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  • 1
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2006
    In:  Geophysical Research Letters Vol. 33, No. 6 ( 2006)
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 33, No. 6 ( 2006)
    Type of Medium: Online Resource
    ISSN: 0094-8276
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2006
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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  • 2
    Online Resource
    Online Resource
    Meteorological Society of Japan ; 2009
    In:  SOLA Vol. 5 ( 2009), p. 53-56
    In: SOLA, Meteorological Society of Japan, Vol. 5 ( 2009), p. 53-56
    Type of Medium: Online Resource
    ISSN: 1349-6476
    Language: English
    Publisher: Meteorological Society of Japan
    Publication Date: 2009
    detail.hit.zdb_id: 2222926-7
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  • 3
    Online Resource
    Online Resource
    Institute of Electrical and Electronics Engineers (IEEE) ; 2016
    In:  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Vol. 9, No. 7 ( 2016-7), p. 3297-3303
    In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Institute of Electrical and Electronics Engineers (IEEE), Vol. 9, No. 7 ( 2016-7), p. 3297-3303
    Type of Medium: Online Resource
    ISSN: 1939-1404 , 2151-1535
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2016
    detail.hit.zdb_id: 2457423-5
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  • 4
    Online Resource
    Online Resource
    Elsevier BV ; 2008
    In:  Journal of Quantitative Spectroscopy and Radiative Transfer Vol. 109, No. 4 ( 2008-3), p. 684-702
    In: Journal of Quantitative Spectroscopy and Radiative Transfer, Elsevier BV, Vol. 109, No. 4 ( 2008-3), p. 684-702
    Type of Medium: Online Resource
    ISSN: 0022-4073
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2008
    detail.hit.zdb_id: 1491916-3
    SSG: 11
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2008
    In:  Journal of Quantitative Spectroscopy and Radiative Transfer Vol. 109, No. 10 ( 2008-7), p. 1943-1950
    In: Journal of Quantitative Spectroscopy and Radiative Transfer, Elsevier BV, Vol. 109, No. 10 ( 2008-7), p. 1943-1950
    Type of Medium: Online Resource
    ISSN: 0022-4073
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2008
    detail.hit.zdb_id: 1491916-3
    SSG: 11
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  • 6
    Online Resource
    Online Resource
    American Meteorological Society ; 2011
    In:  Journal of Atmospheric and Oceanic Technology Vol. 28, No. 6 ( 2011-06-01), p. 767-778
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 28, No. 6 ( 2011-06-01), p. 767-778
    Abstract: To better use the Stratospheric Sounding Unit (SSU) data for reanalysis and climate studies, issues associated with the fast radiative transfer (RT) model for SSU have recently been revisited and the results have been implemented into the Community Radiative Transfer Model version 2. This study revealed that the spectral resolution for the sensor’s spectral response functions (SRFs) calculations is very important, especially for channel 3. A low spectral resolution SRF results, on average, in 0.6-K brightness temperature (BT) errors for that channel. The variations of the SRFs due to the CO2 cell pressure variations have been taken into account. The atmospheric transmittance coefficients of the fast RT model for the Television and Infrared Observation Satellite (TIROS)-N, NOAA-6, NOAA-7, NOAA-8, NOAA-9, NOAA-11, and NOAA-14 have been generated with CO2 and O3 as variable gases. It is shown that the BT difference between the fast RT model and line-by-line model is less than 0.1 K, but the fast RT model is at least two orders of magnitude faster. The SSU measurements agree well with the simulations that are based on the atmospheric profiles from the Earth Observing System Aura Microwave Limb Sounding product and the Sounding of the Atmosphere using Broadband Emission Radiometry on the Thermosphere Ionosphere Mesosphere Energetics and Dynamics satellite. The impact of the CO2 cell pressures shift for SSU has been evaluated by using the Committee on Space Research (COSPAR) International Reference Atmosphere (CIRA) model profiles. It is shown that the impacts can be on an order of 1 K, especially for SSU NOAA-7 channel 2. There are large brightness temperature gaps between observation and model simulation using the available cell pressures for NOAA-7 channel 2 after June 1983. Linear fittings of this channel’s cell pressures based on previous cell leaking behaviors have been studied, and results show that the new cell pressures are reasonable. The improved SSU fast model can be applied for reanalysis of the observations. It can also be used to address two important corrections in deriving trends from SSU measurements: CO2 cell leaking correction and atmospheric CO2 concentration correction.
