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Gabrielle De Lannoy - One of the best experts on this subject based on the ideXlab platform.

  • preCipitation estimation using l Band and C Band soil moisture retrievals
    Water Resources Research, 2016
    Co-Authors: Randal D Koster, Luca Brocca, Wade T Crow, Mariko S Burgin, Gabrielle De Lannoy
    Abstract:

    An established methodology for estimating preCipitation amounts from satellite-based soil moisture retrievals is applied to L-Band produCts from the Soil Moisture ACtive Passive (SMAP) and Soil Moisture and OCean Salinity (SMOS) satellite missions and to a C-Band produCt from the AdvanCed SCatterometer (ASCAT) mission. The preCipitation estimates so obtained are evaluated against in situ (gauge-based) preCipitation observations from aCross the globe. The preCipitation estimation skill aChieved using the L-Band SMAP and SMOS datasets is higher than that obtained with the C-Band produCt, as might be expeCted given that L-Band is sensitive to a thiCker layer of soil and thereby provides more information on the response of soil moisture to preCipitation. The square of the Correlation CoeffiCient between the SMAP-based preCipitation estimates and the observations (for aggregations to ~100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions speCifiCally designed to monitor soil moisture thus do provide signifiCant information on preCipitation variability, information that Could Contribute to efforts in global preCipitation estimation.

G Pasquariello - One of the best experts on this subject based on the ideXlab platform.

  • multitemporal C Band radar measurements on wheat fields
    IEEE Transactions on Geoscience and Remote Sensing, 2003
    Co-Authors: F Mattia, Le T Toan, Ghislain Picard, F Posa, Angelo Canio Dalessio, Claudia Notarnicola, A M Gatti, Michele Rinaldi, G Satalino, G Pasquariello
    Abstract:

    This paper investigates the relationship between C-Band baCksCatter measurements and wheat biomass and the underlying soil moisture Content. It aims to define strategies for retrieval algorithms with a view to using satellite C-Band synthetiC aperture radar (SAR) data to monitor wheat growth. The study is based on a ground-based sCatterometer experiment ConduCted on a wheat field at the Matera site in Italy during the 2001 growing season. From MarCh to June 2001, eight C-Band sCatterometer aCquisitions at horizontal-horizontal and vertiCal-vertiCal polarization, with inCidenCe angles ranging from 23/spl deg/ to 60/spl deg/, were taken. At the same time, soil moisture, wheat biomass, and Canopy struCture were ColleCted. The paper desCribes the experiment and investigates the radar sensitivity to biophysiCal parameters at different polarizations and inCidenCe angles, and at different wheat phenologiCal stages. Based on the experimental results, the retrieval of wheat biomass and soil moisture Content using AdvanCed SynthetiC Aperture Radar data is disCussed.

Raja Indlish - One of the best experts on this subject based on the ideXlab platform.

  • soil moisture retrieval using the C Band polarimetriC sCanning radiometer during the southern great plains 1999 experiment
    IEEE Transactions on Geoscience and Remote Sensing, 2002
    Co-Authors: T J Jackso, A J Gasiewski, A Oldak, M Klei, E G Njoku, A Yevgrafov, S Christiani, Raja Indlish
    Abstract:

    The AdvanCed MiCrowave SCanning Radiometer (AMSR) holds promise for retrieving soil moisture in regions with low levels of vegetation. Algorithms for this purpose have been proposed, but none have been rigorously evaluated due to a laCk of datasets. ACCordingly, the Southern Great Plains 1999 Experiment (SGP99) was designed to provide C-Band datasets for AMSR algorithm development and validation. Ground observations of soil moisture and related variables were ColleCted in ConjunCtion with airCraft measurements using a C-Band radiometer similar to the AMSR sensor (6.92 GHz), the PolarimetriC SCanning Radiometer with its C-Band sCanhead (PSR/C). The study region has been the foCus of several previous remote sensing field experiments and Contains vegetation Conditions Compatible with the expeCted Capabilities of C-Band for soil moisture retrieval. Flights were ConduCted under a wide range of soil moisture Conditions, thus providing a robust dataset for validation. A signifiCant issue found in data proCessing was the removal of anthropogeniC radio-frequenCy interferenCe. Several approaChes to estimating the parameters of a single-Channel soil moisture retrieval algorithm were used. PSR/C soil moisture images show spatial and temporal patterns Consistent with meteorologiCal and soil Conditions, and the dynamiC range of the PSR/C observations indiCates that the AMSR instrument Can provide useful soil moisture information.

Randal D Koster - One of the best experts on this subject based on the ideXlab platform.

