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  • 1
    Online Resource
    Online Resource
    Retrieval of Ice Cloud Parameters Using a Microwave Imaging Radiometer
    American Meteorological Society ; 2000
    In:  Journal of the Atmospheric Sciences Vol. 57, No. 8 ( 2000-04), p. 1069-1081
    Details
    In: Journal of the Atmospheric Sciences, American Meteorological Society, Vol. 57, No. 8 ( 2000-04), p. 1069-1081
    Type of Medium: Online Resource
    ISSN: 0022-4928 , 1520-0469
    URL: Article
    DOI: 10.1175/1520-0469(2000)057〈1069:ROICPU〉2.0.CO;2
    RVK:
    UA 4800
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2000
    detail.hit.zdb_id: 218351-1
    detail.hit.zdb_id: 2025890-2
    SSG: 16,13
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  • 2
    Online Resource
    Online Resource
    Special Sensor Microwave Imager (SSM/I) Intersensor Calibration Using a Simultaneous Conical Overpass Technique
    American Meteorological Society ; 2011
    In:  Journal of Applied Meteorology and Climatology Vol. 50, No. 1 ( 2011-01-01), p. 77-95
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 50, No. 1 ( 2011-01-01), p. 77-95
    Abstract: A new intersensor calibration scheme is developed for the Defense Meteorological Satellite Program Special Sensor Microwave Imager (SSM/I) to correct its scan-angle-dependent bias, the radar calibration beacon interference on the F-15 satellite, and other intersensor biases. The intersensor bias is characterized by the simultaneous overpass measurements with the F-13 SSM/I as a reference. This sensor data record (SDR) intersensor calibration procedure is routinely running at the National Oceanic and Atmospheric Administration and is now used for reprocessing all SSM/I environmental data records (EDR), including total precipitable water (TPW) and surface precipitation. Results show that this scheme improves the consistency of the monthly SDR’s time series from different SSM/I sensors. Relative to the matched rain products from the Tropical Rainfall Measuring Mission, the bias of SSM/I monthly precipitation is reduced by 12% after intersensor calibration. TPW biases between sensors are reduced by 75% over the global ocean and 20% over the tropical ocean, respectively. The intersensor calibration reduces biases by 20.6%, 15.7%, and 6.5% for oceanic, land, and global precipitation, respectively. The TPW climate trend is 1.59% decade−1 (or 0.34 mm decade−1) for the global ocean and 1.39% decade−1 (or 0.63 mm decade−1) for the tropical ocean, indicating related trends decrease of 38% and 54%, respectively, from the uncalibrated SDRs. Results demonstrate the large impacts of this calibration on the TPW climate trend.
    Type of Medium: Online Resource
    ISSN: 1558-8432 , 1558-8424
    URL: Article
    DOI: 10.1175/2010JAMC2271.1
    RVK:
    UA 4547
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2011
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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  • 3
    Online Resource
    Online Resource
    Uses of NOAA-16 and -18 Satellite Measurements for Verifying the Limb-Correction Algorithm
    American Meteorological Society ; 2007
    In:  Journal of Applied Meteorology and Climatology Vol. 46, No. 4 ( 2007-04-01), p. 544-548
    Details
    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
    URL: Article
    DOI: 10.1175/JAM2476.1
    RVK:
    UA 4547
    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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  • 4
    Online Resource
    Online Resource
    Satellite Data Assimilation in Numerical Weather Prediction Models. Part I: Forward Radiative Transfer and Jacobian Modeling in Cloudy Atmospheres
    American Meteorological Society ; 2003
    In:  Journal of the Atmospheric Sciences Vol. 60, No. 21 ( 2003-11), p. 2633-2646
    Details
    In: Journal of the Atmospheric Sciences, American Meteorological Society, Vol. 60, No. 21 ( 2003-11), p. 2633-2646
    Type of Medium: Online Resource
    ISSN: 0022-4928 , 1520-0469
    URL: Article
    DOI: 10.1175/1520-0469(2003)060〈2633:SDAINW〉2.0.CO;2
    RVK:
    UA 4800
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2003
    detail.hit.zdb_id: 218351-1
    detail.hit.zdb_id: 2025890-2
    SSG: 16,13
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  • 5
    Online Resource
    Online Resource
    Cloud Liquid Water Climatology from the Special Sensor Microwave/Imager
    American Meteorological Society ; 1997
    In:  Journal of Climate Vol. 10, No. 5 ( 1997-05), p. 1086-1098
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 10, No. 5 ( 1997-05), p. 1086-1098
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/1520-0442(1997)010〈1086:CLWCFT〉2.0.CO;2
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 1997
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 6
    Online Resource
    Online Resource
    A Microwave Polarimetric Two-Stream Radiative Transfer Model
    American Meteorological Society ; 2002
