Atmospheric Radiation Measurement Climate Research Facility US Department of Energy

lasso > LES ARM Symbiotic Simulation and Observation (LASSO)VAP Type(s) > Baseline • Evaluation

The Alpha 1 release contains initial data bundles from the large-eddy simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) workflow pilot project for five shallow convection days from June and August 2015 plus an interface to a NoSQL approach to querying the simulation skill scores. These bundles represent initial model configurations, evaluation metrics, and products being considered for eventual automation for ongoing LASSO LES simulations. A data bundle is a unified package consisting of LASSO LES input and output, observations, evaluation diagnostics, and model skill scores. LES input includes model configuration information and forcing data. LES output includes profile statistics and full domain fields of cloud and environmental variables. Model evaluation data consists of LES output and ARM observations co-registered on the same grid and sampling frequency. Model performance is quantified by skill scores and diagnostics in terms of cloud and environmental variables.

For most purposes, the Alpha 1 simulations have been superseded by supplemental simulations added to Alpha 2 for the five case dates in 2015. Thus, users seeking LASSO simulations for 2015 should refer to the Alpha 2 set of data bundles. However, not all sensitivity comparisons were re-run for Alpha 2, and thus some users still may consider using the Alpha 1 product. Users interested in using the Alpha 1 simulations should see Appendix D in the Alpha 2 documentation update from April 2018 for details.


The purpose of releasing these data bundles is to share with researchers how the models are behaving, as well as to get feedback on ways to present the data and improve overall results.


  • Fixed
  • AMF1
  • AMF2
  • AMF3

Data Details

Developed By William Gustafson | Andrew Vogelmann | Xiaoping Cheng | Satoshi Endo | Zhijin Li | Tami Toto | Heng Xiao | Bhargavi Krishna
Contact William Gustafson
Resource(s) Data Directory
Data format netCDF, png, gif, jpeg, html, pdf, txt, Cassandra with Spark
Site SGP
Content time range 6 June 2015 - 29 September 2019
Attribute accuracy No formal attribute accuracy tests were conducted.
Positional accuracy No formal positional accuracy tests were conducted.
Data Consistency and Completeness Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. Missing values in input data sets are carried through to the final analysis.
Access Restriction No access constraints are associated with this data.
Use Restriction No use constraints are associated with this data.
File naming convention Mixed--combination of metrics with ARM-like names and model output that uses WRF and SAM naming conventions
Directory Organization Directory organization: See Section 5.1 of
Citations Khairoutdinov, M. F., and D. A. Randall (2003), Cloud resolving modeling of the ARM summer 1997 IOP: Model formulation, results, uncertainties, and sensitivities, J. Atmos. Sci., 60, 607-625, doi:10.1175/1520-0469(2003)060<0607:Crmota>2.0.Co;2.

Li, Z., X. Cheng, W. I. Gustafson, and A. M. Vogelmann (2016), Spectral characteristics of background error covariance and multiscale data assimilation, Int. J. Numer. Meth. Fluids, in press, doi:10.1002/fld.4253.

Li, Z., S. Feng, Y. Liu, W. Lin, M. Zhang, T. Toto, A. M. Vogelmann, and S. Endo (2015), Development of fine-resolution analyses and expanded large-scale forcing properties: 1. Methodology and evaluation, J. Geophys. Res., 120, 654-666, doi:10.1002/2014jd022245.

Li, Z. J., J. C. McWilliams, K. Ide, and J. D. Farrara (2015), A multiscale variational data assimilation scheme: Formulation and illustration, Mon. Wea. Rev., 143, 3804-3822, doi:10.1175/mwr-d-14-00384.1.

Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, M. G. Duda, W. Wang, and J. G. Powers (2008), A description of the advanced research WRF version 3, 113 pp, NCAR Technical Note, NCAR/TN-475+STR, National Center for Atmospheric Research,

Xie, S. C., R. T. Cederwall, and M. H. Zhang (2004), Developing long-term single-column model/cloud system-resolving model forcing data using numerical weather prediction products constrained by surface and top of the atmosphere observations, J. Geophys. Res., 109, D01104, doi:10.1029/2003jd004045.

Zhang, M. H., and J. L. Lin (1997), Constrained variational analysis of sounding data based on column-integrated budgets of mass, heat, moisture, and momentum: Approach and application to ARM measurements, J. Atmos. Sci., 54, 1503-1524, doi:10.1175/1520-0469(1997)054 1503:Cvaosd 2.0.Co;2.

Zhang, M. H., J. L. Lin, R. T. Cederwall, J. J. Yio, and S. C. Xie (2001), Objective analysis of ARM IOP data: Method and sensitivity, Mon. Wea. Rev., 129, 295-311, doi:10.1175/1520-0493(2001)129 0295:Oaoaid 2.0.Co;2.


Xu X, C Lu, Y Liu, S Luo, X Zhou, S Endo, L Zhu, and Y Wang. 2022. "Influences of an entrainment–mixing parameterization on numerical simulations of cumulus and stratocumulus clouds." Atmospheric Chemistry and Physics, 22(8), 10.5194/acp-22-5459-2022.

Griewank P, T Heus, and R Neggers. 2022. "Size‐Dependent Characteristics of Surface‐Rooted Three‐Dimensional Convective Objects in Continental Shallow Cumulus Simulations." Journal of Advances in Modeling Earth Systems, 14(3), e2021MS002612, 10.1029/2021MS002612.

Beamesderfer E, C Buechner, C Faiola, M Helbig, Z Sanchez‐Mejia, A Yáñez‐Serrano, Y Zhang, and A Richardson. 2022. "Advancing Cross‐Disciplinary Understanding of Land‐Atmosphere Interactions." Journal of Geophysical Research: Biogeosciences, 127(2), e2021JG006707, 10.1029/2021JG006707.

Dorsey K, C Ireland, R Jundt, B Mundy, and R Stafford. 2022. 2021 Annual Report. Ed. by Robert Stafford, ARM User Facility. doe-sc-arm-21-023. 10.2172/1843842.


Shin H, L Xue, W Li, G Firl, D D’Amico, D Muñoz‐Esparza, M Ek, Y Chu, Z Wang, W Gustafson, and A Vogelmann. 2021. "Large‐Scale Forcing Impact on the Development of Shallow Convective Clouds Revealed from LASSO Large‐Eddy Simulations." Journal of Geophysical Research: Atmospheres, 126(20), e2021JD035208, 10.1029/2021JD035208.

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William Gustafson
Pacific Northwest National Laboratory

Andrew Vogelmann
Brookhaven National Laboratory

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