1. Does nudging squelch the extremes in regional climate modeling?
Tanya L. Otte, Martin J. Otte, Christopher G. Nolte, and Jared H. Bowden
10th CMAS Conference
Chapel Hill, North Carolina
26 October 2011

2. Our Research Problem…Simplified
Constraint of RCM toward GCM
Freedom of RCM to develop smaller-scale processes
delicate balance
Keeps RCM climate consistent with GCM
Decreases variability
Allows RCM climate to deviate from GCM
Increases variability
More constraint toward GCM
Less constraint toward GCM

3. Connecting Larger-Scale Fields to Smaller-Scale Fields
Larger-Scale Model
Smaller-Scale Model
unrelated solutions
related solutions
output from
larger-scale model
regional output from
larger-scale model
output from
smaller-scale model
Need smaller-scale model to connect to and build upon larger-scale model.
output from
smaller-scale model
taking cues from
larger-scale model’s features 3

4. Nudging…Simplified
Used to constrain smaller-scale fields toward larger-scale fields
Need to determine:
How many to use?
Where to use?
Which color? 4

5. Constraining RCM to GCM with “nudging”
Use “observed” state to influence model (GCM  RCM)
Adds a non-physical term to the model equations
Term is based on difference between model and observation
Can be either toward:
Analyses (direct differences of fields in time/space) – Typical for CMAQ
Attractive when background fields are not significantly more coarse than target resolution
Horizontal wind components, temperature, moisture
Spectra (differences in wave decomposition in time/space) – New in WRF
Attractive when background fields are significantly more coarse than target resolution
Horizontal wind components, temperature, geopotential (~pressure) 5

6. WRFv3.2.1 forced by 2.5° × 2.5° NCEP Reanalysis 2 (R2)
Three 20-Year continuous WRF runs with hourly output.
Compare to 3-h, 32-km NARR, and 1-h, 0.31° CFSR products.
108-km: 81 x 51
36-km:187 x 85
RRTMG Longwave and Shortwave Radiation
WSM6 Microphysics
Grell Ensemble Convective Scheme
Yonsei University PBL Scheme
NOAH Land-Surface Model
Figure from
Bowden et al., J. Climate, in press

7. Mean 2-m Temperature Difference (1988-2007)
Nudging reduces warm bias in Plains and cold bias in Canada.
Differences in complex terrain from topography in WRF vs. CFSR.

8. Mean Annual Precipitation (1988-2007)
WRF overpredicts precipitation by ~250 mm annually.
Patterns improved with nudging, particularly AN.

9. Monthly Area-Average Temperature Difference from NARR
Both types of nudging consistently reduce error.

10. Monthly Area-Averaged Precipitation Total
Higher highs
Lower lows
Greater variability without nudging: Is it real?

11. Monthly Area-Averaged Precipitation Total
Compared to NARR, WRF is too wet.
Nudging reduces erroneous peaks.

12. Annual Days with Temperature Relative to NCDC Threshold
< 32°F
> 90°F
< 0°F
NARR NN AN SN
Nudging adds variability for extreme cold.
Nudging lowers extreme high temperatures…will this verify?

13. Annual Days with Precipitation Exceeding NCDC Threshold
NARR NN AN SN
WRF is generally too wet compared to NARR.
Nudging, especially AN, makes extremes more realistic.

14. Nudging Does Not Appear to Squelch the Extremes in RCM
Both AN and SN improve means
2-m temperature slightly warmer with AN than SN
Precipitation totals simulated better with AN than SN
Precipitation overpredicted by WRF, especially without nudging
SN has more variability than AN
Spectra (not shown) suggest AN coefficients are too strong for RCM
Will weaker AN coefficients improve variability, retain value?
Need hourly observations to validate variability of SN surface fields
Performance is consistent in most regions
Complex terrain qualitatively affects results