Sea Surface Temperature Distribution Research Articles

A framework for reconstructing marine heatwaves from individual foraminifera in sedimentary archives

Marine heatwaves (MHWs) are warm sea surface temperature (SST) anomalies with substantial ecological and economic consequences. Observations of MHWs are based on relatively short instrumental records, which limit the ability to forecast these events on decadal and longer timescales. Paleoclimate reconstructions can extend the observational record and help to evaluate model performance under near future conditions, but paleo-MHW reconstructions have received little attention, primarily because marine sediments lack the temporal resolution to record short-lived events. Individual foraminifera analysis (IFA) of paleotemperature proxies presents an intriguing opportunity to reconstruct past MHW variability if strong relationships exist between SST distributions and MHW metrics. Here, we describe a method to test this idea by systematically evaluating relationships between MHW metrics and SST distributions that mimic IFA data using a 2000-member linear inverse model (LIM) ensemble. Our approach is adaptable and allows users to define MHWs based on multiple duration and intensity thresholds and to model seasonal biases in five different foraminifera species. It also allows uncertainty in MHW reconstructions to be calculated for a given number of IFA measurements. An example application of our method at 12 north Pacific locations suggests that the cumulative intensity of short-duration, low-intensity MHWs is the strongest target for reconstruction, but that the error on reconstructions will rely heavily on sedimentation rate and the number of foraminifera analyzed. This is evident when a robust transfer function is applied to new core-top oxygen isotope data from 37 individual Globigerina bulloides at a site with typical marine sedimentation rates. In this example application, paleo-MHW reconstructions have large uncertainties that hamper comparisons to observational data. However, additional tests demonstrate that our approach has considerable potential to reconstruct past MHW variability at high sedimentation rate sites where hundreds of foraminifera can be analyzed.

MJO Diversity in CMIP6 Models

Abstract Recent studies have shown that individual Madden–Julian oscillation (MJO) events can be categorized into four types based on their propagation characteristics: standing, jumping, slow-propagating, and fast-propagating MJOs. While their structures and impacts are well documented in observations, their representation in state-of-the-art climate models has not been investigated. This study evaluates the four types of MJOs in phase 6 of Coupled Model Intercomparison Project (CMIP6) models. While most models show reasonable MJO propagation characteristics, their performance varies among MJO types, with better performance for the propagating MJO types. To identify the factors that drive each MJO type, background conditions at the surface, troposphere, and stratosphere are examined. We found that the standing and fast MJOs are closely associated with sea surface temperature (SST) and precipitable water (PW) distributions. Specifically, negative and positive SST and PW anomalies are observed over the equatorial Pacific during the standing and fast-propagating MJOs, respectively. In contrast, the jumping and slow-propagating MJOs do not show noticeable SST and PW distributions, suggesting that they may be more strongly influenced by the internal dynamics than by the background conditions. It is further found that the models with more frequent standing MJO than fast MJO generally have stronger negative biases in both SST and PW over the equatorial western Pacific. Although the standing MJO is also preferred when the stratospheric wind at 50 hPa is westerly, such a relationship is absent in the models. These results suggest that MJO diversity in climate models could be improved by better simulation of the mean state, especially for the standing and fast-propagating MJOs.

İskenderun Körfezi kıyı alanlarında sıcaklık ve klorofil-a için uydu ve model temelli veri setlerinin temsil yeteneği üzerine bir değerlendirme

This study investigates the monitoring of sea surface temperature (SST) and chlorophyll-a (chl-a) levels in Iskenderun Bay using satellite and modeling data and evaluates the possible use of these datasets for monitoring marine ecosystems. Datasets derived from MODIS-Aqua satellite imagery and modeling data obtained from the Copernicus MyOcean and in-situ measurements were used in the study. According to the analysis on paried data sets of the distribution of SST and chl-a, sattelite and model datasets showed statistically significant correlations with in-situ measurements for SST. However, only satellite dataset showed significant correlations for Chl-a. Evaluations on uncertainty of the data sets revealed that the satellite dataset had a narrower range and less outlier distribution for SST. For chlorophyll-a, both datasets had wide uncertainty ranges and required further improvement. This study highlights the potential of satellite and model datasets for monitoring SST and chl-a variations in Iskenderun Bay.

