scholarly journals Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Vladimir Krasnopolsky ◽  
Sudhir Nadiga ◽  
Avichal Mehra ◽  
Eric Bayler ◽  
David Behringer
Keyword(s):  
Ocean Color ◽  
Ocean Dynamics ◽  
Upper Ocean ◽  
Satellite Measurements ◽  
Cheap Method ◽  
Sensitivity Studies ◽  
The Impact ◽  
Ocean Observations ◽  
Satellite Ocean Color

A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites andin situphysical observations. Satellite-derived “ocean color” (OC) data are used in this study because OC variability is primarily driven by biological processes related and correlated in complex, nonlinear relationships with the physical processes of the upper ocean. Specifically, ocean color chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as NOAA and NASA ocean surface and upper-ocean observations employed—signatures of upper-ocean dynamics. An NN transfer function is trained, using global data for two years (2012 and 2013), and tested on independent data for 2014. To reduce the impact of noise in the data and to calculate a stable NN Jacobian for sensitivity studies, an ensemble of NNs with different weights is constructed and compared with a single NN. The impact of the NN training period on the NN’s generalization ability is evaluated. The NN technique provides an accurate and computationally cheap method for filling in gaps in satellite ocean color observation fields and time series.

scholarly journals Analyzing Satellite Ocean Color Match-Up Protocols Using the Satellite Validation Navy Tool (SAVANT) at MOBY and Two AERONET-OC Sites

2021 ◽  
Vol 13 (14) ◽  
pp. 2673
Author(s):  
Adam Lawson ◽  
Jennifer Bowers ◽  
Sherwin Ladner ◽  
Richard Crout ◽  
Christopher Wood ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Ocean Color ◽  
Visible Spectrum ◽  
Ground Truth ◽  
Naval Research ◽  
Satellite Validation ◽  
The Difference ◽  
Stability And Accuracy ◽  
Satellite Ocean Color

The satellite validation navy tool (SAVANT) was developed by the Naval Research Laboratory to help facilitate the assessment of the stability and accuracy of ocean color satellites, using numerous ground truth (in situ) platforms around the globe and support methods for match-up protocols. The effects of varying spatial constraints with permissive and strict protocols on match-up uncertainty are evaluated, in an attempt to establish an optimal satellite ocean color calibration and validation (cal/val) match-up protocol. This allows users to evaluate the accuracy of ocean color sensors compared to specific ground truth sites that provide continuous data. Various match-up constraints may be adjusted, allowing for varied evaluations of their effects on match-up data. The results include the following: (a) the difference between aerosol robotic network ocean color (AERONET-OC) and marine optical Buoy (MOBY) evaluations; (b) the differences across the visible spectrum for various water types; (c) spatial differences and the size of satellite area chosen for comparison; and (d) temporal differences in optically complex water. The match-up uncertainty analysis was performed using Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) SNPP data at the AERONET-OC sites and the MOBY site. It was found that the more permissive constraint sets allow for a higher number of match-ups and a more comprehensive representation of the conditions, while the restrictive constraints provide better statistical match-ups between in situ and satellite sensors.

scholarly journals Fine-scale features on the sea surface in SAR satellite imagery – Part 1: Simultaneous in-situ measurements

2012 ◽  
Vol 9 (5) ◽  
pp. 2885-2914 ◽  
Author(s):  
A. Soloviev ◽  
C. Maingot ◽  
S. Matt ◽  
R. E. Dodge ◽  
S. Lehner ◽  
...  
Keyword(s):  
Numerical Models ◽  
Three Dimensional ◽  
Companion Paper ◽  
In Situ Measurements ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
Upper Ocean ◽  
Fine Scale ◽  
Sar Imagery

