Cloud Property Retrieval Products for Graciosa Island, Azores

Dong, Xiquan

doi:10.5439/1169499

Title: Cloud Property Retrieval Products for Graciosa Island, Azores

Dataset
Other Related Research

Abstract

The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, wemore »« less

Authors:: Dong, Xiquan

Publication Date:: Mon May 05 00:00:00 EDT 2014

DOE Contract Number:: DE-AC05-00OR22725

Research Org.:: Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Atmospheric Radiation Measurement (ARM) Archive

Sponsoring Org.:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Collaborations:: PNL, BNL,ANL,ORNL

Subject:: 54 Environmental Sciences

Keywords:: Cloud optical depth; Cloud particle number concentration; Cloud base height; Cloud droplet size; Cloud top height; Liquid water content

OSTI Identifier:: 1169499

DOI:: https://doi.org/10.5439/1169499

Citation Formats


                    Dong, Xiquan. Cloud Property Retrieval Products for Graciosa Island, Azores.  United States: N. p., 2014. 
        Web.  doi:10.5439/1169499.

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                    Dong, Xiquan. Cloud Property Retrieval Products for Graciosa Island, Azores.  United States.  doi:https://doi.org/10.5439/1169499

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                    Dong, Xiquan. 2014.  
"Cloud Property Retrieval Products for Graciosa Island, Azores".  United States.  doi:https://doi.org/10.5439/1169499.  https://www.osti.gov/servlets/purl/1169499. Pub date:Mon May 05 00:00:00 EDT 2014

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@article{osti_1169499,

  title        = {Cloud Property Retrieval Products for Graciosa Island, Azores},

  author       = {Dong, Xiquan},

  abstractNote = {The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.},

  doi          = {10.5439/1169499},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Mon May 05 00:00:00 EDT 2014},

  month        = {Mon May 05 00:00:00 EDT 2014}

}

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DOI: https://doi.org/10.5439/1169499

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