2020
DOI: 10.5194/gmd-13-1513-2020
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An intercomparison of tropospheric ozone reanalysis products from CAMS, CAMS interim, TCR-1, and TCR-2

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 ozonesonde observations o… Show more

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Cited by 30 publications
(32 citation statements)
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“…Among these reanalyses, a smaller bias appears in the reanalyses, which are assimilated with both total column ozone and ozone vertical ozone profile. Huijnen et al (2020) show that a large ozone bias could be related to the lack of direct tropospheric ozone. Therefore, a possible reason of the bias in JRA-55 can be attributed to the use of only total column ozone for data assimilation.…”
Section: Resultsmentioning
confidence: 93%
See 1 more Smart Citation
“…Among these reanalyses, a smaller bias appears in the reanalyses, which are assimilated with both total column ozone and ozone vertical ozone profile. Huijnen et al (2020) show that a large ozone bias could be related to the lack of direct tropospheric ozone. Therefore, a possible reason of the bias in JRA-55 can be attributed to the use of only total column ozone for data assimilation.…”
Section: Resultsmentioning
confidence: 93%
“…The normalized standard deviation and root mean-square error of CAMSRA are smaller than 0.6 and 1.0, respectively. Huijnen et al (2020) indicated that CAMSRA performs statistically better than TCR-2 at 850 hPa in Japan. Not surprisingly, other datasets exhibit larger errors than these three reanalyses (compare Fig.…”
Section: Resultsmentioning
confidence: 97%
“…Data assimilation applied here is based upon on an EnKF approach, the Local Ensemble Transform Kalman Filter (LETKF) (Hunt et al, 2007). The EnKF uses an ensemble forecast to estimate the background error covariance matrix and generates an analysis ensemble mean and covariance that satisfy the Kalman filter equations.…”
Section: Data Assimilation Methodsmentioning
confidence: 99%
“…Stratospheric ozone chemistry in IFS (CB05) is parameterized by a linear ozone scheme (Cariolle & Déqué, 1986;Cariolle & Teyssèdre, 2007). This combination allows a realistic representation of tropospheric and stratospheric ozone concentrations (Huijnen et al, 2020;Inness et al, 2019). The chemistry module of the IFS together with its emissions is documented in more detail in Flemming et al (2015) and Flemming et al (2017) and the updates used in the CAMS reanalysis in Inness et al (2019).…”
Section: Introductionmentioning
confidence: 99%