Sea Surface Temperature Distribution Research Articles

THE EFFECT OF THE DISTRIBUTION OF SEA SURFACE TEMPERATURE IN THE INDIAN OCEAN SOUTH OF JAVA ON THE CATCH OF YELLOWFIN TUNA (Thunnus albacares) USING AQUA MODIS SATELLITE IMAGERY

Tuna (Thunnus sp.) is the second largest foreign exchange earner after shrimp. One type of tuna which is an export commodity is yellowfin tuna (Thunnus albacares). Research on the effect of the distribution of sea surface temperature in the Indian Ocean south of Java on the catch of yellowfin tuna (Thunnus albacares) has been carried out at the Nizam Zachman Ocean Fishery Port (PPS) from April 8 to April 30, 2021. This study aims to determine the effect of sea surface temperature (SST) on the catch of yellowfin tuna. The research method used was the method of observation and analysis of satellite imagery. Coordinate data and the number of catches were obtained from the Ocean Fishery Port Logbook (PPS) Nizam Zachman. SPL data obtained from satellite imagery Modis Aqua Level 3. The data was obtained and then analyzed using a simple regression test and the F test results of regression analysis showed that the correlation coefficient (R) of 12.7% and the coefficient of determination (R2) of 1,6% means that 1.6% of yellowfin tuna catches are influenced by SST and 98.4% is influenced by other factors. The F test results show that the SPL significance value is 0.332. The conclusion is that changes in SST have no significant effect on the catch of yellowfin tuna

Prediction of Sea Surface Temperature in the East China Sea Based on LSTM Neural Network

Sea surface temperature (SST) is an important physical factor in the interaction between the ocean and the atmosphere. Accurate monitoring and prediction of the temporal and spatial distribution of SST are of great significance in dealing with climate change, disaster prevention, disaster reduction, and marine ecological protection. This study establishes a prediction model of sea surface temperature for the next five days in the East China Sea using long-term and short-term memory neural networks (LSTM). It investigates the influence of different parameters on prediction accuracy. The sensitivity experiment results show that, based on the same training data, the length of the input data of the LSTM model can improve the model’s prediction performance to a certain extent. However, no obvious positive correlation is observed between the increase in the input data length and the improvement of the model’s prediction accuracy. On the contrary, the LSTM model’s performance decreases with the prediction length increase. Furthermore, the single-point prediction results of the LSTM model for the estuary of the Yangtze River, Kuroshio, and the Pacific Ocean are accurate. In particular, the prediction results of the point in the Pacific Ocean are the most accurate at the selected four points, with an RMSE of 0.0698 °C and an R2 of 99.95%. At the same time, the model in the Pacific region is migrated to the East China Sea. The model was found to have good mobility and can well represent the long-term and seasonal trends of SST in the East China Sea.

Distribution of Skipjack (Katsuwonus Pelamis) Fishing Areas using Purse Seine Fishing Equipment in WPP 573

Estimation of fishing grounds is one solution to facilitate time efficiency in fishing activities. Efforts are made to predict the fishing ground (fishing ground) through an approach to oceanographic physical conditions. The dynamics of skipjack fishing areas are influenced by oceanographic parameters such as sea surface temperature and chlorophyll-a concentration. Skipjack tuna (Katsuwonus pelamis) is the main type of fish caught in Indonesian waters. This study aims to analyze the dynamics of oceanographic conditions in the form of sea surface temperature and chlorophyll-a distribution, the relationship between skipjack fishing season and the dynamics of sea surface temperature distribution and chlorophyll-a distribution in WPP 573 waters 2016-2020 and predict skipjack fishing season.The catch results show that the average SST value obtained from the fishing grounds is 29.44 oC, the minimum value is 26.76 oC and the maximum value is 32.32 oC, while for the concentration of chlorophyll-a the average value obtained is 0.19 mg/ m3, the minimum value is 0.08 mg/m3 and the maximum value is 0.95 mg/m3. The average temperature and chlorophyll-a 2016-2020 that coincided with the high catch were 28.5oC and 0.23 mg/m3. The results of the MaxEnt model show that the evaluation of the model is in a good category, the percentage of SST contribution is higher than Chlorophyll-a, the probability index value for skipjack fish is around 0.5-0.8 and the results of the validation of fishing data are mostly widespread according to the results of the 2016-2020 MaxEnt model. The results also show that the east season, namely June, July and August, is a good fishing season for skipjack tuna, whereas skipjack catches decline in the west season, December, January and February.

