GMI Calibration Algorithm and Analysis: Theoretical Basis Document

GMI Calibration Algorithm and Analysis:


The goal of the calibration algorithm for the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is the conversion of Level 1A radiometer Earth and calibration
counts from the science and housekeeping telemetry data packets into Level 1B calibrated
top of atmosphere (TOA) brightness temperatures.

The GMI calibration algorithm follows closely the algorithms that have been developed by
Remote Sensing Systems (RSS) for other radiometers, e.g.: the special sensor microwave
imager SSM/I, the tropical rainfall mission (TRMM) microwave imager TMI, the advanced
microwave scanning radiometer AMSR, the WindSat microwave radiometer and the special
sensor microwave imager and sounder SSMIS. There are some deviations from the RSS algorithms to account for unique products from GMI, such as 4-point calibration, non-linearity retrieval, noise diode coupled temperature determination, and hot load backup functionality.

The purpose of the GMI is to collect global microwave radiometry. The GMI Instrument
will operate continuously after being placed on orbit. The instrument consists of all hardware and software to collect radiometric data, perform instrument calibration, and send GMI Science Data Records (GSDRs) and GMI Housekeeping Data Records (GHDRs) to the spacecraft for transmission to the GMI ground station. The data will be processed to produce microwave imagery and other specialized meteorological data using algorithms developed by the government. The GMI Instrument is shown in Figure 1 in its stowed and in Figure 2 deployed configuration.

GMI has similarity to other radiometers in that it measures radiation from two calibration
loads, a cold sky view and a black body (hot load). GMI is distinct in that it also provides
two additional measurements, a cold sky view with noise diode and hot load view with noise  diode. Operational GMI has a calibration cycle that repeats every other scan rotation. On the first rotation, the cold sky view and the hot load are sampled and on the second rotation the cold sky view plus noise diode and hot load plus noise diode is sampled. This provides 4 calibration points, enough information to allow the excess noise temperature of the noise diodes and the nonlinearity of the receivers to be determined in addition to the gain and offset of the receivers.

Algorithm Structure and Submodules 

Remote Sensing Systems