GithubHelp home page GithubHelp logo

zhangweiiowa's Projects

am3 icon am3

AM3 (Donner et al., 2011), the atmospheric component of the GFDL coupled model CM3, was designed with an awareness of key emerging issues in climate science, including aerosol-cloud interactions in climate and climate change, chemistry-climate feedbacks, land and ocean carbon cycles and their interactions with climate change, and decadal prediction. It is GFDL's first global atmospheric model to include cloud-aerosol interactions, with 20 interactive aerosol species. AM3 includes interactive tropospheric and stratospheric chemistry (85 species). AM3 uses emissions to drive its chemistry and aerosols. Its inclusion of stratospheric chemistry and dynamics will enable possible interactions between the stratosphere and troposphere on interannual scales to be included in future studies of decadal predictability. Its stratosphere has increased vertical resolution over AM2, with the uppermost level at about 1 Pascal. AM3's improved simulation of Amazon precipitation will enhance future coupling into an earth-system model. AM3 uses a cubed-sphere implementation of the finite-volume dynamical core. Earth's atmosphere is represented as a cube with six rectangular faces. There is no singularity associated with the north and south poles as with the spherical representation. Computationally, the core is highly scalable and efficient at advecting the large number of tracers associated with AM3's chemistry and aerosols. AM3 uses physically based aerosol activation (Ming et al., 2006) to form cloud droplets. All cloud parameterizations in AM2 were either replaced or augmented to include sub-grid distributions of vertical velocity required for these activation calculations. Sub-grid distributions of vertical velocity are included in AM3's stratiform clouds (Golaz et al., 2011); deep convection (Donner et al., 2001, and Wilcox and Donner, 2007) represented by an ensemble of plumes with mass fluxes and vertical velocities, simple bulk microphysics, and mesoscale updrafts and downdrafts; and shallow convection after Bretherton et al. (2004, Mon. Wea. Rev.) with buoyancy sorting, entraining plumes and vertical velocity. AM3 Code Released March 2012 The code for this model is publicly available. If you are interested in downloading the code, please do so here.

books icon books

Source code for 100+ books, kept here for quick reference

cesm-1_2_2 icon cesm-1_2_2

A clone of the Community Earth System Model, version 1.2.2

climatemodeling icon climatemodeling

Code for Climate Modeling - A undergraduate-level course at Peking University

geodiag icon geodiag

This is a platform which provides tools for diagnosing models.

hiram icon hiram

HiRAM, the GFDL global HIgh Resolution Atmospheric Model, was developed with a goal of providing an improved representation of significant weather events in a global climate model. Our intention was to produce a model capable of simulating the statistics of tropical storms, with sufficient fidelity that it can be used with confidence to study the causes of year-to-year variability in storm activity, recent trends in activity, as well as the predictability of the Atlantic hurricane season. As the credibility of the model improves, based on comparisons with observations, we will apply it to study the effects of global warming on tropical storms. HiRAM was developed based on AM2 (GAMDT 2004) with increased horizontal and vertical resolutions, as well as simplified parameterizations for moist convection and large-scale (stratiform) cloudiness. The idea behind the simplifications in physics is to make the parameterized convection less intrusive so that explicit convection can make significant contributions to the vertical transport of water and energy in the tropics. The idea of the parameterized convection helping the resolved scale convection, rather than supplanting it entirely, is a strategy that we believe will be useful in working with global models with finer and finer resolution, as the resolved convection begins to take on some realistic features (Pauluis and Garner, 2006). Specific changes from AM2 include: 1) the finite-volume dynamical core (Lin 2004) on a latitude-longitude grid has been replaced by a finite-volume core using a cubed-sphere grid topology (Putman and Lin 2007) with a quasi-uniform horizontal grid spacing; 2) the number of vertical levels has been increased from 24 to 32; 3) the relaxed Arakawa-Schubert convective closure (Moorthi and Suarez 1992) in AM2 has been replaced by a scheme based on the parameterization of shallow convection by Bretherton et al. (2004); and 4) the prognostic cloud fraction scheme has been replaced by a simpler diagnostic scheme assuming a sub-grid scale distribution of total water. HiRAM retains the surface flux, boundary layer, land surface, gravity wave drag, large-scale cloud microphysics, and radiative transfer modules from AM2. See Zhao et al. (2009) for more details about the modifications. At about 50km horizontal grid size, the HIRAM (C180-HIRAM) forced by the observed ocean surface temperatures is found to be able to simulate many aspects of the observed tropical cyclone frequency variability for the past few decades, for which reliable observations are available (Zhao et al. 2009). These include the geographical distribution of global hurricane tracks, the seasonal cycle, as well as the inter-annual variability and the decadal trend of hurricane frequency over multiple ocean basins. HiRAM has been used to study hurricane seasonal forecast in the N. Atlantic (Zhao et al. 2010, Chen and Lin 2011) and the results support the view that the overall activity of the Atlantic hurricane season has substantial predictability, if we can predict ocean temperatures. These studies also motivate the development of the GFDL Hybrid Hurricane Forecast System (HyHUFS, Vecchi et al. 2011). HiRAM has also been used to study the response of tropical storms to global warming and CO2 increase (Held and Zhao 2011, Zhao and Held 2010, 2012). HIRAM is also a GFDL model currently participating in the CMIP5 high resolution time-slice simulations (Held et al., in preparation) and the US CLIVAR Hurricane Working Group. The HiRAM atmospheric model is coupled to the new land model LM3, shared by all of the GFDL models contributed to CMIP5.http://www.gfdl.noaa.gov/hiram

mom5 icon mom5

The Modular Ocean Model

mom6 icon mom6

GFDL MOM6 Repository for EMC

oggm icon oggm

Open Global Glacier Model

pcr-globwb_model icon pcr-globwb_model

PCR-GLOBWB (PCRaster Global Water Balance) is a large-scale hydrological model intended for global to regional studies and developed at the Department of Physical Geography, Utrecht University (Netherlands). Contact: Edwin Sutanudjaja ([email protected]).

pycesm icon pycesm

Package for interactive work with the Community Earth System Model

qtcm icon qtcm

A Python Implementation of the Neelin-Zeng QTCM1

uvic2.9 icon uvic2.9

This is the base code of the University of Victoria (UVic) Earth System Climate Model version 2.9 with the Model of Ocean Biogeochemistry and Isotopes (MOBI) version 2.0.

vic icon vic

The Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.