Implementation of a 3D variational data assimilation system at the Canadian Meteorological Centre. Part I: The global analysis

Gauthier, Pierre; Charette, Cécilien; Fillion, Luc; Koclas, P.; Laroche, Stéphane

doi:10.1080/07055900.1999.9649623

Cited by 135 publications

(117 citation statements)

References 30 publications

(16 reference statements)

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“…Unlike meteorology, where the objective analysis or data assimilation cycle of 6 h are most commonly used (Houtekamer and Mitchell, 1998;Gauthier et al, 1999;Brasnett, 2008), in air quality a cycle of 1 h is more appropriate (Blond et al, 2004;Tombette et al, 2009;Wu et al, 2008) since there is a significant diurnal variation of surface pollutants and care must be taken to resolve short or intermittent episodes. Therefore, over the entire study period (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) analyses were produced hourly.…”

Section: The Analysis Schemementioning

confidence: 99%

Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

Robichaud

Ménard

2014

Atmos. Chem. Phys.

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Abstract. Multi-year objective analyses (OA) on a high spatiotemporal resolution for the warm season period (1 May to 31 October) for ground-level ozone and for fine particulate matter (diameter less than 2.5 microns (PM 2.5 )) are presented. The OA used in this study combines model outputs from the Canadian air quality forecast suite with US and Canadian observations from various air quality surface monitoring networks. The analyses are based on an optimal interpolation (OI) with capabilities for adaptive error statistics for ozone and PM 2.5 and an explicit bias correction scheme for the PM 2.5 analyses. The estimation of error statistics has been computed using a modified version of the Hollingsworth-Lönnberg (H-L) method. The error statistics are "tuned" using a χ 2 (chi-square) diagnostic, a semiempirical procedure that provides significantly better verification than without tuning. Successful cross-validation experiments were performed with an OA setup using 90 % of data observations to build the objective analyses and with the remainder left out as an independent set of data for verification purposes. Furthermore, comparisons with other external sources of information (global models and PM 2.5 satellite surface-derived or ground-based measurements) show reasonable agreement. The multi-year analyses obtained provide relatively high precision with an absolute yearly averaged systematic error of less than 0.6 ppbv (parts per billion by volume) and 0.7 µg m −3 (micrograms per cubic meter) for ozone and PM 2.5 , respectively, and a random error generally less than 9 ppbv for ozone and under 12 µg m −3 for PM 2.5 . This paper focuses on two applications: (1) presenting longterm averages of OA and analysis increments as a form of summer climatology; and (2) analyzing long-term (decadal) trends and inter-annual fluctuations using OA outputs. The results show that high percentiles of ozone and PM 2.5 were both following a general decreasing trend in North America, with the eastern part of the United States showing the most widespread decrease, likely due to more effective pollution controls. Some locations, however, exhibited an increasing trend in the mean ozone and PM 2.5 , such as the northwestern part of North America (northwest US and Alberta). Conversely, the low percentiles are generally rising for ozone, which may be linked to the intercontinental transport of increased emissions from emerging countries. After removing the decadal trend, the inter-annual fluctuations of the high percentiles are largely explained by the temperature fluctuations for ozone and to a lesser extent by precipitation fluctuations for PM 2.5 . More interesting is the economic short-term change (as expressed by the variation of the US gross domestic product growth rate), which explains 37 % of the total variance of inter-annual fluctuations of PM 2.5 and 15 % in the case of ozone.

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Section: The Analysis Schemementioning

confidence: 99%

Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

Robichaud

Ménard

2014

Atmos. Chem. Phys.

