Effects of foam on ocean surface microwave emission inferred from radiometric observations of reproducible breaking waves

Includes bibliographical references.WindSat, the first satellite polarimetric microwave radiometer, and the NPOESS Conical Microwave Imager/Sounder both have as a key objective the retrieval of the ocean surface wind vector from radiometric brightness temperatures. Available observations and models to date show that the wind direction signal is only 1-3 K peak-to-peak at 19 and 37 GHz, much smaller than the wind speed signal. In order to obtain sufficient accuracy for reliable wind direction retrieval, uncertainties in geophysical modeling of the sea surface emission on the order of 0.2 K need to be removed. The surface roughness spectrum has been addressed by many studies, but the azimuthal signature of the microwave emission from breaking waves and foam has not been adequately addressed. RECENtly, a number of experiments have been conducted to quantify the increase in sea surface microwave emission due to foam. Measurements from the Floating Instrumentation Platform indicated that the increase in ocean surface emission due to breaking waves may depend on the incidence and azimuth angles of observation. The need to quantify this dependence motivated systematic measurement of the microwave emission from reproducible breaking waves as a function of incidence and azimuth angles. A number of empirical parameterizations of whitecap coverage with wind speed were used to estimate the increase in brightness temperatures measured by a satellite microwave radiometer due to wave breaking in the field of view. These results provide the first empirically based parameterization with wind speed of the effect of breaking waves and foam on satellite brightness temperatures at 10.8, 19, and 37 GHz.This work was supported in part by the Department of the Navy, Office of Naval Research under Awards N00014-00-1-0615 (ONR/YIP) and N00014-03-1-0044 (Space and Remote Sensing) to the University of Massachusetts Amherst, and N00014-00-1-0152 (Space and Remote Sensing) to the University of Washington. The National Polar-orbiting Operational environmental Satellite System Integrated Program Office supported the Naval Research Laboratory's participation through Award NA02AANEG0338 and supported data analysis at Colorado State University and the University of Washington through Award NA05AANEG0153

Development Of An Improved Microwave Ocean Surface Emissivity Radiative Transfer Model

An electromagnetic model is developed for predicting the microwave blackbody emission from the ocean surface over a wide range of frequencies, incidence angles, and wind vector (speed and direction) for both horizontal and vertical polarizations. This ocean surface emissivity model is intended to be incorporated into an oceanic radiative transfer model to be used for microwave radiometric applications including geophysical retrievals over oceans. The model development is based on a collection of published ocean emissivity measurements obtained from satellites, aircraft, field experiments, and laboratory measurements. This dissertation presents the details of methods used in the ocean surface emissivity model development and comparisons with current emissivity models and aircraft radiometric measurements in hurricanes. Especially, this empirically derived ocean emissivity model relates changes in vertical and horizontal polarized ocean microwave brightness temperature measurements over a wide range of observation frequencies and incidence angles to physical roughness changes in the ocean surface, which are the result of the air/sea interaction with surface winds. Of primary importance are the Stepped Frequency Microwave Radiometer (SFMR) brightness temperature measurements from hurricane flights and independent measurements of surface wind speed that are used to define empirical relationships between C-band (4 - 7 GHz) microwave brightness temperature and surface wind speed. By employing statistical regression techniques, we develop a physical-based ocean emissivity model with empirical coefficients that depends on geophysical parameters, such as wind speed, wind direction, sea surface temperature, and observational parameters, such as electromagnetic frequency, electromagnetic polarization, and incidence angle

An Ocean Surface Wind Vector Model Function For A Spaceborne Microwave Radiometer And Its Application

