scholarly journals Assimilating water column and satellite data for marine export production estimation

2013 ◽  
Vol 6 (5) ◽  
pp. 1575-1590 ◽  
Author(s):  
X. Yao ◽  
R. Schlitzer
Keyword(s):  
Water Column ◽  
Production Rate ◽  
Optical Sensors ◽  
Particle Production ◽  
Optical Data ◽  
Small Scale ◽  
Initial State ◽  
Export Production ◽  
Water Column Nutrient ◽  
Nutrient Data

Abstract. Recent advances in satellite retrieval methodology now allow for estimation of particular organic carbon (POC) concentration in ocean surface waters directly from satellite-based optical data. Because of the good coverage, these data reveal small-scale spatial and temporal concentration gradients and document the evolution of surface water POC as well as the underlying driving biogeochemical processes throughout the seasons. Water column nutrient data also reveal biogeochemical activity. However, because of the scarcity of data, the deduction of temporal changes of particle production and export is not possible in most parts of the ocean. Here we present first results from a new study combining both data streams, thereby exploiting the high spatio-temporal resolution of surface POC concentrations from satellite optical sensors with water column nutrient data having sparser coverage but providing information throughout the entire water column. We use a medium-resolution global model with steady-state 3-D circulation that has been optimized by fitting to a large number of hydrographic parameters and tracers, including CFCs and natural radiocarbon. Production and export of POC is allowed to vary monthly, and the magnitudes of the monthly export fluxes are determined by fitting the model to satellite POC data as well as water column nutrient data using the adjoint method. Two cases have been investigated: (1) the production rate of POC is set to be proportional to export production (EP) and the seasonal changes are assumed sinusoidal (meridionally varying amplitude and phase), and (2) the POC production rate is linked to primary production rates (literature). Both cases were run with the same initial state and model settings, and show total cost function decreases of 12 and 95%, respectively. The POC misfit term alone decreased by 75 and 99.8%. The integrated annual global POC exports of the two cases are 9.9 and 12.3 Gt C yr−1, respectively. Overall, the remaining POC and phosphate misfits of both solutions are considered too large, and the difference fields still exhibit significant systematic geographical patterns. This indicates that the present model runs are too simplistic and do not fully explain the data. Further, more refined model setups are needed.

scholarly journals Assimilating water column and satellite data for marine export production estimation

2013 ◽  
Vol 6 (1) ◽  
pp. 2045-2085
Author(s):  
X. Yao ◽  
R. Schlitzer
Keyword(s):  
Water Column ◽  
Production Rate ◽  
Optical Sensors ◽  
Particle Production ◽  
Optical Data ◽  
Small Scale ◽  
Initial State ◽  
Export Production ◽  
Water Column Nutrient ◽  
Nutrient Data

Abstract. Recent advances in satellite retrieval methodology now allow estimation of particular organic carbon (POC) concentration in ocean surface waters directly from satellite-based optical data. Because of the good coverage these data reveal small-scale spatial and temporal concentration gradients and document the evolution of surface water POC as well as the underlying driving biogeochemical processes throughout the seasons. Water column nutrient data also reveal biogeochemical activity. However, because of the scarcity of data the deduction of temporal changes of particle production and export are not possible in most parts of the ocean. Here we present first results from a new study combining both data streams thereby exploiting the high spatio-temporal resolution of surface POC concentrations from satellite optical sensors with water column nutrient data having sparser coverage but providing information throughout the entire water column. We use a medium-resolution global model with steady-state 3-D circulation that has been optimized by fitting to a large number of hydrographic parameters and tracers, including CFCs and natural radiocarbon. Production and export of POC is allowed to vary monthly, and the magnitudes of the monthly export fluxes are determined by fitting the model to satellite POC data as well as water column nutrient data using the adjoint method. Two cases have been investigated: (1) the production rate of POC is set to be proportional to export production EP and the seasonal changes are assumed sinusoidal (meridionally varying amplitude and phase) and (2) the POC production rate is linked to primary production rates (literature). Both cases were run with the same initial state and model settings, and show total cost function decreases of 12 and 95%, respectively. The POC misfit term alone decreased by 75 and 99%. The integrated annual global POC exports of the two cases are 9.9 Gt C yr−1 and 12.3 Gt C yr−1, respectively. Overall, the remaining POC and phosphate misfits of both solutions are considered too large and the difference fields still exhibit significant systematic geographical patterns. This indicates that the present model runs are too simplistic and do not fully explain the data. Further, more refined model setups are needed.

