Parts of the U.S. Government are closed. This site will not be updated; however NOAA websites and social media channels necessary to protect lives and property will be maintained. See https://www.weather.gov for critical weather information. To learn more, see https://www.commerce.gov.
Instrument Calibration for NOAA's Geostationary Operational
Environmental Satellite (GOES) and for the solar reflectance channels of
the Advanced Very High Resolution Radiometer (AVHRR).
What is Calibration and How?
Satellite instrument responds to signal and its working environment.
These "measurements" are recorded as electrical pulses in terms of
"count". Users need the spectral radiation in terms of "radiance" that
is purely from the signal and not affected by the instrument status.
This process of conversion is instrument calibration. Though rightly
transparent to most users, this is a critical step before any satellite
product (picture of cloud or temperature or vegetation) can be
Calibration typically involves characterizing instrument responses to
known signals in such details that instrument responses to unknown
signals can then be interpreted in terms of the known signals. The
Satellite Calibration and Data Assimilation Branch of STAR is responsible for the calibration of all
NOAA satellite instruments.
Why Is Calibration An Integral Part of the NOAA Satellite Program?
Calibration affects all products and users of satellite data because
it is near the source of data stream.
Calibration must be performed and monitored frequently and
throughout the mission life because the working environment of the
instrument may change rapidly and the instrument itself may degrade
Calibration is imperative as scientific community sifts through
historical data for implications of climate changes.
And finally, calibration plays an important role in designing future
satellite instrument and mission.
Calibration support for current satellite operations:
Operational calibration of the AVHRR solar reflectance channels
Operational calibration of the GOES Imager visible channels
Calibration support for GOES Imager and Sounder operations
Member, Calibration Product Oversight Panel
Calibration support for re-processing of historical data:
Re-calibrate the AVHRR solar reflectance channels for the past quarter of century
Calibration support for the development and deployment of future satellite systems:
Instrument Scientist, GOES-N series
Instrument Scientist, Visible/Infrared Imager/Radiometer Suite (VIIRS)
Member, VIIRS Operational Algorithm Team
Leader, Instrument Characterization Team of the NPOESS Data
Exploitation (NDE) Project
Member, GOES-R Atmosphere, Ocean, and Land Products Technical
Member and NOAA Climate Goal Representative, GOES-R Calibration
and Validation Steering Committee
Member, GOES-R Calibration Working Group
Past Employment and Work:
1990 - 1993: Post-Doctoral Fellow at the Cooperative Institute for
Research in Environmental Sciences (CIRES), University of Colorado-Boulder.
Constructed a climatology of the upper tropospheric humidity (UTH)
from the High-resolution Infrared Radiation Sounder (HIRS) archive.
1993 - 2002: Associate Researcher, Assistant Scientist, and Associate
Scientist from 1993-2002 at the Cooperative Institute for Meteorological
Satellite Studies (CIMSS), University of Wisconsin-Madison.
Derived UTH from geostationary satellites to study upper tropospheric
dynamics (in conjunction with satellite-derived wind).
Verified and improved an emissivity model for wind-roughened sea
surface between 8-13 micron.
Developed and implemented the algorithm to produce sea surface
temperature (SST) from GOES.
Assimilated Advanced Microwave Sounding Unit (AMSU) data into NWP
model to infer water vapor and cloud water profiles.
Participated in the post-launch science tests for GOES-10/11/12.
2002 - Present: Physical Scientist at NOAA/NESDIS/STAR.
B.S. (Geography), Beijing Normal University.
M. S. (Meteorology), University of Wisconsin-Madison.
Intercomparison of Earth Radiation Budget Experiment (ERBE) Scanner
and Nonscanner measurements
Ph.D. (Meteorology), University of Wisconsin-Madison.
"Assimilation of ERBE data with nonlinear programming technique to
improve cloud cover diagnosis in numerical weather prediction