scholarly journals VERIFICATION OF PISCES DISSOLVED OXYGEN MODEL USING IN SITU MEASUREMENT IN BIAK, ROTE, AND TANIMBAR SEAS, INDONESIA

2017 ◽  
Vol 14 (1) ◽  
pp. 37 ◽  
Author(s):  
Armyanda Tussadiah ◽  
Joko Subandriyo ◽  
Sari Novita ◽  
Widodo Setyo Pranowo
Keyword(s):  
Standard Deviation ◽  
Linear Regression ◽  
Dissolved Oxygen ◽  
Primary Data ◽  
Biogeochemical Model ◽  
Infrastructure Development ◽  
Indonesian Seas ◽  
In Situ Data ◽  
A Minor

Dissolved oxygen (DO) is one of the most chemical primary data in supported life for marine organisms. Ministry of Marine Affairs and Fisheries Republic of Indonesia through Infrastructure Development for Space Oceanography (INDESO) Project provides dissolved oxygen data services in Indonesian Seas for 7 days backward and 10 days ahead (9,25 km x 9.25 km, 1 daily). The data based on Biogeochemical model (PISCES) coupled with hydrodynamic model (NEMO), with input data from satellite acquisition. This study investigated the performance and accuracy of dissolved oxygen from PISCES model, by comparing with the measurement in situ data in Indonesian Seas specifically in three outermost islands of Indonesia (Biak Island, Rote Island, and Tanimbar Island). Results of standard deviation values between in situ DO and model are around two (St.dev ± 2). Based on the calculation of linear regression between in situ DO with the standard deviation obtained a high determinant coefficient, greater than 0.9 (R2 ≥ 0.9). Furthermore, RMSE calculation showed a minor error, less than 0.05. These results showed that the equation of the linear regression might be used as a correction equation to gain the verified dissolved oxygen.

scholarly journals MODIS STANDARD (OC3) CHLOROPHYLL-A ALGORITHM EVALUATION IN INDONESIAN SEAS

2017 ◽  
Vol 11 (1) ◽  
pp. 11
Author(s):  
Gathot Winarso ◽  
Yennie Marini
Keyword(s):  
Pacific Ocean ◽  
Research And Development ◽  
Chlorophyll A ◽  
A Algorithm ◽  
Concentration Data ◽  
Indonesian Seas ◽  
In Situ Data ◽  
The North ◽  
Level 2

The MODIS-estimated chlorophyll-a information was widely used in some operational application in Indonesia. However, there is no information about the performance of MODIS chlorophyll-a in Indonesian seas and there is no data used in development of algorithm was taken in Indonesian seas. Even the algorithm was validated in other area, it is important to know the performance of the algorithm work in Indonesian seas. Performance of MODIS Standard (OC3) algorithm at Indonesian seas was analyzed in this paper. The in-situ chlorophyll-a concentration data was collected during MOMSEI (Monsoon Offset Monitoring and Its Social and Ecosystem Impact) 2012 Cruise 25th April – 12th   May 2012 and also from archived data of the Research and Development Center for Marine Coastal Resources, Agency of Marine and Fisheries Research and Development, Indonesian Ministry of  Marine Affairs and Fisheries. The in-situ data used in this research is located in Indian Ocean the west of Sumatera part and Pacific Ocean the north of Papua Province part. Satellite data which is used is Ocean Color MODIS Level-2 Product that downloaded from NASA and MODIS L-0 from LAPAN Ground Station. MODIS Level 0 from LAPAN then processed to Level-2  using latest SeaDAS Software. The match-up resulted the MNB(%) is -4.8% that means satellite-estimated was underestimate in 4.8 % and RMSE is 0.058. When the data was separated following to the data source, the correlation and trend line equation became better. From MOMSEI Cruise data, the MNB(%) was -18.8% and RMSE 0.05. From Pacific Ocean Data, MNB (%) was -27 % and RMSE 0.049. From SONNE Cruise 2005, MNB (%) was -27 % and RMSE 0.049. MODIS standard algorithm is work well in Indonesia case-1 seawaters, which contain chlorophyll-a only, and derived that influence to the electromagnetic wave.