    In:  Journal of the Atmospheric Sciences Vol. 59, No. 15 ( 2002-08), p. 2396-2402
    Details
    In: Journal of the Atmospheric Sciences, American Meteorological Society, Vol. 59, No. 15 ( 2002-08), p. 2396-2402
    Type of Medium: Online Resource
    ISSN: 0022-4928 , 1520-0469
    URL: Article
    DOI: 10.1175/1520-0469(2002)059〈2396:AMPTSR〉2.0.CO;2
    RVK:
    UA 4800
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2002
    detail.hit.zdb_id: 218351-1
    detail.hit.zdb_id: 2025890-2
    SSG: 16,13
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  • 7
    Online Resource
    Online Resource
    Satellite Data Assimilation in Numerical Weather Prediction Models. Part II: Uses of Rain-Affected Radiances from Microwave Observations for Hurricane Vortex Analysis
    American Meteorological Society ; 2007
    In:  Journal of the Atmospheric Sciences Vol. 64, No. 11 ( 2007-11-01), p. 3910-3925
    Details
    In: Journal of the Atmospheric Sciences, American Meteorological Society, Vol. 64, No. 11 ( 2007-11-01), p. 3910-3925
    Abstract: A hybrid variational scheme (HVAR) is developed to produce the vortex analysis associated with tropical storms. This scheme allows for direct assimilation of rain-affected radiances from satellite microwave instruments. In the HVAR, the atmospheric temperature and surface parameters in the storms are derived from a one-dimension variational data assimilation (1DVAR) scheme, which minimizes the cost function of both background information and satellite measurements. In the minimization process, a radiative transfer model including scattering and emission is used for radiance simulation (see Part I of this study). Through the use of 4DVAR, atmospheric temperatures from the Advanced Microwave Sounding Unit (AMSU) and surface parameters from the Advanced Microwave Scanning Radiometer (AMSR-E) are assimilated into global forecast model outputs to produce an improved analysis. This new scheme is generally applicable for variable stages of storms. In the 2005 hurricane season, the HVAR was applied for two hurricane cases, resulting in improved analyses of three-dimensional structures of temperature and wind fields as compared with operational model analysis fields. It is found that HVAR reproduces detailed structures for the hurricane warm core at the upper troposphere. Both lower-level wind speed and upper-level divergence are enhanced with reasonable asymmetric structure.
    Type of Medium: Online Resource
    ISSN: 1520-0469 , 0022-4928
    URL: Article
    DOI: 10.1175/2006JAS2051.1
    RVK:
    UA 4800
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2007
    detail.hit.zdb_id: 218351-1
    detail.hit.zdb_id: 2025890-2
    SSG: 16,13
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  • 8
    Online Resource
    Online Resource
    A Spectral Data Compression (SDCOMP) Radiative Transfer Model for High-Spectral-Resolution Radiation Simulations
    American Meteorological Society ; 2020
    In:  Journal of the Atmospheric Sciences Vol. 77, No. 6 ( 2020-06), p. 2055-2066
    Details
    In: Journal of the Atmospheric Sciences, American Meteorological Society, Vol. 77, No. 6 ( 2020-06), p. 2055-2066
    Abstract: With the increasing use of satellite and ground-based high-spectral-resolution (HSR) measurements for weather and climate applications, accurate and efficient radiative transfer (RT) models have become essential for accurate atmospheric retrievals, for instrument calibration, and to provide benchmark RT solutions. This study develops a spectral data compression (SDCOMP) RT model to simulate HSR radiances in both solar and infrared spectral regions. The SDCOMP approach “compresses” the spectral data in the optical property and radiance domains, utilizing principal component analysis (PCA) twice to alleviate the computational burden. First, an optical-property-based PCA is performed for a given atmospheric scenario (atmospheric, trace gas, and aerosol profiles) to simulate relatively low-spectral-resolution radiances at a small number of representative wavelengths. Second, by using precalculated principal components from an accurate radiance dataset computed for a large number of atmospheric scenarios, a radiance-based PCA is carried out to extend the low-spectral-resolution results to desired HSR results at all wavelengths. This procedure ensures both that individual monochromatic RT calculations are efficiently performed and that the number of such computations is optimized. SDCOMP is approximately three orders of magnitude faster than numerically exact RT calculations. The resulting monochromatic radiance has relative errors less than 0.2% in the solar region and brightness temperature differences less than 0.1 K for over 95% of the cases in the infrared region. The efficiency and accuracy of SDCOMP not only make it useful for analysis of HSR measurements, but also hint at the potential for utilizing this model to perform RT simulations in mesoscale numerical weather and general circulation models.