Abstract. This work is aimed at identifying the origin of fine-scale features on the sea surface in synthetic aperture radar (SAR) imagery with the help of in-situ measurements as well as numerical models (presented in a companion paper). We are interested in natural and artificial features starting from the horizontal scale of the upper ocean mixed layer, around 30–50 m. These features are often associated with three-dimensional upper ocean dynamics. We have conducted a number of studies involving in-situ observations in the Straits of Florida during SAR satellite overpass. The data include examples of sharp frontal interfaces, wakes of surface ships, internal wave signatures, as well as slicks of artificial and natural origin. Atmospheric processes, such as squall lines and rain cells, produced prominent signatures on the sea surface. This data has allowed us to test an approach for distinguishing between natural and artificial features and atmospheric influences in SAR images that is based on a co-polarized phase difference filter.

scholarly journals Comparison of Above-Water Seabird and TriOS Radiometers along an Atlantic Meridional Transect

2020 ◽  
Vol 12 (10) ◽  
pp. 1669
Author(s):  
Krista Alikas ◽  
Viktor Vabson ◽  
Ilmar Ansko ◽  
Gavin H. Tilstone ◽  
Giorgio Dall’Olmo ◽  
...  
Keyword(s):  
State Of The Art ◽  
Ocean Color ◽  
Percentage Difference ◽  
Wide Range ◽  
Before And After ◽  
Reference Measurements ◽  
Satellite Ocean Color ◽  
Good Agreement

The Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) project has carried out a range of activities to evaluate and improve the state-of-the-art in ocean color radiometry. This paper described the results from a ship-based intercomparison conducted on the Atlantic Meridional Transect 27 from 23rd September to 5th November 2017. Two different radiometric systems, TriOS-Radiation Measurement Sensor with Enhanced Spectral resolution (RAMSES) and Seabird-Hyperspectral Surface Acquisition System (HyperSAS), were compared and operated side-by-side over a wide range of Atlantic provinces and environmental conditions. Both systems were calibrated for traceability to SI (Système international) units at the same optical laboratory under uniform conditions before and after the field campaign. The in situ results and their accompanying uncertainties were evaluated using the same data handling protocols. The field data revealed variability in the responsivity between TRiOS and Seabird sensors, which is dependent on the ambient environmental and illumination conditions. The straylight effects for individual sensors were mostly within ±3%. A near infra-red (NIR) similarity correction changed the water-leaving reflectance (ρw) and water-leaving radiance (Lw) spectra significantly, bringing also a convergence in outliers. For improving the estimates of in situ uncertainty, it is recommended that additional characterization of radiometers and environmental ancillary measurements are undertaken. In general, the comparison of radiometric systems showed agreement within the evaluated uncertainty limits. Consistency of in situ results with the available Sentinel-3A Ocean and Land Color Instrument (OLCI) data in the range from (400…560) nm was also satisfactory (−8% < Mean Percentage Difference (MPD) < 15%) and showed good agreement in terms of the shape of the spectra and absolute values.

scholarly journals Adjusting Neural Network to a Particular Problem: Neural Network-Based Empirical Biological Model for Chlorophyll Concentration in the Upper Ocean

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Vladimir Krasnopolsky ◽  
Sudhir Nadiga ◽  
Avichal Mehra ◽  
Eric Bayler
Keyword(s):  
Neural Network ◽  
Chlorophyll A ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
Biological Model ◽  
Upper Ocean ◽  
Wide Field ◽  
Biological Processes ◽  
Chl A ◽  
The Impact