Distribution of Chlorophyll-a and Sea Surface Temperature for Skipjack in Nias Water

The fishing area for skipjack is always in a state of change following changes in environmental conditions, which naturally causes fish to choose suitable habitats. Sea surface temperature and chlorophyll-a are factors that affect skipjack fishing areas. The purpose of this study was to look at the potential distribution of sea surface temperature and chlorophyll-a for skipjack fishing areas in the waters of Nias. The data was taken from the Aqua MODIS (Moderate-Resolution Imaging Spectroradiometer) satellite from 2015-2018. Data processing is divided into three seasons, namely transitional season I, east season, and transitional season II. The results showed that the waters of Nias have an average sea surface temperature of 29.40°C – 31.05°C with an average chlorophyll-a ranging from 0.108 mg/m3 – 0.146 mg/m3. Based on the analysis of sea surface temperature and chlorophyll-a, the potential fishing area is assumed to be in transition II with an average seasonal catch of 2497.8 kg with a potential temperature range of 29.73°C and a range of chlorophyll-a the potential is 0.14 mg/m3.

Cause of the Intense Tropics-Wide Tropospheric Warming in Response to El Niño

Abstract During El Niño events, a strong tropics-wide warming of the free troposphere is observed (of order 1 K at 300 hPa). This warming plays an important role for the teleconnection processes associated with El Niño but it remains unclear what initiates this warming. Since convective quasi-equilibrium only holds in regions of deep convection, the strong free-tropospheric warming implies that the warmest surface waters (where atmospheric deep convection occurs) must warm during El Niño. We analyze the evolution of the oceanic mixed layer heat budget over El Niño events as function of sea surface temperature (SST). Data from the ERA5 and an unforced simulation of a coupled climate model both confirm that SSTs during an El Niño event increase at the high end of the SST distribution. The data show that this is due to an anomalous heat flux from the atmosphere into the ocean caused by a decrease in evaporation due anomalously weak low-level winds (i.e., relative to the wind speed observed in the domain of deep convection in the climatological base state). It is hypothesized that the more zonally symmetric circulation during El Niño is responsible for the weakening of low-level winds. The result of a substantial heat flux into the ocean in the domain of atmospheric deep convection (the opposite of the canonical heat flux out of the ocean into the atmosphere observed in the cold eastern Pacific) caused by a decrease in low-level wind speed implies that the prominent tropospheric warming results from mechanical forcing.

Potential Efficiency of Earth Observation for Optimum Fishing Zone Detection of the Pelagic Sardinella aurita Species along the Mediterranean Coast of Egypt

This research utilizes the efficiency of remotely sensed data and advanced digital image processing techniques to assist in monitoring for the management of marine fisheries in Egypt (south Mediterranean Sea region). A newly developed model is applied to the Sardinella aurita fisheries to determine optimal fishing zones, and is then applied to monitor and detect the potentially optimal fishing zones for other locally important and economic fish species. This approach depends on chlorophyll-a (Chl-a) and sea-surface temperature (SST) characteristics that are that known to control this species communities. The ranges and distribution of SST and Chl-a were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) aqua as well as Sentinel-3 satellites during the period from 2018 to 2020. The results revealed that there is a strong link between Sardinella abundance and both the SST and the Chl-a concentration. The suitable months for the abundance of this pelagic fish species were defined to be from May to November, producing 75% of the catch (nearly 42 K tons). Low abundances were recorded during the months from December to April, below the suitable harvest levels for this species. This research highlighted the importance of using satellite data as a tool to help scientists to develop appropriate management strategies for the sustainable management of fisheries resources worldwide.

Sea Surface Temperature (SST) and Rainfall Trends in the Singapore Strait from 2002 to 2019

Studying Singapore Strait waters condition as a form of maritime mitigation is necessary because it is an international shipping lane. The dominant weather changes include rainfall, wind flows, and sea surface temperature (SST). This study aims to reveal the relationship between rainfall and SST activity in the Singapore Strait for over 18 years, from 2002 to 2019. The results showed a negative correlation, where the SST decreases as rainfall increases and vice versa. In addition, the high rainfall and low SST distribution occur in the Western season (December–February). The low rainfall intensity and high (warm) SST distribution occur yearly in the transition from West to East (March–August). Also, the distribution pattern is influenced by rainfall intensity and the water mass from the South China Sea and the Malacca Strait, where the strait is a mixture of these masses. The neural network model confirmed the negative correlation. Hence a small change in SST causes rainfall if it is cooler, and less precipitation if warmer.