    Type of Medium: Online Resource
    ISSN: 0022-4928 , 1520-0469
    URL: Article
    DOI: 10.1175/JAS-D-19-0238.1
    RVK:
    UA 4800
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 218351-1
    detail.hit.zdb_id: 2025890-2
    SSG: 16,13
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  • 9
    Online Resource
    Online Resource
    The Long-Term Trend of Upper-Air Temperature in China Derived from Microwave Sounding Data and Its Comparison with Radiosonde Observations
    American Meteorological Society ; 2020
    In:  Journal of Climate Vol. 33, No. 18 ( 2020-09-15), p. 7875-7895
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 33, No. 18 ( 2020-09-15), p. 7875-7895
    Abstract: Currently, the satellite Microwave Sounding Unit (MSU/AMSU) datasets developed from three organizations—Remote Sensing Systems (RSS), the University of Alabama at Huntsville (UAH), and the NOAA Center for Satellite Applications and Research (STAR)—are often used to monitor the global long-term trends of temperatures in the lower troposphere (TLT), midtroposphere (TMT), total troposphere (TTT), troposphere and stratosphere (TTS), and lower stratosphere (TLS). However, the trend in these temperatures over China has not been quantitatively assessed. In this study, the decadal variability and long-term trend of upper-air temperature during 1979–2018 from three MSU datasets are first evaluated over China and compared with the proxy MSU dataset simulated from homogenized surface and radiosonde profiles (EQU) at 113 stations in China. The regional mean MSU trends over China during 1979–2018 are 0.22–0.27 (TLT), 0.15–0.22 (TMT), 0.20–0.27 (TTT), 0.02–0.14 (TTS), and from −0.33 to −0.36 (TLS) K decade −1 , whereas the EQU trends are 0.31 (TLT), 0.19 (TMT), 0.24 (TTT), 0.07 (TTS), and −0.26 (TLS) K decade −1 . The trends from RSS generally show a better agreement with those from EQU. The trends from both MSU and EQU exhibit seasonal and regional difference with a larger warming in TLT in February and March, and stronger cooling in TLS from late winter to spring. The TLT and TMT over the Tibetan Plateau and northwestern China show larger warming trends. The variability from MSU and EQU agree well except TLT in Tibet and southern China. The major difference in regional mean temperatures over China between MSU and EQU is related primarily to the satellite instrument changes during 1979–98 and the radiosonde system changes in China in the 2000s.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-19-0742.1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 10
    Online Resource
    Online Resource
    Retrieval of Cloud Ice Water Path from Special Sensor Microwave Imager/Sounder (SSMIS)
    American Meteorological Society ; 2012
    In:  Journal of Applied Meteorology and Climatology Vol. 51, No. 2 ( 2012-02), p. 366-379
    Details
    In: Journal of Applied Meteorology and Climatology, American Meteorological Society, Vol. 51, No. 2 ( 2012-02), p. 366-379
    Abstract: The Special Sensor Microwave Imager/Sounder (SSMIS) aboard the Defense Meteorological Satellite Program F-16 spacecraft measures the Earth-emitted radiation at frequencies from 19 to 183 GHz. From its high-frequency channels at 91 and 150 GHz, cloud microphysical parameters can be observed at a spatial resolution of 15 km. In this study, a simplified two-stream radiative transfer model is applied for microwave applications as a three-parameter equation and then used to retrieve the ice cloud water path (IWP) and ice particle effective diameter D e . Since SSMIS is a conically scanning instrument, the retrieved IWP is less dependent on scan position and is a useful product for imaging atmospheric ice-phase clouds related to precipitation. Thus, IWP is also used to estimate surface rainfall rate through the same relationship derived previously and used in Advanced Microwave Sounding Unit (AMSU-B) and Microwave Humidity Sounder applications. The SSMIS-derived ice cloud products are compared with those from other microwave instruments on the MetOp-A satellite, and both agree well in their spatial distributions.
    Type of Medium: Online Resource
    ISSN: 1558-8424 , 1558-8432
    URL: Article
    DOI: 10.1175/JAMC-D-11-021.1
    RVK:
    UA 4547
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2012
    detail.hit.zdb_id: 2227779-1
    detail.hit.zdb_id: 2227759-6
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