fredrick h. m. semazzi north carolina state university
DESCRIPTION
Emerging Research Opportunities at the Climate Modeling Laboratory NC State University (Presentation at NIA Meeting: 9/04/03). Fredrick H. M. Semazzi North Carolina State University Department of Marine, Earth and Atmospheric Sciences & Department of Mathematics. - PowerPoint PPT PresentationTRANSCRIPT
Emerging Research Opportunities at the Climate Modeling
Laboratory
NC State University (Presentation at NIA Meeting: 9/04/03)
Fredrick H. M. SemazziNorth Carolina State University
Department of Marine, Earth and Atmospheric Sciences
&Department of Mathematics
Emerging Research Opportunities at the Climate Modeling
Laboratory
NC State University
For Details
http://climlab4.meas.ncsu.edu
•High Resolution Nested Regional Climate Prediction Models
•High Resolution Global Atmospheric Prediction Models
MAIN AREAS OF EMERGING RESEARCH OPPORTUNITIES
Equations of Motion
rFgvΩv
pDt
D
1
2
01
vDt
D
JDt
Dp
Dt
DTcv
MODEL NUMERICAL-DOMAIN
PERFORMANCE IN AN SIMULATING
CLIMATOLOGY (IRI)1970-1995 AVERAGE
• Observations• ENCHAM GCM• RCM-Low Resolution
Model• RCM-High Resolution
Model
OND ACTUAL RAINFALL (MM/DAY)
1970-95 AVERAGE
Comparison of models performance
Adaptation of RegCM2 for EA
0
50
100
150
200
250
TF KH SC TZ SA EA
Homogeneous climate sub-regions
rain
fall(
mm
)
Obs
Exp.1
Exp.2
Exp.3
Exp.4
Exp.5(Optimum)
Optimization of Regional Numerical Models Based on
Useable Prediction Skill
Useable Skill(Palmer et al, 1999)
Fig.2: Algorithm for computation of forecast value (V) & optimization
USER SECTOR PREDICTION MODELCLIMATE OBSERVATIONS
Define (E)Identity C & L
Set ParametersForecast E
Observe E Compute
o (E)
observed
Fst No Yes No Yes
Region 1
Region 2
Region 9ROC
Hit rate H / False alarm F Perfect Prediction
Model
Mper o CL
oL
CoHo
L
CFM
11
Climatology Prediction Model
MCli minCL
,o
HF
V pt MCli M
MCli Mper
Vopt max V
Savings$ MCli Mopt NL
See fig.3
Parameter updateand optimization
Global Atmospheric Model
==================Variable Resolution
Nonhydrostatic Global
Semi-implicit Semi-Lagrangian
Global Variable Resolution Grid
• No lateral boundary conditions
• Multiple scales
• Single code for multiple problems
• Flexible (easy to customize for different regions)
• Simplifies maintenance and optimization with only one code
Variable Resolution Grid
Nonhydrostatic Dymanics
• Increasing resolutions of atmospheric models
• Little additional computational cost
• Some atmospheric phenomena are nonhydrostatic (e.g. tropical cyclones)
BatesNASA GODDARD
GCM
Bates et al (1993)
NC STATE UNIVERSITY
GCM
Semazzi et al (2003)
Day 2 - 500 hPa
400 m resolution-courant#=3
Hydrostatic Non-Hydrostatic
2 km resolution
Hydrostatic Non-Hydrostatic
Future Work•Optimization of Regional Numerical Models Based on Useable Prediction Skill•Efficiency improvements to semi-implicit semi-Lagrangian (SISL) numerical scheme: solver, interpolation•Physical parameterization: heating, friction, convection, moisture, etc.•Parallel version
in collaboration with NASA and other organizations …