Cross-track Infrared Sounder (CrIS) development status

Glumb, Ronald J.; Williams, Frederick L.; Funk, Nathan C.; Châteauneuf, François; Roney, Alan; Allard, Roch

doi:10.1117/12.508544

Cited by 19 publications

(13 citation statements)

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“…To return to the radiance space, multiply by the noise estimate and add mean radiance i R Random noise, filtered out after reconstruction of the original data by truncated set of optimal number of PCs, can be estimated as the standard deviation of the residual errors between the original and reconstructed data: Knowing the total noise and its random component, the correlated component NEdN c can be easily estimated according to the equation (1). In our experience, only one PC needs to be retained to reconstruct typical BB spectra when random noise is dominant or comparable with spectrally correlated noise.…”

Section: Appendix Pca Approach For Instrument Noise Characterizationmentioning

confidence: 99%

“…Together, these instruments provide precise measurements of vertical distributions of temperature, moisture, and pressure within the Earth's atmosphere. CrIS is a sophisticated interferometric sounding sensor which accurately measures upwelling infrared radiance at very high spectral resolution [1] . The science heritage for CrIS was derived from the Atmospheric Infrared Radiation Sounder (AIRS) on the NASA EOS Aqua satellite [2] and Infrared Atmospheric Sounding Interferometer (IASI) on the European Metop platform [3] [4] .…”

Section: Introductionmentioning

confidence: 99%

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Preflight assessment of the cross-track infrared sounder (CrIS) performance

et al. 2011

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The Cross-track Infrared Sounder (CrIS) is a part of the Crosstrack Infrared and Microwave Sounding Suite (CrIMSS) that will be used to produce accurate temperature, water vapor, and pressure profiles on the NPOESS Preparatory Project (NPP) and upcoming Joint Polar Satellite System (JPSS) operational missions. The NPP CrIS flight model has completed sensor qualification, characterization, and calibration and is now integrated with the NPP spacecraft in preparation for the launch. This paper reviews the CrIS performance during thermal vacuum tests, including the spacecraft integration test, and provides a comparison to the AIRS and IASI heritage sensors that it builds upon. The CrIS system consists of the instrument itself and ground-based scientific algorithms. The data reported in this paper was processed with the latest version of the CrIS science sensor data record (SDR) algorithm and thus reflects the performance of the CrIS SDR system. This paper includes the key test results for Noise Equivalent Differential Noise (NEdN), Radiometric Performance, and Spectral Accuracy. The CrIS sensor performance is outstanding and will meet the mission needs for the NPP /JPSS mission. NEdN is one of the key performance tests for the CrIS sensor. The overall NEdN performance for the CrIS in the LWIR, MWIR and SWIR spectral bands is excellent and is comparable or exceeds NEdN performance of AIRS and IASI. Also discussed is the Principal Component Analysis (PCA) approach developed to estimate contribution of random and spectrally correlated noise components to the total NEDN.

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Section: Appendix Pca Approach For Instrument Noise Characterizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Preflight assessment of the cross-track infrared sounder (CrIS) performance

et al. 2011

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“…The impact is mainly obtained for geopotential height, mean surface level pressure and wind forecast depending on the verification areas. Guidard et al (2011) studied the impact of IASI assimilation in both global and regional Météo-France models. They showed a quite good impact on the forecast skills for large-scale variables such as tropospheric temperature, wind fields and 500 hPa geopotential height both in the global ARPEGE (Action Petite Echelle Grande Echelle) model (Courtier et al, 1991) and the AROME (Actions of Research to Operations at Mesoscale) regional model (Seity et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

