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DEVELOPMENT OF AN OCEANIC RAIN ACCUMULATION PRODUCT IN SUPPORT OF SEA SURFACE SALINITY MEASUREMENTS FROM AQUARIUS/SAC-D
Title
DEVELOPMENT OF AN OCEANIC RAIN ACCUMULATION PRODUCT IN SUPPORT OF SEA SURFACE SALINITY MEASUREMENTS FROM AQUARIUS/SAC-D.
Creator
Aslebagh, Shadi, Jones, W, Wahid, Parveen, Junek, William, University of Central Florida
Abstract / Description
Aquarius/SAC-D is a joint mission by National Aeronautics and Space Administration (NASA) and the Comision Nacional de Actividades Espaciales (CONAE), Argentine Space Agency. The satellite was launched in June 2011 and the prime remote sensing instrument is also named Aquarius (AQ). The main objective of this science program is to provide Sea Surface Salinity (SSS) maps of the global oceans every 7 days for understanding the Earth's hydrologic cycle and for assessing long-term global climate...
Show moreAquarius/SAC-D is a joint mission by National Aeronautics and Space Administration (NASA) and the Comision Nacional de Actividades Espaciales (CONAE), Argentine Space Agency. The satellite was launched in June 2011 and the prime remote sensing instrument is also named Aquarius (AQ). The main objective of this science program is to provide Sea Surface Salinity (SSS) maps of the global oceans every 7 days for understanding the Earth's hydrologic cycle and for assessing long-term global climate change.The Aquarius instrument was built jointly by NASA's Goddard Space Flight Center and the Jet Propulsion Laboratory. It is an active/passive L-band remote sensor that measures ocean brightness temperature (Tb) and radar backscatter, and these quantities are used to infer sea surface salinity.Other environmental parameters (e.g., sea surface temperature, wind speed and rain) also affect the microwave emitted radiance or brightness temperature. The SSS geophysical retrieval algorithm considers all these environmental parameters and makes the Tb corrections before retrieving SSS. Instantaneous rainfall can cause increase roughness that raises the ocean surface Tb. Further short term rain accumulation can produce a fresh water lens that floats on the ocean surface and dilutes the surface salinity.This thesis presents results of a study to develop an oceanic rain accumulation (RA) product that may be valuable to remote sensing engineers and algorithm developers and Aquarius scientists. The use of this RA product, along with in situ ocean salinity measurements from buoys, may be used to mitigate the effects of rain on the SSS retrieval.
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Date Issued
2013
Identifier
CFE0004647, ucf:49906
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004647
A Roughness Correction for Aquarius Ocean Brightness Temperature Using the CONAE MicroWave Radiometer
Title
A Roughness Correction for Aquarius Ocean Brightness Temperature Using the CONAE MicroWave Radiometer.
Creator
Hejazin, Yazan, Jones, W Linwood, Wahid, Parveen, Mikhael, Wasfy, Junek, William, Piepmeier, Jeffrey, University of Central Florida
Abstract / Description
Aquarius/SAC-D is a joint NASA/CONAE (Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using an L-band radiometer that measures ocean brightness temperature (Tb). The application of L-band radiometry to retrieve SSS is a difficult task, and therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that (")warms(") the ocean Tb. The Aquarius (AQ)...
Show moreAquarius/SAC-D is a joint NASA/CONAE (Argentine Space Agency) Earth Sciences satellite mission to measure global sea surface salinity (SSS), using an L-band radiometer that measures ocean brightness temperature (Tb). The application of L-band radiometry to retrieve SSS is a difficult task, and therefore, precise Tb corrections are necessary to obtain accurate measurements. One of the major error sources is the effect of ocean roughness that (")warms(") the ocean Tb. The Aquarius (AQ) instrument (L-band radiometer/scatterometer) baseline approach uses the radar scatterometer to provide this ocean roughness correction, through the correlation of radar backscatter with the excess ocean emissivity.In contrast, this dissertation develops an ocean roughness correction for AQ measurements using the MicroWave Radiometer (MWR) instrument Tb measurements at Ka-band to remove the errors that are caused by ocean wind speed and direction. The new ocean emissivity radiative transfer model was tuned using one year (2012) of on-orbit combined data from the MWR and the AQ instruments that are collocated in space and time. The roughness correction in this paper is a theoretical Radiative Transfer Model (RTM) driven by numerical weather forecast model surface winds, combined with ancillary satellite data from WindSat and SSMIS, and environmental parameters from NCEP. This RTM provides an alternative approach for estimating the scatterometer-derived roughness correction, which is independent. The theoretical basis of the algorithm is described and results are compared with the AQ baseline scatterometer method. Also results are presented for a comparison of AQ SSS retrievals using both roughness corrections.
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Date Issued
2015
Identifier
CFE0005625, ucf:50218
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005625
Forecasting Volcanic Activity Using An Event Tree Analysis System and Logistic Regression
Title
Forecasting Volcanic Activity Using An Event Tree Analysis System and Logistic Regression.
Creator
Junek, William, Jones, W, Simaan, Marwan, Foroosh, Hassan, Woods, Mark, University of Central Florida
Abstract / Description
Forecasts of short term volcanic activity are generated using an event tree process that is driven by a set of empirical statistical models derived through logistic regression. Each of the logistic models are constructed from a sparse and geographically diverse dataset that was assembled from a collection of historic volcanic unrest episodes. The dataset consists of monitoring measurements (e.g. seismic), source modeling results, and historic eruption information. Incorporating this data into...
