The Atmospheric Radiation Measurement (ARM) user facility has made available its first three-dimensional (3D) large-scale forcing data using a 3D constrained variational analysis approach, known as VARANAL3D.
Initially, VARANAL3D evaluation data are available from two field campaigns at ARM’s Southern Great Plains (SGP) atmospheric observatory: the Spring Cloud Intensive Operational Period from March 1 to 22, 2000, and the Midlatitude Continental Convective Clouds Experiment (MC3E) from April 22 to June 6, 2011.
The VARANAL3D product—an extension of the original one-dimensional constrained variational analysis (VARANAL)—includes 3D large-scale forcing terms and evaluation fields for driving and evaluating single-column models, cloud-resolving models, and large-eddy simulations. The 3D structure of the forcing data allows for studies of spatial variation of the large-scale forcing fields and tests of physical parameterizations across scales.
The 3D constrained variational analysis approach extends the original variational analysis method from one atmospheric column into multiple subcolumns, within a similar domain size. Constraint equations are satisfied in each subcolumn, and all subcolumns interact with one another through horizontal fluxes.
An ensemble framework is built by using multiple reanalyses/analyses data as background data to characterize data uncertainties.
Scientists can use the forcing data for model simulation and evaluation. For more information, please refer to Tang and Zhang (2015), Tang et al. (2016), or the VARANAL3D web page.
Feedback and use of the data are always welcomed. If you have questions/suggestions, please contact Shuaiqi Tang or Shaocheng Xie.
Users can access the data set from the ARM Data Center. (Go here to create an account to download the data.)
References: Tang S and M Zhang. 2015. “Three-dimensional constrained variational analysis: Approach and application to analysis of atmospheric diabatic heating and derivative fields during an ARM SGP intensive observational period.” Journal of Geophysical Research: Atmospheres, 120(15): 7283–7299, https://doi.org/10.1002/2015JD023621.
Tang S, M Zhang, and S Xie. 2016. “An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5.” Journal of Geophysical Research: Atmospheres, 121(1): 33–48, https://doi.org/10.1002/2015JD024167.
# # #ARM is a DOE Office of Science user facility operated by nine DOE national laboratories.