Application of a SEEK filter to a 1D biogeochemical model of the Ligurian Sea: Twin experiments and real in-situ data assimilation

2007 ◽  
Vol 65 (1-4) ◽  
pp. 561-583 ◽  
Author(s):  
C. Raick ◽  
A. Alvera-Azcarate ◽  
A. Barth ◽  
J.M. Brankart ◽  
K. Soetaert ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Biogeochemical Model ◽  
Ligurian Sea ◽  
In Situ Data

scholarly journals Dissolved oxygen variability of Indonesian seas over decades as detected by satellite remote sensing

2021 ◽  
Vol 925 (1) ◽  
pp. 012003
Author(s):  
K Triana ◽  
A J Wahyudi
Keyword(s):  
Remote Sensing ◽  
Dissolved Oxygen ◽  
Satellite Remote Sensing ◽  
Potential Temperature ◽  
Seasonal Patterns ◽  
Indonesian Seas ◽  
Variability Analysis ◽  
Arafura Sea

Abstract The dissolved oxygen (DO) decrease in the ocean is a notable issue because of its potential impacts on marine biogeochemical cycles and ecosystem services. Satellite remote sensing application to support in-situ measurement is a time and cost-saving on wide scales DO monitoring. This study aims to determine the DO variability from 1993 to 2020, identify the potential areas to experience deoxygenation, and investigate the correlation between DO and other ocean parameters in Indonesian seas. The validation between in-situ and satellite-derived DO shows the determination coefficient of 0.73, indicating the satellite dataset reliability for the entire analysis. The multiple regression analysis among the long-term satellite-derived ocean parameters shows that the in-situ DO can be estimated by the combination of the potential temperature, total chlorophyll-a, and salinity. The potential temperature was statistically identified as the parameter with the highest correlation and influence on DO. The results of DO variability analysis show the overall decreasing trend with significant decreases in 1998, 2010, and 2016. There is a distinct difference in DO’s seasonal patterns in the southwestern and northeastern regions. The potential of ocean deoxygenation is detected in western Sumatra waters and the Arafura Sea at the 200–1,000 meters depth.

scholarly journals Hydrodynamic and Biochemical Impacts on the Development of Hypoxia in the Louisiana–Texas Shelf Part I: Numerical Modeling and Hypoxia Mechanisms

2022 ◽  
Author(s):  
Yanda Ou ◽  
Z. George Xue
Keyword(s):  
Dissolved Oxygen ◽  
Three Dimensional ◽  
Biogeochemical Model ◽  
The West ◽  
Frequency Distributions ◽  
In Situ Data ◽  
Hypoxic Area ◽  
Water Stratification ◽  
Do Concentration ◽  
Hypoxic Volume

Abstract. A three-dimensional coupled hydrodynamic–biogeochemical model with N, P, Si cycles and multiple phytoplankton and zooplankton functional groups was developed and applied to the Gulf of Mexico to study bottom dissolved oxygen dynamics. A 15-year hindcast was achieved covering the period of 2006–2020. Extensive model validation against in situ data demonstrates that the model is capable of reproducing vertical distributions of dissolved oxygen (DO), frequency distributions of hypoxia thickness, spatial distributions of bottom DO concentration and interannual variations of hypoxic area. The impacts of river plume and along-shore currents on bottom DO dynamics were examined based on multiyear bottom DO climatology, the corresponding long-term trends, and interannual variability. Model results suggest that mechanisms of bottom hypoxia developments are different between the west and east Louisiana–Texas Shelf waters. The mid-Atchafalaya nearshore (10–20 m) region firstly suffers from hypoxia in May, followed by the west-Mississippi nearshore region in June. Hypoxic waters expand in the following months and eventually merge in August. Sediment oxygen consumption (SOC) and water stratification (measured by potential energy anomaly, PEA) are two main factors modulating the variability of bottom DO concentration. Generalized Boosted Regression Models provide analysis of the relative importance of PEA and SOC. The analysis indicates that SOC is the main regulator in nearshore regions, and water stratification outcompetes the sedimentary biochemical processes in the offshore (20–50 m) regions. A strong quadratic relationship was found between hypoxic volume and hypoxic area, which suggests that the volume mostly results from the low DO in bottom water and can be potentially estimated based on the hypoxic area.

scholarly journals A New Approach to Defining Uncertainties for MODIS Land Surface Temperature

2019 ◽  
Vol 11 (9) ◽  
pp. 1021 ◽  
Author(s):  
Darren Ghent ◽  
Karen Veal ◽  
Tim Trent ◽  
Emma Dodd ◽  
Harjinder Sembhi ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Uncertainty Budget ◽  
In Situ Data ◽  
Uncertainty Model ◽  
Absolute Bias ◽  
Moderate Resolution Imaging Spectroradiometer

