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• 1. [Article] The influence of coherent waves on the remotely sensed reflectance

  This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/oe/home.cfm. ...

  Citation × Citation Citation Abstract Copy Title: The influence of coherent waves on the remotely sensed reflectance Author: Zaneveld, J. Ronald V., Boss, Emmanuel, Hwang, Paul A. This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/oe/home.cfm. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law. Title: The influence of coherent waves on the remotely sensed reflectance Author: Zaneveld, J. Ronald V., Boss, Emmanuel, Hwang, Paul A. This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://www.opticsinfobase.org/oe/home.cfm. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law. Close

• 2. [Article] Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies

  Numerical models are effective tools for simulating complex physical processes such as hydrodynamic and water quality processes in aquatic systems. The accuracy of the model is dependent on multiple model ...

  Citation × Citation Citation Abstract Copy Title: Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies Author: Javaheri, Amir Numerical models are effective tools for simulating complex physical processes such as hydrodynamic and water quality processes in aquatic systems. The accuracy of the model is dependent on multiple model parameters and variables that need to be calibrated and regularly updated to reproduce changing aquatic conditions accurately. Multi-sensor water temperature observations, such as remote sensing data and in situ monitoring technologies, can improve model accuracy by providing benefits of individual monitoring technology to the model updating process. In contrast to in-situ temperature sensors, remote sensing technologies (e.g., satellites) provide the benefit of collecting measurements with better X-Y spatial coverage. However, the temporal resolution of satellite data is limited comparing to in-situ measurements. Numerical models and all source of observations have large uncertainty coming from different sources such as errors of approximation and truncation, uncertain model inputs, error in measuring devices and etc. Data assimilation (DA) is able to sequentially update the model state variables by considering the uncertainty in model and observations and estimate the model states and outputs more accurately. Data Assimilation has been proposed for multiple water resources studies that require rapid employment of incoming observations to update and improve accuracy of operational prediction models. The usefulness of DA approaches in assimilating water temperature observations from different types of monitoring technologies (e.g., remote sensing and in-situ sensors) into numerical models of in-land water bodies (e.g., reservoirs, lakes, and rivers) has, however, received limited attention. Assimilating of water temperature measurements from satellites can introduce biases in the updated numerical model of water bodies because the physical region represented by these measurements do not directly correspond with the numerical model's representation of the water column. The main research objective of this study is to efficiently assimilate multi-sensor water temperature data into the hydrodynamic model of water bodies in order to improve the model accuracy. Four specific objectives were addressed in this work to accomplish the overall goal: * Objective 1: Propose a novel approach to address the representation challenge of model and measurements by coupling a skin temperature adjustment technique based on available air and in-situ water temperature observations, with an ensemble Kalman filter (EnKF) based data assimilation technique for reservoirs and lakes. * Objective 2: Investigate whether assimilation of remotely sensed temperature observations using the proposed data fusion approach can improve model accuracy with respect to in-situ temperature observations as well as remote sensing data. * Objective 3: Investigate a global sensitivity analysis tool that combines Latin-hypercube and one-factor-at-a-time sampling to investigate the most sensitive model inputs and parameters in calculating the water age and water temperature of shallow rivers. * Objective 4: Propose an efficient data assimilation framework to take the advantage of both monitoring technologies (e.g., remote sensing and in-situ measurements) to improve the model efficiency of shallow rivers. Results showed that the proposed adjustment approach used in this study for four-dimensional analysis of a reservoir provides reasonably accurate surface layer and water column temperature forecasts, in spite of the use of a fairly small ensemble. Assimilation of adjusted remote sensing data using ensemble Kalman Filter technique improved the overall root mean square difference between modeled surface layer temperatures and the adjusted remotely sensed skin temperature observations from 5.6 °C to 0.51 °C (i.e., 91% improvement). In addition, the overall error in the water column temperature predictions when compared with in-situ observations also decreased from 1.95 °C (before assimilation) to 1.42 °C (after assimilation), thereby, giving a 27% improvement in errors. In contrast, doing data assimilation without the proposed temperature adjustment would have increased this error to 1.98 °C (i.e., 1.5% deterioration). The most effective parameters to calculate water temperature were investigated and perturbed among the acceptable range to create the ensembles. Results show that water temperature is more sensitive to inflow temperature, air temperature, solar radiation, wind speed, flow rate, and wet bulb temperature respectively. Results also show in contrast to in-situ data assimilation, remote sensing data assimilation was able to effectively improve the spatial error of the model. Assimilation of in-situ observation improved the model efficiency at observation site. However, the model error increased by time and after less than two days, the model predictions of updated model were the same as base model before data assimilation. Hence, a maximum acceptable error between model and measurements was defined based on the application of model. Remote