The ACOS CO2 retrieval algorithm - Part 1: Description and validation against synthetic observations
The ACOS CO2 retrieval algorithm - Part 1: Description and validation against synthetic observations
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DOI：
10.5194/amt-5-99-2012
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发表时间：
2012-01-01
影响因子：
3.8
通讯作者：
Wunch, D.
中科院分区：
文献类型：
--
作者：
O'Dell, C. W.;Connor, B.;Wunch, D.
这项工作介绍了美国宇航局大气CO2观测空间（ACOS）X-CO2检索算法，其性能高度逼真，模拟观测。这些试验仅限于陆地上的观测，用于评估在真实的云和气溶胶、极化的非朗伯表面、不完善的气象学和不相关的仪器噪声等情况下的反演误差。我们发现检索后过滤器对于消除最差的检索至关重要，这些检索主要是由于云筛选不完善而产生的。其余检索的RMS误差约为1 ppm。根据温室气体观测卫星飞行中的性能模拟的仪器噪声占这些检索总误差的一半以下。一小部分未经过滤的云，特别是薄卷云，导致类似于0.3 ppm的小的正偏差。总体而言，由于云和气溶胶的不完善的特性的系统误差占主导地位的误差预算，而由于其他简化的假设，特别是那些与先前的气象领域，出现的错误很小。
This work describes the NASA Atmospheric CO2 Observations from Space (ACOS) X-CO2 retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of similar to 0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small.