773 San Marin Drive, Suite 2115, Novato, CA 94998 415.899.0700 

Draft Report 

Evaluation of Preliminary MM5 Meteorological 

Model Simulation for the June-July 2006 

Denver Ozone SIP Modeling Period 

Focused on Colorado 

Prepared for: 

Regional Air Quality Council 

1445 Market Street, Suite 260 

Denver, Colorado 80202 

Prepared by: 

Dennis McNally 

George Schewe 

Alpine Geophysics, LLC 

7341 Poppy Way 

Arvada, Colorado 80007 

Jeremiah Johnson 

Ralph Morris 

ENVIRON International Corporation 

773 San Marin Dr. Suite 2115 

Novato, CA 94998 

February 25, 2008 
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TABLE OF CONTENTS 

1 INTRODUCTION................................................................................................................ 1-1 

2 METHODOLOGY .............................................................................................................. 2-1 

2.1 Model Selection and Application..................................................................................... 2-1 

2.2 Evaluation Approach ....................................................................................................... 2-2 

3 MM5 PERFORMANCE EVALUATION RESULTS ...................................................... 3-1 

3.1 Quantitative Model Evaluation Results ........................................................................... 3-1 

3.1.1 Temperature Bias and Error................................................................................. 3-2 

3.1.2 Mixing Ratio Bias and Error................................................................................ 3-3 

3.1.3 Wind Index of Agreement ................................................................................... 3-4 

3.1.4 Spatial Mean Temperature and Mixing Ratio...................................................... 3-5 

3.1.5 Spatial and Temporal Mean Wind Speed Index of Agreement, 

 Wind Speed and Wind Direction ......................................................................... 3-5

3.2 Qualitative Monthly Precipitation Analysis .................................................................... 3-7 

4 UPPER-AIR METEOROLOGICAL ANALYSIS............................................................ 4-1 

5 COMPARISON WITH OTHER MM5 SIMULATIONS................................................ 5-1 

5.1 Comparison to Other 4 Km Simulations.......................................................................... 5-1 

6 REFERENCES..................................................................................................................... 6-1 

TABLES 

Table 2-1. MM5 Vertical Domain Specification................................................................... 2-3 

Table 3-1. Temperature Bias (K) for June and July 2006 MM5 by 

Month and by State and Region in the 36 km Domain........................................ 3-8 

Table 3-2. Temperature Bias (K) for June and July 2006 MM5 by 

Month and by State in the 12 km Domain. .......................................................... 3-9 

Table 3-3. Temperature Bias (K) for June and July 2006 MM5 in the 4 

km Domain........................................................................................................... 3-9 

Table 3-4. Temperature Error (K) for June and July 2006 MM5 by 

Month and by State and Region in the 36 km Domain........................................ 3-9 

Table 3-5. Temperature Error (K) for June and July 2006 MM5 by 

Month and by State in the 12 km Domain. ........................................................ 3-10 

Table 3-6. Temperature Error (K) for June and July 2006 MM5........................................ 3-10 

Table 3-7. Mixing Ratio Bias (g/kg) for June and July 2006 MM5 by 

Month and by State and Region in the 36 km Domain...................................... 3-10 

Table 3-8. Mixing Ratio Bias (g/kg) for June and July 2006 MM5 by 

Month and by State and Region in the 12 km Domain...................................... 3-11 

Table 3-9. Mixing Ratio Bias (g/kg) for June and July 2006.............................................. 3-12 

Table 3-10. Mixing Ratio Error (g/kg) for June and July 2006 MM5 by 

Month and by State and Region in the 36 km Domain...................................... 3-12 
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Table 3-11. Mixing Ratio Error (g/kg) for June and July 2006 MM5 by 

Month and by State and Region in the 12 km Domain...................................... 3-13 

Table 3-12. Mixing Ratio Error (g/kg) for June and July 2006. ........................................... 3-13 

Table 3-13. Wind Index of Agreement for June and July 2006 MM5 by 

Month and by State and Region in the 36 km Domain...................................... 3-13 