sensing data were assimilated into the model as they become available to improve the model accuracy for the entire river. In-situ data were also assimilated into the model when the error between model and observations exceeds the maximum error. Results showed that by assimilation of in-situ data one to three times per day, the average daily error reduced up to 58% comparing to situation that in-situ data were assimilated only once. In addition, the average spatial error reduced from 2.59 °C to 0.66 °C after assimilation of remote sensing data. Title: Assimilation of Multi-Sensor Data into Numerical Hydrodynamic Models of Inland Water Bodies Author: Javaheri, Amir Numerical models are effective tools for simulating complex physical processes such as hydrodynamic and water quality processes in aquatic systems. The accuracy of the model is dependent on multiple model parameters and variables that need to be calibrated and regularly updated to reproduce changing aquatic conditions accurately. Multi-sensor water temperature observations, such as remote sensing data and in situ monitoring technologies, can improve model accuracy by providing benefits of individual monitoring technology to the model updating process. In contrast to in-situ temperature sensors, remote sensing technologies (e.g., satellites) provide the benefit of collecting measurements with better X-Y spatial coverage. However, the temporal resolution of satellite data is limited comparing to in-situ measurements. Numerical models and all source of observations have large uncertainty coming from different sources such as errors of approximation and truncation, uncertain model inputs, error in measuring devices and etc. Data assimilation (DA) is able to sequentially update the model state variables by considering the uncertainty in model and observations and estimate the model states and outputs more accurately. Data Assimilation has been proposed for multiple water resources studies that require rapid employment of incoming observations to update and improve accuracy of operational prediction models. The usefulness of DA approaches in assimilating water temperature observations from different types of monitoring technologies (e.g., remote sensing and in-situ sensors) into numerical models of in-land water bodies (e.g., reservoirs, lakes, and rivers) has, however, received limited attention. Assimilating of water temperature measurements from satellites can introduce biases in the updated numerical model of water bodies because the physical region represented by these measurements do not directly correspond with the numerical model's representation of the water column. The main research objective of this study is to efficiently assimilate multi-sensor water temperature data into the hydrodynamic model of water bodies in order to improve the model accuracy. Four specific objectives were addressed in this work to accomplish the overall goal: * Objective 1: Propose a novel approach to address the representation challenge of model and measurements by coupling a skin temperature adjustment technique based on available air and in-situ water temperature observations, with an ensemble Kalman filter (EnKF) based data assimilation technique for reservoirs and lakes. * Objective 2: Investigate whether assimilation of remotely sensed temperature observations using the proposed data fusion approach can improve model accuracy with respect to in-situ temperature observations as well as remote sensing data. * Objective 3: Investigate a global sensitivity analysis tool that combines Latin-hypercube and one-factor-at-a-time sampling to investigate the most sensitive model inputs and parameters in calculating the water age and water temperature of shallow rivers. * Objective 4: Propose an efficient data assimilation framework to take the advantage of both monitoring technologies (e.g., remote sensing and in-situ measurements) to improve the model efficiency of shallow rivers. Results showed that the proposed adjustment approach used in this study for four-dimensional analysis of a reservoir provides reasonably accurate surface layer and water column temperature forecasts, in spite of the use of a fairly small ensemble. Assimilation of adjusted remote sensing data using ensemble Kalman Filter technique improved the overall root mean square difference between modeled surface layer temperatures and the adjusted remotely sensed skin temperature observations from 5.6 °C to 0.51 °C (i.e., 91% improvement). In addition, the overall error in the water column temperature predictions when compared with in-situ observations also decreased from 1.95 °C (before assimilation) to 1.42 °C (after assimilation), thereby, giving a 27% improvement in errors. In contrast, doing data assimilation without the proposed temperature adjustment would have increased this error to 1.98 °C (i.e., 1.5% deterioration). The most effective parameters to calculate water temperature were investigated and perturbed among the acceptable range to create the ensembles. Results show that water temperature is more sensitive to inflow temperature, air temperature, solar radiation, wind speed, flow rate, and wet bulb temperature respectively. Results also show in contrast to in-situ data assimilation, remote sensing data assimilation was able to effectively improve the spatial error of the model. Assimilation of in-situ observation improved the model efficiency at observation site. However, the model error increased by time and after less than two days, the model predictions of updated model were the same as base model before data assimilation. Hence, a maximum acceptable error between model and measurements was defined based on the application of model. Remote sensing data were assimilated into the model as they become available to improve the model accuracy for the entire river. In-situ data were also assimilated into the model when the error between model and observations exceeds the maximum error. Results showed that by assimilation of in-situ data one to three times per day, the average daily error reduced up to 58% comparing to situation that in-situ data were assimilated only once. In addition, the average spatial error reduced from 2.59 °C to 0.66 °C after assimilation of remote sensing data. Close

