Literature DB >> 32742077

Spectrally Dependent CLARREO Infrared Spectrometer Calibration Requirement for Climate Change Detection.

Xu Liu1, Wan Wu2, Bruce A Wielicki1, Qiguang Yang2, Susan H Kizer2, Xianglei Huang3, Xiuhong Chen3, Seiji Kato1, Yolanda L Shea1, Martin G Mlynczak1.   

Abstract

Detecting climate trends of atmospheric temperature, moisture, cloud, and surface temperature requires accurately calibrated satellite instruments such as the Climate Absolute Radiance and Reflectivity Observatory (CLARREO). Wielicki et al. have studied the CLARREO measurement requirements for achieving climate change accuracy goals in orbit. Our study further quantifies the spectrally dependent IR instrument calibration requirement for detecting trends of atmospheric temperature and moisture profiles. The temperature, water vapor, and surface skin temperature variability and the associated correlation time are derived using Modern Era Retrospective-Analysis for Research and Applications (MERRA) and European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. The results are further validated using climate model simulation results. With the derived natural variability as the reference, the calibration requirement is established by carrying out a simulation study for CLARREO observations of various atmospheric states under all-sky. We derive a 0.04 K (k=2, or 95% confidence) radiometric calibration requirement baseline using a spectral fingerprinting method. We also demonstrate that the requirement is spectrally dependent and some spectral regions can be relaxed due to the hyperspectral nature of the CLARREO instrument. We further discuss relaxing the requirement to 0.06 K (k=2) based on the uncertainties associated with the temperature and water vapor natural variability and relatively small delay in time-to-detect for trends relative to the baseline case. The methodology used in this study can be extended to other parameters (such as clouds and CO2) and other instrument configurations.

Entities:  

Year:  2017        PMID: 32742077      PMCID: PMC7394084          DOI: 10.1175/JCLI-D-16-0704.1

Source DB:  PubMed          Journal:  J Clim        ISSN: 0894-8755            Impact factor:   5.148


  4 in total

1.  Principal component-based radiative transfer model for hyperspectral sensors: theoretical concept.

Authors:  Xu Liu; William L Smith; Daniel K Zhou; Allen Larar
Journal:  Appl Opt       Date:  2006-01-01       Impact factor: 1.980

2.  Development of a fast and accurate PCRTM radiative transfer model in the solar spectral region.

Authors:  Xu Liu; Qiguang Yang; Hui Li; Zhonghai Jin; Wan Wu; Susan Kizer; Daniel K Zhou; Ping Yang
Journal:  Appl Opt       Date:  2016-10-10       Impact factor: 1.980

3.  Fast and accurate hybrid stream PCRTM-SOLAR radiative transfer model for reflected solar spectrum simulation in the cloudy atmosphere.

Authors:  Qiguang Yang; Xu Liu; Wan Wu; Susan Kizer; Rosemary R Baize
Journal:  Opt Express       Date:  2016-12-26       Impact factor: 3.894

4.  Attribution of observed surface humidity changes to human influence.

Authors:  Katharine M Willett; Nathan P Gillett; Philip D Jones; Peter W Thorne
Journal:  Nature       Date:  2007-10-11       Impact factor: 49.962

  4 in total

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