Table 3-14. Wind Index of Agreement for June and July 2006 MM5 by 

Month and by State and Region in the 12 km Domain...................................... 3-14 

Table 3-15. Wind Index of Agreement for June and July 2006............................................ 3-14 

Table 5-1. Temperature Bias (K) For June and July 4 km MM5 

Simulations. ......................................................................................................... 5-2 

Table 5-2. Temperature Error (K) for June and July 4 km MM5 

Simulations. ......................................................................................................... 5-2 

Table 5-3. Mixing Ratio Bias (g/kg) for June and July 4 km MM5 

Simulations. ......................................................................................................... 5-2 

Table 5-4. Mixing Ratio Error (g/kg) for June and July 4 km MM5 

Simulations. ......................................................................................................... 5-3 

Table 5-5. Wind Index of Agreement for June and July 4 km MM5 

Simulation............................................................................................................ 5-3 

FIGURES 

Figure 2-1 36/12/4 km MM5 Domain. .................................................................................. 2-4 

Figure 3-1. Regional Planning Organization (RPO) Boundaries. ........................................ 3-15 

Figure 3-2. Spatial Mean Temperature (Deg. C) for June 2006 within 

the 4 km Domain................................................................................................ 3-15 

Figure 3-3. Spatial Mean Temperature (Deg. C) for July 2006 within 

the 4 km Domain................................................................................................ 3-16 

Figure 3-4. Spatial Mean Mixing Ratio (g/kg) for June 2006 within the 

4 km Domain...................................................................................................... 3-16 

Figure 3-5. Spatial Mean Mixing Ratio (g/kg) for July 2006 within the 

4 km Domain...................................................................................................... 3-17 

Figure 3-6. Spatial Mean Index of Agreement for June 2006 within the 

4 km Domain ..................................................................................................... 3-17 

Figure 3-7. Spatial Mean Index of Agreement for July 2006 within the 

4 km Domain...................................................................................................... 3-18 

Figure 3-8. Spatial Mean Wind Direction (deg.) for June 2006 within 

the 4 km Domain................................................................................................ 3-18 

Figure 3-9. Vector Mean Wind Speed (m/s) for June 2006 wthin the 4 

km Domain......................................................................................................... 3-19 

Figure 3-10. Spatial Mean Wind Direction (deg.) for July 2006 within 

the 4 km Domain................................................................................................ 3-19 

Figure 3-11. Vector Mean Wind Speed (m/s) for July 2006 within the 4 

km Domain......................................................................................................... 3-20 

Figure 3-12. CPC Analyzed Precipitation for June 2006 over the 36 km 

Domain............................................................................................................... 3-20 

Figure 3-13. MM5 Estimated Precipitation for June 2006 over the 36 km 

Domain............................................................................................................... 3-21 
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Figure 3-14. CPC Analyzed Precipitation for July 2006 over the 36 km 

Domain............................................................................................................... 3-21 

Figure 3-15. MM5 Estimated Precipitation for July 2006 over the 36 km 

Domain............................................................................................................... 3-22 

Figure 3-16. CPC Analyzed Precipitation for June 2006 over the 12 km 

Domain............................................................................................................... 3-22 

Figure 3-17. MM5 Estimated Precipitation for June 2006 over the 12 km 

Domain............................................................................................................... 3-23 

Figure 3-18. CPC Analyzed Precipitation for July 2006 over the 12 km 

Domain............................................................................................................... 3-23 

Figure 3-19. MM5 Estimated Precipitation for July 2006 over the 12 km 

Domain............................................................................................................... 3-24 

Figure 3-20. CPC Analyzed Precipitation for June 2006 over the 4 km 

Domain............................................................................................................... 3-24 

Figure 3-21. MM5 Estimated Precipitation for June 2006 over the 4 km 

Domain............................................................................................................... 3-25 

Figure 3-22. CPC Analyzed Precipitation for July 2006 over the 4 km 

Domain............................................................................................................... 3-25 

