Assessing NOAA-16 HIRS Radiance Accuracy Using Simultaneous Nadir Overpass Observations from AIRS

Wang, Likun; Cao, Changyong; Ciren, Pubu

doi:10.1175/jtech2073.1

Cited by 32 publications

(29 citation statements)

References 25 publications

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“…[3] Often, inter-calibration efforts [Iacovazzi and Cao, 2007;Wang et al, 2007;Goldberg et al, 2011;John et al, 2012b] use only near-nadir measurements and assume the biases estimated for nadir are applicable for all viewing angles. However, as stated above, this is not often true and scan asymmetries must be taken into account while inter-calibrating cross-track scanning instruments.…”

Section: Introductionmentioning

confidence: 99%

Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs)

et al. 2013

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[1] Simultaneous all angle collocations (SAACs) of microwave humidity sounders (AMSU-B and MHS) on-board polar orbiting satellites are used to estimate scan-dependent biases. This method has distinct advantages over previous methods, such as that the estimated scan-dependent biases are not influenced by diurnal differences between the edges of the scan and the biases can be estimated for both sides of the scan. We find the results are robust in the sense that biases estimated for one satellite pair can be reproduced by double differencing biases of these satellites with a third satellite. Channel 1 of these instruments shows the least bias for all satellites. Channel 2 has biases greater than 5 K, thus needs to be corrected. Channel 3 has biases of about 2 K and more and they are time varying for some of the satellites. Channel 4 has the largest bias which is about 15 K when the data are averaged for 5 years, but biases of individual months can be as large as 30 K. Channel 5 also has large and time varying biases for two of the AMSU-Bs. NOAA-15 (N15) channels are found to be affected the most, mainly due to radio frequency interference (RFI) from onboard data transmitters. Channel 4 of N15 shows the largest and time varying biases, so data of this channel should only be used with caution for climate applications. The two MHS instruments show the best agreement for all channels. Our estimates may be used to correct for scan-dependent biases of these instruments, or at least used as a guideline for excluding channels with large scan asymmetries from scientific analyses.

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Section: Introductionmentioning

confidence: 99%

Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs)

et al. 2013

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“…The inter-calibration of the IR and WV bands of MFG-4, -5, -6 with respect to MFG-7 relies on the HIRS channels 8 and 12. By comparison with the Atmospheric Infrared Sounder, Wang, L. et al [50] report a calibration uncertainty of 0.5 K for the HIRS channels used in this work. So, the additional uncertainty due to the MFG satellite inter-calibration can be estimated at 0.6%.…”

Section: Calibration Uncertaintymentioning

confidence: 74%

The CM SAF TOA Radiation Data Record Using MVIRI and SEVIRI

et al. 2017

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Abstract:The CM SAF Top of Atmosphere (TOA) Radiation MVIRI/SEVIRI Data Record provides a homogenised satellite-based climatology of TOA Reflected Solar (TRS) and Emitted Thermal (TET) radiation in all-sky conditions over the Meteosat field of view. The continuous monitoring of these two components of the Earth Radiation Budget is of prime importance to study climate variability and change. Combining the Meteosat MVIRI and SEVIRI instruments allows an unprecedented temporal (30 min/15 min) and spatial (2.5 km/3 km) resolution compared to, e.g., the CERES products. It also opens the door to the generation of a long data record covering a 32 years time period and extending from 1 February 1983 to 30 April 2015. The retrieval method used to process the CM SAF TOA Radiation MVIRI/SEVIRI Data Record is discussed. The overlap between the MVIRI and GERB instruments in the period 2004-2006 is used to derive empirical narrowband to broadband regressions. The CERES TRMM angular dependency models and theoretical models are respectively used to compute the TRS and TET fluxes from the broadband radiances. The TOA radiation products are issued as daily means, monthly means and monthly averages of the hourly integrated values (diurnal cycle). The data is provided on a regular grid at a spatial resolution of 0.05 degrees and covers the region 70 • N-70 • S and 70 • W-70 • E. The quality of the data record has been evaluated by intercomparison with several references. In general, the stability in time of the data record is found better than 4 Wm −2 and most products fulfill the predefined accuracy requirements.

