Preflight assessment of the Cross-track Infrared Sounder (CrIS) performance

被引:10
|
作者
Zavyalov, Vladimir V. [1 ]
Fish, Chad S. [1 ]
Bingham, Gail E. [1 ]
Esplin, Mark [1 ]
Greenman, Mark [1 ]
Scott, Deron [1 ]
Han, Yong [2 ]
机构
[1] Utah State Univ, Space Dynam Lab, 1695 N Res Pk Way, N Logan, UT 84341 USA
[2] Natl Ocean & Atmospher Adm, Ctr Satellite Applicat & Res, Natl Environm Satellite Data & Informat Serv, Camp Springs, MD 20746 USA
关键词
CrIS; ATMS; NPOESS Preparatory Project; JPSS; Calibration; Validation;
D O I
10.1117/12.897674
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
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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收藏
页数:12
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