1. Development of Inter-model differences
Example - pan-Arctic simulation

2. Model domain Baseline Run: 1 Oct. 1985 - 30 Sep. 1986
(grid: 51 x 91; 120 km)
Baseline Run: Oct Sep. 1986
Wetlands Runs: April Sep. 1986
Sensitivity Runs: Oct 85 or July 86

3. 500 hPa Heights: RMS Difference vs. Time (MM5-NCEP)
150
100 50
[m]
1 OCT NOV

4. RMS Difference vs. Baseline (500 hPa)

5. Random Numbers on a Computer
Goals:
Evenly distributed set of numbers in some range
All sequences statistically independent of others
Generated by an algorithm
Hence, repeatable
Hence, not truly random
“Seed” gives a starting point for the algorithm
True Random Numbers?
Sample physical phenomena with known statistical properties
Example:

6. Ensemble Simulation Recognizes inherent “noise” of climate system
Adds noise
via starting conditions of forecast or climate simulation
via changes in parameters or parameterizations
Used to sample noise versus signal
Ensemble:
average appears to give more accurate result
spread indicates periods of greater uncertainty?

7. Ensemble EdGCM Simulation