The space-borne infrared (IR) hyperspectral sounder is one important part of benchmark instruments for detection of the tiny change of long-term global climate. The IR sounder should provide irrefutable benchmarking records by measuring the infrared radiance with an ultra-high accuracy of 0.1 K (k=3, or 99% confidence), and tracing it to the Système Internationale (SI) standard for the Kelvin through the Planck function theory. Besides, the IR sounder would also constitute a reference standard, or calibration observatory, in space to inter-calibrate the international fleet of IR sounders onboard weather satellites, especially those are not as well calibrated. The measurement needs to be well-calibrated with the instrument features being eliminated, and it is critical to investigate the possible error sources associated with the sounder design and its radiometric calibration. One calibration error that arises in Fourier Transform Spectrometers (FTS) has been found associated with the spectrally variable instrument responsivity. According to the theoretical analysis of the current radiometric calibration, this error is an intrinsic feature of the FTS instruments, but it will lead to the measurements no longer being served as the standard radiances because of a radiance error introduced in the calibrated spectrum. In this paper, the radiometric errors result from the instrument responsivity effect are revealed by numerical simulations based on the spectral responses for ideal and close-to-real instruments.
The infrared (IR) benchmark sounder is designed to detect the tiny change of long-term global climate by measuring the spectrally resolved IR radiance emitted from Earth to space with high accuracy. Besides, the IR sounder also serve as a space-borne radiometric reference to convert the international fleet of weather sounders into a climate benchmarking system with excellent global coverage and similar measurement accuracy. In order to achieve high accuracy, the benchmark sounder must be tuned to be a linear response system and be well radiometrically calibrated. So the nonlinearity response in an IR detector signal chain needs to be corrected prior to the linear radiometric calibration. There are some algorithmic approaches being commonly used to correct the nonlinear measurements. These methods use the measured nonlinear interferograms to polynomially fit the corrected linear interferograms, without considering the physical root of non-linearity. However, they work well only when the detector nonlinearity is small. Regarding the large nonlinearity, a correction method is proposed in this paper. It follows the nonlinearity response mechanism of the IR detector, and uses the to-be-solved linear interferogram to polynomially fit the measured non-linear interferogram signal formally, and then derive the correction coefficients from the established equations. According to the correction evaluation and methods comparison using the simulated data as proxy measurements, the proposed method is appropriate for both small and large degree of quadratic nonlinearity detectors.
Fengyun-3C (FY3C) launched on 23 Sep, 2013 and InfraRed Atmospheric Sounder (IRAS) start to
work on 30 Sep. Verification of instrument performance is an essential step before the L1 data
distributed operationally. Verification performance including: BlackBody temperature, channel noises,
radiance data assessment, Geo-location evaluation, instrument parameters trending, et al. Noise
Equivalent Differential Radiance (NEdN) of all IR channels meet specification and got improvement
on FY3B. IRAS L1 data are evaluated with Infrared Atmospheric Sounding Interferometer (IASI)
measurements onboard European MetOp-A satellite using cross comparison method, biases are within
1K for all IR channels except ch1 and ch9. Trends of instruments components temperature are also
discussed.
The Vertical Atmospheric Sounding Suits (VASS) onboard FY-3C satellite includes The Infrared Atmospheric
Sounder (IRAS), Microwave Temperature Sounder (MWTS) and Microwave Temperature and moisture sounder
(MWTHS-II). The IRAS is similar to that onboard FY-3A/B, while the MWTS-II/MWTHS-II is more sophisticated
than their precursors. MWTS has 13 channels mainly at the window region and 57 O2 absorption band, and
MWTHS has 15 channels mainly at the 118 O2 absorption band and the 183 H2O absorption band. A package has
been developed to retrieve the atmospheric temperature profile, moisture profile, atmospheric total ozone, and
other parameters in both clear and cloudy atmospheres from the VASS measurements, which is remap to IRAS
Field of view. The algorithm that retrieves these parameters contains four steps: 1) cloud and precipitation
detection, 2) bias adjustment for VASS measurements, 3) regression retrieval processes, and 4) a nonlinear iterative
physical retrieval. The package does not process precipitation FOV, and for non-precipitation cloud FOV, the
measurements from middle to low channels of IRAS are excluded. Till now all instruments are under orbit
examination stage, and the primary results show that temperature soundings can be produced under partial cloud
cover with RMS errors on the order of, or better than, 2.0 K in 1-km-thick layers from the surface to 700 mb, 1-km
layers from 700–300 mb, 3-km layers from 300–30 mb, and 5-km layers from 30–1 mb; and moisture profiles can
be obtained with an accuracy better than 20% absolute errors in 2-km layers from the surface to nearly 300 mb.
Retrieval of atmospheric profiles from the vertical atmospheric sounding suite aboard the Chinese
FY-3A satellite has been investigated. A statistical retrieval approach is used to generate atmospheric
temperature and moisture profiles. The statistical retrieval method is only applied to the clear-sky
simulated radiances, achieving good retrieval accuracy. For example, in the simulated experiment, the
retrieved atmospheric temperature and moisture profiles show good agreement with independent
atmospheric samples. The RMS is about 1.2K on the average for temperature profile. The RMS is large
for the near surface levels. The RMS of moisture profile is approximately 11%. The temperature and
moisture fields agree well with the NWP analyses of NCEP.
Sensitivity studies of atmospheric temperature and humidity profile retrieval from EOS AQUA/AIRS measurements , that involve spectral coverage sensitivity , channel coverage sensitivity , additional predictors effect , are performed via empirical orthogonal function (eigenvectors of covariance ) expansion , leading to the revealment of new features of high-resolution infrared sounding . Simulation studies on atmospheric temperature profile retrieval based on the channel characteristics and spectral response function of IRAS had also be done In order to investigate the performance of InfRared Atmospheric Sounder (IRAS) which will be onboard the FY-3A satellite.
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