The Influence of Large‐Scale Spatial Warming on Jet Stream Extreme Waviness on an Aquaplanet

AbstractThe effect of modified equator‐to‐pole temperature gradients on the jet stream by low‐level polar warming and upper‐level tropical warming is not fully understood. We perform aquaplanet simulations to quantify the impact of different sea surface temperature distributions on jet stream strength, large wave amplitudes and extreme waviness. The responses to warming in the waviness metrics Sinuosity Index and Local Wave Activity are sensitive to the latitude range over which they are calculated. Therefore, we use a latitude range that accurately represents the position of the jet. The uniform warming scenario strengthens the jet and reduces large wave amplitudes. Reductions in meridional temperature gradients lead to weakened mid‐latitudinal jet strength and show significant decreases in large wave amplitudes and jet stream waviness. These findings contradict the mechanism that weakened jet streams increase wave amplitudes and extreme jet stream waviness. We conclude that weakened jet streams do not necessarily become wavier.

A Non-Uniform Grid Graph Convolutional Network for Sea Surface Temperature Prediction

Sea surface temperature (SST) is an important factor in the marine environment and has significant impacts on climate, ecology, and maritime activities. Most existing SST prediction methods consider the ocean as a uniform field and use a uniform grid to predict SST. However, the marine environment is a complex system, and factors such as solar radiation, differences in land and sea thermal properties, and ocean circulation lead to uneven spatial distributions of SSTs. We propose a non-uniform grid construction method based on an SST spatial gradient to encode SST data, as well as a Non-uniform Grid Graph Convolutional Network (NGGCN) model. The NGGCN consists of two spatiotemporal modules, each of which extracts spatial features from the GCN module, captures temporal correlations through the GRU module, and performs feature restoration and output results through the fully connected module. We selected data from the Yellow Sea and Bohai Sea to validate the effectiveness of the NGGCN in predicting SST at different time scales and prediction steps. The results indicate that our model shows a significant improvement in prediction performance compared to other models.

Spatio Temporal Distribution of SST and Chlorophyll a in WPP 718 Waters during the West Season: A Case Study of Merauke Regency Waters, Indonesia

Sea surface temperature (SST) and chlorophyll-a are critical factors for determining oceanographic conditions in water bodies. This research aims to analyze the spatial and temporal distribution of these parameters in the waters of the Merauke region using remote sensing technology. Descriptive methods and remote sensing techniques were used to collect and analyze data from Aqua-MODIS satellite images from December 2022 to February 2023. The results indicate that the waters of Merauke Regency are fertile and warm, with the highest surface temperature recorded in December 2022 (25.0 - 30.0 Celsius). C) and the lowest in January 2023 (25.0 – 28.0 degrees Celsius). Chlorophyll-a concentrations peaked in December 2022 (0.26-5 mg/m3) and were lowest in February 2023 (0.2-2 mg/m3). These results provide valuable insights for fisheries management and environmental monitoring, aiding in the sustainable use of marine.

Determine SST and SSS distribution and tendency of variation in the northern Atlantic Ocean using k-means clustering

Sea surface temperature (SST) and sea surface salinity (SSS) are crucial parameters in oceanographic research and have important implications for understanding the Earths climate system, ecosystems, and global change. This paper will ascertain SSS and SST in the North Atlantic Ocean. Besides, K-means clustering was utilized to separate the data into several clusters once the data were installed in Matlab. According to the research results, the temperature dropped from the equator to the high northern latitudes. In contrast, salinity showed an initial increase and then a following reduction in trend. Despite rising temperatures and salinity, the region distribution of high SST and high SSS throughout the year remained mostly stable, but the area became larger. One of the regions with high salinity in North Africa has a strong connection to that is adjacent to the Mediterranean. The Earths climate system includes essential elements, including SST and SSS, which are essential to the development and control of the climate. Its better to comprehend seasonal changes in climate patterns and long-term climate trends by investigating temperature and salinity.

