An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2
An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2
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DOI：
10.5194/gmd-2019-297-supplement
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发表时间：
2019-11
影响因子：
5.1
通讯作者：
V. Huijnen;K. Miyazaki;J. Flemming;A. Inness;T. Sekiya;M. Schultz
中科院分区：
文献类型：
--
作者：
V. Huijnen;K. Miyazaki;J. Flemming;A. Inness;T. Sekiya;M. Schultz
抽象的。过去十年来，对使用作为哥白尼大气监测局一部分编制的不同最先进卫星数据同化系统(CAMS-IREAN和CAMS-REAN)以及两个完全独立的再分析(TCR-1和TCR-2，对流层化学再分析)构建的全球对流层臭氧再分析进行了相互比较和评估。更新的再分析(CAMS-REAN和TCR-2)总体上显示，在日变化、天气变化、季节变化和年际变化方面，与其先前版本(CAMS-REAN和TCR-1)相比，与独立的地面和臭氧探空仪观测结果的一致性有了显著改善。例如，对于北半球中纬度地区，来自最新再分析的对流层臭氧层柱(地面到300百帕)显示，与臭氧探测仪的观测结果相比，平均偏差在0.8 DU(道布森单位，相对于观测柱的3%)以内。性能的改善很可能归因于各种升级的混合，例如对化学数据同化的修订，包括同化测量和预报模式的性能。最新的化学再分析在大多数情况下彼此吻合得很好，这突显了目前的化学再分析在各种研究中的用处。同时，所有系统中再分析质量的显著时间变化可以归因于观测系统中的不连续。为了改善时间一致性，需要仔细评估同化结构的变化，例如详细评估不同反演产品之间的偏差。我们的比较表明，改善观测约束，包括卫星观测系统的持续发展，加上沉积和化学反应等模式参数的优化，将导致未来日益一致的长期再分析。
Abstract. Global tropospheric ozone reanalyses constructed using different state-of-the-art satellite data assimilation systems, prepared as part of the Copernicus Atmosphere Monitoring Service (CAMS-iRean and CAMS-Rean) as well as two fully independent reanalyses (TCR-1 and TCR-2, Tropospheric Chemistry Reanalysis), have been intercompared and evaluated for the past decade. The updated reanalyses (CAMS-Rean and TCR-2) generally show substantially improved agreements with independent ground and ozone-sonde observations over their predecessor versions (CAMS-iRean and TCR-1) for diurnal, synoptical, seasonal, and interannual variabilities. For instance, for the Northern Hemisphere (NH) mid-latitudes the tropospheric ozone columns (surface to 300 hPa) from the updated reanalyses show mean biases to within 0.8 DU (Dobson units, 3 % relative to the observed column) with respect to the ozone-sonde observations. The improved performance can likely be attributed to a mixture of various upgrades, such as revisions in the chemical data assimilation, including the assimilated measurements, and the forecast model performance. The updated chemical reanalyses agree well with each other for most cases, which highlights the usefulness of the current chemical reanalyses in a variety of studies. Meanwhile, significant temporal changes in the reanalysis quality in all the systems can be attributed to discontinuities in the observing systems. To improve the temporal consistency, a careful assessment of changes in the assimilation configuration, such as a detailed assessment of biases between various retrieval products, is needed. Our comparison suggests that improving the observational constraints, including the continued development of satellite observing systems, together with the optimization of model parameterizations such as deposition and chemical reactions, will lead to increasingly consistent long-term reanalyses in the future.