The ASSET intercomparison of ozone analyses: method and first results

Abstract

Abstract. This paper aims to summarise the current performance of ozone data assimilation (DA) systems, to show where they can be improved, and to quantify their errors. It examines 11 sets of ozone analyses from 7 different DA systems. Two are numerical weather prediction (NWP) systems based on general circulation models (GCMs); the other five use chemistry transport models (CTMs). The systems examined contain either linearised or detailed ozone chemistry, or no chemistry at all. In most analyses, MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) ozone data are assimilated; two assimilate SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Chartography) observations instead. Analyses are compared to independent ozone observations covering the troposphere, stratosphere and lower mesosphere during the period July to November 2003.Biases and standard deviations are largest, and show the largest divergence between systems, in the troposphere, in the upper-troposphere/lower-stratosphere, in the upperstratosphere and mesosphere, and the Antarctic ozone hole region. However, in any particular area, apart from the troposphere, at least one system can be found that agrees well with independent data. In general, none of the differences can be linked to the assimilation technique (Kalman filter, three or four dimensional variational methods, direct inversion) orCorrespondence to: A. J. Geer (alan.geer@ecmwf.int) the system (CTM or NWP system). Where results diverge, a main explanation is the way ozone is modelled. It is important to correctly model transport at the tropical tropopause, to avoid positive biases and excessive structure in the ozone field. In the southern hemisphere ozone hole, only the analyses which correctly model heterogeneous ozone depletion are able to reproduce the near-complete ozone destruction over the pole. In the upper-stratosphere and mesosphere (above 5 hPa), some ozone photochemistry schemes caused large but easily remedied biases. The diurnal cycle of ozone in the mesosphere is not captured, except by the one system that includes a detailed treatment of mesospheric chemistry. These results indicate that when good observations are available for assimilation, the first priority for improving ozone DA systems is to improve the models.The analyses benefit strongly from the good quality of the MIPAS ozone observations. Using the analyses as a transfer standard, it is seen that MIPAS is ∼5% higher than HALOE (Halogen Occultation Experiment) in the mid and upper stratosphere and mesosphere (above 30 hPa), and of order 10% higher than ozonesonde and HALOE in the lower stratosphere (100 hPa to 30 hPa). Analyses based on SCIA-MACHY total column are almost as good as the MIPAS analyses; analyses based on SCIAMACHY limb profiles are worse in some areas, due to problems in the SCIAMACHY retrievals.

Estimation of the local diffusion tensor and normalization for heterogeneous correlation modelling using a diffusion equation

“…MOCAGE is currently used for several applications, such as chemical weather forecasting (Dufour et al, 2004), chemistry-climate interactions and data assimilation (Massart et al, 2005a, b;Pradier et al, 2006). The first version of the MOCAGE-PALM assimilation system, as it was originally implemented for the ASSET project, provided good-quality ozone fields compared with ozonesondes and measurements from the Upper-Atmosphere Research Satellite/Halogen Occultation Experiment (UARS/HALOE), with errors of the same order as those supplied by several other assimilation systems (Geer et al, 2006). In order to improve the assimilation system, several changes have been recently made to the model resolution and to the backgrounderror characterization .…”

The COST 723 Action

“…Overall, several-month ozone analyses were provided within WG2 and used to evaluate a number of ozone assimilation systems and Envisat data (Geer et al, 2006a). By contrast, only about two months of stratospheric humidity analyses were provided within WG2 (Lahoz et al, 2007b).…”

“…Examples (not exhaustive) of this assimilation approach are provided by the Met Office/DARC (Jackson and Saunders, 2002;Struthers et al, 2002;Jackson, 2004Jackson, , 2007Lahoz et al, 2005Lahoz et al, , 2007aGeer et al, 2006aGeer et al, , 2006bGeer et al, , 2007 and ECMWF (Dethof, 2003;Dethof and Hólm, 2004).…”

“…ozone and stratospheric water vapour from Envisat atmospheric chemistry instruments) into systems based on NWP models and CTMs, and to evaluate research satellite data and the models. Details of the use of assimilation techniques to evaluate Envisat atmospheric chemistry data (MIPAS, SCIAMACHY and GOMOS) are provided in Geer et al (2006a) and Lahoz et al (2007a, b).…”

On the diffusion equation and its application to isotropic and anisotropic correlation modelling in variational assimilation

“…Weaver and Courtier (2001) (hereafter WC01) described the algorithm in more detail and proposed various extensions to account for more general correlation functions than the quasi-Gaussian of the original Derber and Rosati (1989) algorithm. Correlation models based on explicit diffusion methods have been used in various VDA systems in oceanography (Weaver et al, 2003;Di Lorenzo et al, 2007;Muccino et al, 2008;Daget et al, 2009;Kurapov et al, 2009;Moore et al, 2011), meteorology (Bennett et al 1996), and atmospheric chemistry (Geer et al, 2006;Elbern et al, 2010).…”