Figure 3-23. MM5 Estimated Precipitation for July 2006 over the 4 km 

Domain............................................................................................................... 3-26 

Figure 4-1. Radiosonde Sounding Comparison at Denver on 0Z 20 July 

2006...................................................................................................................... 4-3 

Figure 4-2. Radiosonde Sounding Comparison at Denver on 12Z 21 

July 2006.............................................................................................................. 4-3 

Figure 4-3. Radiosonde Sounding Comparison at Denver on 0Z 23 July 

2006...................................................................................................................... 4-4 

Figure 4-4. Radiosonde Sounding Comparison at Denver on 12Z 24 

July 2006.............................................................................................................. 4-4 

Figure 4-5. Radiosonde Sounding Comparison at Denver on 0Z 26 July 

2006...................................................................................................................... 4-5 

Figure 4-6. Radiosonde Sounding Comparison at Denver on 12Z 27 

July 2006.............................................................................................................. 4-5 

Figure 4-7. Radiosonde Sounding Comparison at Denver on 0Z 29 July 

2006...................................................................................................................... 4-6 

Figure 4-8. Radiosonde Sounding Comparison at Denver on 12Z 30 

July 2006.............................................................................................................. 4-6 

 
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1 INTRODUCTION 

Over the past decade, emergent requirements for direct numerical simulation of urban and 

regional scale photochemical and secondary aerosol air quality, spawned largely by particulate 

matter (PM2.5), ozone and regional haze regulations, have led to intensified efforts to construct 

high-resolution emissions, meteorological and air quality modeling data bases. The concomitant 

increase in computational throughput of low-cost modern scientific workstations has ushered in a 

new era of regional air quality modeling. It is now possible, for example, to exercise 

sophisticated mesoscale prognostic meteorological models and Eulerian and Lagrangian 

photochemical/aerosol models, simulating ozone, sulfate and nitrate deposition, and secondary 

organic aerosols (SOA) across the entire United States (U.S.) or over discrete subregions for 

extended periods (e.g., calendar year). 

One such model is the Pennsylvania State University/National Center for Atmospheric Research 

(PSU/NCAR) Mesoscale Model (MM5) (Dudhia, 1993; Grell et al., 1994: 

www.mmm.ucar.edu/mm5). MM5 is a limited-area, non-hydrostatic, terrain-following model 

designed to simulate mesoscale atmospheric circulation. The model is supported by several preand post-processing programs which are referred to collectively as the MM5 modeling system. 

This report describes an application and performance evaluation of MM5 for an atmospheric 

simulation of the June and July 2006 modeling period for a modeling domain that covers the 

continental United States at a 36 km grid spacing, the Southwestern United States at 12 km grid 

spacing, and most of the State of Colorado at 4 km grid resolution. The purpose of the MM5 

modeling is to develop meteorological inputs to support photochemical grid modeling for the 

Denver 8-hour ozone State Implementation Plan (SIP) attainment demonstration modeling. 
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2 METHODOLOGY 

The methodology for this approach is very straightforward. The basic methodology was to apply 

the MM5 model for June and July 2006 at the various grid resolutions (36 km, 12 km, and 4 km) 

and to then compare the model results (wind speeds, wind directions, temperatures, etc.) with 

available surface meteorological observations. 

2.1 Model Selection and Application 

Below we give a brief summary of the MM5 input data preparation procedure used for this two 

monthly meteorological modeling exercise. 

Model Selection: The publicly available non-hydrostatic version of MM5 (version 3.7.4) was 

used for this modeling study. Preprocessor programs of the MM5 modeling system including 

TERRAIN, REGRID, LITTLE_R, and INTERPF were used to develop model inputs. 