• 3. [Article] Depth estimation and frontal imaging via X-band marine radar

  This dissertation focuses on two core aspects of remote sensing: (a) interpretation of the remotely sensed data to identify and characterize sea surface features of interest, and (b) the quantitative analysis ...

  Citation × Citation Citation Abstract Copy Title: Depth estimation and frontal imaging via X-band marine radar Author: Honegger, David Andrew This dissertation focuses on two core aspects of remote sensing: (a) interpretation of the remotely sensed data to identify and characterize sea surface features of interest, and (b) the quantitative analysis of previously characterized features to produce robust estimates of geophysical variables. Specifically, these aspects are addressed in the context of the nearshore coastal ocean, utilizing a land-based, imaging X-band marine radar. With regard to the latter aspect (b), a robust, phase based depth estimate algorithm is extended to marine radar imagery with the purpose of assessing both absolute and relative performance against optical video derived depths. Depth estimates at both a nearby (< 1 km) and a moderately distant (2-3 km) beach are accurate to ∼ 0.5 m, with global bias of ∼±0.3 m; these results are comparable to those acquired via optical video, and performance trends with depth for the two sensors appear complementary. Extended to larger (inlet) domains that require the spatial coverage of marine radar imagery, algorithm performance remains at roughly the same level during slack; currents induce an unmodeled Doppler shift that produces wave frequency-and depth-dependent error that should not be neglected. Mitigation and solution strategies are discussed. With regard to the former aspect (a), sharp internal and interfacial gradients in the water column at a highly stratified estuary mouth are identified in marine radar imagery. The identified features include an internal, oblique hydraulic jump, a bottom salinity front, and a surface intrusion front. Confirmation of co-located, sharp current gradients that induce surface roughness modulations similar to those observed were carried out using remotely sensed surface current estimates (via airborne ATI-SAR) for the jump, and using vertical current profiles collected along cross-front transects via research vessel for the bottom and surface fronts. Presence of the frontal structures below the identified backscatter intensity contrast patterns is directly corroborated using salinity, temperature, and current data from bottom-mounted, ship-mounted, and ship-cast sensors, and presence of the internal jump is indirectly inferred using an inviscid two-layer model. Horizontal evolution of the jump and fronts in the estuary mouth is tracked in quasi-continuous marine radar image time series. Title: Depth estimation and frontal imaging via X-band marine radar Author: Honegger, David Andrew This dissertation focuses on two core aspects of remote sensing: (a) interpretation of the remotely sensed data to identify and characterize sea surface features of interest, and (b) the quantitative analysis of previously characterized features to produce robust estimates of geophysical variables. Specifically, these aspects are addressed in the context of the nearshore coastal ocean, utilizing a land-based, imaging X-band marine radar. With regard to the latter aspect (b), a robust, phase based depth estimate algorithm is extended to marine radar imagery with the purpose of assessing both absolute and relative performance against optical video derived depths. Depth estimates at both a nearby (< 1 km) and a moderately distant (2-3 km) beach are accurate to ∼ 0.5 m, with global bias of ∼±0.3 m; these results are comparable to those acquired via optical video, and performance trends with depth for the two sensors appear complementary. Extended to larger (inlet) domains that require the spatial coverage of marine radar imagery, algorithm performance remains at roughly the same level during slack; currents induce an unmodeled Doppler shift that produces wave frequency-and depth-dependent error that should not be neglected. Mitigation and solution strategies are discussed. With regard to the former aspect (a), sharp internal and interfacial gradients in the water column at a highly stratified estuary mouth are identified in marine radar imagery. The identified features include an internal, oblique hydraulic jump, a bottom salinity front, and a surface intrusion front. Confirmation of co-located, sharp current gradients that induce surface roughness modulations similar to those observed were carried out using remotely sensed surface current estimates (via airborne ATI-SAR) for the jump, and using vertical current profiles collected along cross-front transects via research vessel for the bottom and surface fronts. Presence of the frontal structures below the identified backscatter intensity contrast patterns is directly corroborated using salinity, temperature, and current data from bottom-mounted, ship-mounted, and ship-cast sensors, and presence of the internal jump is indirectly inferred using an inviscid two-layer model. Horizontal evolution of the jump and fronts in the estuary mouth is tracked in quasi-continuous marine radar image time series. Close

