial anemones affects the behavior and survival of the hermit crabs).