 

Horizontal Domain Definition: The computational grid is presented in Figure 2-1. The outer 36 

km domain (D01) has 165 x 129 grid cells, selected to maximize the coverage of the ETA 

analysis region. The mid-scale 12 km domain (D02) has 187 x 157 grid cells, selected to 

maximize the coverage of the western region around Colorado. The inner 4 km domain (D03) 

has 151 x 136 grid cells, selected to maximize the coverage of the Denver Metropolitan area as 

well as the mountain regions to the west and high plains areas to the east of Denver. The 

projection was in Lambert Conformal Coordinates (LCC) with the “national RPO” grid 

projection pole of 40o, -97o with true latitudes of 33o and 45o. The datum set was NWS-84. 

 

Vertical Domain Definition: The MM5 modeling was based on 34 vertical layers from the 

surface to 100 mb (approximately 15 km above ground level) with an approximately 38 meter 

deep surface layer. The MM5 vertical domain is presented in both sigma and height coordinates 

in Table 2-1. 

Topographic Inputs: Topographic information for the MM5 was developed using the NCAR and 

the United States Geological Survey (USGS) terrain databases. The grid was based on the 2 min 

(~4 km) Geophysical Data Center global data. Terrain data was interpolated to the model grid 

using a Cressman-type objective analysis scheme. To avoid interpolating elevated terrain over 

water bodies, after the terrain databases were interpolated onto the MM5 grid, the NCAR graphic 

water body database was used to correct elevations over water bodies. 

Vegetation Type and Land Use Inputs: Vegetation type and land use information was developed 

using the most recently released PSU/NCAR databases provided with the MM5 distribution. 

Standard MM5 surface characteristics corresponding to each land use category were employed. 

Atmospheric Data Inputs: The first guess meteorological fields were taken from the NCAR ETA 

archives. Surface and upper-air observations used in the objective analyses, following the 

procedures outlined by Stauffer and Seaman at PSU, were quality-inspected by MM5 preprocessors using automated gross-error checks and "buddy" checks. In addition, rawinsonde 

soundings were subject to vertical consistency checks. The synoptic-scale data used for this 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 2-2

initialization (and in the analysis nudging discussed below) were obtained from the conventional 

National Weather Service (NWS) twice-daily radiosondes and 3-hourly NWS surface 

observations. 

Water Temperature Inputs: The ETA database contains a “skin temperature” field. This can be 

and was used as the water temperature input to these MM5 simulations. Past studies have shown 

that these skin temperatures, used as the water temperature surrogates, can lead to temperature 

errors along coastlines. However, for this analysis which focuses on bulk continental scale 

transport across the central United States, this issue is likely not important and the skin 

temperatures were used. 

FDDA Data Assimilation: This simulation used analysis based nudging. For these simulations 

analysis nudging coefficients of 2.5x10-4 and 1.0x10-4 were used for winds and temperature. 

Physics Options: The MM5 model physics options were employed in this analysis as follows: 

• Kain-Fritsch 2 Cumulus Parameterization on 36/12 km Domain; 

• No Cumulus Parameterization on 4 km Domain; 

• Pleim-Xiu Land Surface Model (LSM) and Asymmetric Convective Mixing (ACM) 

Planetary Boundary Layer (PBL) Schemes; 

• Reisner 2 Mixed Phase Moisture Scheme; and 

• RRTM Atmospheric Radiation Scheme 

Application Methodology: The MM5 model was executed in 5-day blocks initialized at 12 GMT 

every 4 days with a 90 second time step. Model results were output every 60 minutes and output 

files were split at 24 hour intervals. Twelve (12) hours of spin-up was included in each 4-day 

block before the data was used in this atmospheric simulation and subsequent evaluation. The 

model was run with 36 km and 12 km resolution nests with light smoothing feedback and the 4 

km grid as a one-way nest. 

2.2 Evaluation Approach 

The model evaluation approach was based on a combination of qualitative and quantitative 

analyses. The qualitative approach was to compare the model estimated monthly total 

precipitation with the monthly Center for Prediction of Climate (CPC) precipitation analysis 

using graphical outputs. The statistical approach was to examine tabulations of the model bias 

and error for temperature, and mixing ratio and the index of agreement for the wind fields and 

compare these to similar 36 km, 12 km, and 4 km simulations. 