A quantitative explanation for the large impacts of El Niño during its decaying stage

Abstract This study examines the comparative atmospheric circulation and tropical sea surface temperature (SST) relationships during the developing and decaying stages of El Niño from a meridional structure standpoint. Results indicate a transition in the variability of the first two modes of the Hadley Circulation (HC) during these stages, with the first mode exhibiting a larger explained variance in the decaying stage. The regime change in HC variability corresponds to underlying anomalous SST distributions, as confirmed by sensitive experiments. Quantitative assessment reveals the HC-SST response amplitudes are approximately two times stronger during the decaying stage compared to the developing stage. Employing the Kuo-Eliassen (KE) equation, diabatic heating anomalies during the decaying stage explain the difference in air-sea response intensity between the two stages. Diabatic heating variations are identified as the primary contributor to amplification or reduction of air-sea response intensity during the respective El Niño stages, providing insights into the different air-sea processes throughout the El Niño lifespan.

Revealing Spatial–Temporal Patterns of Sea Surface Temperature in the South China Sea Based on Spatial–Temporal Co-Clustering

To discover the spatial–temporal patterns of sea surface temperature (SST) in the South China Sea (SCS), this paper proposes a spatial–temporal co-clustering algorithm optimized by information divergence. This method allows for the clustering of SST data simultaneously across temporal and spatial dimensions and is adaptable to large volumes of data and anomalous data situations. First, the SST data are initially clustered using the co-clustering algorithm. Second, we use information divergence as the loss function to refine the clustering results iteratively. During the iterative optimization of spatial clustering results, we treat the temporal dimension as a constraint; similarly, during the iterative optimization of temporal clustering, we treat the spatial dimension as a constraint. This is to ensure better robustness of the algorithm. Finally, this paper conducts experiments in the SCS to verify our algorithm. According to the analysis of the experimental results, we have drawn the following conclusions. First, the use of the spatial–temporal co-clustering algorithm reveals that the SST in the SCS exhibits strong seasonal patterns in the temporal clustering results. The spatial distribution of SST varies significantly in different seasons. There is a slight difference in SST between the northern and southern regions of the SCS in winter, but the largest difference is in summer. Second, during ocean anomalies, our proposed algorithm can identify the corresponding abnormal patterns. When ENSO occurs, the seasonal distribution pattern of SST in the SCS is destroyed and replaced by an abnormal temporal pattern. The results indicate that during ENSO events, the SST in specific months in the SCS exhibits a correlation with the SST observed 4–5 months afterward.

Imaging performance prediction of a hypersonic target in a geosynchronous orbit based on multi-dimensional information correlation of radiation, multi-spectral, and polarization

Hypersonic target detection based on infrared intensity characteristics is easily disturbed by sea surface and cloud flares when detected by space-based optical systems, which results in a low detection rate, high false alarm, and difficulty in stable detection. This paper explores a method to improve target detection performance based on the correlation of infrared radiation, multi-spectral and polarization. Firstly, the comprehensive factors that influence complex ambient illumination, atmospheric transmission, and clutter background on spectral-polarization characteristics of hypersonic targets are analyzed. Based on the global radiation scattering theory, the temperature distribution model of the hypersonic target is established by using FLUENT. The polarization emission and pBRDF model of the target is established, and the radiation polarization transfer model is generated. Secondly, the sea surface temperature distribution is obtained by inversion of Landsat8 remote sensing data. The radiation polarization transfer model of the sea surface is established based on the Cox-Munk model combined with pBRDF and the polarization emission model. Thirdly, the polarization scattering effect of atmospheric particles on the upward radiation of the interaction of the target with the sunlight is considered comprehensively, and the 6SV radiative transfer model is used to calculate the polarization effect of atmospheric particles on the upward radiation transmission of the target and the background. Then, combined with the point diffusion of the optical system and the photoelectric conversion of the detector, the multi-dimensional full-chain imaging prediction model of the hypersonic target-sea background-ambient atmosphere-optical system-detector is established. The imaging characteristics and detection performance of the target in different imaging dimensions are simulated and analyzed with the signal-to-clutter ratio (SCR). The research shows that in the direction of reflected sunlight from the sea surface, the sea surface glare is suppressed and the target is highlighted through a target detection method of multi-dimensional information. This method has better detection results than the infrared multi-spectral detection method.