The accuracy of land surface temperature (LST) observations is critical to many applications. Any observation of LST is subject to incomplete knowledge, so an accurate assessment of the uncertainty budget is critical. We present a comprehensive and consistent approach to determining an uncertainty budget for LST products. We apply this approach to the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on-board the Aqua satellite. In order to generate the uncertainty model, a new implementation of the generalised split-window algorithm is applied, in which retrieval coefficients are categorised by viewing angle and water vapour. Validation of the LST against in situ data shows a mean absolute bias of 0.37 K for daytime and 0.73 K for nighttime. The average standard deviation per site is 1.53 K for daytime and 1.21 K for nighttime. Uncertainties from the implemented model are estimates in their own right and are also validated. We do this by comparing the standard deviation of the differences between the satellite and in situ LSTs, and the total uncertainties of the validation matchups. We show that the uncertainty model provides a good fit. Our approach offers a framework for quantifying uncertainties for LST that is equally applicable across different sensors and different retrieval approaches.

scholarly journals IMPACT OF THE PANDEMIC COVID-19 TO THE INDONESIA SEAS

2022 ◽  
Vol 40 (1) ◽  
pp. 30-36
Author(s):  
Yudi N. IHSAN ◽  
◽  
Noir P. PURBA ◽  
Ibnu FAIZAL ◽  
Agnes ANYA ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Atmospheric Conditions ◽  
Economic Shocks ◽  
Indonesian Seas ◽  
In Situ Data ◽  
Noise Observation

This paper presents the effect of the COVID-19 pandemic on the Indonesian seas from April to October 2020. Data were mainly obtained through literature studies focusing on coastal and ecosystem services, noise observation in the ocean, and in-situ data for atmospheric conditions. The results of this study found that the pandemic has given the oceans and ecosystems time to recover from anthropogenic stresses even though the tourism and fisheries sectors have experienced strong economic shocks. A decrease in the amount of pollution in several major cities in Indonesia was also found during the pandemic period.

scholarly journals Pengaruh Pembangunan Infrastruktur Terhadap Kinerja Kepala Desa Bontomanai Kecematan Bungaya Kabupaten Gowa

2021 ◽  
Vol 21 (3) ◽  
pp. 690-699
Author(s):  
Muhammad Bakri ◽  
A. Iman Zulfikar ◽  
Sumarni Sarong ◽  
R Baso ◽  
Jainuddin Jainuddin
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Statistical Method ◽  
Sampling Method ◽  
Linear Regression Analysis ◽  
Primary Data ◽  
Infrastructure Development ◽  
Simple Linear Regression ◽  
Purposive Sampling ◽  
The Village

Penelitian ini bertujuan untuk menguji pengaruh pembangunan infrastruktur terhadap kinerja kepala Desa Bontomanai Kecematan Bungaya Kabupaten Gowa. Pembangunan kadang menjadi tolak ukur suatu kepala pemerintah terhadap kinerjanya. Kepala desa dengan dana desa yang begitu besar sangat besar perlu dipertanyakn jika tidak ada pembangunan yang terjadai. Penelitian ini menggunakan data primer yaitu dengan menyediakan pertanyaan dalam bentuk kuesioner yang dibagikan kepada responden yang merupakan masyarakat yang tersebar dibeberapa dusun lingkup desa Bontomanai. Sampel dipilih dengan menggunakan metode purposive sampling. Responden dalam penelitian ini adalah Masyarakat di Desa Bontomanai.  Sebanyak 97 kuesioner yang bagikan dan 97 kuesioner yang kembali. Data yang diperoleh kemudian diproses dan dianalisis 97 kuesioner. Metode statistik yang digunakan untuk menguji hipotesis adalah analisis regresi linear sederhana. Hasil penelitian ini menunjukkan bahwa pembangunan infrastruktur berpengaruh terhadap kinerja kepala Desa Bontomanai. This study aims to examine the effect of infrastructure development on the performance of the head of Bontomanai Village, Bungaya District, Gowa Regency. Development is sometimes a measure of a head of government's performance. The village head with such large village funds needs to be questioned if no development occurs. This study uses primary data, namely by providing questions in the form of a questionnaire which is distributed to respondents who are people who are scattered in several hamlets within the scope of Bontomanai village. Samples were selected using purposive sampling method. Respondents in this study were people in Bontomanai Village. A total of 97 questionnaires were distributed and 97 were returned. The data obtained were then processed and analyzed by 97 questionnaires. The statistical method used to test the hypothesis is simple linear regression analysis. The results of this study indicate that infrastructure development affects the performance of the head of Bontomanai Village.

