The theoretically calculated radiance plays a crucial role in numerical weather prediction models. Therefore, improving the accuracy of radiative transfer models is essential for precise radiance calculations. This study aims to enhance the accuracy of radiative transfer models by utilizing atmospheric profiles along the satellite-observed slant path rather than the vertical path. This approach is expected to improve the retrieval of temperature and humidity profiles, which are critical for accurate weather predictions. Previous research has shown that slant-path simulations significantly impact regions with high atmospheric variability and large viewing angles, improving RMSD in temperature and wind forecasts by 2-3% in the stratosphere and high latitudes9 This study extends these evaluations to all-sky conditions, considering the parallax effect of clouds for more accurate radiance calculations (B). The findings are expected to enhance weather prediction models by incorporating slant-path radiative transfer simulations.
Monitoring greenhouse gases (GHGs) such as CO2 and CH4 is essential for understanding their role in climate change and informing mitigation strategies. The ASIA-AQ campaign, a multi-country field study on Asian air quality during winter, was jointly organized by research institutions from various countries and NASA. As part of the campaign, a mobile Fourier Transform Spectrometer (FTS) was deployed at Ewha Womans University (EW) in Seoul for targeted observations. The mobile FTS, while offering the advantage of mobility to assess regional GHG characteristics, has a lower spectral resolution of 0.5 cm-1 , compared to the higher 0.02 cm-1 resolution of the stationary FTS at the Anmyeon-do (AMY) Global Atmosphere Watch (GAW) Regional Station in Korea. To validate the accuracy of the mobile FTS, its retrievals were compared with those from the stationary high-resolution FTS before and after the ASIA-AQ campaign through sideby- side observation. Pre-ASIA-AQ, both the IFS125HR and EM27/SUN showed consistent differences in XCO2 and XCH4 concentrations, with both instruments demonstrating high sensitivity, as evidenced by their ability to capture shortterm changes effectively. After the campaign, the difference increased, showing slightly different characteristics compared to before ASIA-AQ. During the ASIA-AQ campaign, XCO2 measurements at EW were slightly lower than those at AMY, though occasional higher concentrations were observed. For XCH4, concentrations were higher at EW. Additionally, the XCH4 to XCO2 ratio remained relatively stable at AMY, while it varied slightly at EW. TROPOMI measurements of XCH4, compared to EM27/SUN, showed similar trends but an underestimation.
A spectral calibration algorithm for the hyperspectral geostationary environmental monitoring spectrometer (GEMS) onboard
GEO-KOMPSAT-2B (GK-2B) planned to launch in 2019 has been developed. Although spectral registration for
the CCD detector is done by the optical parameters prepared during the ground test of the instrument, the algorithm is
applied for the improved spectral accuracy. The prototype algorithm is based on the best fitting of the measured
spectrum to the known high resolution reference spectrum such as the solar irradiance. To characterize the prototype
algorithm, a series of sensitivity tests for various spectral parameters, such as squeeze, shift, spectral response function,
and reference solar spectrum, has been performed. The prototype algorithm shows a minimal sensitive to the
uncertainties associated with several parameters such as squeeze, shift, or spectral band. However, the algorithm
performance degrades by an order if the spectral response function including its shape has uncertainty. Thus, it is
recommended to measure the spectral response function at the ground test as accurately as possible. Furthermore, the
prototype algorithm is also highly sensitive to the used reference solar spectrum, which needs further investigation.
The five channel meteorological imager (MI) on-board the geostationary Communication, Ocean, and Meteorological
Satellite (COMS) of Korea has been operationally used since April 2011. For a better utilization of the MI data, a rigorous
characterization of the four infrared channel data has been conducted using the GSICS (Global Space-based
Inter-Calibration System) approach with the IASI (Infrared Atmospheric Sounding Interferometer) on-board the European
Metop satellite as the reference instrument. Although all four channels show the uncertainty characteristics that are in line
with the results from both the ground tests and the in-orbit-test, there shows an unexpected systematic bias in the water
vapor channel of MI, showing a cold bias at the warm target temperature and a warm bias with the cold target temperature.
It has been shown that this kind of systematic bias could be introduced by the uncertainties in the spectral response function
(SRF) of the specific channel which is similar to the heritage instruments on-board GOES series satellite. An extensive
radiative transfer simulation using a radiative transfer model has confirmed that the SRF uncertainty could indeed
introduce such a systematic bias. By using the collocated data set consisting of the MI data and the hyperspectral IASI data,
the first order correction value for the SRF uncertainty is estimated to be about 2.79 cm-1 shift of the central position of the
current SRF.
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