Seasonal Variability of Sea Surface Chlorophyll-a at West Borneo Island

The optimization of marine fisheries activities can be achieved through an understanding of the timing of fishing, access to good information, and knowledge of oceanographic conditions. These conditions often lead to significant nutrient enrichment in the surface layer of the ocean, which in turn increases the sea surface chlorophyll-a (SSC). In the context of the west Borneo Island region, seasonal variability in SSC plays a crucial role in determining potential fishing grounds. The objectives of this study are examining the seasonal variability of SSC, identifying upwelling and downwelling processes through analysis of sea surface wind (SSW), and determining the climatological distribution of Sea Surface Temperature (SST) and sea surface height (SSH) within the water off Labuan Island, Malaysian Borneo, and the Karimata Strait, West Kalimantan, Indonesia. Remote sensing data spanning from 2007 to 2021 were analyzed, encompassing SSC, SST, SSH anomalies, SSW, wind stress curl, and Ekman pumping. Additionally, rainfall and river discharge were examined as supplementary indicators of these oceanographic processes. The findings indicate that SSW plays a pivotal role in driving upwelling and downwelling processes, which in turn influence SSC variability. In Labuan waters, upwelling occurs primarily from November to February, while downwelling predominates from June to September. In contrast, in the Karimata Strait, upwelling is identified from July to September, with downwelling prevalent between March and May. Upwelling events in both regions are characterized by increasing SSC, accompanied by decreasing SST and SSH, while the opposite trends are observed during downwelling events. The peak of rainfall and river discharge in December is noted to potentially enhance SSC variability in the Karimata Strait compared to Labuan Island waters.

Seasonal variations in chlorophyll–a and sea surface temperature in the exclusive economic zone of Sri Lanka

Oceanic phytoplankton plays a crucial role in regulating the biogeochemical cycle in marine ecosystems. Light harvesting pigments such as chlorophyll–a (chl–a) can be used to understand marine primary productivity, especially phytoplankton abundance. Sea surface temperature is closely linked with phytoplankton abundance and climatic changes. The objective of the current study is to determine spatial and temporal variations of chl–a and sea surface temperature and their co-variation, over 12 years using statistical methodologies and Remote Sensing, Geographic Information System (GIS) and Cloud Computing Approach. In this study, the available sea surface temperature and chl–a data acquired from a Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor were proceeded through Google Earth Engine and Earth Science Data System. Data visualization was carried out using ArcMap™ software. Results show a weak negative linear relationship (−0.40, P < 0.05) between sea surface temperature and chl–a. Therefore, additional favorable environmental factors such as coastal upwelling, and nutrient discharge through river run-off can control the primary productivity of phytoplankton. We also illustrated spatial and temporal maps for chl–a and sea surface temperature distribution in the exclusive economic zone of Sri Lanka. Chlorophyll–a concentration is enhanced during the southwest monsoon, and the lowest concentration is observed during the first inter-monsoon period. Next, the highest sea surface temperature is recorded during the first inter-monsoon period, and the lowest sea surface temperature is observed during the northeast monsoon. Seasonal behavior of chl–a concentration and sea surface temperature are changed as chl–a (SWM) > chl–a (NEM) > chl–a (SIM) > chl–a (FIM) and SST (FIM) > SST (SIM) > SST (SWM) > SST (NEM), respectively. In addition, both trend lines for each variable show a positive gradient, which may be attributed to global warming. Finally, we observed the alteration of chl–a and sea surface temperature that linked to changes in ocean chemistry during the global COVID–19 pandemic.

