The Experts below are selected from a list of 285 Experts worldwide ranked by ideXlab platform

Frank J Wentz - One of the best experts on this subject based on the ideXlab platform.

  • wind vector retrievals under rain with Passive Satellite microwave radiometers
    IEEE Transactions on Geoscience and Remote Sensing, 2009
    Co-Authors: Thomas Meissner, Frank J Wentz
    Abstract:

    We have developed algorithms that retrieve ocean-surface wind speed and direction under rain using brightness-temperature (TB) measurements from Passive Satellite microwave radiometers. For accurate radiometer retrievals of wind speeds in the rain, it is essential to use TB signals at different frequencies, whose spectral signature makes it possible to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. The wind-speed retrieval accuracy of an algorithm that utilizes C-band frequencies and is trained for tropical cyclones ranges from 2.0 m/s in light rain to 4.0 m/s in heavy rain. We have also trained and tested global algorithms that are less accurate in tropical storms but can be applied under all conditions. The wind-direction retrieval accuracy degrades from about 10deg in light rain to 30deg at the onset of heavy rain. We compare the performance of wind-vector retrievals under rain from microwave radiometers with those from scatterometers and discuss advantages and shortcomings of both instruments. We have also analyzed the wind-induced sea-surface emissivity, including its wind-direction dependence for wind speeds up to 45 m/s.

  • wind vector retrievals under rain with Passive Satellite microwave radiometers
    Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment - MicroRad'08, 2009
    Co-Authors: Thomas Meissner, Frank J Wentz
    Abstract:

    We have developed algorithms that retrieve ocean-surface wind speed and direction under rain using brightness-temperature (TB) measurements from Passive Satellite microwave radiometers. For accurate radiometer retrievals of wind speeds in the rain, it is essential to use TB signals at different frequencies, whose spectral signature makes it possible to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. The wind-speed retrieval accuracy of an algorithm that utilizes C-band frequencies and is trained for tropical cyclones ranges from 2.0 m/s in light rain to 4.0 m/s in heavy rain. We have also trained and tested global algorithms that are less accurate in tropical storms but can be applied under all conditions. The wind-direction retrieval accuracy degrades from about 10° in light rain to 30° at the onset of heavy rain. We compare the performance of wind-vector retrievals under rain from microwave radiometers with those from scatterometers and discuss advantages and shortcomings of both instruments. We have also analyzed the wind-induced sea-surface emissivity, including its wind-direction dependence for wind speeds up to 45 m/s.

  • Wind retrievals under rain for Passive Satellite microwave radiometers and its application to hurricane tracking
    2008 Microwave Radiometry and Remote Sensing of the Environment, 2008
    Co-Authors: Thomas Meissner, Frank J Wentz
    Abstract:

    We have developed an algorithm that retrieves wind speed under rain using C-band and X-band channels of Passive microwave Satellite radiometers. The spectral difference of the brightness temperature signals due to wind or rain allows to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. We have trained a statistical algorithm that applies under hurricane conditions and is able to measure wind speeds in hurricanes to an estimated accuracy of about 2 m/s. We have also developed a global algorithm, that is less accurate but can be applied under all conditions. Its estimated accuracy is between 2 and 5 m/s, depending on wind speed and rain rate. We also extend the wind speed region in our model for the wind induced sea surface emissivity from currently 20 m/s to 40 m/s. The data indicate that the signal starts to saturate above 30 m/s. Finally, we make an assessment of the performance of wind direction retrievals from polarimetric radiometers as function of wind speed and rain rate.

Sungwook Hong - One of the best experts on this subject based on the ideXlab platform.

  • detection of small scale roughness and refractive index of sea ice in Passive Satellite microwave remote sensing
    Remote Sensing of Environment, 2010
    Co-Authors: Sungwook Hong
    Abstract:

    Polar ice masses and sheets are sensitive indicators of climate change. Small-scale surface roughness significantly impacts the microwave emission of the sea ice/snow surface; however, published results of surface roughness measurements of sea ice are rare. Knowing the refractive index is important to discriminate between objects. In this study, the small-scale roughness and refractive index over sea ice are estimated with AMSR-E observations and a unique method. Consequently, the small-scale surface roughness of 0.25 cm to 0.5 cm at AMSR-E 6.9 GHz shows reasonable agreement with the results of known observations, ranging from 0.2 cm to 0.6 cm for the sea ice in the Antarctic and Arctic regions. The refractive indexes are retrieved from 1.6 to 1.8 for winter, from 1.2 to 1.4 for summer in the Arctic and the Antarctic, which are similar to those of the sea ice and results from previous studies. This research shows the physical characteristics of the sea ice edges and melting process. Accordingly, this investigation provides an effective procedure for retrieving the small-scale roughness and refractive index of sea ice and snow. Another advantage of this study is the ability to distinguish sea ice from the sea surface by their relative small-scale roughness.

