An Adaptive Calibration Window for Noise Reduction of Satellite Microwave Radiometers

Time series of the noise of 183±1 and ±3 GHz with the fixed and adaptive window. There is a significant noise reduction with the adaptive window as much as over 50%
Time series of the noise of 183±1 and ±3 GHz with the fixed and adaptive window. There is a significant noise reduction with the adaptive window as much as over 50%

ESSIC scientists John Xun Yang, Yalei You, and Ralph Ferraro are co-authors on a new paper in Institute of Electrical and Electronics Engineers (IEEE) that describes a newly developed adaptive window for calibration on microwave sounders at EUMETSAT and NOAA.

 

Over the years, a fixed window for smoothing radiometer cold-space and warm-load counts and processing brightness temperature in calibration has been used for all microwave sounders at EUMETSAT and NOAA. This process is based on ground tests and legacy satellites, but it remains unclear if this parameter is optimal for in-orbit radiometers, as the space environment is different from the ground and radiometers may drift.

 

The researchers found that the fixed window is not optimal and leads to large noise. In response, they have developed an adaptive window that accommodates channel differences and temporal changes in hardware. This has led to a noise reduction by as much as 50% for 183 GHz channels of MetOp-C MHS. They observed temporal jumps and shifts in counts, gain and noise of 89 and 190 GHz, and accordingly, the adaptive window can adjust to reduce such an impact. This study suggests that an adaptive method has advantages over the fixed method for considering channel differences and time-varying noise.

 

Yang is an Assistant Research Scientist at ESSIC/CISESS. His research areas include Earth remote sensing, microwave radiometry, hardware development, calibration, and retrievals. He has been involved with a number of NASA/NOAA satellite missions, including the Aquarius, GPM, CYGNSS, JPSS, and TROPICS. He is a senior member of IEEE and an associate editor of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS).

 

You is an Associate Research Scientist at ESSIC/CISESS. received his B.S. and M.S. degrees in atmospheric science from Yunnan University, Kunming, Yunnan, China, in 2005 and 2008, respectively, and the Ph.D. degree in meteorology from Florida State University, Tallahassee, FL, USA, in 2013. His research interests include passive microwave precipitation algorithm development, precipitation data set validation, and microwave instrument calibration. You has served as an Associate Editor for the Journal of Hydrometeorology and the Journal of Applied Meteorology and Climatology.

 

Ferraro is the Associate Director of ESSIC. His current research focuses on the use of environmental satellite remote sensing for both weather and climate studies with an emphasis on precipitation and other hydrological cycle products.

 

The other authors of the article are William Blackwell from MIT Lincoln Laboratory (who has previously given an ESSIC Seminar); Quanhua Liu from National Environmental Satellite, Data, and Information Service; David Draper from Ball Aerospace and Technologies Corporation; Nigel Atkinson from Met Office; Tim Hewison from European Organization for the Exploitation of Meteorological Satellites (EUMETSAT); Sidharth Misra from NASA Jet Propulsion Laboratory; and Jinzheng Peng from NASA Goddard Space Flight Center.


To access the article, click here: “An Adaptive Calibration Window for Noise Reduction of Satellite Microwave Radiometers”.