Efficient inference and learning of a generative model for ENSO predictions from large multi-model datasets

Historical simulations of global sea-surface temperature (SST) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) are analyzed. A state-of-the-art deep learning approach is applied to provide a unified access to the diversity of simulations in the large multi-model dataset in order to go beyond the current technological paradigm of ensemble averaging. Based on the concept of a variational auto-encoder (VAE), a generative model of global SST is proposed in combination with an inference model that aims to solve the problem of determining a joint distribution over the data generating factors. With a focus on the El Niño Southern Oscillation (ENSO), the performance of the VAE-based approach in simulating various central features of observed ENSO dynamics is demonstrated. A combination of the VAE with a forecasting model is proposed to make predictions about the distribution of global SST and the corresponding future path of the Niño index from the learned latent factors. The proposed ENSO emulator is compared with historical observations and proves particularly skillful at reproducing various aspects of observed ENSO asymmetry between the two phases of warm El Niño and cold La Niña. A relationship between ENSO asymmetry and ENSO predictability is identified in the ENSO emulator, which improves the prediction of the simulated Niño index in a number of CMIP5 models.

Investigating extreme marine summers in the Mediterranean Sea

Abstract. The Mediterranean Sea (MS) has undergone significant surface warming, particularly pronounced during summers and associated with devastating impacts on marine life. Alongside the ongoing research on warming trends and marine heatwaves (MHWs), here we address the importance of understanding anomalously warm conditions also on the seasonal timescale. We propose the concept of extreme marine summers (EMSs) and investigate their characteristics in the MS, using sea surface temperature (SST) reanalysis data spanning 1950–2020. We define EMSs at a particular location, as the summers with a mean summer SST exceeding the 95th percentile. A marine summer may become extreme, under various SST substructures. Results show that, in most of the basin, EMSs are formed primarily due to the warmer summer days being warmer than normal. Areas where the warmest (coldest) part of the SST distribution is more variable experience EMSs primarily due to the warmest (coldest) part of the distribution being anomalously warm. MHWs occurring within EMSs are more intense, longer lasting, and more frequent than usual mainly in the northern MS regions. These enhanced MHW conditions occur mainly within the warmest part of the SST distribution. By means of temporal coverage of MHW conditions, a more pronounced occurrence of MHWs in EMSs is found for the central and eastern basin where up to 55 % of MHW days over 1950–2020 fall within EMSs. The role of air–sea heat fluxes in driving EMSs is quantified through a newly proposed metric. Results suggest that surface fluxes primarily drive EMSs in the northern half of the MS, while oceanic processes play a major role in southern regions. Upper-ocean preconditioning also contributes to the formation of EMSs. Finally, a detrended dataset was produced to examine how the SST multi-decadal variability affects the studied EMS features. Despite leading to warmer EMSs basin-wide, the multi-decadal signal does not significantly affect the dominant SST substructures during EMSs. Results also highlight the fundamental role of latent heat flux in modulating the surface heat budget during EMSs, regardless of the long-term trends.

Emergent Constraint on Projection of the North Pacific Monsoon Trough and Its Implications for Typhoon Activity Using CMIP6 Models

AbstractThe North Pacific monsoon trough (NPMT) is an imperative large‐scale circulation pattern influencing tropical cyclone (TC) activity in the western North Pacific (WNP), thus its future change has great implications for the WNP TC activity. Here future change in the NPMT and its uncertainty are examined by using 35 climate models from Phase six of Coupled Model Intercomparison Project (CMIP6). Due to the El Niño‐like sea surface temperature (SST) pattern, the multi‐model ensemble (MME) mean projects an eastward extension of the NPMT in the latter half of the 21st century. However, considerable inter‐model uncertainty exists in the projection, which is associated with the diversity in the zonal SST gradient across the tropical Pacific. This diversity in the projected SST is largely rooted in the simulated precipitation biases in the tropical Pacific in the historical experiments of CMIP6 models, which can modulate future Pacific SST distribution through the shortwave‐SST feedback. This linkage between biases in historical climate and future climate allows us to constrain the projection by using observational data sets. Emergent constraint using observational precipitation data set reduces the projection uncertainty by 48% and projects an eastward extension of the north Pacific NPMT by 6.2°. This eastward extension of the NPMT indicates an eastward migration of TC genesis location, and elongated TC track and thus strengthened TC intensity, suggesting an increased TC‐related disaster for residents near the WNP.