Ocean surface wind vectors over the ocean present vital information for scientists and forecasters in their attempt to understand the Earth\u27s global weather and climate. As the demand for global wind velocity information has increased, the number of satellite missions that carry wind-measuring sensors has also increased; however, there are still not sufficient numbers of instruments in orbit today to fulfill the need for operational meteorological and scientific wind vector data. Over the last three decades operational measurements of global ocean wind speeds have been obtained from passive microwave radiometers. Also, vector ocean surface wind data were primarily obtained from several scatterometry missions that have flown since the early 1990\u27s. However, other than SeaSat-A in 1978, there has not been combined active and passive wind measurements on the same satellite until the launch of the second Advanced Earth Observing Satellite (ADEOS-II) in 2002. This mission has provided a unique data set of coincident measurements between the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR). AMSR observes the vertical and horizontal brightness temperature (TB) at six frequency bands between 6.9 GHz and 89.0 GHz. Although these measurements contain some wind direction information, the overlying atmospheric influence can easily obscure this signal and make wind direction retrieval from passive microwave measurements very difficult. However, at radiometer frequencies between 10 and 37 GHz, a certain linear combination of vertical and horizontal brightness temperatures causes the atmospheric dependence to be nearly cancelled and surface parameters such as wind speed, wind direction and sea surface temperature to dominate the resulting signal. This brightness temperature combination may be expressed as ATBV-TBH, where A is a constant to be determined and the TBV and TBH are the brightness temperatures for the vertical and horizontal polarization respectively. In this dissertation, an empirical relationship between the AMSR\u27s ATBV-TBH and SeaWinds\u27 surface wind vector retrievals was established for three microwave frequencies: 10, 18 and 37 GHz. This newly developed model function for a passive microwave radiometer could provide the basis for wind vector retrievals either separately or in combination with scatterometer measurements

Faraday Rotation Correction for Passive Microwave Remote Sensing from Space

Faraday rotation (FR) is one of the main error sources for passive microwave remote sensing from space especially in frequencies less than or equal to 10.7 GHz. In this paper, Faraday rotation correction for the vertical brightness temperature at L band and the third Stokes parameter brightness temperature at 10.7 GHz are discussed. Two approaches are studied to remove the influence of FR: correction by auxiliary data and correction by polarimetric mode. At 1.4 GHz, correction by polarimetric mode performs better than correction by auxiliary data. At 10.7 GHz, correction by auxiliary data is feasible while polarimetric mode correction becomes invalid. We propose a new method of using TEC data released by international GNSS service (IGS) for correction. It has been proved that the residual correction errors are reduced. IGS data method greatly improves the correction accuracy

Inter-satellite Microwave Radiometer Calibration

The removal of systematic brightness temperature (Tb) biases is necessary when producing decadal passive microwave data sets for weather and climate research. It is crucial to achieve Tb measurement consistency among all satellites in a constellation as well as to maintain sustained calibration accuracy over the lifetime of each satellite sensor. In-orbit inter-satellite radiometric calibration techniques provide a long term, group-wise solution; however, since radiometers operate at different frequencies and viewing angles, Tb normalizations are made before making intermediate comparisons of their near-simultaneous measurements. In this dissertation, a new approach is investigated to perform these normalizations from one satellite\u27s measurements to another. It uses Taylor\u27s series expansion around a source frequency to predict Tb of a desired frequency. The relationship between Tb\u27s and frequencies are derived from simulations using an oceanic Radiative Transfer Model (RTM) over a wide variety of environmental conditions. The original RTM is built on oceanic radiative transfer theory. Refinements are made to the model by modifying and tuning algorithms for calculating sea surface emission, atmospheric emission and attenuations. Validations were performed with collocated WindSat measurements. This radiometric calibration approach is applied to establish an absolute brightness temperature reference using near-simultaneous pair-wise comparisons between a non-sun synchronous radiometer and two sun-synchronous polar-orbiting radiometers: the Tropical Rain Measurement Mission (TRMM) Microwave Imager (TMI), WindSat (on Coriolis) and Advanced Microwave Scanning Radiometer (AMSR) on Advanced Earth Observing System -II (ADEOSII), respectively. Collocated measurements between WindSat and TMI as well as between AMSR and TMI, within selected 10 weeks in 2003 for each pair, are collected, filtered and applied in the cross calibration. AMSR is calibrated to WindSat using TMI as a transfer standard. Accuracy prediction and error source analysis are discussed along with calibration results. This inter-satellite radiometric calibration approach provides technical support for NASA\u27s Global Precipitation Mission which relies on a constellation of cooperative satellites with a variety of microwave radiometers to make global rainfall measurements

