首页> 外文OA文献 >The ACOS CO_2 retrieval algorithm – Part II: Global X_(CO_2) data characterization
【2h】

The ACOS CO_2 retrieval algorithm – Part II: Global X_(CO_2) data characterization

机译:ACOS CO_2检索算法–第二部分:全局X_(CO_2)数据表征

摘要

Here, we report preliminary estimates of the column averaged carbon dioxide (CO_2) dry air mole fraction, X_(CO_2), retrieved from spectra recorded over land by the Greenhouse gases Observing Satellite, GOSAT (nicknamed "Ibuki"), using retrieval methods originally developed for the NASA Orbiting Carbon Observatory (OCO) mission. After screening for clouds and other known error sources, these retrievals reproduce much of the expected structure in the global X_(CO_2) field, including its variation with latitude and season. However, low yields of retrieved X_(CO_2) over persistently cloudy areas and ice covered surfaces at high latitudes limit the coverage of some geographic regions, even on seasonal time scales. Comparisons of early GOSAT X_(CO_2) retrievals with X_(CO_2) estimates from the Total Carbon Column Observing Network (TCCON) revealed a global, −2% (7–8 parts per million, ppm, with respect to dry air) X_(CO_2) bias and 2 to 3 times more variance in the GOSAT retrievals. About half of the global X_(CO_2) bias is associated with a systematic, 1% overestimate in the retrieved air mass, first identified as a global +10 hPa bias in the retrieved surface pressure. This error has been attributed to errors in the O_2 A-band absorption cross sections. Much of the remaining bias and spurious variance in the GOSAT X_(CO_2) retrievals has been traced to uncertainties in the instrument's calibration, oversimplified methods for generating O_2 and CO_2 absorption cross sections, and other subtle errors in the implementation of the retrieval algorithm. Many of these deficiencies have been addressed in the most recent version (Build 2.9) of the retrieval algorithm, which produces negligible bias in X_(CO_2) on global scales as well as a ~30% reduction in variance. Comparisons with TCCON measurements indicate that regional scale biases remain, but these could be reduced by applying empirical corrections like those described by Wunch et al. (2011b). We recommend that such corrections be applied before these data are used in source sink inversion studies to minimize spurious fluxes associated with known biases. These and other lessons learned from the analysis of GOSAT data are expected to accelerate the delivery of high quality data products from the Orbiting Carbon Observatory-2 (OCO-2), once that satellite is successfully launched and inserted into orbit.
机译:在这里,我们报告了最初使用检索方法从温室气体观测卫星GOSAT(昵称“ Ibuki”)从陆地上记录的光谱中检索到的列平均二氧化碳(CO_2)干空气摩尔分数X_(CO_2)的初步估计。为NASA轨道碳天文台(OCO)任务而开发。在筛选了云和其他已知的错误源之后,这些取回再现了全球X_(CO_2)字段中的大部分预期结构,包括其随纬度和季节的变化。但是,在持续多云的地区和高纬度冰覆盖的表面上,低收得的X_(CO_2)产量限制了某些地理区域的覆盖范围,即使在季节性时标上也是如此。将早期的GOSAT X_(CO_2)取回与总碳柱观测网络(TCCON)的X_(CO_2)估算值进行比较,发现全球-2%(相对于干燥空气,百万分之7-8 ppm)X_( GOSAT检索中的CO_2)偏差和2到3倍更多的方差。全局X_(CO_2)偏差的大约一半与回收的空气质量的系统性高估1%有关,首先将其确定为回收的表面压力的全局+10 hPa偏差。该错误归因于O_2 A波段吸收截面中的错误。 GOSAT X_(CO_2)检索中大部分剩余的偏差和虚假方差可追溯到仪器校准中的不确定性,生成O_2和CO_2吸收截面的方法过于简化以及检索算法实施中的其他细微错误。这些缺陷中的许多缺陷已在最新版本的检索算法(版本2.9)中得到了解决,该算法在全局范围内对X_(CO_2)的影响可忽略不计,并且方差减少了约30%。与TCCON测量结果的比较表明,区域尺度偏差仍然存在,但是可以通过应用经验校正(如Wunch等人的描述)来减小。 (2011b)。我们建议在将这些数据用于源汇反演研究之前进行此类校正,以最大程度减少与已知偏差相关的寄生通量。一旦卫星成功发射并插入轨道,有望从GOSAT数据分析中学到的这些以及其他经验教训将加速从轨道碳观测站2(OCO-2)交付高质量的数据产品。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号