Diagnosis of regime‐dependent cloud simulation errors in CMIP5 models using "A‐Train" satellite observations and reanalysis data. Issue 7 (8th April 2013)
- Record Type:
- Journal Article
- Title:
- Diagnosis of regime‐dependent cloud simulation errors in CMIP5 models using "A‐Train" satellite observations and reanalysis data. Issue 7 (8th April 2013)
- Main Title:
- Diagnosis of regime‐dependent cloud simulation errors in CMIP5 models using "A‐Train" satellite observations and reanalysis data
- Authors:
- Su, Hui
Jiang, Jonathan H.
Zhai, Chengxing
Perun, Vince S.
Shen, Janice T.
Del Genio, Anthony
Nazarenko, Larissa S.
Donner, Leo J.
Horowitz, Larry
Seman, Charles
Morcrette, Cyril
Petch, Jon
Ringer, Mark
Cole, Jason
von Salzen, Knut
d S. Mesquita, Michel
Iversen, Trond
Kristjansson, Jon Egill
Gettelman, Andrew
Rotstayn, Leon
Jeffrey, Stephen
Dufresne, Jean‐Louis
Watanabe, Masahiro
Kawai, Hideaki
Koshiro, Tsuyoshi
Wu, Tongwen
Volodin, Evgeny M.
L'Ecuyer, Tristan
Teixeira, Joao
Stephens, Graeme L. - Abstract:
- Abstract: [1] The vertical distributions of cloud water content (CWC) and cloud fraction (CF) over the tropical oceans, produced by 13 coupled atmosphere‐ocean models submitted to the Phase 5 of Coupled Model Intercomparison Project (CMIP5), are evaluated against CloudSat/CALIPSO observations as a function of large‐scale parameters. Available CALIPSO simulator CF outputs are also examined. A diagnostic framework is developed to decompose the cloud simulation errors into large‐scale errors, cloud parameterization errors and covariation errors. We find that the cloud parameterization errors contribute predominantly to the total errors for all models. The errors associated with large‐scale temperature and moisture structures are relatively greater than those associated with large‐scale midtropospheric vertical velocity and lower‐level divergence. All models capture the separation of deep and shallow clouds in distinct large‐scale regimes; however, the vertical structures of high/low clouds and their variations with large‐scale parameters differ significantly from the observations. The CWCs associated with deep convective clouds simulated in most models do not reach as high in altitude as observed, and their magnitudes are generally weaker than CloudSat total CWC, which includes the contribution of precipitating condensates, but are close to CloudSat nonprecipitating CWC. All models reproduce maximum CF associated with convective detrainment, but CALIPSO simulator CFs generallyAbstract: [1] The vertical distributions of cloud water content (CWC) and cloud fraction (CF) over the tropical oceans, produced by 13 coupled atmosphere‐ocean models submitted to the Phase 5 of Coupled Model Intercomparison Project (CMIP5), are evaluated against CloudSat/CALIPSO observations as a function of large‐scale parameters. Available CALIPSO simulator CF outputs are also examined. A diagnostic framework is developed to decompose the cloud simulation errors into large‐scale errors, cloud parameterization errors and covariation errors. We find that the cloud parameterization errors contribute predominantly to the total errors for all models. The errors associated with large‐scale temperature and moisture structures are relatively greater than those associated with large‐scale midtropospheric vertical velocity and lower‐level divergence. All models capture the separation of deep and shallow clouds in distinct large‐scale regimes; however, the vertical structures of high/low clouds and their variations with large‐scale parameters differ significantly from the observations. The CWCs associated with deep convective clouds simulated in most models do not reach as high in altitude as observed, and their magnitudes are generally weaker than CloudSat total CWC, which includes the contribution of precipitating condensates, but are close to CloudSat nonprecipitating CWC. All models reproduce maximum CF associated with convective detrainment, but CALIPSO simulator CFs generally agree better with CloudSat/CALIPSO combined retrieval than the model CFs, especially in the midtroposphere. Model simulated low clouds tend to have little variation with large‐scale parameters except lower‐troposphere stability, while the observed low cloud CWC, CF, and cloud top height vary consistently in all large‐scale regimes. Key points: Modeled regime‐dependent cloud vertical structures differ greatly from obs Cloud parameterization errors dominate the total cloud errors Simulator cloud fraction (CF) agrees better with the observed than model CF … (more)
- Is Part Of:
- Journal of geophysical research. Volume 118:Issue 7(2013:Jul.)
- Journal:
- Journal of geophysical research
- Issue:
- Volume 118:Issue 7(2013:Jul.)
- Issue Display:
- Volume 118, Issue 7 (2013)
- Year:
- 2013
- Volume:
- 118
- Issue:
- 7
- Issue Sort Value:
- 2013-0118-0007-0000
- Page Start:
- 2762
- Page End:
- 2780
- Publication Date:
- 2013-04-08
- Subjects:
- Clouds -- Climate Model -- Satellite Observation -- CMIP5 -- A‐Train -- large‐scale regimes -- conditional sampling -- model error diagnosis
Atmospheric physics -- Periodicals
Geophysics -- Periodicals
551.5 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2169-8996 ↗
http://www.agu.org/journals/jd/ ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1029/2012JD018575 ↗
- Languages:
- English
- ISSNs:
- 2169-897X
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4995.001000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 2222.xml