The Hurricane Imaging Radiometer (HIRAD): Instrument Status and Performance Predictions

The Hurricane Imaging Radiometer (HIRAD) is an innovative radiometer which offers new and unique remotely sensed observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR) [Uhlhorn and Black, 2004]. The HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology [Ruf et al., 1988]. This sensor operates over 4-7 GHz, where the required tropical cyclone remote sensing physics has been validated by both SFMR and WindSat radiometer [Bettenhausen et al., 2006; Brown et al., 2006]. HIRAD incorporates a new and unique array antenna design along with several technologies successfully demonstrated by the Lightweight Rain Radiometer instrument [Ruf et al., 2002; Ruf and Principe, 2003]. HIRAD will be a compact, lightweight, low-power instrument with no moving parts that will produce wide-swath imagery of ocean winds and rain in hurricane conditions. Accurate observations of surface ocean vector winds (OVW) with high spatial and temporal resolution are required for understanding and predicting tropical cyclones. The Hurricane Imaging Radiometer (HIRAD) is an innovative architecture which offers new and unique remotely sensed observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR), which is a proven remote sensing technique for observing tropical cyclone (TC) ocean surface wind speeds and rain rates. The proposed HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology combined with a a unique array antenna design. The overarching design concept of HIRAD is to combine the multi-frequency C-band observing strategy of the SFMR with STAR technology to produce a wide-swath imager. Single frequency STAR technology The Hurricane Imaging Radiometer (HIRAD) is an innovative radiometer which offers new and unique remotely sensed observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR) [Uhlhorn and Black, 2004]. The HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology [Ruf et al., 1988]. This sensor operates over 4-7 GHz, where the required tropical cyclone remote sensing physics has been validated by both SFMR and WindSat radiometer [Bettenhausen et al., 2006; Brown et al., 2006]. HIRAD incorporates a new and unique array antenna design along with several technologies successfully demonstrated by the Lightweight Rain Radiometer instrument [Ruf et al., 2002; Ruf and Principe, 2003]. HIRAD will be a compact, lightweight, low-power instrument with no moving parts that will produce wide-swath imagery of ocean winds and rain in hurricane conditions. Accurate observations of surface ocean vector winds (OVW) with high spatial and temporal resolution are required for understanding and predicting tropical cyclones. The Hurricane Imaging Radiometer (HIRAD) is an innovative architecture which offers new and unique remotely sensed observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR), which is a proven remote sensing technique for observing tropical cyclone (TC) ocean surface wind speeds and rain rates. The proposed HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology combined with a a unique array antenna design. The overarching design concept of HIRAD is to combine the multi-frequency C-banbserving strategy of the SFMR with STAR technology to produce a wide-swath imager. Single frequency STAR technolog

Ocean Vector Wind Measurement Potential from the Global Precipitation Measurement Mission using a Combined Active and Passive Algorithm