Monitoring the Seasonal Distribution and Variation of Sea Surface Temperature and Chlorophyll Concentration in Bay of Bengal using MODIS Satellite Images

Using MODIS Global Satellite products from 2016 to 2020, the variance in sea surface temperature (SST) and chlorophyll concentrations in the waters of the Bay of Bengal (BoB) is investigated during this study. Seasonal maps prepared from the monthly average of SST are compared to observe the change throughout the timeframes of spring, summer, autumn, and winter. The annual cycle of SST depicts the phases of cooling in winter, heating in summer, and warming in spring. It has been found that the presence of heated pools (SST > 30°C) prolongs the summer endurance within the Bay in summer. The SST variations are also strongly linked to regional-scale climate variations from late winter to early spring. Anomalies in chlorophyll are often considered early indicators and drivers of changes in marine resources. However, there has been little assessment of the abnormality in this component in coastal waters of the BoB. The measured chlorophyll distribution during the study reveals anomalies consistent in magnitude having a prominent north-south gradient, where the greater concentrations lie in the northern part. In addition, the fluvial input provided in the central part of the Bay by the Ganges-Brahmaputra-Meghna River system during monsoon contributes additional credence to this assertion.

SKIPJACK TUNA FISHING SEASON AND ITS RELATIONSHIP WITH OCEANOGRAPHIC CONDITIONS IN PALABUHANRATU WATERS, WEST JAVA

Skipjack tuna (Katsuwonus pelamis) is the main catch species in Indonesian Palabuhanratu waters. The dynamics of skipjack fishing areas are influenced by oceanographic parameters such as sea surface temperature and chlorophyll-a concentration. This study aims to predict the skipjack fishing season, analyze the dynamics of oceanographic conditions, especially the distribution of sea surface temperature and the distribution of chlorophyll-a, and determine the relationship between skipjack fishing season and the dynamics of the distribution of sea surface temperature and the distribution of chlorophyll-a in the waters of Palabuhanratu, West Java. Catch per unit effort analysis was used to determine the fishing season index, while the dynamics of sea surface temperature and distribution of chlorophyll-a were analyzed from MODIS image data. The results showed that skipjack fishing season in Palabuhanratu waters was from July to November. Monthly sea surface temperatures range from 26-30℃ with an average value of 29℃. The distribution value of chlorophyll-a concentration ranged from 0.09 mg/m3 to 0.51 mg/m3 with an average value of 0.23 mg/m3. Skipjack tuna production tends to increase when sea surface temperatures are low and chlorophyll-a concentrations increase.

Distribution of Chlorophil-A and Sea Surface Temperature (SST) on Operation of Payang Catching Equipment in Gorontalo Bay Waters

This research was carried out in January - August 2020 with the aim of looking at the temporal and spatial distribution of Chlorophyll-a (CHL-a) and Sea Surface Temperature (SST) in the waters of Gorontalo Bay, their effect on payang catches. The data used in the form of field data and image data were analyzed by descriptive analysis and analysis of Geographic Information Systems (GIS). Based on the results of the study, it was found that the existence of payang fishing gear in Gorontalo Bay is in an area that has a high chlorophyll content between the West Season, West-East Transition Season and East Season. The highest average payang catch was found in the West-East transition season compared to other seasons. The West-East transition season has sea surface temperatures between 30.64°C-30.99°C while the density of chlorophyll-a is 0.1701 mg/m3-0.1925 mg/m3.

STUDY OF SNPP-VIIRS SATELLITE IMAGE FOR ESTIMATION SURFACE GILL NETS FISHING GROUND IN SEMARANG WATERS, CENTRAL JAVA, INDONESIA