scholarly journals Structural and optical properties of amorphous Si–Ge–Te thin films prepared by combinatorial sputtering

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
C. Mihai ◽  
F. Sava ◽  
I. D. Simandan ◽  
A. C. Galca ◽  
I. Burducea ◽  
...  
Keyword(s):  
Optical Properties ◽  
Data Storage ◽  
Optical Sensors ◽  
Material Selection ◽  
Functional Materials ◽  
Stability Study ◽  
Optical Data Storage ◽  
Optical Data ◽  
Structural And Optical Properties ◽  
Topological Constraint

AbstractThe lack of order in amorphous chalcogenides offers them novel properties but also adds increased challenges in the discovery and design of advanced functional materials. The amorphous compositions in the Si–Ge–Te system are of interest for many applications such as optical data storage, optical sensors and Ovonic threshold switches. But an extended exploration of this system is still missing. In this study, magnetron co-sputtering is used for the combinatorial synthesis of thin film libraries, outside the glass formation domain. Compositional, structural and optical properties are investigated and discussed in the framework of topological constraint theory. The materials in the library are classified as stressed-rigid amorphous networks. The bandgap is heavily influenced by the Te content while the near-IR refractive index dependence on Ge concentration shows a minimum, which could be exploited in applications. A transition from a disordered to a more ordered amorphous network at 60 at% Te, is observed. The thermal stability study shows that the formed crystalline phases are dictated by the concentration of Ge and Te. New amorphous compositions in the Si–Ge–Te system were found and their properties explored, thus enabling an informed and rapid material selection and design for applications.

Application of close range photogrammetry in structural health monitoring by processing generated point cloud datasets

2021 ◽  
Author(s):  
Ali Mirzazade ◽  
Cosmin Popescu ◽  
Thomas Blanksvärd ◽  
Björn Täljsten
Keyword(s):  
Health Monitoring ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Optical Data ◽  
Small Scale ◽  
Relevant Parameter ◽  
Bridge Inspection ◽  
Close Range Photogrammetry ◽  
Close Range

<p>In bridge inspection, vertical displacement is a relevant parameter for both short and long-term health monitoring. Assessing change in deflections could also simplify the assessment work for inspectors. Recent developments in digital camera technology and photogrammetry software enables point cloud with colour information (RGB values) to be generated. Thus, close range photogrammetry offers the potential of monitoring big and small-scale damages by point clouds. The current paper aims to monitor geometrical deviations in Pahtajokk Bridge, Northern Sweden, using an optical data acquisition technique. The bridge in this study is scanned two times by almost one year a part. After point cloud generation the datasets were compared to detect geometrical deviations. First scanning was carried out by both close range photogrammetry (CRP) and terrestrial laser scanning (TLS), while second scanning was performed by CRP only. Analyzing the results has shown the potential of CRP in bridge inspection.</p>

scholarly journals Determining Bottom Reflectance and Water Optical Properties Using Unmanned Underwater Vehicles under Clear or Cloudy Skies

2006 ◽  
Vol 23 (2) ◽  
pp. 314-324 ◽  
Author(s):  
David C. English ◽  
Kendall L. Carder
Keyword(s):  
Optical Properties ◽  
Water Column ◽  
Optical Sensors ◽  
Light Field ◽  
Field Measurements ◽  
Underwater Vehicles ◽  
Unmanned Underwater Vehicles ◽  
Cloudy Weather ◽  
Sea Grass ◽  
Ocean Color Imagery