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2011
    detail.hit.zdb_id: 2021720-1
    detail.hit.zdb_id: 48441-6
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  • 7
    Online Resource
    Online Resource
    American Meteorological Society ; 2014
    In:  Journal of Atmospheric and Oceanic Technology Vol. 31, No. 11 ( 2014-11), p. 2522-2529
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 31, No. 11 ( 2014-11), p. 2522-2529
    Abstract: Operational sea surface temperature (SST) retrieval algorithms are stratified into nighttime and daytime. The nighttime algorithm uses two split-window Visible Infrared Imaging Radiometer Suite (VIIRS) bands—M15 and M16, centered at ~11 and ~12 m, respectively—and a shortwave infrared band—M12, centered at ~3.7 m. The M12 is most transparent and critical for accurate SST retrievals. However, it is not used during the daytime because of contamination by solar radiation, which is reflected by the ocean surface and scattered by atmospheric aerosols. As a result, daytime VIIRS SST and cloud mask products and applications are degraded and inconsistent with their nighttime counterparts. This study proposes a method to remove the solar contamination from the VIIRS M12 based on theoretical radiative transfer model analyses. The method uses either of the two VIIRS shortwave bands, centered at 1.6 m (M10) or 2.25 m (M11), to correct for the effect of solar reflectance in M12. Subsequently, the corrected daytime brightness temperature in M12 can be used as input into nighttime cloud mask and SST algorithms. Preliminary comparisons with the European Centre for Medium-Range Weather Forecasts (ECMWF) SST analysis suggest that the daytime SST products can be improved and potentially reconciled with the nighttime SST product. However, more substantial case studies and assessments using different SST products are required before the transition of this research work into operational products.
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2014
    detail.hit.zdb_id: 2021720-1
    detail.hit.zdb_id: 48441-6
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  • 8
    Online Resource
    Online Resource
    American Meteorological Society ; 2012
    In:  Journal of Atmospheric and Oceanic Technology Vol. 29, No. 3 ( 2012-03-01), p. 382-396
    In: Journal of Atmospheric and Oceanic Technology, American Meteorological Society, Vol. 29, No. 3 ( 2012-03-01), p. 382-396
    Abstract: The line-by-line radiative transfer model (LBLRTM) is used to derive the channel transmittances. The channel transmittance from a level to the top of the atmosphere can be approximated by three methods: Planck-weighted transmittance 1 (PW1), Planck-weighted transmittance 2 (PW2), and non-Planck-weighted transmittance (ORD). The PW1 method accounts for a radiance variation across the instrument’s spectral response function (SRF) and the Planck function is calculated with atmospheric layer temperature, whereas the PW2 method accounts for the variation based on the temperatures at the interface between atmospheric layers. For channels with broad SRFs, the brightness temperatures (BTs) derived from the ORD are less accurate than these from either PW1 or PW2. Furthermore, the BTs from PW1 are more accurate than these from PW2, and the BT differences between PW1 and PW2 increase with atmospheric optical thickness. When the band correction is larger than 1, the PW1 method should be used to account for the Planck radiance variation across the instrument’s SRF. When considering the solar contribution in daytime, the correction of the solar reflection has been made for near-infrared broadband channels (~3.7 μm) when using PW1 transmittance. The solar transmittance is predicted by using explanatory variables, such as PW1 transmittance, the secant of zenith angle, and the surface temperature. With this correction, the errors can be significantly reduced.
    Type of Medium: Online Resource
    ISSN: 0739-0572 , 1520-0426
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2012
    detail.hit.zdb_id: 2021720-1
    detail.hit.zdb_id: 48441-6
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  • 9
    Online Resource
    Online Resource
    American Meteorological Society ; 2007
    In:  Journal of Applied Meteorology and Climatology Vol. 46, No. 4 ( 2007-04-01), p. 544-548
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 46, No. 4 ( 2007-04-01), p. 544-548
    Abstract: The Advanced Microwave Sounding Unit (AMSU) images display strong dependence on the scanning angle because of the temperature gradient of the atmosphere and the change in the optical pathlength between Earth and the satellite. Using a limb-adjustment algorithm, the temperature gradients can be restored from the images. Various limb-correction algorithms have been developed for infrared and microwave sounders by aid of radiative transfer simulations. Together with the National Oceanic and Atmospheric Administration (NOAA)-16 AMSU, the NOAA-18 satellite with AMSU (launched on 20 May 2005) provides the best opportunity to collocate observations from two satellites. The collocated measurement pairs from NOAA-16 and NOAA-18 contain data for which both observations have the same scanning angle and various scanning angles—in particular, off-nadir observations from NOAA-16 and nadir observations from NOAA-18. The coincident data pair having the same scan position from NOAA-16 and NOAA-18 can be used for intercalibration of the sensors of the two satellites. The coincident data pair having nadir measurement from NOAA-18 and off-nadir measurement from NOAA-16 can be used for testing the limb-adjustment algorithm using pure satellite measurements. This study applies collocated measurements to evaluate the performance of the current NOAA microwave limb-correction algorithm for brightness temperatures at AMSU-A channels 5, 6, and 7 for the first time. With the limb correction, the warm core of Hurricane Katrina in 2005 can also be detected using a cross-scan sensor such as AMSU-A.
    Type of Medium: Online Resource
    ISSN: 1558-8432 , 1558-8424
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2007
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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  • 10
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2013
    In:  Journal of Geophysical Research: Atmospheres Vol. 118, No. 20 ( 2013-10-27), p. 11,664-11,678
    In: Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), Vol. 118, No. 20 ( 2013-10-27), p. 11,664-11,678
    Type of Medium: Online Resource
    ISSN: 2169-897X
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2013
    detail.hit.zdb_id: 710256-2
    detail.hit.zdb_id: 2016800-7
    detail.hit.zdb_id: 2969341-X
    SSG: 16,13
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