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ARM Cloud Retrieval Ensemble Data (ACRED) is a multi-year ensemble cloud microphysical property data set, created by assembling nine existing ground-based cloud retrievals of ARM measurements from cloud radars, lidars, and the Atmospheric Emitted Radiance Interferometer (AERI). The major cloud properties in ACRED are the cloud liquid effective radius, liquid water content, liquid water path, cloud ice effective radius, ice water content, and ice water path. For each variable, three types of quantities are provided: the time means, standard deviations, and quality control flags. Currently, ACRED is available at the ARM Southern Great Plains (SGP), North Slope of Alaska (NSA), and Tropical Western Pacific atmospheric observatories (TWP). For each site, ACRED contains three to six retrieval products for multiple years. The current version of ACRED includes hourly averaged cloud properties and has 512 vertical layers with a resolution of 45 m, which are consistent with the ARM Best Estimate (ARMBE) data products.

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This data set is developed to address the uncertainty issue within current cloud retrievals (Zhao et al. 2012), as large differences exist in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. It provides a rough estimate of the uncertainties in current ARM retrieved cloud microphysical properties for climate model evaluation and development. Additionally, the ACRED serves as a useful tool to understand uncertainties or bias that are closely associated with the retrieval techniques, which is an important step to further improve the representation of cloud processes in climate models.

One concern is that the uncertainty in each ensemble member has not been determined for all meteorological conditions. This can be addressed by 1) to generate an ensemble data set for each algorithm by perturbing key parameters and/or changing key assumptions used in these selected retrieval methods (Zhao et al. 2014), 2) to create observation system simulation experiment data sets and run the algorithms on these. In general, the retrieval techniques used by the nine ARM ground-based retrieval products differ from each other in their retrieval fundamental basis, assumptions used, retrieval inputs, and retrieval constraints. We recommend that users refer to the technical report and references below for more information.



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Content time range 1 January 1997 - 30 June 2009


Shupe MD, DD Turner, A Zwink, MM Thieman, EJ Mlawer, and T Shippert. 2015. "Deriving Arctic Cloud Microphysics at Barrow, Alaska: Algorithms, Results, and Radiative Closure." Journal of Applied Meteorology and Climatology, 54(7), 10.1175/jamc-d-15-0054.1.
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Forbes RM and M Ahlgrimm. 2014. "On the Representation of High-Latitude Boundary Layer Mixed-Phase Cloud in the ECMWF Global Model." Monthly Weather Review, 142(9), 10.1175/mwr-d-13-00325.1.


Xie S, X Liu, C Zhao, and Y Zhang. 2013. "Sensitivity of CAM5-Simulated Arctic Clouds and Radiation to Ice Nucleation Parameterization." Journal of Climate, 26(16), 10.1175/jcli-d-12-00517.1.
Research Highlight

Sivaraman S. 2013. ARM Climate Research Facility Quarterly Value-Added Product Report January 1–March 31, 2013. Ed. by U.S. Department of Energy, DOE/SC-ARM-13-010.

Zhang Y and SA Klein. 2013. "Factors Controlling the Vertical Extent of Fair-Weather Shallow Cumulus Clouds over Land: Investigation of Diurnal-Cycle Observations Collected at the ARM Southern Great Plains Site." Journal of the Atmospheric Sciences, 70(4), 10.1175/jas-d-12-0131.1.
Research Highlight

Riihimaki L, S McFarlane, C Sivaraman, T Shippert, K Gaustad, Y Shi, and J Comstock. 2013. VAP Highlights for the CAPI Working Group. Presented at 4th Atmospheric System Research (ASR) Science Team Meeting. Potomac, MD.

McCoy R, S Xie, Y Zhang, and C Zhao. 2013. Update on ARM Climate Modeling Data Development at Lawrence Livermore National Laboratory. Presented at 4th Atmospheric System Research (ASR) Science Team Meeting. Potomac, MD.

Sivaraman C. 2013. ARM Climate Research Facility Quarterly Value-Added Product Report October 01–December 31, 2012. U.S. Department of Energy. DOE/SC-ARM-13-002.


Zhao C, S Xie, SA Klein, A Protat, MD Shupe, SA McFarlane, JM Comstock, J Delanoë, M Deng, M Dunn, RJ Hogan, D Huang, MP Jensen, GG Mace, R McCoy, EJ O'Connor, DD Turner, and Z Wang. 2012. "Toward understanding of differences in current cloud retrievals of ARM ground-based measurements." Journal of Geophysical Research: Atmospheres, 117(D10), D10206, 10.1029/2011jd016792.

Zhao C, SA Klein, S Xie, X Liu, JS Boyle, and Y Zhang. 2012. "Aerosol first indirect effects on non-precipitating low-level liquid cloud properties as simulated by CAM5 at ARM sites." Geophysical Research Letters, 39(8), L08806, 10.1029/2012gl051213.
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