Abstract An unmanned underwater vehicle (UUV) with hyperspectral optical sensors that measure downwelling irradiance and upwelling radiance was deployed over sandy bottoms, sea grass patches, and coral reefs near Lee Stocking Island, Bahamas, during the Coastal Benthic Optical Properties (CoBOP) program of 2000. These deployments occurred during both sunny and cloudy weather. If the rate of irradiance change due to cloud cover is slight, then the inclusion of a variable cloudy-irradiance factor will allow a reasonable estimation of water column absorption. Examination of data from a deployment in May 2000 under cloudy skies shows that the combination of hyperspectral light-field measurements, knowledge of the UUV's position in the water column, and a cloudy-irradiance factor permits consistent estimations of bottom reflectivity to be made from UUV measured reflectances. The spatial distribution of reflectance estimates obtained from a UUV may be useful for validation of airborne ocean color imagery.

Preventing waterlogging in irrigated agriculture with a multi-satellite sensor approach

2021 ◽  
Author(s):  
Nadja den Besten ◽  
Susan Steele-Dunne ◽  
Richard de Jeu ◽  
Pieter van der Zaag
Keyword(s):  
Water Stress ◽  
Brightness Temperature ◽  
Passive Microwave ◽  
Sensor Data ◽  
Optical Data ◽  
Irrigated Agriculture ◽  
Small Scale ◽  
Drought Event ◽  
Flooding Event ◽  
Microwave Data

&lt;p&gt;Satellite sensors have been used widely to determine water shortages to detect crop stress, with special emphasis on water stress. However, stress resulting from waterlogging has so far received little attention. This is surprising because approximately twenty percent of the global agricultural land suffers from the consequences of waterlogging and secondary soil salinization. While irrigation is expected to increase productivity, excess water can hamper the crop growth and decrease water use efficiency.&lt;/p&gt;&lt;p&gt;Traditionally, satellite driven water accounting for irrigation assistance uses optical and/or thermal sensors that can detect crop stress. The observed crop stress is often interpreted as water stress, whereby stress resulting from waterlogging cannot be distinguished. We hypothesize that a multi-sensor approach is required to distinguish waterlogging from water shortage, by including microwave observations that can determine the soil moisture status. However, localizing a small-scale phenomena as waterlogging with multi-sensor data with different resolutions is a major challenge.&lt;/p&gt;&lt;p&gt;In our research we focus on an irrigated sugarcane plantation along the river Incomati in Xinavane, Mozambique. Waterlogging is a common issue in the estate and is threatening productivity. We assess and combine optical and passive microwave data for a large drought (2016) and flooding event (2012) to look at the possibility of downscaling the data for detection of waterlogging. We find that optical indices are able to localize waterlogged areas. Additionally, the built up of the drought event and retreat of the flooding event are clearly visible in the brightness temperature in different frequencies. We demonstrate a procedure to combine brightness temperature with optical data to detect waterlogging at a higher spatial resolution.&amp;#160;&lt;/p&gt;&lt;p&gt;The results show that a combination of optical and passive microwave data can detect regions within the sugarcane plantation of waterlogging. However, high resolution topographic data is required to enhance the detection of waterlogging to finer scales.&amp;#160;&lt;/p&gt;

scholarly journals The Dynamics of Baroclinic Zonal Jets*

2015 ◽  
Vol 72 (3) ◽  
pp. 1137-1151 ◽  
Author(s):  
Paul D. Williams ◽  
Christopher W. Kelsall
Keyword(s):  
Root Mean Square ◽  
Power Law ◽  
Zonal Flow ◽  
Small Scale ◽  
Mean Square ◽  
Initial State ◽  
Zonal Jets ◽  
Rotation Periods ◽  
Inverse Energy Cascade ◽  
Geostrophic Turbulence