F. Remy - One of the best experts on this subject based on the ideXlab platform.

  • SYNERGY OF ACTIVE AND Passive Satellite MICROWAVE DATA FOR CRYOSPHERIC STUDIES
    2005
    Co-Authors: A.v. Kouraev, F. Papa, N.m. Mognard, A. Cazenave, J.-f. Cretaux, Elena Zakharova, Sergei V. Semovski, F. Remy
    Abstract:

    RESUME We demonstrate benefits, drawbacks and potential for application of use of the TOPEX/Poseidon simultaneous active (backscatter coefficient at 13 GHz) and Passive (brightness temperature at 18 and 37 GHz) microwave measurements together with SMMR and SSM/I Passive microwave data to estimate sea, lake and river ice extent and timing. We present results of studies for the Caspian and Aral seas, Baikal lake and Ob' river watershed. This synergetic approach for combination of active (radar altimeter) and Passive (radiometers) microwave data may be successfully used for new Satellite missions, such as Jason-1 and ENVISAT. 1. INTODUCTION Studies of continental sea, lake and river ice require continuous weather-independent observations, covering large and often remote areas. In situ observations are rather sparse in these environments. In many instances, existing monitoring networks suffer from problems that prevent to routinely monitor natural parameters. Often data exist, but are not accessible to the public - for many arctic regions time series of observations on ice cover are available only up to early 1990s. Even when data are available, there are often issues of time resolution (which is often insufficient) and delivery time (for the cases of near real-time studies). Satellite observations could be a valuable support for ice monitoring and studies. However, for many natural objects application of Satellite data has been mostly limited to imagery in the visible and infra-red range, sensitive to presence of cloud. Satellite microwave measurements for ice studies have advantage because they are not influenced by cloud cover, and do not depend on daylight availability, providing weather- independent, continuous and reliable data on various environmental parameters. We show that additional improvement lies in complementing Passive microwave observations by active ones, thus enhancing the radiometric resolution of studies and providing new insights for cryospheric studies.

  • Synergy of active and Passive Satellite microwave data for the study of first-year sea ice in the Caspian and Aral seas
    IEEE Transactions on Geoscience and Remote Sensing, 2004
    Co-Authors: A.v. Kouraev, F. Papa, N.m. Mognard, P.i. Buharizin, A. Cazenave, J.-f. Cretaux, J. Dozortseva, F. Remy
    Abstract:

    The paper discusses application of active and Passive microwave data for assessment of time and space variations of first-year ice cover. The Caspian and Aral seas are chosen as main study areas. The Caspian Sea evolution is primarily climate driven, while for the Aral Sea there is a mix of anthropic and climate factors. We analyze ice cover conditions using a novel method that combines active and Passive Satellite measurements for ice discrimination. This method uses the synergy of simultaneous data from active (radar altimeter) and Passive (radiometer) microwave instruments onboard the TOPEX/Poseidon (T/P) Satellite, launched in 1992. The benefits, drawbacks, and potential of ice cover studies using the proposed method are discussed. We analyze in detail how this method is influenced by the difference in footprints of the T/P sensors and by the radiometric properties of ice and snow at different stages of ice cover evolution. In order to link the T/P-derived results to historical observations that end in the mid-1980s, long time series of Passive microwave data from SMMR and SSM/I sensors have also been analyzed. Satellite time series of ice cover extent and duration of ice period have been obtained for the Caspian and Aral seas since 1978. A good agreement is obtained between historical and Satellite data, with significant spatial and temporal variability of ice conditions. There is a marked decrease of both duration of ice season and ice extent during the winters 1998/1999-2001/2002. These Satellite-derived time series of sea ice parameters are very valuable in view of the heterogeneous and mostly unpublished data on ice conditions over the Caspian and Aral seas since the mid-1980s.

Thomas Meissner - One of the best experts on this subject based on the ideXlab platform.

