Zong Xuemei. Estimating the inversion accuracy of atmospheric temperature and water vapor profile under limb sounding. J Appl Meteor Sci, 2020, 31(4): 471-481. DOI:  10.11898/1001-7313.20200409.
Citation: Zong Xuemei. Estimating the inversion accuracy of atmospheric temperature and water vapor profile under limb sounding. J Appl Meteor Sci, 2020, 31(4): 471-481. DOI:  10.11898/1001-7313.20200409.

Estimating the Inversion Accuracy of Atmospheric Temperature and Water Vapor Profile Under Limb Sounding

DOI: 10.11898/1001-7313.20200409
  • Received Date: 2020-02-10
  • Rev Recd Date: 2020-03-31
  • Publish Date: 2020-07-31
  • Profiles of atmospheric temperature and water vapor are important for studying atmospheric state and play an important role in the energy balance of earth-atmosphere system. Limb remote sensing is an important means to obtain the profile of atmospheric parameters. The atmospheric radiation ultra-high spectral detector developed by Shanghai Institute of Technical Physics, Chinese Academy of Sciences, has a detection band range of 650-3050 cm-1 and the spectral resolution on limb view is as high as 0.015 cm-1, which will be the highest spectral resolution that the world's Fourier spectral detector can achieve. A method by using information and weighting function linearization are proposed to evaluate the inversion accuracy of the research instrument in advance. Weighting functions of atmospheric temperature and water vapor at 16 different tangent points are simulated and calculated by RFM model. The degree of signal freedom and the entropy reduction are also calculated by the information content method, and the optimal number of inversion channels is determined to be 200 by the stepwise iterative algorithm. Combined with the threshold (0.3 K) of detectable brightness temperature and the linearized weighting function of the instrument, the available spectral channel numbers of atmospheric temperature and volume mixing ratio of water vapor profiles under different inversion accuracy of six atmosphere models (US standard atmosphere, tropical atmosphere, middle-latitude summer atmosphere, middle-latitude winter atmosphere, subarctic summer atmosphere, subarctic winter atmosphere) are calculated and analyzed, and the inversion accuracy is estimated theoretically. On the demanded optimal 200 channels, the inversion accuracy of the whole temperature profile is 0.6 K, but if the inversion accuracy of the temperature profile is required to be 0.5 K, the number of channels available for inversion at a higher tangent height is smaller. Except the tropical atmosphere model, there are enough channels for the other five atmosphere models meeting 5% accuracy demands of the inversion of water vapor volume mixing ratio profiles. However, the inversion of the water vapor profile of the tropical atmosphere has barely enough channels at 16-20 km for 10% relative inversion accuracy of volume mixing ratio. The number of channels usable for atmospheric parameters retrieving increases by the decreasing of inversion accuracy. Among six atmosphere models, the tropical atmosphere is relatively special and its inversion accuracy is lower, which may be related to the unique temperature profile of the tropical atmosphere. There is no isothermal layer in the tropical atmosphere, which may lead to fewer atmospheric parameter inversion channels near the height of sharp temperature transition.
  • Fig. 1  Weighting function of atmospheric temperature at different tangent heights

    Fig. 2  Linear diagram(a) and logarithmic diagram(b) of CO2's line intensity(I)

    Fig. 3  Weighting function of water vapor at different tangent heights

    Fig. 4  Linear diagram(a) and logarithmic diagram(b) of water vapor's line intensity(I′)

    Fig. 5  Degree of signal freedom and entropy reduction of atmospheric temperature change with spectral channel numbers

    Fig. 6  Six atmospheric temperature profiles

    Fig. 7  Six volume mixing ratio profiles of water vapor

    Table  1  The sum of degree of signal freedom and entropy reduction at tangent heights of 11.0 km and 25.3 km for atmospheric temperature and water vapor for different channel numbers

    光谱通道数温度(11.5 km)水汽(11.5 km)温度(25.3 km)水汽(25.3 km)
    信号自由度熵减少量信号自由度熵减少量信号自由度熵减少量信号自由度熵减少量
    52.19411.072.1794.892.26010.742.1164.23
    102.78911.532.7655.342.88711.232.7194.69
    203.40511.983.3405.773.51011.693.3535.16
    504.22112.584.0776.314.33012.294.2175.80
    1004.84013.034.6356.714.94912.744.8776.28
    2005.46013.485.2277.145.54913.185.5336.75
    3005.82513.745.5817.405.88213.425.9217.03
    4006.08513.935.8377.586.11113.586.1797.22
    5006.28814.086.0387.736.28813.716.3837.37
    DownLoad: Download CSV

    Table  2  Available channel numbers under six different atmospheric temperature inversion accuracy conditions

    大气种类精度/K切点高度
    0.0 km4.6 km11.5 km16.1 km20.7 km25.3 km34.5 km
    0.4085534139880
    美国标准大气0.5382220346807940424219940
    0.68340387232215733531451988244
    0.4032865420001
    热带大气0.515017435364859198872
    0.614633661767314142369474582
    0.4043750528200
    中纬度夏季大气0.5601176232087525417311557
    0.62717366535057524171189571397
    0.4023081349843160
    中纬度冬季大气0.5200524629144878950223533
    0.695624321416853792450751349201
    0.4076969391000
    副北极夏季大气0.5193621870150348126112641
    0.65587393881146342792036731276
    0.40415510611679250
    副北极冬季大气0.543288531257101982225065
    0.684584755913159973470421407262
    DownLoad: Download CSV

    Table  3  Available channel numbers under six different volume mixing ratio of water vapor inversion accuracy conditions

    大气种类精度/%切点高度
    0.0 km4.6 km11.5 km16.1 km20.7 km25.3 km34.5 km
    美国标准大气53211975188971548115526821403
    10178530326175791412412749121488797
    热带大气501848413144007851791
    10027393210394108695790579279
    中纬度夏季大气50197281220853569120812204
    1025289581997311114114331161510160
    中纬度冬季大气5494176795445245125792686887
    10290029436157021670014937124177803
    副北极夏季大气5422021265052042275932852235
    10550296611591415428155951347910273
    副北极冬季大气53873141745223251930922206918
    101372326523159561735115782123268048
    DownLoad: Download CSV
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    • Received : 2020-02-10
    • Accepted : 2020-03-31
    • Published : 2020-07-31

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