1. MM5I simulations for NARCCAP
Raymond Arritt
with material borrowed from William Gutowski
Iowa State University

2. MM5 Heritage Started as a 3-layer hurricane model around 1970.
Evolved into a general mesoscale model with improved physics, nonhydrostatic dynamical core, routines for initialization and postprocessing, etc.
MM4, mid 1980s. First widely used public version.
MM5 (nonhydrostatic), mid 1990s.
MM4 / MM5 was probably the most widely used mesoscale model of its time. Developed an extensive support structure and user community.

3. MM5 Heritage Descendants:
RegCM, developed by Giorgi and colleagues starting in the late 1980s based on the MM4 hydrostatic dynamical core with different physics (partly adapted from the NCAR CCM).
WRF, developed in the late 1990s using many of the MM4/5 physics options but different dynamical core.
MM5 is no longer actively supported but continues to be used. Performs comparably to other mesoscale weather/climate models.

4. MM5 features compared to the NARCCAP suite of RCMs
Dynamics: Non-hydrostatic (like 2 others)
Spectral nudging: No (like 3 others)
Vertical levels: 23 (others: 18 – 35)
Lateral “sponge zone”: 15(?) grid points (4 – 15)
Land model: NOAH, 4 soil layers (like 2 others)
Convection: Kain-Fritsch2 (unique)
Cloud microphysics: Dudhia simple ice (unique)
Boundary layer: Hong-Pan, non-local K (like 1 other)

5. Simulations completed for NARCCAP
Current climate driven by NCEP Reanalysis-2 ("observations")
Current and future climates driven by NCAR CCM3
In progress: current and future climate driven by HadCM3
now appears to be running successfully after a series of false starts

6. Temperature Bias [˚C] DJF
Spatial RMSE = 2.8˚C

7. Temperature Bias [˚C] JJA
Spatial RMSE = 2.3˚C

8. Precipitation Bias [%] DJF?
Spatial RMSE = 1.1 mm/d

9. Precipitation Bias [%] JJA
LLJ?
Spatial RMSE =
0.6 mm/d
Notice a swath of lower-than-observed precipitation that roughly follows the axis of the Great Plains Low Level Jet.

10. Winter temperature change for CCSM driven RCMs
MM5I
CRCM
WRFG

11. Summer temperature change
CCSM
Summer temperature change likely is more strongly affected by RCM physical parameterizations
MM5I
CRCM
WRFG

12. Winter precipitation change
CCSM
MM5I
CRCM
WRFG

13. Summer precipitation change
CCSM
MM5I
CRCM
WRFG

14. Ranked Monthly Precipitation for 10 wettest cold season months – Coastal California
ECPC wet
This figure uses the 10 wettest cold-season months (wettest 10%) during an 18-yr period ( ) for a coastal California region. UW = University of Washington gridded observed precipitation. RCMs = output from 5 NARCCAP RCMs driven by NCEP/DOE lateral boundary conditions. Cold seaason=Oct-Mar. Figure shows the frequency distribution of when the extreme months occur in the observations (UW) and in the RCMs. RCM curve is the average among the distributions from the 5 RCMs. The shaded region and I-bars show the spread of frequency distribution among the RCMs. The models capture the seasonal variation in occurrence of extreme monthly precipitation.
HRM3 dry 14

15. Final Remarks
MM5I tends to fall in the middle of the NARCCAP RCMs, both compared to observations and in predicted climate changes.
Note regional differences, especially in summer. (This does not mean to simply use the “best” model for a region.)
See poster: Future Heat Waves in the Greater St. Louis Area by Claire Steinweg, William J. Gutowski Jr., Brandon Fisel, Sho Kawazoe