Geostationary satellite‐based 6.7 μm band best water vapor information layer analysis over the Tibetan Plateau

The best water vapor information layer (BWIL) of the 6.7 μm water vapor absorption infrared (IR) band for the FengYun-2E is investigated over the Tibetan Plateau with standard atmospheric profile and European Centre for Medium-Range Weather Forecasts (ECMWF) operational model analysis data. The sensitivity tests show that surface characteristics over the Tibetan Plateau have a significant influence on the BWIL. To be specific, topographic elevation, colder skin temperature, and lower emissivity tend to lift the altitude of the BWIL, decrease its magnitude, and narrow the half-width range. The results from statistical analysis indicate that the altitude of the BWIL reaches the highest in summer and the lowest in winter. Meanwhile, the altitude of the BWIL is highly correlated with the water vapor amount above 500 hPa over the Tibetan Plateau and above 300 hPa over the East China Plain, respectively. The diurnal variation in the BWIL is synchronous with the diurnal variation in the surface skin temperature. It can be concluded from the study that surface characteristics over high terrain in dry and cold atmospheres have more significant impacts on the BWIL. With multiple water vapor absorption IR bands, the imagers on board the new generation of geostationary satellites will provide crucial improvement in water vapor remote sensing over the current single water vapor band on board the FY-2 series according to the analysis in this study.

[1]  Eva Borbas,et al.  Development of a Global Infrared Land Surface Emissivity Database for Application to Clear Sky Sounding Retrievals from Multispectral Satellite Radiance Measurements , 2008 .

[2]  Brian J. Soden,et al.  The diurnal cycle of convection, clouds, and water vapor in the tropical upper troposphere , 2000 .

[3]  Peter G. Black,et al.  Environmental Influences on the Rapid Intensification of Hurricane Opal (1995) over the Gulf of Mexico , 2000 .

[4]  Timothy J. Schmit,et al.  The GOES-R Advanced Baseline Imager and the Continuation of Current Sounder Products , 2008 .

[5]  Jun Li,et al.  Retrieving clear-sky atmospheric parameters from SEVIRI and ABI infrared radiances , 2008 .

[6]  Francis P. Bretherton,et al.  Interpretation of TOVS water vapor radiances in terms of layer-average relative humidities: Method and climatology for the upper, middle, and lower troposphere , 1996 .

[7]  Francis P. Bretherton,et al.  Evaluation of water vapor distribution in general circulation models using satellite observations , 1994 .

[8]  D. Aminou,et al.  Plans for EUMETSAT’s Third Generation Meteosat geostationary satellite programme , 2005 .

[9]  James M. Russell,et al.  The evolution of the stratopause during the 2006 major warming: Satellite data and assimilated meteorological analyses , 2008 .

[10]  S. Manabe,et al.  The Role of Mountains in the South Asian Monsoon Circulation , 1975 .

[11]  Chang-Hoi Ho,et al.  Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery , 2015, Advances in Atmospheric Sciences.

[12]  Li Jun,et al.  Temperature and water vapor weighting functions from radiative transfer equation with surface emissivity and solar reflectivity , 1994 .

[13]  E. Hilsenrath,et al.  Meteorological applications of the Nimbus 4 Temperature-Humidity Infrared Radiometer, 6.7 micron channel data , 1972 .

[14]  Chaohua Dong,et al.  China’s Current and Future Meteorological Satellite Systems , 2006 .

[15]  William L. Smith,et al.  Vertical Resolution and Accuracy of Atmospheric Infrared Sounding Spectrometers. , 1992 .

[17]  Hartmut H. Aumann,et al.  Deep convective clouds at the tropopause , 2010 .

[18]  Fuzhong Weng,et al.  On water vapor Jacobian in fast radiative transfer model , 2010 .

[19]  H. Fischer,et al.  Information Content of METEOSAT and Nimbus/THIR Water Vapor Channel Data: Altitude Association of Observed Phenomena , 1981 .

[20]  Duzheng Ye,et al.  Some Characteristics of the Summer Circulation Over the Qinghai-Xizang (Tibet) Plateau and Its Neighborhood , 1981 .

[21]  Jun Li,et al.  Trade-off studies of a hyperspectral infrared sounder on a geostationary satellite. , 2007, Applied optics.

[22]  W. Paul Menzel,et al.  Global Soundings of the Atmosphere from ATOVS Measurements: The Algorithm and Validation , 2000 .

[23]  Jun Yu Li,et al.  Impact of Terrain Altitude and Cloud Height on Ozone Remote Sensing from Satellite , 2014 .

[24]  Dong‐Kyou Lee,et al.  Improvement in background error covariances using ensemble forecasts for assimilation of high-resolution satellite data , 2011 .

[25]  Retrieval of upper tropospheric relative humidity by the GMS-5 water vapor channel: A study of the technique , 2004 .

[26]  D. Keyser,et al.  The use of VAS satellite data in weather analysis, prediction and diagnosis , 1982 .

[27]  G. Manney,et al.  On the Relation of 6.7 μm Water Vapour Features to Isentropic Distributions of Potential Vorticity , 1987 .

[28]  W. Paul Menzel,et al.  GOES sounding improvement and applications to severe storm nowcasting , 2008 .

[29]  F. Bretherton,et al.  Upper tropospheric relative humidity from the GOES 6.7 μm channel: method and climatology for July 1987 , 1993 .

[30]  W. Paul Menzel,et al.  INTRODUCING THE NEXT-GENERATION ADVANCED BASELINE IMAGER ON GOES-R , 2005 .

[31]  Kiyoshi Tsuchiya,et al.  Classification of cloud types based on data of multiple satellite sensors , 1994 .

[32]  Eva Borbas,et al.  International MODIS and AIRS processing package: AIRS products and applications , 2007 .

[33]  Quantitative Studies of Meteosat Water-Vapor Channel Data , 1980 .

[34]  L. Larrabee Strow,et al.  Atmospheric infrared fast transmittance models: a comparison of two approaches , 1996, Optics + Photonics.

[35]  Steven J. Nieman,et al.  Upper-Tropospheric Winds Derived from Geostationary Satellite Water Vapor Observations , 1997 .

[36]  Zhou Fengxian,et al.  Simultaneous non-linear retrieval of atmospheric temperature and absorbing constituent profiles from satellite infrared sounder radiances , 1994 .

[37]  Anoop Kumar Mishra,et al.  A New Technique to Estimate Precipitation at Fine Scale Using Multifrequency Satellite Observations Over Indian Land and Oceanic Regions , 2013, IEEE Transactions on Geoscience and Remote Sensing.

[38]  B. Soden,et al.  Diurnal cycle of convection, clouds, and water vapor in the tropical upper troposphere: Satellites versus a general circulation model , 2004 .

[39]  Steven A. Ackerman,et al.  High-Spectral- and High-Temporal-Resolution Infrared Measurements from Geostationary Orbit , 2009 .

[40]  D. Keyser,et al.  Delineating mid- and low-level water vapor patterns in pre-convective environments using VAS moisture channels , 1984 .

[41]  J. Marshall.  Cloud and water vapour motion vectors in tropical cyclone track forecasting — A review , 1998 .