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“…Mixing spectral response-induced biases (i.e., spectral biases) with instrument calibration biases (i.e., radiometric biases) will lead to erroneous analyses. It is generally recognized in scientific literature that different SRFs will cause measurement biases for the infrared sounding channels (Cao et al 2005b;Wang et al 2007). However, studies have shown that a prelaunch measurement of the SRFs has uncertainties based on comparisons of measurements by both the vendor and National Institute of Standards and Technology (NIST).…”

Section: Methodology For Estimating Hirs Spectral Biases a Quantifyimentioning

confidence: 99%

“…First, due to the small orbital variation of the intersatellite biases for band 8, an intersatellite bias found in the polar region at the SNOs can be applied to global datasets for this particular channel, especially when the correlation in radiances between satellites is established. This is possible also because HIRS is proven to be stable with little orbital variation in the calibration biases in normal operating conditions because of the fact that the radiation reaching the HIRS detector is dominated by aft optics temperatures, which are very stable (Cao et al 2007). For example, the variation of the orbital gain for band 8 is typically at 0.009%, and the maximum orbital gain variation is on the order of 0.3% per orbit (e.g., average slope: 20.03769; standard deviation: 0.00003414; maximum 2 minimum 5 0.0001364).…”

Section: Using the Iasi/hirs Spectral Bias Bell Curves To Identify Himentioning

confidence: 99%

Spectral Bias Estimation of Historical HIRS Using IASI Observations for Improved Fundamental Climate Data Records

Cao

Goldberg

Wang³

2009

Journal of Atmospheric and Oceanic Technology

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A prerequisite for climate change detection from satellites is that the measurements from a series of historical satellites must be consistent and ideally made traceable to the International System of Units (SI). Unfortunately, this requirement is not met for the 14 High Resolution Infrared Radiation Sounders (HIRS) on the historical NOAA satellites, because the instrument was developed for weather forecasts and lacks accuracy and consistency across satellites. It is well known that for HIRS, differences in the spectral response functions (SRF) between instruments and their prelaunch measurement uncertainties often lead to observations of the atmosphere at different altitudes. As a result of the atmospheric lapse rate, they both can introduce significant intersatellite biases. The SRF-dependent biases are further mixed with other effects such as the diurnal cycle because of observation time differences and orbital drifts, on board calibration, and algorithm issues. In this study, the Infrared Atmospheric Sounding Interferometer (IASI) observations are used to calculate the radiances for the 14 Television Infrared Observation Satellite series N (TIROS-N; to MetOp-A) HIRS instruments in different climate regimes and seasons to separate the SRF-induced intersatellite biases from other factors. It is found that the calculated radiance ratio (a bias indicator) using IASI observations for the HIRS satellite pairs forms bell-shaped curves that vary with the HIRS model and channel as well as climate regimes. This suggests that a bias found in the polar regions at the Simultaneous Nadir Overpass (SNO) cannot be blindly used for bias correction globally; instead, the IASI/HIRS spectral bias bell curves should be used as a complement to more fully address the biases. These bell curves also serve as lookup charts for separating the bias due to true SRF differences from that caused by SRF prelaunch measurement errors to resolve the inconsistency, which sheds new light on reprocessing and reanalysis in generating fundamental climate data records from HIRS.

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Assessing NOAA-16 HIRS Radiance Accuracy Using Simultaneous Nadir Overpass Observations from AIRS

Cited by 32 publications

References 25 publications

Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs)

Monitoring scan asymmetry of microwave humidity sounding channels using simultaneous all angle collocations (SAACs)

The CM SAF TOA Radiation Data Record Using MVIRI and SEVIRI

Spectral Bias Estimation of Historical HIRS Using IASI Observations for Improved Fundamental Climate Data Records

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