Optimization of the OCO-2 Cloud Screening Algorithm and Evaluation against MODIS and TCCON Measurements over Land Surfaces in Europe and Japan

A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2(OCO-2)cloud screening algorithms.Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations,which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO2 dry air mole fraction(XCO2).Based on the radiance measurements in the 0.76μm O2A band,1.61μm(weak),and 2.06μm(strong)CO2 bands,the current combination of the A-Band Preprocessor(ABP)algorithm and Iterative Maximum A Posteriori(IMAP)Differential Optical Absorption Spectroscopy(DOAS)Preprocessor(IDP)algorithm passes around 20%-25%of all soundings,which means that some contaminated scenes also pass the screening process.In this work,three independent pairs of threshold parameters used in the ABP and IDP algorithms are sufficiently tuned until the overall pass rate is close to the monthly clear-sky fraction from the MODIS cloud mask.The tightened thresholds are applied to observations over land surfaces in Europe and Japan in 2016.The results show improvement of agreement and positive predictive value compared to the collocated MODIS cloud mask,especially in summer and fall.In addition,analysis indicates that XCO2 retrievals with more stringent thresholds are in closer agreement with measurements from collocated Total Carbon Column Observing Network(TCCON)sites.     

基于OCO-2卫星观测模拟高精度XCO2的空间分布

本文首次基于OCO-2卫星观测数据,采用高精度曲面建模（High Accuracy Surface Modeling, HASM）的方法来模拟大范围高精度的二氧化碳柱浓度（XCO₂）的空间分布。首先,探讨分析HASM方法应用于模拟OCO-2卫星观测XCO₂的空间分布的可行性。从2014年9月至2015年8月OCO-2观测的12个月的XCO₂数据中,分别随机选取其各个月90%的XCO₂数据用于空间插值,剩余10%作为精度验证点。自验证结果表明,12个月的平均绝对值误差为0.34 ppm。由此可见,HASM适用于模拟OCO-2卫星观测XCO₂的空间分布。然后,采用HASM对OCO-2在2014年9月至2015年8月的各个月观测数据进行空间插值,获取空间分辨率为0.5°×0.5°的各个月均值XCO₂的空间分布,同时基于地基观测TCCON( Total Carbon Column Observing Network)站的XCO₂数据对HASM模拟结果进行交叉验证。验证结果表明,HASM模拟的XCO₂与TCCON站对应观测数据相比,其平均绝对值误差为0.81 ppm,相关系数为0.88。因此,HASM在模拟OCO-2卫星观测的XCO₂空间分布上具有很大的优势。     

Model-Simulated Atmospheric Carbon Dioxide: Comparisons with Satellite Retrievals and Ground-Based Observations

Atmospheric CO2 concentrations from January 2010 to December 2010 were simulated using the GEOS-Chem（Goddard Earth Observing System-Chemistry） model and the results were compared to satellite Gases Observing Satellite（GOSAT） and ground-based the Total Carbon Column Observing Network（TCCON） data. It was found that CO2 concentrations based on GOSAT satellite retrievals were generally higher than those simulated by GEOS-Chem. The differences over the land area in January and April ranged from 1 to 2 ppm, and there were major differences in June and August. At high latitudes in the Northern Hemisphere in June, as well as south of the Sahara, the difference was greater than 5 ppm. In the high latitudes of the Northern Hemisphere the model results were higher than the GOSAT retrievals, while in South America the satellite data were higher. The trend of the difference in the high latitudes of the Northern Hemisphere and the Saharan region in August was opposite to June. Maximum correlation coefficients were found in April, reaching 0.72, but were smaller in June and August. In January, the correlation coefficient was only 0.36. The comparisons between GEOS-Chem data and TCCON observations showed better results than the comparison between GEOS and GOSAT. The correlation coefficients ranged between 0.42（Darwin） and 0.92（Izana）. Analysis of the results indicated that the inconsistency between satellite observations and model simulations depended on inversion errors caused by data inaccuracies of the model simulation＇s inputs, as well as the mismatch of satellite retrieval model input parameters.