Assessment of the cloud liquid water from climate models and reanalysis using satellite observations

Li, Jui-lin F.; Lee, Seungwon; Ma, Hsi-Yen; Stephens, G.; Guan, Bin

doi:10.3319/TAO.2018.07.04.01

Title: Assessment of the cloud liquid water from climate models and reanalysis using satellite observations

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Abstract

We perform here a model-observation comparison and report on the state-of-the-art cloud liquid water content (CLWC) and path (CLWP) outputs from the present-day global climate models (GCMs) simulations in CMIP3/CMIP5, two other GCMs (UCLA and GEOS5) and two reanalyses (ECMWF Interim and MERRA) in comparison with two satellites observational datasets (CloudSat and MODIS). We use two different liquid water observation products from CloudSat and MODIS, for CLWP and their combined product for LWC with a method to remove the contribution from precipitating and convective core hydrometeors so that more meaningful model-observation comparisons can be made. Considering the CloudSat’s limitations of CLWC retrievals due to contamination from the precipitation and from radar clutter near the surface, an estimate CLWC is synergistically constructed using MODIS CLWP and CloudSat CLWC. The model-observation comparison shows that most of the CMIP3/CMIP5 annual mean CLWP values are overestimated by factors of 2 - 10 compared to observations globally. There are a number of CMIP5 models, including CSIRO, MPI, and the UCLA GCM that perform well compared to the other models. For the vertical structure of CLWC, significant systematic biases are found with many models biased significantly high above the mid-troposphere. In the tropics, systematic high biasesmore »« less

Authors:

Li, Jui-lin F. ^[1]; Lee, Seungwon ^[1]; Ma, Hsi-Yen ^[2]; Stephens, G. ^[1]; Guan, Bin ^[3]

California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
California Inst. of Technology (CalTech), Pasadena, CA (United States). Jet Propulsion Lab.; Univ. of California, Los Angeles, CA (United States). Joint Inst. for Regional Earth System Science and Engineering

Publication Date:: Sat Dec 01 00:00:00 EST 2018

Research Org.:: Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); California Institute of Technology (CalTech), Pasadena, CA (United States)

Sponsoring Org.:: USDOE; National Aeronautics and Space Administration (NASA)

OSTI Identifier:: 1498459

Report Number(s):: LLNL-JRNL-765388
Journal ID: ISSN 1017-0839; 955422

Grant/Contract Number:: AC52-07NA27344

Resource Type:: Accepted Manuscript

Journal Name:: TAO: Terrestrial, Atmospheric and Oceanic Sciences

Additional Journal Information:: Journal Volume: 29; Journal Issue: 6; Journal ID: ISSN 1017-0839

Publisher:: The Chinese Geoscience Union

Country of Publication:: United States

Language:: English

Subject:: 54 ENVIRONMENTAL SCIENCES

Citation Formats


                    Li, Jui-lin F., Lee, Seungwon, Ma, Hsi-Yen, Stephens, G., and Guan, Bin. Assessment of the cloud liquid water from climate models and reanalysis using satellite observations.  United States: N. p., 2018. 
Web.  doi:10.3319/TAO.2018.07.04.01.

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                    Li, Jui-lin F., Lee, Seungwon, Ma, Hsi-Yen, Stephens, G., & Guan, Bin. Assessment of the cloud liquid water from climate models and reanalysis using satellite observations.  United States.  https://doi.org/10.3319/TAO.2018.07.04.01

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                    Li, Jui-lin F., Lee, Seungwon, Ma, Hsi-Yen, Stephens, G., and Guan, Bin. Sat .  
"Assessment of the cloud liquid water from climate models and reanalysis using satellite observations".  United States.  https://doi.org/10.3319/TAO.2018.07.04.01.  https://www.osti.gov/servlets/purl/1498459.

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@article{osti_1498459,

  title        = {Assessment of the cloud liquid water from climate models and reanalysis using satellite observations},

  author       = {Li, Jui-lin F. and Lee, Seungwon and Ma, Hsi-Yen and Stephens, G. and Guan, Bin},

  abstractNote = {We perform here a model-observation comparison and report on the state-of-the-art cloud liquid water content (CLWC) and path (CLWP) outputs from the present-day global climate models (GCMs) simulations in CMIP3/CMIP5, two other GCMs (UCLA and GEOS5) and two reanalyses (ECMWF Interim and MERRA) in comparison with two satellites observational datasets (CloudSat and MODIS). We use two different liquid water observation products from CloudSat and MODIS, for CLWP and their combined product for LWC with a method to remove the contribution from precipitating and convective core hydrometeors so that more meaningful model-observation comparisons can be made. Considering the CloudSat’s limitations of CLWC retrievals due to contamination from the precipitation and from radar clutter near the surface, an estimate CLWC is synergistically constructed using MODIS CLWP and CloudSat CLWC. The model-observation comparison shows that most of the CMIP3/CMIP5 annual mean CLWP values are overestimated by factors of 2 - 10 compared to observations globally. There are a number of CMIP5 models, including CSIRO, MPI, and the UCLA GCM that perform well compared to the other models. For the vertical structure of CLWC, significant systematic biases are found with many models biased significantly high above the mid-troposphere. In the tropics, systematic high biases occur at all levels above 700 hPa. Based on the Taylor diagram, the ensemble performance of CMIP5 CLWP simulation shows little or no improvement relative to CMIP3.},

  doi          = {10.3319/TAO.2018.07.04.01},

  journal      = {TAO: Terrestrial, Atmospheric and Oceanic Sciences},

  number       = 6,

  volume       = 29,

  place        = {United States},

  year         = {Sat Dec 01 00:00:00 EST 2018},

  month        = {Sat Dec 01 00:00:00 EST 2018}

}

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