YOTC, a joint activity of the World Climate Research Programme (WCRP) and World Weather Research Programme (WWRP)/THORPEX is year of coordinated observing, modeling, and forecasting with a focus on organized tropical convection, its prediction, and predictability.
A reference source for GCM-type radiative transfer (RT) code evaluation. Contributes to the improvement of solar and thermal RT parameterizations.
Global Land Data Assimilation System
The goal of the Global Land Data Assimilation System (GLDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques, in order to generate optimal fields of land surface states and fluxes (Rodell et al., 2004a).
The Global Modeling Initiative (GMI) is part of the NASA Modeling Analysis and Prediction (MAP) program. GMI investigations support the development and integration of a state-of-the-art modular 3-D chemistry and transport model (CTM) that includes full chemistry for both the troposphere and stratosphere.
The Goddard Cumulus Ensemble (GCE) model, a cloud resolving model (CRM), has been developed and improved at NASA Goddard Space Flight Center over the past two decades. The development and main features of the GCE model were published in Tao and Simpson (1993) and Tao et al. (2003b). A review of the applications of the GCE model to develop a better understanding of precipitation processes can be found in Simpson and Tao (1993) and Tao (2003). The 3D version of the GCE model is typically run using 256 x 256 up to 1024 x 1024 horizontal grid points at 1-2 km resolution or better. An MPI version of the GCE model was recently developed (Juang et al. 2006). It is well documented and easy to modify and improve. It is also flexible enough to run on many different platforms using any number of CPUs.
The current incarnation of the GISS series of coupled atmosphere-ocean models is now available. Called ModelE, it provides the ability to simulate many different configurations of Earth System Models - including interactive atmospheric chemsitry, aerosols, carbon cycle and other tracers, as well as the standard atmosphere, ocean, sea ice and land surface components.
The project seeks to characterize the Global Aerosol System using a combination of satellite observations and chemical transport models. The end goal is to understand and quantify aerosol effects and aerosol forcing on global and regional climate.
Whenever a scattering medium, such as clouds or sea ice, is highly inhomogeneous and optically thick, then 3-dimensional radiative transfer (3DRT) techniques are required. These can be based on Monte Carlo, discrete ordinates, and/or finite volume methodologies. I3RC has defined various baseline cloud cases and coordinated the application of a wide variety of codes to these cases, as a means of certifying the accuracy of codes, and enhancing the ability of codes to handle a variety of cases, and produce the variety of outputs needed for the modeling and remote sensing of clouds and other inhomogeneous scattering media. I3RC is one activity of the 3DRT Working Group of the International Radiation Commission (IRC), and is jointly funded by the NASA Radiation Sciences Program and the DoE Atmospheric Radiation Measurement Program.
The land-surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. The characterization of the spatial and temporal variability of water and energy cycles is critical to improve our understanding of the land-surface-atmosphere interaction and the impact of land-surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land-surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes.
A methodology under development here is to implement a Land Data Assimilation System (LDAS), which consists of land-surface models (uncoupled from an atmospheric model) forced with observations, and thus not affected by NWP forcing biases.
A web-based research and collaboration resource for the scientific model development community. Modeling Guru is intended as a central repository where users can communicate with each other and find information related to the many aspects of scientific modeling development and NASA’s High-End Computing Systems.
MERRA is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5). The Project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and places the NASA EOS suite of observations in a climate context.
The Goddard Multi-scale Modeling Framework (MMF) is based on the coupling of the two-dimensional Goddard Cumulus Ensemble Model (GCE) and the finite-volume GCM (fvGCM). The MMF, which replaces cloud parameterizations with a cloud resolving model (CRM), is a very promising approach in climate modeling. It provides a way to couple low-resolution and high-resolution model physics in an unified framework. The embedded CRMs can explicitly simulate cloud dynamical and physical processes and provide cloud properties and statistics that match the scale of high-resolution satellite observations.
The GMAO interacts with the NCA providing both data and expertise in the utilization of observational analyses and retrospective analyses, and also take feedback on the development of metrics and variables important to decision-making.
The goal of the North American Land Data Assimilation System (NLDAS) is to construct quality-controlled, and spatially and temporally consistent, land-surface model (LSM) datasets from the best available observations and model output to support modeling activities.
The Tropical Rainfall Measuring Mission (TRMM) has its own unique Precipitation Processing System (PPS) to process information from the satellite. PPS analyzes TRMM rainfall data as well as data from other Precipitation based missions and also provides validation from nearly a dozen TRMM ground radar sites.
The WRF is a next-generation mesoscale forecast model and assimilation system that will be used to advance the understanding and the prediction of mesoscale precipitation systems. It consists of four primary subsystems, (1) WRF Standard Initialization (WRFSI), (2) WRF Variational Data assimilation system (WRF-Var), (3) Advanced Research WRF (ARW) dynamic solver, (4) Numerous physics packages contributed by research community. The WRF model will be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. WRF can resolve the small-scale weather features such as front, localized convection, hurricane core, and topographic effect much better than the global model.