MICROBASEEN

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microbaseen > Microbase Ensemble Data ProductsVAP Type(s) > Evaluation

MICROBASE Ensemble Data Products (MICROBASEEN) for Cloud Retrievals provides ensemble means, ensemble standard deviations and probabilistic density distributions of the cloud microphysical properties retrieved by atmospheric radiation measurement (ARM) baseline cloud microphysical algorithm (MICROBASE) at the ARM Southern Great Plains (SGP) Central Facility (CF) site. This data set is processed with a variance-based method [Chen et al., 2014] that enables a probabilitization of MICROBASE by adding normally distributed perturbations to the modes of sample-means of the input profiles at typical model temporal resolution (0.5 hour) and uniformly distributed perturbations to the empirical retrieval algorithm parameters. This data set facilitates objective validation of climate models against cloud retrievals under a probabilistic framework for rigorous statistical inferences. The data is currently available for the March 2000 intensive observational period at the ARM SGP CF site and will be extended to longer periods.

Purpose

Data were collected in order to help and improve the climate and earth system models

Measurements

Locations

  • Fixed
  • AMF1
  • AMF2
  • AMF3

Data Details

Developed By Xiao Chen | Shaocheng Xie | Qi Tang
Contact Xiao Chen
Resource(s) Data Directory
ReadMe
Data format netcdf
Site SGP
Content time range 29 February 2000 - 30 March 2000
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 addtional details.
Access Restriction No access constraints are associated with this data.
Use Restriction No use constraints are associated with this data.
Citations Chen, X., Q. Tang, S. Xie and C. Zhao, 2015: A variance-Based decomposition and global sensitivity index method for uncertainty quantification: application to retrieved ice cloud properties, J. Geophys. Res., DOI: 10.1002/2014JD022750.

Zhao, C., S. Xie, X. Chen, M. P. Jensen, and M. Dunn, 2014: Quantifying uncertainties of cloud microphysical property retrievals with a perturbation method, J. Geophys. Res., 119, 1-11.

2021

Russell LM, D Lubin, I Silber, E Eloranta, J Muelmenstaedt, S Burrows, A Aiken, D Wang, M Petters, M Miller, A Ackerman, A Fridlind, M Witte, M Lebsock, D Painemal, R Chang, J Liggio, and M Wheeler. 2021. Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) Science Plan. Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-21-009.

Theisen A, A Lindenmaier, J Mather, J Comstock, S Collis, and S Giangrande. 2021. ARM FY2021 Radar Plan. Ed. by Robert Stafford, ARM user facility. DOE/SC-ARM-TR-269.

2020

Zhang M, S Xie, X Liu, W Lin, K Zhang, H Ma, X Zheng, and Y Zhang. 2020. "Toward Understanding the Simulated Phase Partitioning of Arctic Single‐Layer Mixed‐Phase Clouds in E3SM." Earth and Space Science, 7(7), e2020EA001125, 10.1029/2020EA001125.
Research Highlight

2016

Van Weverberg K, IA Boutle, CJ Morcrette, and RK Newsom. 2016. "Towards retrieving critical relative humidity from ground-based remote-sensing observations." Quarterly Journal of the Royal Meteorological Society, 142(700), 10.1002/qj.2874.
Research Highlight

Shupe M, J Comstock, D Turner, and G Mace. 2016. "Cloud Property Retrievals in the ARM Program." Meteorological Monographs, 57, 10.1175/AMSMONOGRAPHS-D-15-0030.1.

Shupe M. 2016. Final Report: Investigations of Mixed-Phase Cloud Microphysical, Radiative, and Dynamical Processes. Ed. by Robert Stafford, ARM Climate Research Facility. DOE-CUB-7005.

Shupe MD, JM Comstock, DD Turner, and GG Mace. 2016. Cloud property retrievals in the ARM Program. In The Atmospheric Radiation Program: The First 20 Years, pp. 1-20. .

2015

Xie X and M Zhang. 2015. "Scale-aware parameterization of liquid cloud inhomogeneity and its impact on simulated climate in CESM." Journal of Geophysical Research: Atmospheres, 120(16), 10.1002/2015jd023565.
Research Highlight

Chen X, Q Tang, S Xie, and C Zhao. 2015. "A variance-based decomposition and global sensitivity index method for uncertainty quantification: Application to retrieved ice cloud properties." Journal of Geophysical Research: Atmospheres, 120(9), 10.1002/2014jd022750.

2014

Huang D and Y Liu. 2014. "Statistical characteristics of cloud variability. Part 2: Implication for parameterizations of microphysical and radiative transfer processes in climate models." Journal of Geophysical Research: Atmospheres, 119(18), 10.1002/2014jd022003.


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