  • wind vector retrievals under rain with Passive Satellite microwave radiometers
    IEEE Transactions on Geoscience and Remote Sensing, 2009
    Co-Authors: Thomas Meissner, Frank J Wentz
    Abstract:

    We have developed algorithms that retrieve ocean-surface wind speed and direction under rain using brightness-temperature (TB) measurements from Passive Satellite microwave radiometers. For accurate radiometer retrievals of wind speeds in the rain, it is essential to use TB signals at different frequencies, whose spectral signature makes it possible to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. The wind-speed retrieval accuracy of an algorithm that utilizes C-band frequencies and is trained for tropical cyclones ranges from 2.0 m/s in light rain to 4.0 m/s in heavy rain. We have also trained and tested global algorithms that are less accurate in tropical storms but can be applied under all conditions. The wind-direction retrieval accuracy degrades from about 10deg in light rain to 30deg at the onset of heavy rain. We compare the performance of wind-vector retrievals under rain from microwave radiometers with those from scatterometers and discuss advantages and shortcomings of both instruments. We have also analyzed the wind-induced sea-surface emissivity, including its wind-direction dependence for wind speeds up to 45 m/s.

  • wind vector retrievals under rain with Passive Satellite microwave radiometers
    Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment - MicroRad'08, 2009
    Co-Authors: Thomas Meissner, Frank J Wentz
    Abstract:

    We have developed algorithms that retrieve ocean-surface wind speed and direction under rain using brightness-temperature (TB) measurements from Passive Satellite microwave radiometers. For accurate radiometer retrievals of wind speeds in the rain, it is essential to use TB signals at different frequencies, whose spectral signature makes it possible to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. The wind-speed retrieval accuracy of an algorithm that utilizes C-band frequencies and is trained for tropical cyclones ranges from 2.0 m/s in light rain to 4.0 m/s in heavy rain. We have also trained and tested global algorithms that are less accurate in tropical storms but can be applied under all conditions. The wind-direction retrieval accuracy degrades from about 10° in light rain to 30° at the onset of heavy rain. We compare the performance of wind-vector retrievals under rain from microwave radiometers with those from scatterometers and discuss advantages and shortcomings of both instruments. We have also analyzed the wind-induced sea-surface emissivity, including its wind-direction dependence for wind speeds up to 45 m/s.

  • Wind retrievals under rain for Passive Satellite microwave radiometers and its application to hurricane tracking
    2008 Microwave Radiometry and Remote Sensing of the Environment, 2008
    Co-Authors: Thomas Meissner, Frank J Wentz
    Abstract:

    We have developed an algorithm that retrieves wind speed under rain using C-band and X-band channels of Passive microwave Satellite radiometers. The spectral difference of the brightness temperature signals due to wind or rain allows to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. We have trained a statistical algorithm that applies under hurricane conditions and is able to measure wind speeds in hurricanes to an estimated accuracy of about 2 m/s. We have also developed a global algorithm, that is less accurate but can be applied under all conditions. Its estimated accuracy is between 2 and 5 m/s, depending on wind speed and rain rate. We also extend the wind speed region in our model for the wind induced sea surface emissivity from currently 20 m/s to 40 m/s. The data indicate that the signal starts to saturate above 30 m/s. Finally, we make an assessment of the performance of wind direction retrievals from polarimetric radiometers as function of wind speed and rain rate.

Malik Chami - One of the best experts on this subject based on the ideXlab platform.

  • Determination of sea surface wind speed using the polarimetric and multidirectional properties of Satellite measurements in visible bands
    Geophysical Research Letters, 2012
    Co-Authors: Tristan Harmel, Malik Chami
    Abstract:

    [1] The reflection of the direct sunlight onto the rough sea surface (sun glint) generates a strong signal which is informative on wind speed. An original method is described to determine the wind speed values and their associated uncertainty over the ocean using multidirectional and polarimetric data measured by a Passive Satellite sensor in the visible/near infrared bands, namely PARASOL sensor. The method is able to derive wind speed values for almost 80% of a cloud-free scene. Comparisons with buoys and with the operational wind product of the AMSR-E sensor (NASA) show a satisfactory agreement (coefficient of correlation r > 0.84). This study demonstrates that Passive Satellite sensors that are able to measure the polarization and multidirectionality features of the radiation at solar wavelengths can be relevant alternative approaches to quantify the wind speed at a spatial resolution at least four times higher than that currently obtained using Passive or active microwave sensors.