“…A huge quantity of improvements have taken place in the first decade of the 21st century with the launch of new infrared (IR) sounders such as the Atmospheric Infrared Sounder (AIRS) in 2002 (Aumann et al, 2003), the Infrared Atmospheric Sounding Interferometer (IASI) in 2006 (Cayla, 2001;Chalon et al, 2001) and the Cross-track Infrared Sounder (CrIS) in 2011 (Glumb et al, 2003). These instruments have drastically raised the amount of information available for meteorological purposes compared to the precedent HIRS (High-resolution Infrared Radiation Sounder) infrared sounder, launched in the late 1970s, which offers 19 IR and 1 visible channels as compared with the thousands of channels available in this new generation of instruments.…”

Section: Introductionmentioning

confidence: 99%

A simulated observation database to assess the impact of the IASI-NG hyperspectral infrared sounder

et al. 2018

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Abstract. The highly accurate measurements of the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) are used in numerical weather prediction (NWP), atmospheric chemistry and climate monitoring. As the second generation of the European Polar System (EPS-SG) is being developed, a new generation of IASI instruments has been designed to fly on board the MetOp-SG constellation: IASI New Generation (IASI-NG). In order to prepare the arrival of this new instrument, and to evaluate its impact on NWP and atmospheric chemistry applications, a set of IASI and IASI-NG simulated data was built and made available to the public to set a common framework for future impact studies. This paper describes the information available in this database and the procedure followed to run the IASI and IASI-NG simulations. These simulated data were evaluated by comparing IASI-NG to IASI observations. The result is also presented here. Additionally, preliminary impact studies of the benefit of IASI-NG compared to IASI on the retrieval of temperature and humidity in a NWP framework are also shown in the present work. With a channel dataset located in the same wave numbers for both instruments, we showed an improvement of the temperature retrievals throughout the atmosphere, with a maximum in the troposphere with IASI-NG and a lower benefit for the tropospheric humidity.

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“…Fourier transform spectrometers like Infrared Atmospheric Sounding Interferometer (IASI) [Diebel et al, 1996], Cross-Track Infrared Sounder (CrIS) [Glumb et al, 2003], Geostationary Imaging Fourier Transform Spectrometer (GIFTS) [Smith et al, 2001], and Hyperspectral Environmental Sounder (HES) [Li et al, 2003], and grating spectrometers like the Atmospheric Infrared Sounder (AIRS) [Aumann and Miller, 1995;Rosenkranz and Staelin, 1994] represent the present and the future of the atmospheric remote sensing in the infrared part of the spectrum. The observing capabilities of these systems, in terms of accuracy and spatial resolution of the retrieved geophysical parameters, can be significantly improved by increasing the spectral resolutions and/or enhancing the signal to noise ratios [Smith et al, 1979;Huang et al, 1992;Zhou et al, 2002].…”

Section: Introductionmentioning

confidence: 99%

A principal component noise filter for high spectral resolution infrared measurements

et al. 2004

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[1] This paper describes the application of principal component analysis to reduce the random noise present in the hyperspectral infrared observations. Within a set of spectral observations the number of components needed to characterize the atmosphere is far less than the number of wavelengths observed, typically by a factor between 50 and 70. The higher-order components, which mainly serve to characterize noise, can be eliminated along with the noise that they characterize. The results obtained depend on the variability of the selected sets of observations and on specific instrument characteristics such as spectral resolution and noise statistics. For a set of 10,000 Fourier transform spectrometer (FTS) simulated spectra, whose standard deviation is about 10% of the mean, we were able to obtain noise reduction factors between 5 and 8. Results obtained from real FTS, with standard deviation of about 10% of the mean, indicated practical noise reduction between 5 and 6. To avoid loss of information in the presence of highly deviant observations, it is necessary to use a conservative number of principal components higher than the optimum to maximum noise reduction. However, even then, noise reduction factors of 4 are still achievable.

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Cross-track Infrared Sounder (CrIS) development status

Cited by 19 publications

References 0 publications

Preflight assessment of the cross-track infrared sounder (CrIS) performance

Preflight assessment of the cross-track infrared sounder (CrIS) performance

A simulated observation database to assess the impact of the IASI-NG hyperspectral infrared sounder

A principal component noise filter for high spectral resolution infrared measurements

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