scholarly journals SONIC LAYER DEPTH VARIATION ANALYSIS UTILIZING BIDE (BANDA ITF DYNAMIC EXPERIMENT) ARGO FLOAT IN SITU OBSERVATION FOR UNDERSEA WARFARE TACTICAL ENVIRONMENT SUPPORT

JOURNAL ASRO ◽  
2018 ◽  
Vol 9 (1) ◽  
pp. 62
Author(s):  
D Armansyah ◽  
N B Sukoco ◽  
W S Pranowo
Keyword(s):  
Time Series ◽  
Annual Cycle ◽  
Series Data ◽  
Variation Analysis ◽  
Dynamic Experiment ◽  
Layer Depth ◽  
Depth Variation ◽  
Argo Float ◽  
Cycle Variation

ABSTRACT Sonic Layer Depth is the vertical distance from surface to the depth where the speed of sound reach it’s local maximum. Global Navy as well as Indonesan Navy operates in this kind of layers on a daily basis, wether it be in an anti submarine warfare operation through its ships and aircrafts or in an anti-surface warfare operation waged by its submarines. For the navy, the importance of knowing the exact value of the SLD is because it determines the minimum cut off frequency and sound wave propagation above which sound tends to be trapped and below which a shadow zone exist. This has a direct impact on where the navy operates its sensors and places its platforms in the water column. The best way to estimate SLD is by performing own measurement on the ocean using instrument such as expendable bathytermographs, which can be relatively expensive and time consuming for an operational navy ships, furthermore such measurement may be impractical in the case of mission planning or emergencies. Dedicated oceanography survey for the purpose of science and defense is relatively scarce due to prioritization concerning to the budget available resulting lack of time series in situ CTD observation which cover full annual cycle variation in Indonesia waters. Banda Indonesia Through Flow Dynamic Experiment (BIDE) is multi institution and bilateral oceanography experiment led by Indonesian scientist which utilizes argo float to perform in situ CTD measurement in Banda Sea to get an adequate time series data that cover full annual cycle variation. The dataset is publicly available so defense community as well may utilize the data for defense interest such as sonic layer depth variation analysis in Banda Sea.   Keyword : sonic layer depth, BIDE, argo float, undersea warfare, tactical environment

scholarly journals Contextualizing time-series data: quantification of short-term regional variability in the San Pedro Channel using high-resolution in situ glider data

2018 ◽  
Vol 15 (20) ◽  
pp. 6151-6165 ◽  
Author(s):  
Elizabeth N. Teel ◽  
Xiao Liu ◽  
Bridget N. Seegers ◽  
Matthew A. Ragan ◽  
William Z. Haskell ◽  
...  
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Water Column ◽  
Time Series Data ◽  
Series Data ◽  
Regional Variability ◽  
Modes Of Variability ◽  
Subsurface Chlorophyll Maximum ◽  
San Pedro

Abstract. Oceanic time series have been instrumental in providing an understanding of biological, physical, and chemical dynamics in the oceans and how these processes change over time. However, the extrapolation of these results to larger oceanographic regions requires an understanding and characterization of local versus regional drivers of variability. Here we use high-frequency spatial and temporal glider data to quantify variability at the coastal San Pedro Ocean Time-series (SPOT) site in the San Pedro Channel (SPC) and provide insight into the underlying oceanographic dynamics for the site. The dataset could be described by a combination of four water column profile types that typified active upwelling, a surface bloom, warm-stratified low-nutrient conditions, and a subsurface chlorophyll maximum. On weekly timescales, the SPOT station was on average representative of 64 % of profiles taken within the SPC. In general, shifts in water column profile characteristics at SPOT were also observed across the entire channel. On average, waters across the SPC were most similar to offshore profiles, suggesting that SPOT time series data would be more impacted by regional changes in circulation than local coastal events. These results indicate that high-resolution in situ glider deployments can be used to quantify major modes of variability and provide context for interpreting time series data, allowing for broader application of these datasets and greater integration into modeling efforts.

A 50-Year Sr/Ca Time Series from an Enclosed, Shallow-Water Guam Coral: In situ Monitoring and Extraction of a Temperature Trend, Annual Cycle, and ENSO and PDO Signals

2019 ◽  
Vol 35 (2) ◽  
pp. 269
Author(s):  
Tomoko Bell ◽  
Mark A. Lander ◽  
John W. Jenson ◽  
Richard H. Randall ◽  
Judson W. Partin ◽  
...  
Keyword(s):  
Time Series ◽  
Shallow Water ◽  
Annual Cycle ◽  
Temperature Trend ◽  
In Situ Monitoring

scholarly journals Comparison of In Situ Soil Moisture Measurements: An Examination of the Neutron and Dielectric Measurements within the Illinois Climate Network

2016 ◽  
Vol 33 (8) ◽  
pp. 1749-1758 ◽  
Author(s):  
Evan J. Coopersmith ◽  
Michael H. Cosh ◽  
Jennifer M. Jacobs
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Time Series Data ◽  
Series Data ◽  
Data Series ◽  
Neutron Probe ◽  
Dielectric Sensor ◽  
Continuous Record ◽  
Data Record

AbstractThe continuity of soil moisture time series data is crucial for climatic research. Yet, a common problem for continuous data series is the changing of sensors, not only as replacements are necessary, but as technologies evolve. The Illinois Climate Network has one of the longest data records of soil moisture; yet, it has a discontinuity when the primary sensor (neutron probes) was replaced with a dielectric sensor. Applying a simple model coupled with machine learning, the two time series can be merged into one continuous record by training the model on the latter dielectric model and minimizing errors against the former neutron probe dataset. The model is able to be calibrated to an accuracy of 0.050 m3 m−3 and applying this to the earlier series and applying a gain and offset, an RMSE of 0.055 m3 m−3 is possible. As a result of this work, there is now a singular network data record extending back to the 1980s for the state of Illinois.

scholarly journals Identifying Alternative Wetting and Drying Adoption (AWD) in the Vietnamese Mekong River Delta: A Change Detection Approach

2019 ◽  
Vol 8 (7) ◽  
pp. 312 ◽  
Author(s):  
Robin J. Lovell
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Radar Data ◽  
River Delta ◽  
Mekong River ◽  
Series Data ◽  
Wetting And Drying ◽  
Mekong River Delta ◽  
The Impact

Alternative wetting and drying (AWD) is an increasingly popular water-saving practice in rice production in the Vietnamese Mekong River Delta, especially considering the impact of projected climate change and reduced water availability. Unfortunately, it is very difficult to determine adoption without deploying thousands of costly household surveys. This research used European Space Agency Sentinel-1a and 1b radar data, combined with in-situ moisture readings, to determine AWD adoption through change detection of a time series wetness index (WI). By using a beta coefficient of the radar data, the WI avoided the pitfalls of cloud cover, surface roughness, and vegetative interference that arise from the sigma coefficient data. The analysis illustrated an AWD adoption likelihood scale across the delta and it showed potential for the use of remotely sensed data to detect adoption. Trends across the Vietnamese delta showed higher adoption rates inland, with lower adoption of AWD in the coastal provinces. These results were supported by a simultaneous effort to collect household level adoption data as part of the same project. However, correlation between the WI values and in situ soil moisture meter readings were most accurate in alluvial soils, illustrating a particularly strong relationship between soil type and WI model robustness. The research suggests that future change detection efforts should focus on retrieving a multi-season dataset and employing a power density analysis on the time series data to fully understand the periodicity of dry down patterns.

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