The ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). III: Experimental results

Andersson, Erik; Haseler, Jan; Undén, Per; Courtier, Philippe; Kelly, Graeme; Vasiljevic, Drasko; Branković, Čedo; Gaffard, C.; Hollingsworth, A.; Jakob, Christian; Janssen, Peter A. E. M.; Klinker, E.; Lanzinger, Andreas; Miller, M. J.; Rabier, Florence; Simmons, A. J.; Strauss, B.; Viterbo, Pedro; Cardinali, Carla; Thépaut, Jean‐Noël

doi:10.1002/qj.49712455004

Cited by 121 publications

(24 citation statements)

References 30 publications

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“…Our goal is to assimilate the regular daily global mapping of the 2-D column AOD by the National Aeronautics and Space Administration (NASA) Terra and Aqua satellites (Remer et al, 2005) with the 3-D CTM modelling of the major tropospheric aerosols. We use the variational 3-D-FGAT (first guess at appropriate time) method (Andersson et al, 1998), which is implemented in the CTM using the PALM coupler (Buis et al, 2006;Massart et al, 2007, Projet d'Assimilation par Logiciel Multi-Méthodes). The assimilated fields can then be evaluated independently against a large range of aerosol properties (2-D and 3-D) measured by other satellites and in situ and ground-based instruments.…”

Section: Introductionmentioning

confidence: 99%

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

et al. 2016

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Abstract. In this study, we describe the development of the aerosol optical depth (AOD) assimilation module in the chemistry transport model (CTM) MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle). Our goal is to assimilate the spatially averaged 2-D column AOD data from the National Aeronautics and Space Administration (NASA) Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, and to estimate improvements in a 3-D CTM assimilation run compared to a direct model run. Our assimilation system uses 3-D-FGAT (first guess at appropriate time) as an assimilation method and the total 3-D aerosol concentration as a control variable. In order to have an extensive validation dataset, we carried out our experiment in the northern summer of 2012 when the pre-ChArMEx (CHemistry and AeRosol MEditerranean EXperiment) field campaign TRAQA (TRAnsport à longue distance et Qualité de l'Air dans le bassin méditerranéen) took place in the western Mediterranean basin. The assimilated model run is evaluated independently against a range of aerosol properties (2-D and 3-D) measured by in situ instruments (the TRAQA size-resolved balloon and aircraft measurements), the satellite Spinning Enhanced Visible and InfraRed Imager (SE-VIRI) instrument and ground-based instruments from the Aerosol Robotic Network (AERONET) network. The evaluation demonstrates that the AOD assimilation greatly improves aerosol representation in the model. For example, the comparison of the direct and the assimilated model run with AERONET data shows that the assimilation increased the correlation (from 0.74 to 0.88), and reduced the bias (from 0.050 to 0.006) and the root mean square error in the AOD (from 0.12 to 0.07). When compared to the 3-D concentration data obtained by the in situ aircraft and balloon measurements, the assimilation consistently improves the model output. The best results as expected occur when the shape of the vertical profile is correctly simulated by the direct model. We also examine how the assimilation can influence the modelled aerosol vertical distribution. The results show that a 2-D continuous AOD assimilation can improve the 3-D vertical profile, as a result of differential horizontal transport of aerosols in the model.

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Section: Introductionmentioning

confidence: 99%

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

et al. 2016

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“…As for observations, satellite observations are increasing continuously, and their use becomes essential. A major improvement by introducing the three-dimensional variational (3D-Var) method in the operational NWP was due to its capability of a nonlinear observational operator, which enabled the direct assimilation of satellite radiances (e.g., Andersson et al 1998).…”

Section: Introductionmentioning

confidence: 99%

Assimilating Satellite Radiances with a Local Ensemble Transform Kalman Filter (LETKF) Applied to the JMA Global Model (GSM)

Miyoshi

Sato

2007

SOLA

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A four-dimensional local ensemble transform Kalman filter (4D-LETKF) is applied to the JMA global model (GSM) at a TL159/L40 resolution to assimilate real observations including satellite radiances. It turns out that the vertical error covariance localization plays an essential role in assimilating satellite radiances. This study proposes and tests a new approach of the vertical localization, where the normalized sensitivity function of satellite sensors is used as the localization weights. With the vertical localization, AMSU-A, AMSU-B, SSM/I, TMI, and AMSR-E satellite channels are assimilated appropriately and indicate clear positive impacts. Thus, the proposed localization technique is a promising way of assimilating satellite radiances within the LETKF system.

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“…This method is similar to other data assimilation systems, such as those described by Le Dimet and Talagrand (1986), Andersson et al (1998) and Gustafsson et al (2001).…”

Section: Introductionmentioning

confidence: 82%

Assimilation of wind speed and direction observations: results from real observation experiments

Gao

Huang

Jacobs

et al. 2015

Tellus A: Dynamic Meteorology and Oceanography

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A B S T R A C TThe assimilation of wind observations in the form of speed and direction (asm_sd) by the Weather Research and Forecasting Model Data Assimilation System (WRFDA) was performed using real data and employing a series of cycling assimilation experiments for a 2-week period, as a follow-up for an idealised post hoc assimilation experiment. The satellite-derived Atmospheric Motion Vectors (AMV) and surface dataset in Meteorological Assimilation Data Ingest System (MADIS) were assimilated. This new method takes into account the observation errors of both wind speed (spd) and direction (dir), and WRFDA background quality control (BKG-QC) influences the choice of wind observations, due to data conversions between (u,v) and (spd, dir). The impacts of BKG-QC, as well as the new method, on the wind analysis were analysed separately. Because the dir observational errors produced by different platforms are not known or tuned well in WRFDA, a practical method, which uses similar assimilation weights in comparative trials, was employed to estimate the spd and dir observation errors. The asm_sd produces positive impacts on analyses and short-range forecasts of spd and dir with smaller root-mean-square errors than the u,v-based system. The bias of spd analysis decreases by 54.8%. These improvements result partly from BKG-QC screening of spd and dir observations in a direct way, but mainly from the independent impact of spd (dir) data assimilation on spd (dir) analysis, which is the primary distinction from the standard WRFDA method. The potential impacts of asm_sd on precipitation forecasts were evaluated. Results demonstrate that the asm_sd is able to indirectly improve the precipitation forecasts by improving the prediction accuracies of key wind-related factors leading to precipitation (e.g. warm moist advection and frontogenesis).

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The ECMWF implementation of three‐dimensional variational assimilation (3D‐Var). III: Experimental results

Cited by 121 publications

References 30 publications

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

Aerosol data assimilation in the chemical transport model MOCAGE during the TRAQA/ChArMEx campaign: aerosol optical depth

Assimilating Satellite Radiances with a Local Ensemble Transform Kalman Filter (LETKF) Applied to the JMA Global Model (GSM)

Assimilation of wind speed and direction observations: results from real observation experiments

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