The versatility of the neural network (NN) technique allows it to be successfully applied in many fields of science and to a great variety of problems. For each problem or class of problems, a generic NN technique (e.g., multilayer perceptron (MLP)) usually requires some adjustments, which often are crucial for the development of a successful application. In this paper, we introduce a NN application that demonstrates the importance of such adjustments; moreover, in this case, the adjustments applied to a generic NN technique may be successfully used in many other NN applications. We introduce a NN technique, linking chlorophyll “a” (chl-a) variability—primarily driven by biological processes—with the physical processes of the upper ocean using a NN-based empirical biological model for chl-a. In this study, satellite-derived surface parameter fields, sea-surface temperature (SST) and sea-surface height (SSH), as well as gridded salinity and temperature profiles from 0 to 75m depth are employed as signatures of upper-ocean dynamics. Chlorophyll-a fields from NOAA’s operational Visible Imaging Infrared Radiometer Suite (VIIRS) are used, as well as Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a concentrations. Different methods of optimizing the NN technique are investigated. Results are assessed using the root-mean-square error (RMSE) metric and cross-correlations between observed ocean color (OC) fields and NN output. To reduce the impact of noise in the data and to obtain a stable computation of the NN Jacobian, an ensemble of NN with different weights is constructed. This study demonstrates that the NN technique provides an accurate, computationally cheap method to generate long (up to 10 years) time series of consistent chl-a concentration that are in good agreement with chl-a data observed by different satellite sensors during the relevant period. The presented NN demonstrates a very good ability to generalize in terms of both space and time. Consequently, the NN-based empirical biological model for chl-a can be used in oceanic models, coupled climate prediction systems, and data assimilation systems to dynamically consider biological processes in the upper ocean.

scholarly journals Performance evaluation of ocean color satellite models for deriving accurate chlorophyll estimates in the Gulf of Saint Lawrence

2014 ◽  
Vol 11 (6) ◽  
pp. 9299-9340
Author(s):  
M. Montes-Hugo ◽  
H. Bouakba ◽  
R. Arnone
Keyword(s):  
Chlorophyll Concentration ◽  
Ocean Color ◽  
Atmospheric Correction ◽  
Relative Bias ◽  
Wide Field ◽  
Absolute Bias ◽  
Analysis System ◽  
Data Analysis System ◽  
The Impact

Abstract. The understanding of phytoplankton dynamics in the Gulf of the Saint Lawrence (GSL) is critical for managing major fisheries off the Canadian East coast. In this study, the accuracy of two atmospheric correction techniques (NASA standard algorithm, SA, and Kuchinke's spectral optimization, KU) and three ocean color inversion models (Carder's empirical for SeaWiFS (Sea-viewing Wide Field-of-View Sensor), EC, Lee's quasi-analytical, QAA, and Garver- Siegel-Maritorena semi-empirical, GSM) for estimating the phytoplankton absorption coefficient at 443 nm (aph(443)) and the chlorophyll concentration (chl) in the GSL is examined. Each model was validated based on SeaWiFS images and shipboard measurements obtained during May of 2000 and April 2001. In general, aph(443) estimates derived from coupling KU and QAA models presented the smallest differences with respect to in situ determinations as measured by High Pressure liquid Chromatography measurements (median absolute bias per cruise up to 0.005, RMSE up to 0.013). A change on the inversion approach used for estimating aph(443) values produced up to 43.4% increase on prediction error as inferred from the median relative bias per cruise. Likewise, the impact of applying different atmospheric correction schemes was secondary and represented an additive error of up to 24.3%. By using SeaDAS (SeaWiFS Data Analysis System) default values for the optical cross section of phytoplankton (i.e., aph(443) = aph(443)/chl = 0.056 m2mg−1), the median relative bias of our chl estimates as derived from the most accurate spaceborne aph(443) retrievals and with respect to in situ determinations increased up to 29%.

scholarly journals The Contribution of High-Frequency Wind-Generated Surface Waves to the Stokes Drift

2020 ◽  
Vol 50 (12) ◽  
pp. 3455-3465
Author(s):  
Luc Lenain ◽  
Nick Pizzo
Keyword(s):  
Surface Waves ◽  
Wave Spectrum ◽  
Ocean Dynamics ◽  
Stokes Drift ◽  
Upper Ocean ◽  
Sea State ◽  
Instrument Measurement ◽  
Wave Models ◽  
Surface Wave Field