Ocean surface vector wind (OVW) is an essential parameter for understanding the physics and dynamics of the ocean-atmosphere system, thereby improving weather forecasting and climate studies. Satellite scatterometers, synthetic aperture radars, and polarimetric microwave radiometers have provided almost global coverage of ocean surface vector wind for the last four decades. Nonetheless, a consistent and uninterrupted long-time data record with the capability of resolving sub-diurnal variability has remained a critical challenge over the years. The Global Precipitation Measurement Mission (GPM) is a satellite mission designed to provide space-based precipitation information on a global scale with complete diurnal sampling. This dissertation presents a combined active and passive retrieval algorithm to investigate the feasibility of ocean surface vector wind measurements from the GPM core satellite by utilizing its Ku- and Ka-band Dual-frequency Precipitation Radar (DPR) and the multi-frequency GPM Microwave Imager (GMI) observations. The unique GPM active and passive geophysical model functions were empirically developed by characterizing the anisotropic nature of ocean backscatter of normalized radar cross-section (δ°) and brightness temperature (TB) at multiple bands. For passive GMF, the modified 2nd Stoke\u27s parameter (linear combination of V and H-pol TBs) was used to mitigate the atmospheric contamination and to enhance the anisotropic wind direction signal superimposed on GMI TBs. The GMFs were combined in a maximum likelihood estimation (MLE) algorithm to infer the OVW. Finally, the retrieval algorithm was validated by comparing OVW retrievals with collocated NASA Advanced Scatterometer (ASCAT) wind vectors. The wind speed and direction retrieval performance statistics are promising and comparable with those of conventional scatterometer and polarimetric radiometer data products. The algorithm demonstrates the capability of the GPM to provide a long-term OVW data record for the entire GPM-TRMM era, which may include unique monthly diurnal OVW statistics

Insights on the OAFlux ocean surface vector wind analysis merged from scatterometers and passive microwave radiometers (1987 onward)

Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 119 (2014): 5244–5269, doi:10.1002/2013JC009648.A high-resolution global daily analysis of ocean surface vector winds (1987 onward) was developed by the Objectively Analyzed air-sea Fluxes (OAFlux) project. This study addressed the issues related to the development of the time series through objective synthesis of 12 satellite sensors (two scatterometers and 10 passive microwave radiometers) using a least-variance linear statistical estimation. The issues include the rationale that supports the multisensor synthesis, the methodology and strategy that were developed, the challenges that were encountered, and the comparison of the synthesized daily mean fields with reference to scatterometers and atmospheric reanalyses. The synthesis was established on the bases that the low and moderate winds (<15 m s−1) constitute 98% of global daily wind fields, and they are the range of winds that are retrieved with best quality and consistency by both scatterometers and radiometers. Yet, challenges are presented in situations of synoptic weather systems due mainly to three factors: (i) the lack of radiometer retrievals in rain conditions, (ii) the inability to fill in the data voids caused by eliminating rain-flagged QuikSCAT wind vector cells, and (iii) the persistent differences between QuikSCAT and ASCAT high winds. The study showed that the daily mean surface winds can be confidently constructed from merging scatterometers with radiometers over the global oceans, except for the regions influenced by synoptic weather storms. The uncertainties in present scatterometer and radiometer observations under high winds and rain conditions lead to uncertainties in the synthesized synoptic structures.The project is sponsored by the NASA Ocean Vector Wind Science Team (OVWST) activities under grant NNA10AO86G.2015-02-1

A Roughness Correction for Aquarius Ocean Brightness Temperature Using the CONAE MicroWave Radiometer

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) 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

Simulation Of Brightness Temperatures For The Microwave Radiometer On The Aquarius/sac-d Mission.

Microwave radiometers are highly sensitive receivers capable of measuring low levels of natural blackbody microwave emissions. Remote sensing by satellite microwave radiometers flying on low-earth, polar orbiting, satellites can infer a variety of terrestrial and atmospheric geophysical parameters for scientific and operational applications, such as weather and climate prediction. The objective of this thesis is to provide realistic simulated ocean brightness temperatures for the 3-channel Microwave Radiometer (MWR), which will be launched in May 2010 on the joint NASA/CONAE Aquarius/SAC-D Mission. These data will be used for pre-launch geophysical retrieval algorithms development and validation testing. Analyses are performed to evaluate the proposed MWR measurement geometry and verify the requirements for spatial/temporal sampling. Finally, a preliminary study is performed for the post-launch inter-satellite radiometric calibration using the WindSat polarimetric radiometer on the Coriolis satellite