Interpretation of bulk statistics over a continental or regional scale domain is problematic. To 

detect if the model is missing important sub-regional features is difficult. For this analysis the 

statistics were performed on a state by state basis, a Regional Planning Organization (RPO) 

basis, and on a domain-wide for the continental 36 km domain and the regional 12 km domain. 

For the 4 km domain, the statistics were generated for the area covered by the domain which is 

most of Colorado. As with the continental scale and regional scale calculations, the 

interpretation of the statistics may be problematic given the significant differences across the 

State in elevation and microclimates. Nonetheless, these statistics are offered as some measure 

of the quality of the data set generated. 
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The observed database for winds, temperature, and water mixing ratio used in this analysis was 

the NOAA Forecast Systems Lab (FSL) MADIS surface observations. The rain observations are 

taken from the CPC retrospective rainfall archives available at: 

http://www.cpc.ncep.noaa.gov/products/precip/realtime/retro.shtml. 

Table 2-1. MM5 Vertical Domain Specification.

.k(MM5) Sigma Pressure.(mb) Height(m) Depth(m) 

34 0.000 10000 15674 2004 

33 0.050 14500 13670 1585 

32 0.100 19000 12085 1321 

31 0.150 23500 10764 1139 

30 0.200 28000 9625 1004 

29 0.250 32500 8621 900 

28 0.300 37000 7720 817 

27 0.350 41500 6903 750 

26 0.400 46000 6153 693 

25 0.450 50500 5461 645 

24 0.500 55000 4816 604 

23 0.550 59500 4212 568 

22 0.600 64000 3644 536 

21 0.650 68500 3108 508 

20 0.700 73000 2600 388 

19 0.740 76600 2212 282 

18 0.770 79300 1930 274 

17 0.800 82000 1657 178 

16 0.820 83800 1478 175 

15 0.840 85600 1303 172 

14 0.860 87400 1130 169 

13 0.880 89200 961 167 

12 0.900 91000 794 82 

11 0.910 91900 712 82 

10 0.920 92800 631 81 

9 0.930 93700 550 80 

8 0.940 94600 469 80 

7 0.950 95500 389 79 

6 0.960 96400 310 78 

5 0.970 97300 232 78 

4 0.980 98200 154 39 

3 0.985 98650 115 39 

2 0.990 99100 77 38 

1 0.995 99550 38 38 

0 1.000 100000 0 0 
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-2880-2520-2160-1800-1440-1080 -720 -360 0 360 720 1080 1440 1800 2160 2520 2880

-2160

-1800

-1440

-1080

-720

-360

0

360

720

1080

1440

1800

2160

MM5 36 km

MM5 12km

MM5 4km

36 km: 165 x 129 dot points (-2952, -2304) to (2952, 2304)

12 km: 187 x 157 dot points (-1836, -936) to ( 396, 936)

04 km: 151 x 136 dot points ( -984, -324) to ( -384, 216)

Denver MM5 Domain

Figure 2-1. 36/12/4 km MM5 Domain. 
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3 MM5 PERFORMANCE EVALUATION RESULTS 

Both quantitative and qualitative model evaluation results of the MM5 meteorological modeling 

for the overall region at the 36 km, 12 km, and 4 km grid spacing are presented in this section. 

3.1 Quantitative Model Evaluation Results 

Statistical model evaluation results are presented in this section. A nested, muli-month model 

evaluation is very difficult to summarize in a single document. With this in mind, this section 

presents results so potential data users can independently judge the adequacy of the model 

simulation. Overall comparisons are offered herein to judge the model efficacy, but this review 

does not necessarily cover all potential user needs and applications. 