AbstractThe effects of nonbreaking surface waves on upper-ocean dynamics enter the wave-averaged primitive equations through the Stokes drift. Through the resulting upper-ocean dynamics, Stokes drift is a catalyst for the fluxes of heat and trace gases between the atmosphere and ocean. However, estimates of the Stokes drift rely crucially on properly resolving the wave spectrum. In this paper, using state-of-the-art spatial measurements (in situ and airborne remote sensing) from a number of different field campaigns, with environmental conditions ranging from 2 to 13 m s−1 wind speed and significant wave height of up to 4 m, we characterize the properties of the surface wave field across the equilibrium and saturation ranges and provide a simple parameterization of the transition between the two regimes that can easily be implemented in numerical wave models. We quantify the error associated with instrument measurement limitations, or incomplete numerical parameterizations, and propose forms for the continuation of these spectra to properly estimate the Stokes drift. Depending on the instrument and the sea state, predictions of surface Stokes drift may be underestimated by more than 50%.

scholarly journals Improved Value of the Observing System Through Integrated Satellite and In-Situ Design

2021 ◽  
Vol 55 (3) ◽  
pp. 88-89
Author(s):  
Andrea McCurdy ◽  
Nadya Vinogradova-Shiffer
Keyword(s):  
Operations Research ◽  
Ocean Color ◽  
Satellite Observation ◽  
Satellite Measurements ◽  
Or Groups ◽  
Multidisciplinary Working ◽  
Design Requirements ◽  
Field Campaigns

Abstract Primary among the goals for this Ocean-Shot will be to support the important role of, and maintenance of the continuity of space-based, broad-scale measurements of the essential ocean surface variables; e.g., OSVW, SSH, SST, SSS, Precipitation, Ocean Color, by building on associated in-situ measurements. Projects and pilots will seek to enhance the value of satellite observation with measurements made of physics, biogeochemistry, and biology within the water column, and the atmosphere. This endeavor will also contribute to the well-established infrastructure in place to improve the calibration, evaluation, and validation of satellite measurements, and to intercalibrate different satellite missions and instruments. This project will highlight community awareness of the interfaces and activities that will ensure the sustained observations needed for EOV satellite and in-situ observational operations, research, and monitoring.Activities will include convening and/or joining an international, multidisciplinary working group or groups consisting of members of requirements setting, implementation teams, and data managers. In time the project will develop a series of use cases highlighting satellite field campaigns that have resulted in enhanced system design and to an improved understanding of the ocean. Over the decade the project will seek to create mechanisms resulting in ongoing recommendations for additional co-design requirements among the scientific, remote sensing, and in-situ community.

Improvement of radiation modelling during cloudy sky days using in-situ and satellite measurements. 

2021 ◽  
Author(s):  
Lea Al Asmar ◽  
Luc Musson-Genon ◽  
Eric Dupont ◽  
Karine Sartelet
Keyword(s):  
Solar Radiation ◽  
Wrf Model ◽  
Cloud Fraction ◽  
Satellite Measurements ◽  
Radiation Model ◽  
Radiometric Measurements ◽  
Observational Site ◽  
Radiation Modelling ◽  
The Impact