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“…The second term on the right-hand side is much smaller than the first, so to a good approximation increments to temperature are determined by the vertical gradient of the pressure increments p . These are composed of a geostrophically unbalanced part p u and a geostrophic part p g , which through the 'local balance equation' p = ρf ψ (Gauthier et al, 1999) can be seen to be approximately proportional to the stream function increment ψ . p u and ψ are localized together, so to a good approximation the effect of localization on p is equivalent to the direct application of the localization covariance.…”

Section: Vertical Mode Smoothingmentioning

confidence: 99%

Operational implementation of a hybrid ensemble/4D‐Var global data assimilation system at the Met Office

Clayton

Lorenc

Barker

2012

Quart J Royal Meteoro Soc

327

329

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“…  . within a 3D-Var analysis (Parrish and Derber, systematic positive impact on the quality of 1992 Courtier et al, 1998;Gauthier et al, 1996) forecasts, at least with an assimilation period but a 4-dimensional variational assimilation of 6 hrs.…”

Section: Introductionmentioning

confidence: 99%

A validation of the incremental formulation of 4D variational data assimilation in a nonlinear barotropic flow

Laroche¹,

Gauthier²

1998

Tellus A

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In order to meet current operational limitations, the incremental approach is being used to reduce the computational cost of 4D variational data assimilation (4D-Var). In the incremental 4D-Var, the tangent linear (TLM) and adjoint of a simplified lower-resolution model are used to describe the time evolution of increments around a trajectory defined by a complete fullresolution model. For nonlinear problems, the trajectory needs to be updated regularly by integrating the full-resolution model during the minimization. These are referred to as outer iterations (or updates) by opposition to inner iterations done with the simpler TLM and adjoint models to minimize a local quadratic approximation to the actual cost function. In this study, the role of the inner and outer iterations is investigated in relation to the convergence properties as well as to the interactions between the large (resolved by both models) and small scale components of the flow. A 2D barotropic non-divergent model on a b-plane is used at two different resolutions to define the complete and simpler models. Our results show that it is necessary to have a minimal number of updates of the trajectory for the incremental 4D-Var to converge reasonably well. To assess the impact of restricting the gradient to its large scale components, experiments are carried out with a so-called truncated 4D-Var in which the complete model is used to compute the gradient which is truncated afterwards to retain only those components used in the incremental 4D-Var. A comparison between the truncated and incremental 4D-Var shows that the large-scale components of the gradient are well approximated by the lower resolution model. With frequent updates to the trajectory, the incremental 4D-Var converges to an analysis which is close to that obtained with the truncated 4D-Var. This conclusion is verified when perfect observations with a complete spatial and temporal coverage are used or when they are restricted to be available at a coarser resolution (in space and time) than that of the model. Finally, unbiased observational error was introduced and the results showed that at some point, the minimization is overfitting the observations and degrades the analysis. In this context, a criterion related to the level of observational noise is found to determine when to stop the minimization when the complete 4D-Var is used. This criterion does not hold however for the incremental and truncated 4D-Var, thereby indicating that it may be very difficult to establish in a more realistic context when the error is biased and the model itself is introducing a biased error. The analysis and forecasts from the incremental 4D-Var compare well to those from a full-resolution 4D-Var and are more accurate than those obtained from a low-resolution 4D-Var that uses only the simplified model.

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Implementation of a 3D variational data assimilation system at the Canadian Meteorological Centre. Part I: The global analysis

Abstract: In this paper, the operational 3D variational data assimilation system (3D-var)

Cited by 135 publications

References 30 publications

Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

Operational implementation of a hybrid ensemble/4D‐Var global data assimilation system at the Met Office

A validation of the incremental formulation of 4D variational data assimilation in a nonlinear barotropic flow

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Implementation of a 3D variational data assimilation system at the Canadian Meteorological Centre. Part I: The global analysis

Abstract: In this paper, the operational 3D variational data assimilation system (3D-var)

Cited by 135 publications

References 30 publications

Multi-year objective analyses of warm season ground-level ozone and PM&lt;sub&gt;2.5&lt;/sub&gt; over North America using real-time observations and Canadian operational air quality models

Multi-year objective analyses of warm season ground-level ozone and PM&lt;sub&gt;2.5&lt;/sub&gt; over North America using real-time observations and Canadian operational air quality models

Operational implementation of a hybrid ensemble/4D‐Var global data assimilation system at the Met Office

A validation of the incremental formulation of 4D variational data assimilation in a nonlinear barotropic flow

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Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models

Multi-year objective analyses of warm season ground-level ozone and PM<sub>2.5</sub> over North America using real-time observations and Canadian operational air quality models