Community Radiative Transfer Model (CRTM) for Satellite Radiance Data Applications

1
Community Radiative Transfer Model (CRTM) for
Satellite Radiance Data Applications
Yong Han1(GOVERNMENT PRINCIPLE INVESTIGATOR),5,
Fuzhong Weng1(GOVERNMENT PRINCIPLE
INVESTIGATOR),5, Paul VanDelst2,5, Quanhua
Liu3,5, David Groff2,5, Banghua Yan3,5, Yong
Chen4,5, and Ron Vogel3,5
1NOAA/NESDIS/STAR/SMCD, 2SAIC/NCEP, 3PGS/NESDIS,
4CIRA/NESDIS, 5Joint Center for Satellite Data
Assimilation
CRTM

• Requirement
• Increase lead time and accuracy for weather and
  water warnings and forecasts
• Improve predictability of the onset, duration,
  and impact of hazardous and severe weather and
  water events
• Reduce uncertainty associated with weather and
  water forecasts, assessments, and decision tools
• Increase development, application, and transition
  of advanced science and technology to operations
  and services
• Describe and understand the state of the climate
  system through integrated observations, analysis,
  and data stewardship
• Science
• How can satellite radiances data be accurately
  and rapidly simulated and assimilated into
  Numerical Weather Prediction (NWP) models?
• Benefit
• National Weather Services, planned National
  Climate Services and their customers
• Numerical weather prediction and climate centers
  in assimilation of satellite radiance data in NWP
  and climate models
• Operational institutes in generation of satellite
  radiance data products
• Research and academic community in weather and
  climate studies and development of advanced space
  sensors
• International users

• What CRTM does?
• Simulate satellite radiances for given
  atmospheric and Earth surface state variables
• Compute radiance sensitivities needed for
  radiance assimilations and state variable
  retrievals
• What RT components included?
• Atmospheric molecular absorption and scattering
  (H2O, O3, CO2 and etc.)
• Cloud absorption and scattering
• Aerosol absorption and scattering
• Surface emission and reflection for various
  surface types
• Absorption and reflection of solar radiation
• Zeeman-splitting effect
• Which sensors included?
• Microwave, Infrared and Visible radiometric
  sensors
• Broadband and hyper-spectral sensors
• US historical, current and future sensors EU and
  other international sensors

CRTM is A Poweful Tool for Satellite Radiance
Data Assimilation and Used by JCSDA Partners

• Numerical Weather Prediction (NWP) model needs
  data to initialize the state variables
• CRTM can be used to map the state variables to
  radiances measured by satellite
• With the CRTM, radiance data are assimilated into
  the NWP models uses of the data have shown large
  impacts on forecast accuracy (see the figure on
  the right)
• CRTM has been continuously improved and expanded
  by joint efforts from the JCSDA community

NWP impact tests with (red, green and blue
curves) and without (black curve) uses of
satellite radiance data. CRTM plays a key role
for assimilating radiance data in NWP model.
CRTM major modules
Support more than 100 Sensors GOES-R ABI TIROS-N
to NOAA-19 AVHRR TIROS-N to NOAA-19 HIRS GOES-8
to 14 Imager GOES-8 to 14 sounder Terra/Aqua
MODIS METEOSAT-SG1 SEVIRI Aqua AIRS,
AMSR-E AMSU-A, HSB NOAA-15 to 19 AMSU-A NOAA-15
to 17 AMSU-B NOAA-18, 19 MHS TIROS-N to
NOAA-14 MSU DMSP F13 to 15 SSM/I DMSP F13,15
SSM/T1 DMSP F14,15 SSM/T2 DMSP F16-20 SSMIS
Coriolis Windsat TiROS to NOAA-14 SSU METOP-A
IASI AMSUA, MHS, HIRS, AVHRR FY-3 IRAS, MWTS,
MWHS, MWRI NPP/NPOSESS CrIS/ATMS
CRTM for simulating radiation intensity measured
by satellite-based radiometers
CRTM major modules

• Science Challenges
• Surface emissivity/reflectivity for surface
  sensitive channels over land are difficult to
  model to meet operational requirements
• Cloudy radiances have not been assimilated into
  NWP models due to a number of difficult issues
  such as cloud mass inhomogeneity across the
  radiance footprint
• Next steps
• Improve surface emissivity/reflectivity models
  and data bases for various land types,
• Implement the Bidirectional Reflection
  Distribution Functions (BRDF) model
• Improve CRTM performance under cloudy conditions
• Transition Path
• CRTM has been used in NCEP GFS and NESDIS
  Microwave Integrated Retrieval System (MIRS) and,
  therefore, new development and improvements in
  CRTM model can be rapidly applied in operations
• New version is delivered directly to NOAA/NCEP
  and a note of the new released is sent out
  through email to all other registered CRTM users.

Retrieved Water vapor from NOAA-18
CRTM Used in Calibration, Sensor Design and State
Variable Retrieval
Observation minus CRTM simulations before and
after the SRF shift

• A tool for radiance monitoring and calibration
• A model for sensor design and impact studies
  through the Observing System Simulation
  Experiments (OSSE)
• A key component in retrieval systems to derive
  atmospheric and surface parameters
• A model to generate proxy data for future sensors
  such as the GOES-R and JPSS sensors

CRTM is a key component of NOAA Microwave
Retrieval System (MIRS)
CRTM is used to determine frequency shift for
GOES-12 channel-14 spectral response function
(SRF). Radiance error is largely reduced (by
6K).
Example of NCEP radiance monitoring plots (CRTM
simulated observation) for NOAA-15 AMSUA ch1-4.
http//www.emc.ncep.noaa.gov/gmb/gdas/radiance/esa
fford/opr
CRTM simulated GOES-R ABI radiance in the 0.64µ
channel observing deep convective clouds over
Arizona and off the coast of South Carolina. (R.
Bradley Pierce et al.)