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

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.

2020 ◽  
Vol 13 (3) ◽  
pp. 1267-1284 ◽  
Author(s):  
Theo Baracchini ◽  
Philip Y. Chu ◽  
Jonas Šukys ◽  
Gian Lieberherr ◽  
Stefan Wunderle ◽  
...  

Abstract. The understanding of physical dynamics is crucial to provide scientifically credible information on lake ecosystem management. We show how the combination of in situ observations, remote sensing data, and three-dimensional hydrodynamic (3D) numerical simulations is capable of resolving various spatiotemporal scales involved in lake dynamics. This combination is achieved through data assimilation (DA) and uncertainty quantification. In this study, we develop a flexible framework by incorporating DA into 3D hydrodynamic lake models. Using an ensemble Kalman filter, our approach accounts for model and observational uncertainties. We demonstrate the framework by assimilating in situ and satellite remote sensing temperature data into a 3D hydrodynamic model of Lake Geneva. Results show that DA effectively improves model performance over a broad range of spatiotemporal scales and physical processes. Overall, temperature errors have been reduced by 54 %. With a localization scheme, an ensemble size of 20 members is found to be sufficient to derive covariance matrices leading to satisfactory results. The entire framework has been developed with the goal of near-real-time operational systems (e.g., integration into meteolakes.ch).


2013 ◽  
Vol 13 (5) ◽  
pp. 1402-1409
Author(s):  
Adam Trescott ◽  
Elizabeth Isenstein ◽  
Mi-Hyun Park

The objective of this study was to develop cyanobacteria remote sensing models using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) as an alternative to shipboard monitoring efforts in Lake Champlain. The approach allowed for estimation of cyanobacteria directly from satellite images, calibrated and validated with 4 years of in situ monitoring data from Lake Champlain's Long-Term Water Quality and Biological Monitoring Program (LTMP). The resulting stepwise regression model was applied to entire satellite images to provide distribution of cyanobacteria throughout the surface waters of Lake Champlain. The results demonstrate the utility of remote sensing for estimating the distribution of cyanobacteria in inland waters, which can be further used for presenting the initiation and propagation of cyanobacterial blooms in Lake Champlain.


2014 ◽  
Vol 11 (13) ◽  
pp. 3547-3602 ◽  
Author(s):  
P. Ciais ◽  
A. J. Dolman ◽  
A. Bombelli ◽  
R. Duren ◽  
A. Peregon ◽  
...  

Abstract. A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO2 proxy measurements such as radiocarbon in CO2 and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.


2015 ◽  
Vol 19 (7) ◽  
pp. 3203-3216 ◽  
Author(s):  
J. Iwema ◽  
R. Rosolem ◽  
R. Baatz ◽  
T. Wagener ◽  
H. R. Bogena

Abstract. The Cosmic-Ray Neutron Sensor (CRNS) can provide soil moisture information at scales relevant to hydrometeorological modelling applications. Site-specific calibration is needed to translate CRNS neutron intensities into sensor footprint average soil moisture contents. We investigated temporal sampling strategies for calibration of three CRNS parameterisations (modified N0, HMF, and COSMIC) by assessing the effects of the number of sampling days and soil wetness conditions on the performance of the calibration results while investigating actual neutron intensity measurements, for three sites with distinct climate and land use: a semi-arid site, a temperate grassland, and a temperate forest. When calibrated with 1 year of data, both COSMIC and the modified N0 method performed better than HMF. The performance of COSMIC was remarkably good at the semi-arid site in the USA, while the N0mod performed best at the two temperate sites in Germany. The successful performance of COSMIC at all three sites can be attributed to the benefits of explicitly resolving individual soil layers (which is not accounted for in the other two parameterisations). To better calibrate these parameterisations, we recommend in situ soil sampled to be collected on more than a single day. However, little improvement is observed for sampling on more than 6 days. At the semi-arid site, the N0mod method was calibrated better under site-specific average wetness conditions, whereas HMF and COSMIC were calibrated better under drier conditions. Average soil wetness condition gave better calibration results at the two humid sites. The calibration results for the HMF method were better when calibrated with combinations of days with similar soil wetness conditions, opposed to N0mod and COSMIC, which profited from using days with distinct wetness conditions. Errors in actual neutron intensities were translated to average errors specifically to each site. At the semi-arid site, these errors were below the typical measurement uncertainties from in situ point-scale sensors and satellite remote sensing products. Nevertheless, at the two humid sites, reduction in uncertainty with increasing sampling days only reached typical errors associated with satellite remote sensing products. The outcomes of this study can be used by researchers as a CRNS calibration strategy guideline.


2020 ◽  
Author(s):  
Tuukka Petäjä ◽  
Ella-Maria Duplissy ◽  
Ksenia Tabakova ◽  
Julia Schmale ◽  
Barbara Altstädter ◽  
...  

Abstract. The role of polar regions increases in terms of megatrends such as globalization, new transport routes, demography and use of natural resources consequent effects of regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project iCUPE – integrative and Comprehensive Understanding on Polar Environments to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth Observations (EO) and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns and satellites to deliver data products, metrics and indicators to the stakeholders concerning the environmental status, availability and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and provision of novel data in atmospheric pollution, local sources and transboundary transport, characterization of arctic surfaces and their changes, assessment of concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, quantification of emissions from natural resource extraction and validation and optimization of satellite Earth Observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of integration of comprehensive in situ observations, satellite remote sensing and multiscale modeling in the Arctic context.


2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yabin Sun ◽  
Dadiyorto Wendi ◽  
Dong Eon Kim ◽  
Shie-Yui Liong

AbstractThe rainfall intensity–duration–frequency (IDF) curves play an important role in water resources engineering and management. The applications of IDF curves range from assessing rainfall events, classifying climatic regimes, to deriving design storms and assisting in designing urban drainage systems, etc. The deriving procedure of IDF curves, however, requires long-term historical rainfall observations, whereas lack of fine-timescale rainfall records (e.g. sub-daily) often results in less reliable IDF curves. This paper presents the utilization of remote sensing sub-daily rainfall, i.e. Global Satellite Mapping of Precipitation (GSMaP), integrated with the Bartlett-Lewis rectangular pulses (BLRP) model, to disaggregate the daily in situ rainfall, which is then further used to derive more reliable IDF curves. Application of the proposed method in Singapore indicates that the disaggregated hourly rainfall, preserving both the hourly and daily statistic characteristics, produces IDF curves with significantly improved accuracy; on average over 70% of RMSE is reduced as compared to the IDF curves derived from daily rainfall observations.


2009 ◽  
Vol 30 (17) ◽  
pp. 4343-4357 ◽  
Author(s):  
T. Motohka ◽  
K. N. Nasahara ◽  
A. Miyata ◽  
M. Mano ◽  
S. Tsuchida

Sign in / Sign up

Export Citation Format

Share Document