Gillnet fishermen in Semarang often have difficulty determining the fishing grounds. The aims of the study were to analysed the spatial and temporal distribution of sea surface temperature (SST) and chlorophyll-a, to analysed the relationship between variables and to study the estimation of fishing grounds. The data collection method used purposive sampling. Map processing using the Inverse Distance Weighted (IDW) method. The data processing method uses normality test, classical assumption test and linear regression test. Analysis of image data spatially (4 miles from the shoreline) and temporally (west, east and transition monsoons). SST and chlorophyll-a tend to be high near the shore. The lowest SST (28.82OC) and the highest chlorophyll-a (5.11 mg/L) occurred in the east monsoon. The highest SST (31.74OC) and the lowest chlorophyll-a occurred in the west monsoon (1.31 mg/L). SST and chlorophyll-a have an erratic distribution pattern during the transitional monsoon. The value of SST and chlorophyll-a correlation partially to catch was 14.3% (weak) and 74% (very strong). The correlation value of SST to chlorophyll-a is 30.2% (medium). The correlation value of SST and chlorophyll-a simultaneously with catch is 75.3% (very strong). Determination of fishing areas based on high chlorophyll-a1 values and low SST. The coordinates for determining the fishing ground include 6° 53' 24,858" South Latitude 110° 26' 0.071" east west monsoon, 6° 55' 43,941" LS 110° 24' 47,903" east longitude transitional monsoon I, 6° 55' 29,439" latitude 110° 25' 54,790" east longitude, and 6° 55' 11,394" latitude 110° 26' 15,904" east longitude of transitional monsoon II.

Hubungan Klorofil-a dan Suhu Permukaan Laut (SPL) Terhadap Hasil Tangkapan Ikan Lemuru Sardinella lemuru di Selat Bali Menggunakan Citra Aqua MODIS Tahun 2009-2018

Oceanographic parameters such as sea surface temperature (SST) and chlorophyll-a in the water can influence the productivity of pelagic fish such as Lemuru. Many studies have been conducted on the relationship between SST and chlorophyll-a and the fluctuations in the catch of Lemuru fish, especially using satellite databased sensing technology. Most of the research using satellite data is done in a short-term period (not climatology), so there are still a lot of unanswered questions. One of them is: how the correlation between the fluctuation in the number of Lemuru fish catches is related to SST and chlorophyll-a in the ENSO and IOD periods. The purpose of this study is to determine the distribution of SST and chlorophyll-a concentrations and their relationship with the yield of Lemuru fish catches in the Bali Strait from 2009 to 2018. Aqua Moderate Imaging Spectroradiometer (MODIS) satellite data level 2 from Oceancolor and data on the number of fish caught in the Bali Strait from the National Fisheries Port (PPN) Pengambengan and UPT PPP Muncar. The method is used with correlation analysis between SST and chlorophyll-a to the number of Lemuru fish caught. The monthly average SST in Bali Strait waters from 2009 to 2018 was approximately 24,76 0C-30, 11 0C, with an estimated monthly chlorophyll-a concentration of 0,10 mg/m3-3,68 mg/m3. The spatial distribution of SST tends to be low in the southern Bali Strait and tends to be high in the northern Bali Strait. The spatial distribution of chlorophyll-a appears to have a high value in the near land area. The cross-correlation test between chlorophyll-a and the number of Lemuru catches showed a positive correlation yield at the 4th month lag. While the correlation of SST to the number of Lemuru fish catches shows a positive correlation at lag (-1).

Testing the effect of bioturbation and species abundance upon discrete-depth individual foraminifera analysis

Abstract. We used a single foraminifera enabled, holistic hydroclimate-to-sediment transient modelling approach to fundamentally evaluate the efficacy of discrete-depth individual foraminifera analysis (IFA) for reconstructing past sea surface temperature (SST) variability from deep-sea sediment archives, a method that has been used, amongst other applications, for reconstructing El Niño–Southern Oscillation (ENSO). The computer model environment allows us to strictly control for variables such as SST, foraminifera species abundance response to SST, as well as depositional processes such as sediment accumulation rate (SAR) and bioturbation depth (BD) and subsequent laboratory processes such as sample size and machine error. Examining a number of best-case scenarios, we find that IFA-derived reconstructions of past SST variability are sensitive to all of the aforementioned variables. Running 100 ensembles for each scenario, we find that the influence of bioturbation upon IFA-derived SST reconstructions, combined with typical samples sizes employed in the field, produces noisy SST reconstructions with poor correlation to the original SST distribution in the water. This noise is especially apparent for values near the tails of the SST distribution, which is the distribution region of particular interest in the case of, e.g. ENSO. The noise is further increased in the case of increasing machine error, decreasing SAR and decreasing sample size. We also find poor agreement between ensembles, underscoring the need for replication studies in the field to confirm findings at particular sites and time periods. Furthermore, we show that a species abundance response to SST could in theory bias IFA-derived SST reconstructions, which can have consequences when comparing IFA-derived SST distributions from markedly different mean climate states. We provide a number of idealised simulations spanning a number of SAR, sample size, machine error and species abundance scenarios, which can help assist researchers in the field to determine under which conditions they could expect to retrieve significant results.

