Atmospheric temporal variations in the pre-landfall environment of typhoon Nangka (2015) observed by the Himawari-8 AHI

The next generation Geostationary Operational Environmental Satellite-R series (GOES-R) Advanced Baseline Imager (ABI) legacy atmospheric profile (LAP) retrieval algorithm is applied to the Advanced Himawari Imager (AHI) radiance measurements from the Himawari-8 satellite. Derived products included atmospheric temperature/moisture profiles, total precipitable water (TPW), and atmospheric stability indices. Since both AHI and ABI have 9 similar infrared bands, the GOES-R ABI LAP retrieval algorithm can be applied to the AHI measurements with minimal modifications. With the capability of frequent (10-min interval) full disk observations over the East Asia and Western Pacific regions, the AHI measurements are used to investigate the atmospheric temporal variation in the pre-landfall environment for typhoon Nangka (2015). Before its landfall over Japan, heavy rainfalls from Nangka occurred over the southern region of Honshu Island. During the pre-landfall period, the trends of the AHI LAP products indicated the development of the atmospheric environment favorable for heavy rainfall. Even though, the AHI LAP products are generated only in the clear skies, the 10-minute interval AHI measurements provide detailed information on the pre-landfall environment for typhoon Nangka. This study shows the capability of the AHI radiance measurements, together with the derived products, for depicting the detailed temporal features of the pre-landfall environment of a typhoon, which may also be possible for hurricanes and storms with ABI on the GOES-R satellite.

[1]  H. Huntrieser,et al.  Comparison of Traditional and Newly Developed Thunderstorm Indices for Switzerland , 1997 .

[2]  W. Paul Menzel,et al.  Operational retrieval of atmospheric temperature, moisture, and ozone from MODIS infrared radiances , 2003, SPIE Asia-Pacific Remote Sensing.

[3]  P. Jayakrishnan,et al.  Assessment of Convective Activity Using Stability Indices as Inferred from Radiosonde and MODIS Data , 2014 .

[4]  Fuzhong Weng,et al.  JCSDA Community Radiative Transfer Model ( CRTM ) , 2005 .

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

[6]  Timothy J. Schmit,et al.  Geostationary Operational Environmental Satellite (GOES)-14 super rapid scan operations to prepare for GOES-R , 2013 .

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

[8]  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 .

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

[10]  LI JUN,et al.  Warning Information in a Preconvection Environment from the Geostationary Advanced Infrared Sounding System — A Simulation Study Using the IHOP Case , 2011 .

[11]  Robert C Miller,et al.  Notes on Analysis and Severe-Storm Forecasting Procedures of the Air Force Global Weather Central , 1972 .

[12]  Timothy J. Schmit,et al.  Applications of Full Spatial Resolution Space-Based Advanced Infrared Soundings in the Preconvection Environment , 2012 .

[13]  Timothy J. Schmit,et al.  A Closer Look at the ABI on the GOES-R Series , 2017 .

[14]  Timothy J. Schmit,et al.  Rapid Refresh Information of Significant Events: Preparing Users for the Next Generation of Geostationary Operational Satellites , 2015 .

[15]  Naimeng Lu,et al.  Geostationary satellite‐based 6.7 μm band best water vapor information layer analysis over the Tibetan Plateau , 2016 .

[16]  Fuzhong Weng,et al.  Comparison of two transmittance algorithms in the community radiative transfer model: Application to AVHRR , 2012 .

[17]  Daniel T. Lindsey,et al.  10.35 μm: an atmospheric window on the GOES-R Advanced Baseline Imager with less moisture attenuation , 2012 .

[18]  S. Liang,et al.  GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document For , 2010 .

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

[20]  Timothy J. Schmit,et al.  Warning Information in a Preconvection Environment from the Geostationary Advanced Infrared Sounding System—A Simulation Study Using the IHOP Case , 2011 .

[21]  W. Paul Menzel,et al.  Forecasting and nowcasting improvement in cloudy regions with high temporal GOES sounder infrared radiance measurements , 2009 .

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

[23]  Jun Li,et al.  Evaluation of the GOES-R ABI LAP Retrieval Algorithm Using the GOES-13 Sounder , 2014 .

[24]  Yuh-Lang Lin,et al.  Some Common Ingredients for Heavy Orographic Rainfall , 2001 .

[25]  H. Masunaga.  A Satellite Study of the Atmospheric Forcing and Response to Moist Convection over Tropical and Subtropical Oceans , 2012 .

[26]  A. Okuyama,et al.  An Introduction to Himawari-8/9— Japan’s New-Generation Geostationary Meteorological Satellites , 2016 .