Regional Comparison of Performance between EnKF and EnOI in the North Pacific

Abstract The North Pacific is divided into different regions based on ocean currents and sea surface temperature (SST) distribution. Data assimilation is a useful tool for generating accurate ocean estimates because of the limited availability of observational data. This study compared the performances of two data assimilation methods, ensemble optimal interpolation (EnOI) and ensemble Kalman filter (EnKF), in various North Pacific subregions using an ocean model configured with the Regional Ocean Modeling System (ROMS). Both methods assimilated spaceborne SST observations, and the simulation results varied by subregion. The study found that EnKF and EnOI methods performed better than the control model in all regions when compared against satellite SST. EnOI reproduced SST as well as EnKF and required fewer computational resources. However, EnOI performed worse than the control model at sea surface height (SSH) in the equatorial region, while EnKF’s performance improved. This was due to the crushed mean state in the EnOI, which used long-term historical data as an ensemble member. El Niño–Southern Oscillation at the equator drove substantial interannual variability that crushed the ensemble mean of SSH in the EnOI. It is crucial to use a suitable assimilation method for the target area, considering the regional properties of ocean variables. Otherwise, the performance of the assimilated model may be even worse than that of the control model. While EnKF is better suited for regions with high variability in ocean variables, EnOI requires fewer computational resources. Thus, it is crucial to use a suitable assimilation method for accurately predicting and understanding the dynamics of the North Pacific.

Aquaplanet simulations with winter and summer hemispheres: model setup and circulation response to warming

Abstract. To support further understanding of circulation changes in a warming climate, an idealised aquaplanet model setup containing summer and winter hemispheres is presented, and the results of circulation changes under warming are discussed. First, a setup is introduced that enables aquaplanet simulations with a warmer and a colder hemisphere, including realistic-looking summer and winter jet streams, storm tracks, and precipitation patterns that are fairly similar to observations, as well as a more intense and equatorward storm track in the winter compared to the summer hemisphere. The sea surface temperature (SST) distribution used here is inspired by the June–July–August zonal mean SST found in reanalysis data and is flexible to allow control of the occurrence of a single or double intertropical convergence zone (ITCZ). The setup is then used to investigate circulation changes under uniform warming, as motivated by recent research. For example, the stronger poleward shift of the storm tracks during summer compared to winter is reproduced. Furthermore, the jet waviness decreases under warming when compared on isentropes with maximum wind speed or isentropes at similar heights in pressure space. Jet stream waviness increases under warming when compared at similar-valued isentropes but primarily because the corresponding isentrope is closer to the surface in the warmer climate and waviness climatologically increases downwards in the atmosphere. A detailed analysis of the changes in wave amplitude for different wavenumbers confirms that the amplitude of large waves increases with warming, while that of short waves decreases with warming. The reduction in wave amplitude of short synoptic waves is found to dominate in the jet core region, where jet waviness also decreases and is more pronounced on the equatorward side of the jet. Long waves increase in amplitude on the poleward side of the jet and at upper stratospheric levels, which is consistent with increased jet waviness at these levels. The projected increased amplitude of planetary waves and the reduced amplitude of synoptic waves are thus clear in our aquaplanet simulations and do not require zonal asymmetries or regional warming patterns. During so-called high-amplitude wave events, there is no evidence for a preferential phase of Rossby waves of wavenumbers 5 or 7, indicating the crucial role of stationary waves forced by orography or land–sea contrast in establishing previously reported preferential phases. We confirm that feature-based block detection requires significant tuning to the warmer climate to avoid the occurrence of spurious trends. After adjustment for changes in tropopause height, the block detection used here shows no trend in the summer hemisphere and an increase in blocking in the colder hemisphere. We also confirm previous findings that the number of surface cyclones tends to decrease globally under warming and that the cyclone lifetimes become shorter, except for very long-lived cyclones.