&lt;p&gt;Solar radiation modelling is important for the evaluation and deployment of solar renewable energy systems. The amount of solar radiation reaching the ground is influenced by geographical parameters (seasons, latitude and local characteristics of the site) and meteorological and atmospheric parameters (like humidity, clouds or particles). Those parameters have important spatio-temporal variations that make solar radiation hard to model.&amp;#160;&lt;/p&gt;&lt;p&gt;Various radiation models exist in literature. Among them, the 1D radiation model part of the computational fluid dynamics software &amp;#8220;Code_Saturne&amp;#8221; estimates the global and direct solar irradiances at the ground. It takes into account the impact of meteorology, atmospheric gas, particles and clouds whose influence is represented using the two-stream approximation.&amp;#160;&lt;/p&gt;&lt;p&gt;The model showed satisfactory results during clear-sky days &amp;#160;but not during cloudy-sky days. It is a common problem in solar radiation modelling, because of the complexity to accurately represent &amp;#160;clouds, which are extremely variable in space and time and have a strong influence on the depletion of solar irradiance. &amp;#160;&lt;/p&gt;&lt;p&gt;In the current study, the estimation of radiation during cloudy-sky days is improved by coupling the 1D radiation model of Code_Saturne with on-site and satellite measurements of the cloud optical properties. Meteorological data are obtained from the Weather Research and Forecasting (WRF) model, aerosol&amp;#8217;s concentrations from the air-quality modelling platform Polyphemus, and on-site measurements from the SIRTA observational site (close to Paris). Two periods are simulated: 'august 2009' and 'year 2014'. It is shown that the introduction of the measured cloud properties in the computation of the surface radiation fluxes leads to a strong reduction of the simulated errors, compared to the case where these properties are derived from the WRF model. &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160; &amp;#160;&lt;/p&gt;&lt;p&gt;A sensitivity analysis on the parameters representing clouds in the model is conducted. It enabled us to identify the most influencing parameters - cloud optical thickness (COD) and cloud fraction - and instruments that are sufficient and mandatory for a good description of solar radiation during cloudy-sky days. A fitted model is developed to deduce the COD from liquid water path measurements. Satellite and radiometric measurements could both be used, although satellite measurements are not always available. &amp;#160;For the estimation of cloud fraction, the best results are obtained from shortwave radiometric measurements or from a sky imager. Moreover, large error cases in hourly values of solar fluxes are examined to understand their origin. For a large part of these error cases, there is a high variation within the hour of satellite or in situ measurements, or the presence of low clouds (in more than 50% of these cases in august 2009).&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

Impact of Assimilating Underwater Glider Data on Hurricane Gonzalo (2014) Forecasts

2017 ◽  
Vol 32 (3) ◽  
pp. 1143-1159 ◽  
Author(s):  
Jili Dong ◽  
Ricardo Domingues ◽  
Gustavo Goni ◽  
George Halliwell ◽  
Hyun-Sook Kim ◽  
...  
Keyword(s):  
Initial Conditions ◽  
Storm Track ◽  
Upper Ocean ◽  
Underwater Glider ◽  
Intensity Forecast ◽  
Spatial Coverage ◽  
Ocean Conditions ◽  
The Impact ◽  
Ocean Observations ◽  
Limited Coverage

Abstract The initialization of ocean conditions is essential to coupled tropical cyclone (TC) forecasts. This study investigates the impact of ocean observation assimilation, particularly underwater glider data, on high-resolution coupled TC forecasts. Using the coupled Hurricane Weather Research and Forecasting (HWRF) Model–Hybrid Coordinate Ocean Model (HYCOM) system, numerical experiments are performed by assimilating underwater glider observations alone and with other standard ocean observations for the forecast of Hurricane Gonzalo (2014). The glider observations are able to provide valuable information on subsurface ocean thermal and saline structure, even with their limited spatial coverage along the storm track and the relatively small amount of data assimilated. Through the assimilation of underwater glider observations, the prestorm thermal and saline structures of initial upper-ocean conditions are significantly improved near the location of glider observations, though the impact is localized because of the limited coverage of glider data. The ocean initial conditions are best represented when both the standard ocean observations and the underwater glider data are assimilated together. The barrier layer and the associated sharp density gradient in the upper ocean are successfully represented in the ocean initial conditions only with the use of underwater glider observations. The upper-ocean temperature and salinity forecasts in the first 48 h are improved by assimilating both underwater glider and standard ocean observations. The assimilation of glider observations alone does not make a large impact on the intensity forecast due to their limited coverage along the storm track. The 126-h intensity forecast of Hurricane Gonzalo is improved moderately through assimilating both underwater glider data and standard ocean observations.

Sign in / Sign up

Export Citation Format

Share Document