Study of surface and vertical sea temperatures during the process of tropical cyclone formation in the territory of Indonesia (case study 2019-2021)

A tropical cyclone is an atmospheric phenomenon that has a system of low air pressure that forms over the oceans in the warm tropics. Tropical cyclones can form in oceans with sea surface temperatures above 26.5°C. In addition to the sea surface temperature which must be more than 26.5°C, the depth of warm sea water temperature strongly supports the formation of tropical cyclones in the territory of Indonesia. In this study, research was conducted on the surface and vertical temperatures of the sea during the formation of tropical cyclones or when cyclone seeds occurred in the case of tropical cyclones that occurred in 2019-2021 in the territory of Indonesia. The data used is processed using Ocean Data View 4.1 to determine the distribution of surface and vertical sea temperatures. Based on the results on this study, the vertical distribution of sea surface temperatures during the formation of tropical cyclones in Indonesia has an average sea temperature higher than 26.5°C which reaches a depth of 64 meters to 70 meters. Then the sea surface temperature during the tropical cyclone formation process averaged 28 °C to 29 °C.

Immense variability in the sea surface temperature near macro tidal flat revealed by high-resolution satellite data (Landsat 8)

Sea surface temperature (SST) is crucial for understanding the physical characteristics and ecosystems of coastal seas. SST varies near the tidal flat, where exposure and flood recur according to the tidal cycle. However, the variability of SST near the tidal flat is poorly understood owing to difficulties in making in-situ observations. The high resolution of Landsat 8 enabled us to determine the variability of SST near the macro tidal flat. The spatial distribution of the SST extracted from Landsat 8 changed drastically. The seasonal SST range was higher near the tidal flat than in the open sea. The maximum seasonal range of coastal SST exceeded 23 °C, whereas the range in the open ocean was approximately 18 °C. The minimum and maximum horizontal SST gradients near the tidal flat were approximately − 0.76 °C/10 km in December and 1.31 °C/10 km in June, respectively. The heating of sea water by tidal flats in spring and summer, and cooling in the fall and winter might result in a large horizontal SST gradient. The estimated heat flux from the tidal flat to the seawater based on the SST distribution shows seasonal change ranging from − 4.85 to 6.72 W/m2.

Validation of satellite-based sea surface temperature products against in situ observations off the western coast of Sumatra

This study validated the sea surface temperature (SST) datasets from the Group for High-Resolution SST Multi Product Ensemble (GMPE), National Oceanic and Atmospheric Administration (NOAA) Optimal Interpolation (OI) SST version 2 and 2.1 (OIv2 and OIv2.1), and Estimating the Circulation and Climate of the Ocean, Phase II (ECCO2) in the area off the western coast of Sumatra against in situ observations. Furthermore, the root mean square differences (RMSDs) of OIv2, OIv2.1, and ECCO2 were investigated with respect to GMPE, whose small RMSD < 0.2 K against in situ observations confirmed its suitability as a reference. Although OIv2 showed a large RMSD (1–1.5 K) with a significant negative bias, OIv2.1 (RMSD < 0.4 K) improved remarkably. In the average SST distributions for December 2017, the differences among the 4 datasets were significant in the areas off the western coast of Sumatra, along the southern coast of Java, and in the Indonesian inland sea. These results were consistent with the ensemble spread distribution obtained with GMPE. The large RMSDs of OIv2 corresponded to high clouds, and it was suggested that the change in the satellites used for SST estimation contributed to the improvement in OIv2.1.

Changes in the Eastward Movement Speed of the Madden–Julian Oscillation with Fluctuation in the Walker Circulation

Abstract The eastward movement of a convectively active region is a distinguishing characteristic of the Madden–Julian oscillation (MJO). However, knowledge about the mechanisms that determine the eastward movement speed remains limited. This study investigates how the background environment modulates the speed of the boreal winter MJO and describes an intrinsic relationship between the MJO and background atmospheric circulation. We calculated the speed of the MJO events from the daily tracking of the locations of the minimum values of the outgoing longwave radiation anomaly in the time–longitude space. These speeds were then used to analyze systematic differences in the sea surface temperature (SST) distribution associated with the MJO speed. The analysis revealed a deceleration of the MJO under low-frequency (&gt;90 days) SST distributions that increased toward the western Pacific from both the Indian Ocean and the eastern Pacific. In contrast, the dependency on SST variability in intraseasonal frequencies (20–90 days) was small. Subsequently, the relationship between the MJO speed and background circulation, which is largely determined by the lower boundary condition set by the low-frequency SST distribution, was analyzed. The analysis counterintuitively revealed that the MJO tends to decelerate when the large-scale zonal circulation with low-level westerlies and upper-level easterlies from the Indian Ocean to the Maritime Continents is strong. The results suggest a novel view that the MJO is an integral component of the Walker circulation and that its eastward movement is modulated by the state of the large-scale flow of the Walker circulation.

