Large-Scale Forcing Data Released for CACTI Campaign

Published: 20 April 2023
A map focused on the variational analysis domain around the main site of the CACTI campaign in Córdoba, Argentina
The map shows the variational analysis domain (enclosed by the red circle) for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The domain is centered at 64.1oW, 32oS. The first ARM Mobile Facility (AMF1) at Córdoba, Argentina, is located near the southwestern corner of the variational analysis domain.

Continuous large-scale forcing data are now available for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The Atmospheric Radiation Measurement (ARM) user facility conducted the CACTI campaign from October 2018 through April 2019 in the Sierras de Córdoba range in north-central Argentina.

Forcing data for CACTI were developed from a constrained variational analysis approach (Zhang and Lin 1997; Zhang et al. 2001). Scientists can use this value-added product (VAP), known as VARANAL, to drive single-column models, cloud-resolving models, and large-eddy simulation models for different cloud and convective systems. To help validate model simulations, the VAP includes diagnostic fields such as diabatic heating profiles, cloud fields, surface measurements, and large-scale conditions.

Considering the steep slope of the terrain and the effect of the surface terrain on the derived large-scale forcing fields, two versions of CACTI large-scale forcing data are available for users to evaluate.

One is the standard version, which was originally designed for a cylindrical atmospheric column using the pressure coordinate algorithm. The pressure coordinate algorithm assumes that the variational analysis domain has a flat surface, with the surface pressure equal to the pressure at the center of the domain.

The other version uses a new terrain-following sigma coordinate algorithm (Tang et al. 2020). This algorithm was designed to better treat the varying slope of the terrain in the analysis so that the effect of the surface terrain on the derived large-scale forcing fields can be captured and represented.

Both versions of the CACTI large-scale forcing data are based on the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) and are constrained by observed surface precipitation and satellite-derived top-of-atmosphere radiative fluxes. The forcing data represent an average over the analysis domain, centered at 64.1oW, 32oS with a radius of 75 kilometers.

The standard and sigma data sets are in netCDF format, with a time resolution of 60 minutes and a vertical resolution of 25 hPa.

Scientists can begin using the CACTI large-scale variational analysis forcing data for model simulation and evaluation. Please note: Because the standard and sigma data sets represent averages over the analysis domain, users need to be cautious when comparing these data sets with ARM single-point measurements.

More information about VARANAL can be found on the VAP web page. Additional details about ARM continuous forcing data are in Xie et al. (2004).

To ask questions, report data issues, or provide feedback on the new CACTI evaluation products, please contact Cheng Tao or Shaocheng Xie.

Access the data sets in the ARM Data Center. (Go here to create an account to download the data.)

To cite the standard VARANAL data, please use doi:10.5439/1860369. The sigma data can be referenced as doi:10.5439/1961987.


Zhang M and J 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.” Journal of the Atmospheric Sciences, 54(11), 1503-1524, doi:10.1175/1520-0469(1997)054<1503:CVAOSD>2.0.CO;2.

Zhang M, J Lin, RT Cederwall, JJ Yio, and SC Xie. 2001. “Objective Analysis of ARM IOP Data: Method and Sensitivity.” Monthly Weather Review, 129(2), 295-311, doi:10.1175/1520-0493(2001)129<0295:OAOAID>2.0.CO;2.

Tang S, S Xie, M Zhang, and S Endo. 2020. “Improvement of Atmospheric Objective Analysis Over Sloping Terrain and Its Impact on Shallow-Cumulus Clouds in Large-Eddy Simulations.” Journal of Geophysical Research: Atmospheres, 125(13), e2020JD032492, doi:10.1029/2020JD032492.

Xie S, RT Cederwall, and MH 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.” Journal of Geophysical Research: Atmospheres, 109(D1), D01104, doi:10.1029/2003JD004045.

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ARM is a DOE Office of Science user facility operated by nine DOE national laboratories.