• 4. [Article] Independent Benthic Microbial Fuel Cells Powering Sensors and Acoustic Communications with the MARS Underwater Observatory

  Access to this item has been restricted by repository administrators at the request of the publisher until September 30, 2016.

  Citation × Citation Citation Abstract Copy Title: Independent Benthic Microbial Fuel Cells Powering Sensors and Acoustic Communications with the MARS Underwater Observatory Author: Reimers, Clare E., Doolan, Cody, Delaney, Jennifer, Wolf, Michael, Schrader, Paul S., Green, Dale, Girguis, Peter Access to this item has been restricted by repository administrators at the request of the publisher until September 30, 2016. Title: Independent Benthic Microbial Fuel Cells Powering Sensors and Acoustic Communications with the MARS Underwater Observatory Author: Reimers, Clare E., Doolan, Cody, Delaney, Jennifer, Wolf, Michael, Schrader, Paul S., Green, Dale, Girguis, Peter Access to this item has been restricted by repository administrators at the request of the publisher until September 30, 2016. Close

• 5. [Article] High-use areas, seasonal movements and dive patterns of juvenile loggerhead sea turtles in the Southwestern Atlantic Ocean

  To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by Inter-Research ...

  Citation × Citation Citation Abstract Copy Title: High-use areas, seasonal movements and dive patterns of juvenile loggerhead sea turtles in the Southwestern Atlantic Ocean Author: Giffoni, Bruno, Marcovaldi, Maria, Ortega, Leonardo, Sales, Gilberto, McNaughton, Lianne, Heppell, Selina S., Miller, Philip, Domingo, Andres, Swimmer, Yonat, Barcelo, Caren To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by Inter-Research and can be found at: http://www.int-res.com/home/. Title: High-use areas, seasonal movements and dive patterns of juvenile loggerhead sea turtles in the Southwestern Atlantic Ocean Author: Giffoni, Bruno, Marcovaldi, Maria, Ortega, Leonardo, Sales, Gilberto, McNaughton, Lianne, Heppell, Selina S., Miller, Philip, Domingo, Andres, Swimmer, Yonat, Barcelo, Caren To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by Inter-Research and can be found at: http://www.int-res.com/home/. Close

• 6. [Article] Laboratory investigation of dune erosion using stereo video

  Simple parameterizations of dune erosion are necessary for forecasting erosion potential prior to an oncoming storm. Dune erosion may be parameterized in terms of the elevation of the total water level ...