Abstract Multiple alternating zonal jets are a ubiquitous feature of planetary atmospheres and oceans. However, most studies to date have focused on the special case of barotropic jets. Here, the dynamics of freely evolving baroclinic jets are investigated using a two-layer quasigeostrophic annulus model with sloping topography. In a suite of 15 numerical simulations, the baroclinic Rossby radius and baroclinic Rhines scale are sampled by varying the stratification and root-mean-square eddy velocity, respectively. Small-scale eddies in the initial state evolve through geostrophic turbulence and accelerate zonally as they grow in horizontal scale, first isotropically and then anisotropically. This process leads ultimately to the formation of jets, which take about 2500 rotation periods to equilibrate. The kinetic energy spectrum of the equilibrated baroclinic zonal flow steepens from a −3 power law at small scales to a −5 power law near the jet scale. The conditions most favorable for producing multiple alternating baroclinic jets are large baroclinic Rossby radius (i.e., strong stratification) and small baroclinic Rhines scale (i.e., weak root-mean-square eddy velocity). The baroclinic jet width is diagnosed objectively and found to be 2.2–2.8 times larger than the baroclinic Rhines scale, with a best estimate of 2.5 times larger. This finding suggests that Rossby wave motions must be moving at speeds of approximately 6 times the turbulent eddy velocity in order to be capable of arresting the isotropic inverse energy cascade.

scholarly journals Analyzing Water Dynamics Based on Sentinel-1 Time Series—a Study for Dongting Lake Wetlands in China

2020 ◽  
Vol 12 (11) ◽  
pp. 1761 ◽  
Author(s):  
Juliane Huth ◽  
Ursula Gessner ◽  
Igor Klein ◽  
Hervé Yesou ◽  
Xijun Lai ◽  
...  
Keyword(s):  
Time Series ◽  
Wetland Management ◽  
Dongting Lake ◽  
Water Dynamics ◽  
Minimum Size ◽  
Optical Data ◽  
Small Scale ◽  
Lake Area ◽  
Ramsar Site ◽  
Extreme Flood

In China, freshwater is an increasingly scarce resource and wetlands are under great pressure. This study focuses on China’s second largest freshwater lake in the middle reaches of the Yangtze River—the Dongting Lake—and its surrounding wetlands, which are declared a protected Ramsar site. The Dongting Lake area is also a research region of focus within the Sino-European Dragon Programme, aiming for the international collaboration of Earth Observation researchers. ESA’s Copernicus Programme enables comprehensive monitoring with area-wide coverage, which is especially advantageous for large wetlands that are difficult to access during floods. The first year completely covered by Sentinel-1 SAR satellite data was 2016, which is used here to focus on Dongting Lake’s wetland dynamics. The well-established, threshold-based approach and the high spatio-temporal resolution of Sentinel-1 imagery enabled the generation of monthly surface water maps and the analysis of the inundation frequency at a 10 m resolution. The maximum extent of the Dongting Lake derived from Sentinel-1 occurred in July 2016, at 2465 km2, indicating an extreme flood year. The minimum size of the lake was detected in October, at 1331 km2. Time series analysis reveals detailed inundation patterns and small-scale structures within the lake that were not known from previous studies. Sentinel-1 also proves to be capable of mapping the wetland management practices for Dongting Lake polders and dykes. For validation, the lake extent and inundation duration derived from the Sentinel-1 data were compared with excerpts from the Global WaterPack (frequently derived by the German Aerospace Center, DLR), high-resolution optical data, and in situ water level data, which showed very good agreement for the period studied. The mean monthly extent of the lake in 2016 from Sentinel-1 was 1798 km2, which is consistent with the Global WaterPack, deviating by only 4%. In summary, the presented analysis of the complete annual time series of the Sentinel-1 data provides information on the monthly behavior of water expansion, which is of interest and relevance to local authorities involved in water resource management tasks in the region, as well as to wetland conservationists concerned with the Ramsar site wetlands of Dongting Lake and to local researchers.

Water column nutrient processing rates in rivermouths of Green Bay (Lake Michigan)

2018 ◽  
Vol 142 (1) ◽  
pp. 73-93 ◽  
Author(s):  
James H. Larson ◽  
Mary Anne Evans ◽  
Faith A. Fitzpatrick ◽  
Paul C. Frost ◽  
Sean Bailey ◽  
...  
Keyword(s):  
Water Column ◽  
Lake Michigan ◽  
Green Bay ◽  
Nutrient Processing ◽  
Water Column Nutrient
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