DART/CAM: An Ensemble Data Assimilation System for CESM Atmospheric Models

Raeder, K.; Anderson, Jeffrey L.; Collins, Nancy; Hoar, T. J.; Kay, J. E.; Lauritzen, P. H.; Pincus, Robert

doi:10.1175/jcli-d-11-00395.1

Cited by 77 publications

(99 citation statements)

References 47 publications

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“…One example of a popular data assimilation package is the Data Assimilation and Research Test bed, DART (see http://www.image. ucar.edu/DAReS/DART; Anderson et al, 2009;Raeder et al, 2012). It offers many out-of-the-box options for data assimilation and supports a wide range of platforms and possible applications.…”

Section: Motivation For Ctdasmentioning

confidence: 99%

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015

et al. 2017

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Abstract. Data assimilation systems are used increasingly to constrain the budgets of reactive and long-lived gases measured in the atmosphere. Each trace gas has its own lifetime, dominant sources and sinks, and observational network (from flask sampling and in situ measurements to spacebased remote sensing) and therefore comes with its own optimal configuration of the data assimilation. The CarbonTracker Europe data assimilation system for CO 2 estimates global carbon sources and sinks, and updates are released annually and used in carbon cycle studies. CarbonTracker Europe simulations are performed using the new modular implementation of the data assimilation system: the CarbonTracker Data Assimilation Shell (CTDAS). Here, we present and document this redesign of the data assimilation code that forms the heart of CarbonTracker, specifically meant to enable easy extension and modification of the data assimilation system. This paper also presents the setup of the latest version of CarbonTracker Europe (CTE2016), including the use of the gridded state vector, and shows the resulting carbon flux estimates. We present the distribution of the carbon sinks over the hemispheres and between the land biosphere and the oceans. We show that with equal fossil fuel emissions, 2015 has a higher atmospheric CO 2 growth rate compared to 2014, due to reduced net land carbon uptake in later year. The European carbon sink is especially present in the forests, and the average net uptake over 2001-2015 was 0.17 ± 0.11 PgC yr −1 with reductions to zero during drought years. Finally, we also demonstrate the versatility of CTDAS by presenting an overview of the wide range of applications for which it has been used so far.

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Section: Motivation For Ctdasmentioning

confidence: 99%

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015

et al. 2017

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“…DART is an open-source community facility developed at NCAR (Anderson et al, 2009) that provides data assimilation tools to work with either loworder or high-order models for different research activities (Raeder et al, 2012;Karspeck et al, 2013;Schwartz et al, 2015;Hoteit et al, 2013).…”

Section: Ensemble Modeling and Data Assimilation In The Tssmentioning

confidence: 99%

OSSE for a sustainable marine observing network in the Sea of Marmara

Aydoğdu

Hoar

Vukićević

et al. 2018

Nonlin. Processes Geophys.

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Abstract. An observing system simulation experiment (OSSE) is presented in the Sea of Marmara. A highresolution ocean circulation model (FESOM) and an ensemble data assimilation tool (DART) are coupled. The OSSE methodology is used to assess the possible impact of a FerryBox network in the eastern Sea of Marmara. A reference experiment without assimilation is performed. Then, synthetic temperature and salinity observations are assimilated along the track of the ferries in the second experiment. The results suggest that a FerryBox network in the Sea of Marmara has potential to improve the forecasts significantly. The salinity and temperature errors get smaller in the upper layer of the water column. The impact of the assimilation is negligible in the lower layer due to the strong stratification. The circulation in the Sea of Marmara, particularly the Bosphorus outflow, helps to propagate the error reduction towards the western basin where no assimilation is performed. Overall, the proposed FerryBox network can be a good start to designing an optimal sustained marine observing network in the Sea of Marmara for assimilation purposes.

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“…DART has been successfully applied to a host of meteorological and atmospheric composition data assimilation problems (e.g., Arellano et al, 2007;Khade et al, 2013;Raeder et al, 2012;Hacker and Angevine, 2013, and many more) and provides the option to interface to a number of different filter types, including EAKF, EnKF, and kernel and particle filters. ENAAPS was interfaced with DART to take advantage of its EAKF algorithm and is further referred to as the ENAAPS-DART system.…”

Section: Ensemble Data Assimilation and Dartmentioning

confidence: 99%

Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS) and its application of the Data Assimilation Research Testbed (DART) in support of aerosol forecasting

Rubin

Reid²,

Hansen³

et al. 2016

Atmos. Chem. Phys.

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Abstract. An ensemble-based forecast and data assimilation system has been developed for use in Navy aerosol forecasting. The system makes use of an ensemble of the Navy Aerosol Analysis Prediction System (ENAAPS) at 1 × 1 • , combined with an ensemble adjustment Kalman filter from NCAR's Data Assimilation Research Testbed (DART). The base ENAAPS-DART system discussed in this work utilizes the Navy Operational Global Analysis Prediction System (NOGAPS) meteorological ensemble to drive offline NAAPS simulations coupled with the DART ensemble Kalman filter architecture to assimilate bias-corrected MODIS aerosol optical thickness (AOT) retrievals. This work outlines the optimization of the 20-member ensemble system, including consideration of meteorology and sourceperturbed ensemble members as well as covariance inflation. Additional tests with 80 meteorological and source members were also performed. An important finding of this work is that an adaptive covariance inflation method, which has not been previously tested for aerosol applications, was found to perform better than a temporally and spatially constant covariance inflation. Problems were identified with the constant inflation in regions with limited observational coverage. The second major finding of this work is that combined meteorology and aerosol source ensembles are superior to either in isolation and that both are necessary to produce a robust system with sufficient spread in the ensemble members as well as realistic correlation fields for spreading observational information. The inclusion of aerosol source ensembles improves correlation fields for large aerosol source regions, such as smoke and dust in Africa, by statistically separating freshly emitted from transported aerosol species. However, the source ensembles have limited efficacy during long-range transport. Conversely, the meteorological ensemble generates sufficient spread at the synoptic scale to enable observational impact through the ensemble data assimilation. The optimized ensemble system was compared to the Navy's current operational aerosol forecasting system, which makes use of NAVDAS-AOD (NRL Atmospheric Variational Data Assimilation System for aerosol optical depth), a 2-D variational data assimilation system. Overall, the two systems had statistically insignificant differences in root-mean-squared error (RMSE), bias, and correlation relative to AERONETobserved AOT. However, the ensemble system is able to better capture sharp gradients in aerosol features compared to the 2DVar system, which has a tendency to smooth out aerosol events. Such skill is not easily observable in bulk metrics. Further, the ENAAPS-DART system will allow for new avenues of model development, such as more efficient lidar and surface station assimilation as well as adaptive sourcePublished by Copernicus Publications on behalf of the European Geosciences Union. 3928 J. I. Rubin et al.: Development of the ENAAPS and its application of the DART functions. At this early stage of development, the parity with th...

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DART/CAM: An Ensemble Data Assimilation System for CESM Atmospheric Models

Cited by 77 publications

References 47 publications

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015

The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015

OSSE for a sustainable marine observing network in the Sea of Marmara

Development of the Ensemble Navy Aerosol Analysis Prediction System (ENAAPS) and its application of the Data Assimilation Research Testbed (DART) in support of aerosol forecasting

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