On the Role of Wind–Evaporation–SST Feedbacks in the Subseasonal Variability of the East Pacific ITCZ

Abstract The intertropical convergence zone (ITCZ) is a zonally elongated band of near-surface convergence and precipitation near the equator. During boreal spring, the eastern Pacific ITCZ migrates latitudinally on daily to subseasonal time scales, and climate models exhibit the greatest ITCZ biases during this time of the year. In this work, we investigate the air–sea interactions associated with the variability in the eastern Pacific ITCZ’s latitudinal location for consecutive days when the ITCZ is only located north of the equator (nITCZ events) compared to when the ITCZ is on both sides of the equator or south of the equator (dsITCZ events) during February–April. The distribution of sea surface temperature (SST) anomalies and surface latent heat flux (SLHF) anomalies during the nITCZ and dsITCZ events follow the classic wind–evaporation–SST (WES) positive feedback mechanism. However, an alternative mechanism, embracing the effect of SST anomalies on vertical stratification and momentum mixing, gives rise to a negative WES feedback. Our results show that in the surface layer, there is a general progression of positive WES feedbacks happening in the weeks leading to the events followed by negative WES feedbacks occurring after the ITCZ events, with an alternate mechanism involving air–sea humidity differences limiting evaporation occurring in between. Additionally, the spatial structures of the components of the feedbacks are nearly mirror images for these opposite ITCZ events over the east Pacific during boreal spring. In closing, we find that understanding the air–sea interactions during daily to weekly varying ITCZ events (nITCZ and dsITCZ) helps to pinpoint how fundamental processes differ for ITCZs in different hemispheres.

Geospatial analysis for prediction of potential fishing zones in the Banggai Waters using hydroacoustic data and satellite remote sensing

Banggai waters are a strategic area rich in fish resources and a source of livelihood for most of the local population. Mapping fish stocks is important to ensure the sustainability of fishing in the area. One of them uses hydroacoustic data and satellite imagery to provide more comprehensive results on fish stocks and more accurate predictions of potential fishing zones. This study will spatially estimate fish density in Banggai waters using hydroacoustic data and investigate the distribution of chlorophyll-a and sea surface temperature using Himawari-8 imagery. Hydroacoustic data processing will produce target strength (TS) and volume backscatter strength (Sv) values to determine the value and distribution of fish density. Meanwhile, ZPPI results are obtained from the overlay of chlorophyll-a and sea surface temperature. From the results of mapping the potential fishing zone, the high category has the highest percentage of 43%, low 28% and medium 29%. The ZPPI point distribution map then shows the concentration of ZPPI points in the southern Banggai waters. The fish density distribution map shows that the spatial distribution tends to be around the coast of Banggai Peninsula, dominated by small and very small fish categories. Correlation of fish density point distribution with ZPPI results and oceanographic parameters has a positive influence on fish density from GAM modelling.

Analysis of Chlorophyll-A Distribution And Sea Surface Temperature for Estimation of Skipjack Fishing Grounds (Katsuwonus Pelamis) Based on Different Seasons in South Buton Waters

The success of fishing activities is certainly greatly influenced by the conditions of the Fishing Ground (FG). Therefore, information about potential fishing areas is needed by fishermen in fishing activities. Chlorophyll-a is the primary productivity in water. The development of aquatic chlorophyll is influenced by Sea Surface Temperature (SST). The purpose of this study was to analyze the distribution of chlorophyll-a and sea surface temperature (SST) for estimating fish fishing areas based on different seasons in South Buton Waters. This type of research is exploratory research. This study used remote sensing method. The direct interview method with respondents aims to validate data (fishermen) from remote sensing processing. The study used Aqua Modis satellite imagery data to derive parameter values of chlorophyll-a and sea surface temperature. The results of the analysis of the distribution of chlorophyll-a in South Buton waters are the highest with chlorophyll-a concentrations ranging from 0.3-3.0 mg / m³ spread in the waters of Sampolawa and Batauga Districts with surface temperatures ranging from 26 °C and 33 °C. Eastern and Transitional Season II have high levels of chlorophyll-a concentration. This season will be a potential skipjack fishing area in South Buton Waters.