Show moreForecasts of short term volcanic activity are generated using an event tree process that is driven by a set of empirical statistical models derived through logistic regression. Each of the logistic models are constructed from a sparse and geographically diverse dataset that was assembled from a collection of historic volcanic unrest episodes. The dataset consists of monitoring measurements (e.g. seismic), source modeling results, and historic eruption information. Incorporating this data into a single set of models provides a simple mechanism for simultaneously accounting for the geophysical changes occurring within the volcano and the historic behavior of analog volcanoes. A bootstrapping analysis of the training dataset allowed for the estimation of robust logistic model coefficients. Probabilities generated from the logistic models increase with positive modeling results, escalating seismicity, and high eruption frequency. The cross validation process produced a series of receiver operating characteristic (ROC) curves with areas ranging between 0.78 - 0.81, which indicate the algorithm has good predictive capabilities. In addition, ROC curves also allowed for the determination of a false positive rate and optimum detection threshold for each stage of the algorithm. The results demonstrate the logistic models are highly transportable and can compete with, and in some cases outperform, non-transportable empirical models trained with site specific information. The incorporation of source modeling results into the event tree's decision making process has begun the transition of volcano monitoring applications from simple mechanized pattern recognition algorithms to a physical model based forecasting system.
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Date Issued
2012
Identifier
CFE0004253, ucf:49517
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0004253
Investigation of the effect of rain on sea surface salinity
Title
Investigation of the effect of rain on sea surface salinity.
Creator
Santos Garcia, Andrea, Jones, W Linwood, Mikhael, Wasfy, Wahid, Parveen, Junek, William, Asher, William, Wilheit, Thomas, University of Central Florida
Abstract / Description
The Aquarius/SAC-D mission provided Sea Surface Salinity (SSS), globally over the ocean, for almost 4 years. As a member of the AQ/SAC-D Cal/Val team, the Central Florida Remote Sensing Laboratory has analyzed these salinity measurements in the presence of precipitation and has noted the high correlation between the spatial patterns of reduced SSS and the spatial distribution of rain. It was determined that this is the result of a cause and effect relation, and not SSS measurement errors....
Show moreThe Aquarius/SAC-D mission provided Sea Surface Salinity (SSS), globally over the ocean, for almost 4 years. As a member of the AQ/SAC-D Cal/Val team, the Central Florida Remote Sensing Laboratory has analyzed these salinity measurements in the presence of precipitation and has noted the high correlation between the spatial patterns of reduced SSS and the spatial distribution of rain. It was determined that this is the result of a cause and effect relation, and not SSS measurement errors. Thus, it is important to understand these salinity changes due to seawater dilution by rain and the associated near-surface salinity strati?cation. This research addresses the effects of rainfall on the Aquarius (AQ) SSS retrieval using a macro-scale Rain Impact Model (RIM). This model, based on the superposition of a one-dimension eddy diffusion (turbulent diffusion) model, relates SSS to depth, rainfall accumulation and time since rain. To identify instantaneous and prior rainfall accumulations, a Rain Accumulation product was developed. This product, based on the NOAA CMORPH precipitation data set, provides the rainfall history for 24 hours prior to the satellite observation time, which is integrated over each AQ IFOV. In this research results of the RIM validation are presented by comparing AQ and SMOS measured and RIM simulated SSS. The results show the high cross correlation for these comparisons and also with the corresponding SSS anomalies relative to HYCOM.
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Date Issued
2016
Identifier
CFE0006175, ucf:51133
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0006175
CONAE MicroWave Radiometer (MWR) Counts to Brightness Temperature Algorithm
Title
CONAE MicroWave Radiometer (MWR) Counts to Brightness Temperature Algorithm.
Creator
Ghazi, Zoubair, Jones, W Linwood, Wei, Lei, Mikhael, Wasfy, Wu, Thomas, Junek, William, Piepmeier, Jeffrey, University of Central Florida
Abstract / Description
This dissertation concerns the development of the MicroWave Radiometer (MWR) brightness temperature (Tb) algorithm and the associated algorithm validation using on-orbit MWR Tb measurements. This research is sponsored by the NASA Earth Sciences Aquarius Mission, a joint international science mission, between NASA and the Argentine Space Agency (Comision Nacional de Actividades Espaciales, CONAE). The MWR is a CONAE developed passive microwave instrument operating at 23.8 GHz (K-band) H-pol...
Show moreThis dissertation concerns the development of the MicroWave Radiometer (MWR) brightness temperature (Tb) algorithm and the associated algorithm validation using on-orbit MWR Tb measurements. This research is sponsored by the NASA Earth Sciences Aquarius Mission, a joint international science mission, between NASA and the Argentine Space Agency (Comision Nacional de Actividades Espaciales, CONAE). The MWR is a CONAE developed passive microwave instrument operating at 23.8 GHz (K-band) H-pol and 36.5 GHz (Ka-band) H- (&) V-pol designed to complement the Aquarius L-band radiometer/scatterometer, which is the prime sensor for measuring sea surface salinity (SSS). MWR measures the Earth's brightness temperature and retrieves simultaneous, spatially collocated, environmental measurements (surface wind speed, rain rate, water vapor, and sea ice concentration) to assist in the measurement of SSS.This dissertation research addressed several areas including development of: 1) a signal processing procedure for determining and correcting radiometer system non-linearity; 2) an empirical method to retrieve switch matrix loss coefficients during thermal-vacuum (T/V) radiometric calibration test; and 3) an antenna pattern correction (APC) algorithm using Inter-satellite radiometric cross-calibration of MWR with the WindSat satellite radiometer. The validation of the MWR counts-to-Tb algorithm was performed using two years of on-orbit data, which included special deep space calibration measurements and routine clear sky ocean/land measurements.
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Date Issued
2014
Identifier
CFE0005496, ucf:50366
Format
Document (PDF)
PURL
http://purl.flvc.org/ucf/fd/CFE0005496