scholarly journals Uncertainty Assessment of Ice Discharge Using GPR-Derived Ice Thickness from Gourdon Glacier, Antarctic Peninsula

Geosciences ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 12 ◽  
Author(s):  
Stefan Lippl ◽  
Norbert Blindow ◽  
Johannes J. Fürst ◽  
Sebastián Marinsek ◽  
Thorsten C. Seehaus ◽  
...  
Keyword(s):  
Uncertainty Assessment ◽  
In Situ Measurements ◽  
Ice Thickness ◽  
Outlet Glacier ◽  
In Situ Data ◽  
Continuity Equations ◽  
Reconstruction Methods ◽  
A Minor ◽  
Ground Penetrating

Ice cliffs within a glacier represent a challenge for the continuity equations used in many glacier models by interrupting the validity of input parameters. In the case of Gourdon Glacier on James Ross Island, Antarctica, a ∼300–500 m high, almost vertical cliff, separates the outlet glacier from its main accumulation area on the plateau of the island. In 2017 and 2018 we conducted ice thickness measurements during two airborne ground penetrating radar campaigns in order to evaluate differences to older measurements from the 1990s. The observed differences are mostly smaller than the estimated error bars. In comparison to the in situ data, the published “consensus ice thickness estimate” strongly overestimates the ice thickness at the outlet. We analyse three different interpolation and ice thickness reconstruction methods. One approach additionally includes the mass input from the plateau. Differences between the interpolation methods have a minor impact on the ice discharge estimation if the used flux gates are in areas with a good coverage of in situ measurements. A much stronger influence was observed by uncertainties in the glacier velocities derived from remote sensing, especially in the direction of the velocity vector in proximity to the ice cliff. We conclude that the amount of in situ measurements should be increased for specific glacier types in order to detect biases in modeled ice thickness and ice discharge estimations.

scholarly journals Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-interim reanalysis

2015 ◽  
Vol 8 (1) ◽  
pp. 23-55 ◽  
Author(s):  
N. Vuichard ◽  
D. Papale
Keyword(s):  
Standard Deviation ◽  
Land Surface ◽  
Meteorological Data ◽  
Internal Variability ◽  
Fair Use ◽  
Meteorological Variable ◽  
Continuous Data ◽  
High Temporal Resolution ◽  
In Situ Data

Abstract. Exchanges of carbon, water and energy between the land surface and the atmosphere are monitored by eddy covariance technique at the ecosystem level. Currently, the FLUXNET database contains more than 500 sites registered and up to 250 of them sharing data (Free Fair Use dataset). Many modelling groups use the FLUXNET dataset for evaluating ecosystem model's performances but it requires uninterrupted time series for the meteorological variables used as input. Because original in-situ data often contain gaps, from very short (few hours) up to relatively long (some months), we develop a new and robust method for filling the gaps in meteorological data measured at site level. Our approach has the benefit of making use of continuous data available globally (ERA-interim) and high temporal resolution spanning from 1989 to today. These data are however not measured at site level and for this reason a method to downscale and correct the ERA-interim data is needed. We apply this method on the level 4 data (L4) from the LaThuile collection, freely available after registration under a Fair-Use policy. The performances of the developed method vary across sites and are also function of the meteorological variable. On average overall sites, the bias correction leads to cancel from 10 to 36% of the initial mismatch between in-situ and ERA-interim data, depending of the meteorological variable considered. In comparison to the internal variability of the in-situ data, the root mean square error (RMSE) between the in-situ data and the un-biased ERA-I data remains relatively large (on average overall sites, from 27 to 76% of the standard deviation of in-situ data, depending of the meteorological variable considered). The performance of the method remains low for the wind speed field, in particular regarding its capacity to conserve a standard deviation similar to the one measured at FLUXNET stations. The ERA-interim reanalysis data debiased at FLUXNET sites can be downloaded from the PANGAEA data center (http://doi.pangaea.de/10.1594/PANGAEA.838234).

Sign in / Sign up

Export Citation Format

Share Document