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The real-time monitoring of ocean wave data is a crucial element in marine environmental monitoring and the development of marine resources. It is unfortunate that the majority of wave measurement devices remain challenging, relatively high-priced, and require sophisticated technology. This study investigates the validation of a new type of ocean wave measurement, designed based on the mini wave gauge (MWG), using low-cost materials. The study utilizes an accelerometer sensor, specifically the ADXL335, which is converted to measure wave height, and the GY-271 designed to measure wave direction. This research addresses the validation of MWG by comparing measurements from the acoustic doppler current profiler (ADCP) and HOBO. The validation of wave height demonstrates high accuracy, with a MAPE percentage of 0.46% between MWG and ADCP, and 23.30% between MWG and HOBO. In contrast, the validation of MWG for wave direction by ADCP still requires improvement, with a MAPE of 36.75%. This is due to the sensor's sensitivity to the earth's magnetic field, which requires further improvement of the buoy design to accommodate the direction of incoming waves. Additionally, the MWG's sampling rate in milliseconds allows for analyzing wave characteristics based on wave periods using the fast Fourier transform (FFT) method. [ABSTRACT FROM AUTHOR]

Anthropogenic activities on land will affect the carbon system in coastal waters. This condition will affect the role of coastal waters as a source or sink of carbon. This research will examine the distribution of carbonate systems and estimate CO2 fluxes. Water samples were taken at 30 stations as well as measuring in situ water parameters including pH, temperature, salinity, and pressure. Alkalinity was analysed based on the titration method, chl-a using the fluorometer method, and carbonate system parameters (pCO2(sea) and DIC) calculated using CO2SYS.xlsm. The pCO2(atm) value is calculated based on atmospheric data from satellite data, including the saturation vapour pressure of sea air in the atmosphere, fraction mol of CO2, and sea level pressure. Pearson correlation analysis was used to see the correlation between the measured parameters and CO2 flux. Carbon flux is determined based on the difference between atmospheric and oceanic pCO2. The DIC calculation result was in the range of 1,946.09 µmol/kg - 2,061.65 µmol/kg and the total alkalinity was 2,156.86 µmol/kg - 2,264.71 µmol/kg. Based on this value, Jepara coastal waters have pCO2(sea) of 573,800 micro-atmospheric (µatm) which is higher than pCO2(atm) (i.e., 386,772 µatm). The input of organic/inorganic carbon resulting from anthropogenic processes on land has influenced Jepara coastal waters which act as a source of CO2 into the atmosphere amounting to 103,799 mmol/m2/day. The results of this research can be used as a reference for managing coastal areas to achieve low carbon emissions. [ABSTRACT FROM AUTHOR]

The seas along the Northern Coast of Papua constitute a region with complex oceanographic conditions as they are situated within the Indo-Pacific warm pool (IPWP). The geographical location in the southern hemisphere induces upwelling during the west monsoon season (December-January-February). Additionally, interannual phenomena such as the El Niño Southern Oscillation (ENSO) can impact the intensity of upwelling in these waters. This study aimed to compare the upwelling intensity in the seas along the Northern Coast of Papua during neutral phases and ENSO phases. The main indicators of upwelling are sea surface temperature (SST) and Ekman mass transport (EMT). The data utilized in this study include SST from GHRSST and surface wind from ASCAT. The data processing employed the monthly composite method with spatiotemporal analysis based on anomaly results derived from monthly climatology. The analysis results reveal that El Niño 2015-2016 led to an increase in upwelling intensity ranging from 1.82 to 4.00 m/s², while La Niña 2010-2011 resulted in a weakening of upwelling intensity ranging from 4.95 to 6.56 m/s² in the seas along the Northern Coast of Papua. On the basis of correlation and regression analysis, it can be concluded that offshore EMT significantly influences upwelling anomalies in the southeastern waters, whereas the northwestern waters are more influenced by the shifting IPWP during ENSO. [ABSTRACT FROM AUTHOR]

The fluctuation of suspended particulate matter (SPM) is essential to the biogeochemical cycle and ecological health of coastal waters. Anthropogenic activities potentially trigger an increase in SPM, so it needs to be monitored continuously. Spatial and temporal monitoring of SPM can be carried out cost-effectively with broad coverage using a remote sensing application. This study aims to build the SPM algorithm and estimate its temporal variability. The algorithm model in this study is based on an empirical formula between field data and reflectance data with the same acquisition. Water samples were taken from 100 stations in July 2022. Half were used for model building and the other for model validation. Suspended Particulate Matter was determined gravimetrically and estimated their temporal variability was based on Landsat 9 image records from December 2021 - November 2022. The results of the analysis show that the best algorithm for SPM estimation can be built based on coastal aerosol canals (B1), blue canals (B2), and green canals (B3) with the accuracy test result of (R² = 0.68; RMSE = 5.551 mg.L-1; MAPE= 7.07%; Bias= 0.28). The SPM temporal fluctuations were generally higher in the west monsoon and lowered in the east monsoon, ranging from 30 to 70 mg.L-1. On the other hand, the spatial distribution shows a higher magnitude in the estuary than in the offshore waters, with a deviation of about 30 mg.L-1. Regional authorities can use the results obtained to improve the management of coastal water quality and monitoring systems. [ABSTRACT FROM AUTHOR]