  Citation × Citation Citation Abstract Copy Title: Laboratory investigation of dune erosion using stereo video Author: Holman, Robert A., Palmsten, Margaret L. Simple parameterizations of dune erosion are necessary for forecasting erosion potential prior to an oncoming storm. Dune erosion may be parameterized in terms of the elevation of the total water level (composed of surge, tide, and wave runup) above the dune base and period of exposure of the dune to waves. In this work, we test several versions of this model using observations from a large wave tank experiment designed to model a storm hydrograph, and we develop a new method for acquiring the appropriate data with confidence intervals using stereo video techniques. The stereo method results in observations of dune morphology at higher spatial and temporal resolutions than traditional survey methods allow. Resolution of the stereo technique was 0.1 m in the horizontal and 0.04 m in the vertical, and errors in stereo observations were on the order of 0.02 to 0.08 m (1 to 2 pixels) when compared with surveys. A new method was developed to estimate confidence intervals on stereo observations. When the unchanging dune top was repeatedly sampled, the new confidence intervals encompassed 2 standard deviations of scatter about the mean dune surface 98% of the time. Observations from the stereo method were used to quantify wave runup and dune erosion. We tested a variety of runup statistics based on a Gaussian distribution of swash properties, and found that the most predictive statistic for dune erosion was the 16% exceedance elevation above the dune base, lower than the often used 2% exceedance value. We found that the parameterization of runup was sensitive to the definition of beach slope and that the most accurate beach slope for predicting runup was through the region of the beach profile defined by the mean water level plus one standard deviation of swash. The dune base retreated along a relatively constant trajectory that was a half of the initial beach slope. Finally, a simple model for dune erosion was tested and found to reproduce 64% of the observed variance in dune erosion rate given known forcing at the dune and 49% of the observed variance in dune erosion rate given parameterized forcing. Integrating the simple model over time, 93% of the observed dune retreat distance was reproduced given offshore forcing. Title: Laboratory investigation of dune erosion using stereo video Author: Holman, Robert A., Palmsten, Margaret L. Simple parameterizations of dune erosion are necessary for forecasting erosion potential prior to an oncoming storm. Dune erosion may be parameterized in terms of the elevation of the total water level (composed of surge, tide, and wave runup) above the dune base and period of exposure of the dune to waves. In this work, we test several versions of this model using observations from a large wave tank experiment designed to model a storm hydrograph, and we develop a new method for acquiring the appropriate data with confidence intervals using stereo video techniques. The stereo method results in observations of dune morphology at higher spatial and temporal resolutions than traditional survey methods allow. Resolution of the stereo technique was 0.1 m in the horizontal and 0.04 m in the vertical, and errors in stereo observations were on the order of 0.02 to 0.08 m (1 to 2 pixels) when compared with surveys. A new method was developed to estimate confidence intervals on stereo observations. When the unchanging dune top was repeatedly sampled, the new confidence intervals encompassed 2 standard deviations of scatter about the mean dune surface 98% of the time. Observations from the stereo method were used to quantify wave runup and dune erosion. We tested a variety of runup statistics based on a Gaussian distribution of swash properties, and found that the most predictive statistic for dune erosion was the 16% exceedance elevation above the dune base, lower than the often used 2% exceedance value. We found that the parameterization of runup was sensitive to the definition of beach slope and that the most accurate beach slope for predicting runup was through the region of the beach profile defined by the mean water level plus one standard deviation of swash. The dune base retreated along a relatively constant trajectory that was a half of the initial beach slope. Finally, a simple model for dune erosion was tested and found to reproduce 64% of the observed variance in dune erosion rate given known forcing at the dune and 49% of the observed variance in dune erosion rate given parameterized forcing. Integrating the simple model over time, 93% of the observed dune retreat distance was reproduced given offshore forcing. Close

• 7. [Article] cBathy Bathymetry Estimation in the Mixed Wave-Current Domain of a Tidal Estuary

  This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Coastal Education and Research Foundation (CERF) and can be found at: http://ww...

  Citation × Citation Citation Abstract Copy Title: cBathy Bathymetry Estimation in the Mixed Wave-Current Domain of a Tidal Estuary Author: Stanley, John, Holman, Rob This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Coastal Education and Research Foundation (CERF) and can be found at: http://www.jcronline.org/. Title: cBathy Bathymetry Estimation in the Mixed Wave-Current Domain of a Tidal Estuary Author: Stanley, John, Holman, Rob This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Coastal Education and Research Foundation (CERF) and can be found at: http://www.jcronline.org/. Close

• 8. [Article] The Diurnal Cycle of Cloud-Top Height and Cloud Cover over the Southeastern Pacific as Observed by GOES-10

  To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by the American ...

  Citation × Citation Citation Abstract Copy Title: The Diurnal Cycle of Cloud-Top Height and Cloud Cover over the Southeastern Pacific as Observed by GOES-10 Author: Minnis, Patrick, Painemal, David To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by the American Meteorological Society and can be found at: http://www.ametsoc.org/. Title: The Diurnal Cycle of Cloud-Top Height and Cloud Cover over the Southeastern Pacific as Observed by GOES-10 Author: Minnis, Patrick, Painemal, David To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by the American Meteorological Society and can be found at: http://www.ametsoc.org/. Close