Skip to main content
Duke University Libraries
DukeSpace Scholarship by Duke Authors
  • Login
  • Ask
  • Menu
  • Login
  • Ask a Librarian
  • Search & Find
  • Using the Library
  • Research Support
  • Course Support
  • Libraries
  • About
View Item 
  •   DukeSpace
  • Duke Scholarly Works
  • Scholarly Articles
  • View Item
  •   DukeSpace
  • Duke Scholarly Works
  • Scholarly Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

The Ocean-Land-Atmosphere-Model: Optimization and Evaluation of Simulated Radiative Fluxes and Precipitation

Thumbnail
View / Download
3.3 Mb
Date
2010
Authors
Medvigy, David
Walko, Robert L
Otte, Martin J
Avissar, Roni
Repository Usage Stats
463
views
387
downloads
Abstract
This work continues the presentation and evaluation of the Ocean Land Atmosphere Model (OLAM), focusing on the model's ability to represent radiation and precipitation. OLAM is a new, state-of-the-art earth system model, capable of user-specified grid resolution and local mesh refinement. An objective optimization of the microphysics parameterization is carried out. Data products from the Clouds and the Earth's Radiant Energy System (CERES) and the Global Precipitation Climatology Project (GPCP) are used to construct a maximum likelihood function, and thousands of simulations using different values for key parameters are carried out. Shortwave fluxes are found to be highly sensitive to both the density of cloud droplets and the assumed shape of the cloud droplet diameter distribution function. Because there is considerable uncertainty in which values for these parameters to use in climate models, they are targeted as the tunable parameters of the objective optimization procedure, which identified high-likelihood volumes of parameter space as well as parameter uncertainties and covariances. Once optimized, the model closely matches observed large-scale radiative fluxes and precipitation. The impact of model resolution is also tested. At finer characteristic length scales (CLS), smaller-scale features such as the ITCZ are better resolved. It is also found that the Amazon was much better simulated at 100- than 200-km CLS. Furthermore, a simulation using OLAM's variable resolution functionality to cover South America with 100-km CLS and the rest of the world with 200-km CLS generates a precipitation pattern in the Amazon similar to the global 100-km CLS run.
Type
Other article
Subject
cloud microphysics parameterization
part ii
numerical-simulation
global precipitation
boundary-layers
arctic stratus
climate
system
rams
shallow
meteorology & atmospheric sciences
Permalink
https://hdl.handle.net/10161/4277
Published Version (Please cite this version)
10.1175/2009MWR3131.1
Citation
Medvigy,David;Walko,Robert L.;Otte,Martin J.;Avissar,Roni. 2010. The Ocean-Land-Atmosphere-Model: Optimization and Evaluation of Simulated Radiative Fluxes and Precipitation. Monthly Weather Review 138(5): 1923-1939.
Collections
  • Scholarly Articles
More Info
Show full item record
Open Access

Articles written by Duke faculty are made available through the campus open access policy. For more information see: Duke Open Access Policy

Rights for Collection: Scholarly Articles


Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info

Make Your Work Available Here

How to Deposit

Browse

All of DukeSpaceCommunities & CollectionsAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit DateThis CollectionAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit Date

My Account

LoginRegister

Statistics

View Usage Statistics
Duke University Libraries

Contact Us

411 Chapel Drive
Durham, NC 27708
(919) 660-5870
Perkins Library Service Desk

Digital Repositories at Duke

  • Report a problem with the repositories
  • About digital repositories at Duke
  • Accessibility Policy
  • Deaccession and DMCA Takedown Policy

TwitterFacebookYouTubeFlickrInstagramBlogs

Sign Up for Our Newsletter
  • Re-use & Attribution / Privacy
  • Harmful Language Statement
  • Support the Libraries
Duke University