Tables 3-1 through 3-15 present the statistical metrics for each state, for each Regional Planning 

Organization (RPO) area as appropriate, and for the full area as a portion of the United States 

that is covered by each of the 36 km, 12 km, and 4 km modeling domains (called “ALL” in each 

table). For reference, a graphic of RPO boundaries is presented in Figure 3-1 and the individual 

boundaries of the domains are presented in Figure 2-1. In these comparisons the vertical level 1 

(~19 m) model estimates are compared directly with the nominal ~2 m temperature and moisture 

and ~10 m wind measurements. 

To evaluate the performance of the MM5 2006 36 km, 12 km, and 4 km simulations for the U.S., 

for the western U.S., and for Colorado, respectively, a number of performance benchmarks for 

comparison were used. Emery and co-workers (2001), have derived and proposed a set of daily 

performance “benchmarks” for typical meteorological model performance. These standards 

were based upon the evaluation of about 30 MM5 and RAMS meteorological simulations in 

support of air quality applications performed over several years and reported by Tesche et al. 

(2001). The purpose of these benchmarks was not to give a passing or failing grade to any one 

particular meteorological model application, but rather to put its results into the proper context of 

other models and meteorological data sets. The key to the benchmarks is to understand how 

good or poor the results are relative to other model applications run for the U.S. Thus, this 

section compares the calculated statistical measures against these benchmarks to assess the MM5 

performance in terms of its viability for use in modeling and meteorological assessments and 

Section 4 presents a comparison to other similar model applications. These benchmarks include 

bias and error in temperature and mixing ratio as well as the Wind Speed Index of Agreement 

(IA) between the models and data bases. The benchmark for acceptability for each variable is: 

• Temperature bias: <±0.5 K 

• Temperature error: <2.0 K 

• Mixing ratio bias: <±1.0 g/kg 

• Mixing ratio error: <2.0 g/kg 

• Wind Speed Index of Agreement (IA): 0 = worst, 1 = best, 0.6 = acceptable 
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3.1.1 Temperature Bias and Error 

Temperature bias statistics are presented in Tables 3-1 through 3-3 for the 36 km, 12 km, and 4 

km modeling domains. Each is evaluated in turn. 

Temperature bias statistics are presented in Table 3-1 for the 36 km modeling domain. As can be 

seen in Table 3-1, when the temperatures are averaged over the June-July 2006 period for the 

entire modeling domain (ALL), the model has a bias of -0.12 K, thus underestimating on average 

temperature across the U.S. In reviewing these results on a state-by-state and region-by-region 

basis, the most obvious trend is that the western states and a handful of Eastern Coastal states 

(Florida, New York, Virginia, and Rhode Island) are underestimated by a few tenths of a degree 

Kelvin (guideline within the +/-0.5 K benchmark) up to a bias of -2.13 K in California with 

several western states being just outside of the guideline range (Arizona, Colorado, Nevada, New 

Mexico, Wyoming, Montana, and Oregon ranging from -0.59 to -1.42 K). All other states and 

regional RPOs have temperature bias on the positive side generally within the guideline 

benchmark. Differences between June and July 2006 temperature bias is generally insignificant 

indicating that the above observations on the June-July 2006 averages hold for each individual 

month’s performance review as well. 

Temperature bias statistics are presented in Table 3-2 for the 12 km domain. As can be seen in 

Table 3-2, when the temperatures are averaged over the June-July 2006 period for the entire 12 

km modeling domain (ALL), the model has a slight negative bias of -0.01 K for the 12 km 

domain, which is an improvement over the 36 km results. As with the 36 km Western U.S. 

temperature bias, most of the states within the 12 km domain have bias that is slightly negative 

and within the guideline benchmark bias, except for Nevada (with -0.73 K). Little difference 

was discerned between the June and July 2006 bias for each state reported in the 12 km domain 

in Table 3-2 except for Utah with a positive bias in June (0.40 K) and a negative bias in July (-

0.09 K), both of which were within guidelines. 

Temperature bias statistics are presented in Table 3-3 for the 4 km domain. As can be seen in 

Table 3-3, when the temperature biases are averaged over the June-July 2006 period for the 

entire 4 km Colorado modeling domain (Mean), the model has a bias of -0.20 K. The model has 

a negative temperature bias in June 2006 and a positive temperature bias in July 2006 over the 4 

km domain. Both months were within the guideline range of the temperature bias threshold of 

<±0.5 K for the 4 km domain. 

