A Novel Channel‐Synthesizing Method for Reducing Uncertainties in Satellite Radiative Transfer Modeling

Most sounding channels sensitive to atmosphere layers close to Earth's surface are also sensitive to Earth's surface properties. Biases and uncertainties in Earth's surface emissivity and skin temperature may degrade the values of these observations being assimilated into weather prediction models. A method that combines several individual channels into a synthesized channel is proposed here to reduce such uncertainties. The effectiveness of such channel‐synthesizing method is first demonstrated through perfect model experiments, where brightness temperatures are simulated and compared before and after noises added to surface emissivity and skin temperature. Real‐case experiments that compare simulated brightness temperature and satellite observations further show that the synthesized channel can effectively reduce the mean bias of simulated brightness temperature from 1 to 3 K for individual GOES‐R channels to near zero for the synthesized channel, suggesting great potential of the approach for more effective assimilation of surface‐sensitive sounding channels.

[1]  W. Paul Menzel,et al.  Satellite-Based Atmospheric Infrared Sounder Development and Applications , 2017 .

[2]  Yuan Xue,et al.  Atmospheric and Forest Decoupling of Passive Microwave Brightness Temperature Observations Over Snow-Covered Terrain in North America , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[3]  Steven A. Ackerman,et al.  Comparison of Satellite-, Model-, and Radiosonde-Derived Convective Available Potential Energy in the Southern Great Plains Region , 2017 .

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

[5]  Fuzhong Weng,et al.  Characterization of Bias of Advanced Himawari Imager Infrared Observations from NWP Background Simulations Using CRTM and RTTOV , 2016 .

[6]  Fuqing Zhang,et al.  Potential impacts of assimilating all‐sky infrared satellite radiances from GOES‐R on convection‐permitting analysis and prediction of tropical cyclones , 2016 .

[7]  Isabel F. Trigo,et al.  Comparison of model land skin temperature with remotely sensed estimates and assessment of surface‐atmosphere coupling , 2015 .

[8]  Brett Candy,et al.  Assimilation of surface‐sensitive infrared radiances over land: Estimation of land surface temperature and emissivity , 2014 .

[9]  Richard Marriott,et al.  The impact of Metop and other satellite data within the Met Office global NWP system using an adjoint-based sensitivity method , 2013 .

[10]  W. Paul Menzel,et al.  Determining diurnal variations of land surface emissivity from geostationary satellites , 2012 .

[11]  Fuzhong Weng,et al.  Synthetic radiance simulation and evaluation for a Joint Observing System Simulation Experiment , 2012 .

[12]  Weizhong Zheng,et al.  Improvement of daytime land surface skin temperature over arid regions in the NCEP GFS model and its impact on satellite data assimilation , 2012 .

[13]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[14]  Timothy J. Schmit,et al.  Land surface emissivity from high temporal resolution geostationary infrared imager radiances: Methodology and simulation studies , 2011 .

[15]  Jun Li,et al.  An objective methodology for infrared land surface emissivity evaluation , 2010 .

[16]  Debbie Clifford,et al.  Global estimates of snow water equivalent from passive microwave instruments: history, challenges and future developments , 2010 .

[17]  S. Hook,et al.  The ASTER spectral library version 2.0 , 2009 .

[18]  Stephen J. English,et al.  The Importance of Accurate Skin Temperature in Assimilating Radiances From Satellite Sounding Instruments , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[19]  V. Caselles,et al.  Influence of soil water content on the thermal infrared emissivity of bare soils: Implication for land surface temperature determination , 2007 .

[20]  Daniel K. Zhou,et al.  Physical retrieval of surface emissivity spectrum from hyperspectral infrared radiances , 2007 .

[21]  Peter J. Minnett,et al.  The Global Ocean Data Assimilation Experiment High-resolution Sea Surface Temperature Pilot Project , 2007 .

[22]  D. Blumstein,et al.  The IASI/MetOp1 Mission: First observations and highlights of its potential contribution to GMES2 , 2007 .

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

[24]  Leonardo F. Peres,et al.  Emissivity maps to retrieve land-surface temperature from MSG/SEVIRI , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[25]  Kenneth Sassen,et al.  Cloud Type and Macrophysical Property Retrieval Using Multiple Remote Sensors , 2001 .

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

[27]  M. Matricardi,et al.  An improved fast radiative transfer model for assimilation of satellite radiance observations , 1999 .

[28]  X. Wu,et al.  Emissivity of rough sea surface for 8-13 num: modeling and verification. , 1997, Applied optics.

[29]  S. Schwartz,et al.  The Atmospheric Radiation Measurement (ARM) Program: Programmatic Background and Design of the Cloud and Radiation Test Bed , 1994 .

[30]  J. Salisbury,et al.  Emissivity of terrestrial materials in the 3–5 μm atmospheric window☆ , 1992 .

[31]  Jimy Dudhia,et al.  A Description of the Advanced Research WRF Model Version 4 , 2019 .

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

[33]  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 .

[34]  G. Powers,et al.  A Description of the Advanced Research WRF Version 3 , 2008 .

[35]  Fuzhong Weng,et al.  JCSDA Community Radiative Transfer Model (CRTM) : version 1 , 2006 .

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

[37]  Jean-Noël Thépaut,et al.  An improved general fast radiative transfer model for the assimilation of radiance observations , 2004 .

[38]  N. R. Smith,et al.  The Global Ocean Data Assimilation Experiment , 2000 .

[39]  W. C. Snyder,et al.  Classification-based emissivity for land surface temperature measurement from space , 1998 .