The seas of Southern Java are located at the eastern equatorial Indian Ocean and therefore, they are strongly influenced by the Indian Ocean Dipole (IOD). Strong negative IOD occurred in 2016. However, none of the previous studies investigated its effect on the seas of Southern Java. This study aims to reveal the influence of the strong negative IOD in 2016 on the upwelling intensity along the seas of Southern Java as represented by surface temperature and chlorophyll-a. This research was conducted using satellite-based data and the analysis was based on climatology, and anomaly for 15 years (2007-2021). The data used includes sea surface temperature (OISST), wind (ASCAT), IOD index (DMI), chlorophyll-a (OC-CCI), and sea level anomaly (altimetry). The findings show that the strong negative IOD in 2016 had a significant impact on sea surface temperatures which made these waters warmer. The most visible impact is through the sea surface temperature anomaly map where in 2016 throughout the year it experienced a positive anomaly with a value of 2°C higher than the climatological average. The value of chlorophyll-a in these waters has also dropped drastically which, when viewed from the anomaly map, has a value of 0.2 mg/m³ lower than the climatological average, especially during the upwelling month. This means that, strong negative IOD in 2016 reduced the upwelling intensity along the seas of Southern Java. We also found the propagation of downwelling Kelvin waves from the Indian Ocean to the Southern Java waters which bring warm temperatures and cause downwelling events during the strong negative IOD in 2016 that hampers coastal upwelling along the seas of Southern Java. [ABSTRACT FROM AUTHOR]

Accurate and reliable relative humidity forecasting is of significant importance when evaluating the climate change impacts on humans and ecosystems. However, the complex interactions among geophysical parameters are challenging and may result in inaccurate weather forecasting. This study combines long short-term memory (LSTM) and extreme learning machines (ELM) to create a hybrid model-based forecasting technique to predict relative humidity to improve the accuracy of forecasts. Detailed experiments with univariate and multivariate problems were conducted, and the results show that LSTM-ELM and ELM-LSTM have the lowest MAE and RMSE results compared to stand- alone LSTM and ELM for the univariate problem. In addition, LSTM- ELM and ELM-LSTM result in lower computation time compared to stand-alone LSTM. The experiment results demonstrate that the proposed hybrid models outperform the comparative methods in relative humidity forecasting. We employed the recursive feature elimination (RFE) method and show that dewpoint temperature, temperature, and wind speed are the factors that most affect relative humidity. A higher dewpoint temperature indicates more moisture in the air, which equates to high relative humidity. Humidity levels also rise as the temperature rises. [ABSTRACT FROM AUTHOR]

Research focusing on seagrass ecosystems as carbon storage has been conducted in various Indonesian waters. However, an essential aspect that remains unexplored is the simultaneous analysis of blue carbon storage in seagrass alongside carbon dioxide (CO2) flux values, particularly within Karimunjawa waters. This study aims to assess the organic carbon stock and sea–air CO2 flux in seagrass ecosystems in Karimunjawa. Our hypothesis posits that although seagrass ecosystems release CO2 into the water, their role as blue carbon ecosystems enables them to absorb and accumulate organic carbon within seagrass biomass and sediments. This investigation took place in Karimunjawa waters, encompassing both vegetated (seagrass meadows) and unvegetated (non-seagrass meadows) areas during August 2019, 2020, and 2022. Over this period, the organic carbon stock in seagrass and sediment displayed an increase, rising from 28.90 to 35.70 gCorg m−2 in 2019 and from 37.80 to 45.25 gCorg m−2 in 2022. Notably, the expanse of seagrass meadows in Karimunjawa dwindled by 328.33 ha from 2019 to 2022, resulting in a total carbon stock reduction of the seagrass meadows of 452.39 tC to 218.78 tC. Sediment emerges as a pivotal element in the storage of blue carbon in seagrass, with sedimentary organic carbon outweighing seagrass biomass in storage capacity. The conditions in Karimunjawa, including a high A:B ratio, low dry bulk density, and elevated water content, foster a favorable environment for sediment carbon absorption and storage, facilitated by the waters' CO2 emission during the southeast monsoon season. Notably, our findings reveal that CO2 release within vegetated areas is lower compared to unvegetated areas. This outcome underscores how seagrass ecosystems can mitigate CO2 release through their adeptness at storing organic carbon within biomass and sediment. However, the presence of inorganic carbon in the form of calcium carbonate introduces a nuanced dynamic. This external source, stemming from allochthonous origins like mangroves, brown algae like Padina pavonica, and calcareous epiphytes, leads to an increase in sedimentary organic carbon stock of 53.2 ± 6.82 gCorg m−2. Moreover, it triggers the release of CO2 into the atmosphere, quantified at 83.4 ± 18.26 mmol CO2 m−2 d−1. [ABSTRACT FROM AUTHOR]