A study of sea surface temperature effect on purse seine catch in Aceh North Waters, Indonesia

Aceh fishermen in Ocean Fishing Port Kutaraja Banda Aceh generally carry out fishing operations around Aceh North waters which have abundant and diverse biological potential. Catches in Aceh North waters are still heavily influenced by several natural factors that often occur in certain seasons, one of which is the factor of Sea Surface Temperature (SST) based on this research about the effect of SST on purse seine catches based in Kutaraja Banda Aceh Ocean Fishery Port. This study aims to determine the catches of purse seine fishermen in Kutaraja Ocean Fishery Port to know the SST distribution, and to determine the effect of SST on purse seine catches based in Kutaraja Banda Aceh Ocean Fishery Port. This research was conducted in November 2019 at Kutaraja Ocean Fishery Port. Data analysis used in this study is purse seine catch data obtained from UPTD from 2015-2019 tabulated in tabular and graphical format, SST distribution obtained from Aqua-MODIS satellites from 2015-2019 using SeaDas software and analysis used to see the effect of SST on catch is using linear regression analysis. The conclusian is based on the results of studies on how ocean SPL affect the fish catches using purse seine with the highest vessel size of 11-20 GT in 2018 with a total of 2,499,634 kg while the lowest catch in 2016 with a total of 1,460,220 kg. SST distribution found in Aceh North waters shows that the highest temperature occurred in 2015 which was 30.24oC while the lowest occurred in 2016 which was 29.04oC. From linear regression analysis results showed that SST in Aceh North waters showed a coefficient of determination (R²) of 0.2279. This value can give a picture that the SST parameters contribute to fish catches of 22.79% and the rest is influenced by other oceanographic factors. While the correlation coefficient (r) of 0.477 means that this condition can indicate sufficient correlation have a positive

Mapping potential fishing zones based on sea surface temperature and Chlorophyll-A in the Waters of Aceh Besar, Indonesia

Utilization of potential fishery and marine resources is still not maximally used by fishermen. Sea surface temperatures and the spread of chlorophyll-a through remote sensing systems can be used as potential fishing zones. This study aims to determine potential fishing zones using geographic information systems through the distribution of sea surface temperatures and the value of chlorophyll-a concentrations in Aceh Besar waters which is expected to improve the sustainability of fishing efforts. This research was conducted in January-December 2019 using geographic information system by extracting from Aqua-MODIS satellite image with resolution of 4 km and sea surface temperature overlay method with chlorophyll-a concentration. The results found the highest sea surface temperature value was in April at 31.62°C and the lowest temperature was in December at 28.45°C. The highest average chlorophyll-a concentration in Aceh Besar waters was 1.53 mg/m3 in December and the lowest concentration of chlorophyll-a in June and September was 0.20 mg/m3. Suspected potential fishing zones during January to December 2019 were found as many as 62 potential fishing zones, namely in the Western, Northwest and Eastern waters of Aceh Besar. The most zones are in December as many as eight zones, namely in the Western, Northwest and East parts of Aceh Besar waters and the least found in July as many as one zone that is in the Western part of Aceh Besar waters. When compared to fishing operations areas, the potential fishing zone is in the western part of Aceh Besar waters.

Emergent Constraints on Future Expansion of the Indo‐Pacific Warm Pool

AbstractThe latest climate models realistically simulate the present‐day climate Indo‐Pacific Warm Pool (IPWP) area, but there is considerable inter‐model spread in future projections. Here we show a strong negative relationship between the present‐day of IPWP area and its future change. When using this “emergent relationship” to constrain future IPWP area change, inter‐model spread of future projections is reduced by more than half compared to raw projections. This emergent constraint is found to be due to the negatively skewed distribution of sea surface temperature (SST) over the Indo‐Pacific Ocean as well as a negative SST‐shortwave radiation feedback in the western Pacific, which leads to a large IPWP expansion in climate models having a small IPWP area in the present‐day climate. This result indicates that a more accurate simulation of the IPWP area in the present‐day climate is crucial to reliable future projections of the tropical climate.