Impact of aerosol and thin cirrus on retrieving and validating XCO2 from GOSAT shortwave infrared measurements
Impact of aerosol and thin cirrus on retrieving and validating XCO2 from GOSAT shortwave infrared measurements
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DOI：
10.1002/jgrd.50332
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发表时间：
2013-05-27
影响因子：
4.4
通讯作者：
Aben, I.
中科院分区：
文献类型：
--
作者：
Guerlet, S.;Butz, A.;Aben, I.
气溶胶散射处理不当可能是一个显着的错误来源时，检索柱平均干空气摩尔分数的CO2（XCO 2）从空间为基础的测量后向散射太阳短波辐射。我们已经开发了一种检索算法，远程，检索三个气溶胶参数（量，大小和高度）同时与XCO 2。在这里，我们评估的能力，遥感占云，亚可见卷云和气溶胶的光路修改时，从温室气体观测卫星（GOSAT）的热量和近红外传感器碳观测（TANSO）傅里叶变换光谱仪（FTS）测量检索XCO 2。我们首先评估云过滤器的基础上测量的云和气溶胶成像仪和卷云过滤器，使用TANSO-FTS测量的辐射在2微米的光谱区域，具有较强的吸水性。对于云幕场景，我们然后评估由于气溶胶的误差。我们发现，RemoTeC是很好的能够占气溶胶的散射气溶胶光学厚度在750 nm的值高达0.25。虽然没有显着的相关性的错误，发现与检索气溶胶参数的相关性。为了进一步提高XCO 2的精度，我们提出并评估了一个偏差校正方案。本研究以全球总碳柱观测网（TCCON）12个地面站的观测数据为参考。我们表明，空间托管标准可以放宽使用额外的约束条件的基础上建模XCO 2梯度，以增加验证数据的大小和多样性，并提供更强大的评估GOSAT检索。在全球范围内验证卫星数据仍然具有挑战性，将通过扩大TCCON覆盖范围加以改进。
Inadequate treatment of aerosol scattering can be a significant source of error when retrieving column-averaged dry-air mole fractions of CO2 (XCO2) from space-based measurements of backscattered solar shortwave radiation. We have developed a retrieval algorithm, RemoTeC, that retrieves three aerosol parameters (amount, size, and height) simultaneously with XCO2. Here we evaluate the ability of RemoTeC to account for light path modifications by clouds, subvisual cirrus, and aerosols when retrieving XCO2 from Greenhouse Gases Observing Satellite (GOSAT) Thermal and Near-infrared Sensor for carbon Observation (TANSO)-Fourier Transform Spectrometer (FTS) measurements. We first evaluate a cloud filter based on measurements from the Cloud and Aerosol Imager and a cirrus filter that uses radiances measured by TANSO-FTS in the 2micron spectral region, with strong water absorption. For the cloud-screened scenes, we then evaluate errors due to aerosols. We find that RemoTeC is well capable of accounting for scattering by aerosols for values of aerosol optical thickness at 750nm up to 0.25. While no significant correlation of errors is found with albedo, correlations are found with retrieved aerosol parameters. To further improve the XCO2 accuracy, we propose and evaluate a bias correction scheme. Measurements from 12 ground-based stations of the Total Carbon Column Observing Network (TCCON) are used as a reference in this study. We show that spatial colocation criteria may be relaxed using additional constraints based on modeled XCO2 gradients, to increase the size and diversity of validation data and provide a more robust evaluation of GOSAT retrievals. Global-scale validation of satellite data remains challenging and would be improved by increasing TCCON coverage.