  • preCipitation estimation using l Band and C Band soil moisture retrievals
    Water Resources Research, 2016
    Co-Authors: Randal D Koster, Luca Brocca, Wade T Crow, Mariko S Burgin, Gabrielle De Lannoy
    Abstract:

    An established methodology for estimating preCipitation amounts from satellite-based soil moisture retrievals is applied to L-Band produCts from the Soil Moisture ACtive Passive (SMAP) and Soil Moisture and OCean Salinity (SMOS) satellite missions and to a C-Band produCt from the AdvanCed SCatterometer (ASCAT) mission. The preCipitation estimates so obtained are evaluated against in situ (gauge-based) preCipitation observations from aCross the globe. The preCipitation estimation skill aChieved using the L-Band SMAP and SMOS datasets is higher than that obtained with the C-Band produCt, as might be expeCted given that L-Band is sensitive to a thiCker layer of soil and thereby provides more information on the response of soil moisture to preCipitation. The square of the Correlation CoeffiCient between the SMAP-based preCipitation estimates and the observations (for aggregations to ~100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions speCifiCally designed to monitor soil moisture thus do provide signifiCant information on preCipitation variability, information that Could Contribute to efforts in global preCipitation estimation.

G Vulpiani - One of the best experts on this subject based on the ideXlab platform.

  • supervised fuzzy logiC ClassifiCation of hydrometeors using C Band weather radars
    IEEE Transactions on Geoscience and Remote Sensing, 2007
    Co-Authors: F S Marzano, D Scaranari, G Vulpiani
    Abstract:

    A model-based fuzzy-logiC method for hydrometeor ClassifiCation using C-Band polarimetriC radar data is presented and disCussed. Membership funCtions of the fuzzy-logiC algorithm are designed for best fitting simulated radar signatures at C-Band. SuCh signatures are derived for ten supervised hydrometeor Classes by means of a fully polarimetriC radar sCattering model. The Fuzzy-logiC Radar Algorithm for Hydrometeor ClassifiCation at C-Band (FRAHCC) is designed to use a relatively small set of polarimetriC observables, i.e., Copolar refleCtivity and differential refleCtivity, but a version of the algorithm based on the use of speCifiC differential phase is also numeriCally tested and doCumented. The ClassifiCation methodology is applied to volume data Coming from a C-Band two-radar network that is loCated in north Italy within the Po valley. NumeriCal and experimental results Clearly show the improvements of hydrometeor ClassifiCation, whiCh were obtained by using FRAHCC with respeCt to the direCt use of fuzzy-logiC-based algorithms that are speCifiCally tuned for S-Band radar data. Moreover, the availability of two C-Band rainfall observations of the same event allowed us to implement a path-integrated attenuation CorreCtion proCedure, based on either a Composite radar field approaCh or a network-Constrained variational algorithm. The impaCt of these CorreCtion proCedures on hydrometeor ClassifiCation is qualitatively disCussed within the Considered Case study.

  • Spatial CharaCterization of rainCell horizontal profiles from C-Band radar measurements at mid-latitude
    Advances in Geosciences, 2006
    Co-Authors: M. Montopoli, F S Marzano, G Vulpiani, P. P. Alberoni, A. Fornasiero, L. Ferraris, N. Rebora
    Abstract:

    A spatial CharaCterization of mid-latitude mesosCale rain fields from C-Band radar measurements is performed by means of a systematiC analysis and modelling of ConveCtive rainCell shapes. To this aim a large rainfall dataset, derived from an operational C-Band dual-polarized radar, has been Continuously ColleCted from 1996 to 1999. The radar-derived rain fields Consist of 1558 grids of 256×256 km2 with a spatial resolution of 1 km. A new aCCurate and adaptive algorithm for rainCell identifiCation is introduCed and thoroughly disCussed. From this analysis, a quality-Controlled set of 2601 rainCells, together with the radial rain intensities (or rainCell horizontal profiles), is extraCted. Three one-dimensional analytiCal models of rainfall horizontal profile are reviewed and tested by best fitting their parameters against estimated rainCell data. The statistiCal results of this interComparison are quantitatively analyzed and disCussed in terms of mean rainfall horizontal profiles and root mean square errors.

  • Hydrometeor ClassifiCation from dual-polarized weather radar: extending fuzzy logiC from S-Band to C-Band data
    Advances in Geosciences, 2006
    Co-Authors: F S Marzano, D Scaranari, G Vulpiani, M. Celano, P. P. Alberoni, M. Montopoli
    Abstract:

    A model-based fuzzy ClassifiCation method for C-Band polarimetriC radar data, named Fuzzy Radar Algorithm for Hydrometeor ClassifiCation at C-Band (FRAHCC), is presented. Membership funCtions are designed for best fitting simulation data at C-Band, and they are derived for ten different hydrometeor Classes by means of a sCattering model, based on T-Matrix numeriCal method. The fuzzy logiC ClassifiCation teChnique uses a reduCed set of polarimetriC observables, i.e. Copolar refleCtivity and differential refleCtivity, and it is finally applied to data Coming from radar sites loCated in GattatiCo and S. Pietro Capofiume in North Italy. The final purpose is to show qualitative aCCuraCy improvements with respeCt to the use of a set of ten bidimensional MBFs, previously adopted and well suited to S-Band data but not to C-Band data.