Methodology

The Goddard Cumulus Ensemble (GCE) model has been developed and improved at NASA/Goddard Space Flight Center (GSFC) over the past two decades and is considered one of the state-of-the-art CRMs (Cloud Resolving Models) in the research community.  As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, the 3-D GCE model has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability.  One of the primary objectives of this IDS Project aims at investigating various cloud systems in Tropics and mid-latitudes, as well as producing “Cloud Library” by conducting a series of long-term simulations using the 3-D GCE model that is driven by the implemented large-scale temperature and moisture forcing data obtained either from sounding observations or the GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis (in compensating the scarcity of real field campaign data in both time and space (location)).  Several convective episodes [e.g., involving field campaigns such as SCSMEX (South China Sea Monsoon Experiment), KWAJEX (Kwajalein Experiment), and CRYSTAL-FACE study (Cirrus Regional Study of Tropical Anvils and Cirrus layers – Florida Area Cumulus Experiment)] have recently been successfully simulated.  A handful of extra long-term simulations have been proposed targeting at different geographic locations will soon be performed.

All modeling systems described in the "Models" section have been used in many different experiments and produced many cloud data sets. All data sets have been archived in the cloud library. The viewgrpahs listed below show some examples from these modeling systems. If you are interested in using these data sets, click on "Access Protocol", it will take you to the cloud library dataportal.

GCE-Cloud Resolving Model:

Coupling of Clouds and Precipitation to Land Surface

Clouds and precipitation are highly coupled with land surface on the timescales of days to months, which challenges current weather and climate prediction models. High-resolution cloud models, coupled with land surface models, can address this process explicitly. Recently, the GCE (Goddard Cumulus Ensemble) model is coupled with LIS (Land Information System), and model results are evaluated with observations.

Click an image to enlarge:

ARM observed cloud amount

Modeled cloud amount with ARM surface fluxes as input

Modeled cloud amount with LIS surface fluxes as input

Zeng, X., W.-K. Tao, M. Zhang, C. Peters-Lidard, S. Lang, J. Simpson, S. Kumar, S. Xie, J. L. Eastman, C.-L. Shie and J. V. Geiger, 2007: Evaluating clouds in long-term cloud-resolving model simulations with observational data. J. Atmos. Sci. (in press).

top

Improving the Simulation of Convective Cloud Systems:
Higher resolution and more realistic ice physics

The Goddard Cumulus Ensemble (GCE) model is a cloud-resolving model developed at NASA Goddard by Dr. W.-K. Tao to simulate convective cloud systems.

High resolution simulation of 23 Feb 1999 TRMM LBA case Image by J. Williams (Scientific Visualization Studio)

Click an image to enlarge:

Improvements to the cloud microphysics results in less high-density ice and more realistic hydrometeor profiles for use in satellite retrievals

Higher horizontal model resolution leads to a more realistic, gradual transition from shallow to deep convection

Lang, S., W.-K. Tao, R. Cifelli, W. Olson, J. Halverson, S. Rutledge, and J. Simpson, 2007: Improving simulations of convective systems from TRMM LBA: Easterly and westerly regimes. J. Atmos. Sci., 64, 1141-1164.

top

Impact of Aerosol on Precipitation Processes

OBJECTIVE: Use Goddard Cloud Ensemble Model with spectral-bin microphys to asses the impact of atmospheric aerosol concentration on deep convections.

Click an image to enlarge:

Dirty (or high) CCN can either suppress or enhance precipitation processes, depending on environmental conditions and cloud dynamics/microphysics interactions; Clean (Low) CCN produces earlier rain onset and enhances surface rain only at initial stages; CCN variations can modulate surface rainfall characteristics, e.g. stratiform area and intensity.

Tao, W.-K., X. Li, A. Khain, T. Matsui, S. Lang, and J. Simpson, 2007: The role of atmospheric aerosol concentration on deep convective precipitation: Cloud-resolving model simulations. J. Geophys. Res., submitted.

top

Coupled WRF-GCE-LIS (High-resolution Weather Forecast Model):

Importance of the microphysics in high-resolution weather forecast models

Microphysical (cloud) processes developed at NASA Goddard were implemented into a next generation of weather forecast model (e.g. WRF). The explicit and realistic representation of microphysics in the high-resolution numerical weather forecast model is crucial for accurate prediction of the midlatitude mesoscale convective systems and the intensity and track of hurricanes.

Click an image to enlarge:

Three-day forecast tracks for Hurricane Katrina (2005). The actual track is shown in black.

WRF simulation - accumulated precipitation at 4 resolutions from IHOP June 12 2002 case

Tao, W.-K., J. Shi, S. Chen, S. Lang, S.-Y. Hong, G. Thompson, C. Peters-Lidard, A. Hou, S. Braun, and J. Simpson, 2007: Revised bulk-microphysical schemes for studying precipitation processes: Part I: Comparison with different microphysical schemes, Mon. Wea. Rev., (submitted).

top

Global Mesoscale Model (fvGCM):

Forecasts of Katrina's Track, Intensity, Structures with a Global Mesoscale Model

It is known that General Circulation Models (GCMs) have insufficient resolution to accurately simulate hurricane near-eye structure and intensity. Their physics packages (e.g., cumulus parameterizations) are also known limiting factors in simulating hurricanes.

Six 5-day simulations of Katrina at both 0.25o and 0.125o show comparable track forecasts, but the higher-resolution (0.125o) runs provide much better intensity forecasts, producing the center pressure with errors of only +- 12 hPa. Realistic near-eye wind distribution and vertical structure are also obtained as cumulus parameterizations are disabled.

Shen, B.-W., R. Atlas, O. Reale, S.-J. Lin, J.-D. Chern, J. Chang, C. Henze, J.-L. Li, 2006: Hurricane Forecasts with a Global Mesoscale-resolving model: Preliminary results with Hurricane Katrina (2005). GRL, 33, L13812, doi:10.1029/2006GL026143.

Click an image to enlarge:

Landfall errors: e32 (1/4o): 50km, g48(1/8o): 14km, g48ncps (1/8o w/o CPs): 30km

GFS Analysis (~35km) valid at 08/29/12z	96 h Simulations with no CPS
High-resolution runs simulate realistic intensity, RMW (radius of max wind) and warm core (shaded)

Near-eye Wind Distributions in a 2ox2o box (a) AOML high-resolution surface wind analysis, (b) the 0.25o 99h simulations, (c) the 0.125o 99h simulations, (d) the 0.125o 96h simulations without convection parameterizations (CPs).

top

Coupled fvGCM-GCE MMF (Multi-scale Modeling Framework):

Diurnal Variation of Precipitation from NASA Satellites and Goddard MMF

The diurnal cycle is a fundamental mode of atmospheric variability and has a major impact on weather and climate prediction. In addition, it provides a robust test of physical processes represented in atmospheric models that are used for studying the water and energy cycles. Most climate models simulate precipitation too early over both land and ocean.

NASA satellite retrievals in general show that precipitation occurs most frequently in the late afternoon and early morning over major continents and oceans, respectively. The Goddard Multi-scale Modeling Framework (MMF) that replaces the sub-grid cloud parameterization with an explicit cloud-resolving model, is superior to the Goddard fvGCM (a convectional climate model) in reproducing the correct timing of the diurnal cycle of precipitation frequency both over lands and oceans.

Click an image to enlarge:

Yellow: Late Afternoon Rain Blue: Early Morning Rain

top