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Analysis of 3D cloud effects in OCO-2 XCO2 retrievals
Atmospheric Measurement Techniques ( IF 3.2 ) Pub Date : 2021-02-25 , DOI: 10.5194/amt-14-1475-2021 Steven T. Massie , Heather Cronk , Aronne Merrelli , Christopher O'Dell , K. Sebastian Schmidt , Hong Chen , David Baker
Atmospheric Measurement Techniques ( IF 3.2 ) Pub Date : 2021-02-25 , DOI: 10.5194/amt-14-1475-2021 Steven T. Massie , Heather Cronk , Aronne Merrelli , Christopher O'Dell , K. Sebastian Schmidt , Hong Chen , David Baker
The presence of 3D cloud radiative effects in OCO-2 retrievals is
demonstrated from an analysis of 2014–2019 OCO-2 XCO2 raw retrievals, bias-corrected XCO2bc data, ground-based Total Carbon Column Observation Network
(TCCON) XCO2, and Moderate Resolution Imaging Spectroradiometer (MODIS)
cloud and radiance fields. In approximate terms, 40 % (quality flag –
QF = 0, land or ocean) and 73 % (QF = 1, land or ocean) of the
observations are within 4 km of clouds. 3D radiative transfer calculations
indicate that 3D cloud radiative perturbations at this cloud distance, for
an isolated low-altitude cloud, are larger in absolute value than those due
to a 1 ppm increase in CO2. OCO-2 measurements are therefore
susceptible to 3D cloud effects. Four 3D cloud metrics, based upon MODIS
radiance and cloud fields as well as stand-alone OCO-2 measurements, relate
XCO2bc–TCCON averages to 3D cloud effects. This analysis indicates that the
operational bias correction has a nonzero residual 3D cloud bias for both
QF = 0 and QF = 1 data. XCO2bc–TCCON averages at small cloud distances
differ from those at large cloud distances by −0.4 and −2.2 ppm for the QF = 0 and QF = 1 data over the ocean. Mitigation of 3D cloud biases with a
table lookup technique, which utilizes the nearest cloud distance (Distkm) and
spatial radiance heterogeneity (CSNoiseRatio) 3D metrics, reduces QF = 1
ocean and land XCO2bc–TCCON averages from −1 ppm to near ±0.2 ppm.
The ocean QF = 1 XCO2bc–TCCON averages can be reduced to the 0.5 ppm level
if 60 % (70 %) of the QF = 1 data points are utilized by applying
Distkm (CSNoiseRatio) metrics in a data screening process. Over land the
QF = 1 XCO2bc–TCCON averages are reduced to the 0.5 (0.8) ppm level if 65 % (63 %) of the data points are utilized by applying Diastkm (CSNoiseRatio)
data screening. The addition of more terms to the linear regression
equations used in the current bias correction processing without data
screening, however, did not introduce an appreciable improvement in the
standard deviations of the XCO2bc–TCCON statistics.
中文翻译:
OCO-2 XCO2检索中的3D云效应分析
通过对2014–2019年OCO-2 XCO2原始检索,偏差校正的XCO2bc数据,地面总碳柱观测网络(TCCON)XCO2和中等分辨率的分析证明了OCO-2检索中存在3D云辐射效应成像光谱仪(MODIS)的云和辐射场。大致而言, 观测值的40%(质量标志– QF = 0,陆地或海洋)和73%(QF = 1,陆地或海洋)在云的4公里以内。3D辐射传递计算表明,对于一个孤立的低空云,此云距离处的3D云辐射扰动的绝对值大于因CO 2增加1 ppm而产生的扰动。。因此,OCO-2测量容易受到3D云效应的影响。四个基于MODIS辐射和云场以及独立OCO-2测量的3D云度量将XCO2bc–TCCON平均值与3D云效果相关联。该分析表明,对于QF = 0和QF = 1数据,操作偏差校正均具有非零的残留3D云偏差 。对于QF = 0和QF =,小云距离处的XCO2bc–TCCON平均值与大云距离处的平均值相差− 0.4和− 2.2 ppm。 1海洋数据。使用表格查找技术缓解3D云偏差,该技术利用最近的云距离(Distkm)和空间辐射异质性(CSNoiseRatio)3D度量标准,将QF = 1海洋和陆地XCO2bc–TCCON平均值从− 1 ppm降低至接近± 0.2 ppm 。 如果 通过在数据筛选过程中应用Distkm(CSNoiseRatio)指标来利用60%(70%)的QF = 1数据点,则海洋QF = 1 XCO2bc–TCCON的平均值可以降低到0.5 ppm 。陆上合格条件 = 如果通过应用Diastkm(CSNoiseRatio)数据筛选利用了65%(63%)的数据点,则1 XCO2bc–TCCON平均值将降低至0.5(0.8)ppm的水平。在不进行数据筛选的情况下,将更多项添加到当前偏差校正处理中使用的线性回归方程中,并没有对XCO2bc–TCCON统计数据的标准偏差带来可观的改善。
更新日期:2021-02-25
中文翻译:
OCO-2 XCO2检索中的3D云效应分析
通过对2014–2019年OCO-2 XCO2原始检索,偏差校正的XCO2bc数据,地面总碳柱观测网络(TCCON)XCO2和中等分辨率的分析证明了OCO-2检索中存在3D云辐射效应成像光谱仪(MODIS)的云和辐射场。大致而言, 观测值的40%(质量标志– QF = 0,陆地或海洋)和73%(QF = 1,陆地或海洋)在云的4公里以内。3D辐射传递计算表明,对于一个孤立的低空云,此云距离处的3D云辐射扰动的绝对值大于因CO 2增加1 ppm而产生的扰动。。因此,OCO-2测量容易受到3D云效应的影响。四个基于MODIS辐射和云场以及独立OCO-2测量的3D云度量将XCO2bc–TCCON平均值与3D云效果相关联。该分析表明,对于QF = 0和QF = 1数据,操作偏差校正均具有非零的残留3D云偏差 。对于QF = 0和QF =,小云距离处的XCO2bc–TCCON平均值与大云距离处的平均值相差− 0.4和− 2.2 ppm。 1海洋数据。使用表格查找技术缓解3D云偏差,该技术利用最近的云距离(Distkm)和空间辐射异质性(CSNoiseRatio)3D度量标准,将QF = 1海洋和陆地XCO2bc–TCCON平均值从− 1 ppm降低至接近± 0.2 ppm 。 如果 通过在数据筛选过程中应用Distkm(CSNoiseRatio)指标来利用60%(70%)的QF = 1数据点,则海洋QF = 1 XCO2bc–TCCON的平均值可以降低到0.5 ppm 。陆上合格条件 = 如果通过应用Diastkm(CSNoiseRatio)数据筛选利用了65%(63%)的数据点,则1 XCO2bc–TCCON平均值将降低至0.5(0.8)ppm的水平。在不进行数据筛选的情况下,将更多项添加到当前偏差校正处理中使用的线性回归方程中,并没有对XCO2bc–TCCON统计数据的标准偏差带来可观的改善。