Temperature error data are presented in Table 3-4 for the 36 km modeling domain. The overall 

temperature error (ALL category) over all states and for the June-July 2006 period is 1.53 K on 

the 36 km domain. All mean annual temperature errors over each state and region were in the 

range from the lowest value of 0.84 K in Delaware to the highest error of 3.05 K in Nevada. Far 

Western states in the vicinity of Colorado were all generally greater than the benchmark of 2.0 K 

including Arizona, Colorado, Nevada, Wyoming, Idaho, California, Oregon, and Utah with 

exception of New Mexico, Montana, and Washington. The average of the WRAP RPO states 

was 2.30 K. All other states and RPOs for this June-July 2006 period had temperature errors less 

than the benchmark over the 36 km domain. Most individual monthly temperature errors 

mimicked the Mean results (guideline performance) except for the Montana July 2006 

temperature error which was 2.13 K. 
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Temperature error data are presented in Table 3-5 for the 12 km grid spaced western area 

modeling domain. The overall temperature error over the June-July 2006 period (Mean) for the 

12 km domain (ALL category) was 1.42 K which is a slight improvement over the 36 km domain 

results. On a state by state basis for those in this western 12 km domain, all states improved in 

terms of their temperature error (had errors less than the 36 km domain) although two states, 

namely, Colorado and Nevada (2.06 and 2.05 K, respectively) were slightly just above the 

guideline benchmark. 

Temperature error data are presented in Table 3-6 for the 4 km modeling domain. The overall 

June-July 2006 temperature error (Mean) is 1.78 K. Both months were within the guideline 

benchmark for the 4 km domain. 

3.1.2 Mixing Ratio Bias and Error 

Mixing ratio bias data are presented in Table 3-7 for the 36 km modeling domain. Averaged 

over the June-July 2006 period, over all states, the model has a bias of 0.10 g/kg for the 36 km 

domain as shown by the “ALL” category in Table 3-7. The MM5 model results were well within 

the guideline range of the mixing ratio threshold of ±1.0 g/kg for all states and RPOs. The range 

of underprediction bias was from a low of -0.71 g/kg in Idaho to -0.1 g/kg in California and the 

range of overprediction bias was from a low of 0.00 g/kg in Tennessee to 0.68 g/kg in New 

Mexico. Regional tendencies that were evident over the 36 km domain was that most 

Midwestern states around or adjacent to the Ohio River Valley all had negative mixing ratio bias 

and extreme Southwestern states had the highest positive mixing ratio bias. Little June to July 

variations in the mixing ratio bias were evident across most states although a few states had 

higher changes in bias (e.g., Arizona from 1.06 in June to 0.26 g/kg in July and New Mexico 

from 1.32 in June to 0.04 g/kg in July0 and others had swings from positive to negative mixing 

ratio bias (e.g., Colorado from 0.39 in June to -0.94 g/kg in July and Montana from -0.42 in June 

to 0.45 g/kg in July). Only two states, namely, Arizona and New Mexico, had June values (1.06 

and 1.32, respectively) greater than the benchmark of ±1.0 g/kg. 

Mixing ratio bias data are presented in Table 3-8 for the 12 km modeling domain. As can be 

seen in Table 3-8, when the mixing ratio biases are averaged over the June-July 2006 period for 

the entire 12 km modeling domain (ALL), the model has a slight positive bias of 0.09 g/kg for 

the 12 km domain, which is about the same as for the 36 km domain results. For these 

southwestern states the mixing ratio biases were all well within the guideline range of the 

benchmark of ±1.0 g/kg with slight improvement in bias in some states and slight degradation of 

bias in other states. 

Mixing ratio bias data are presented in Table 3-9 for the 4 km modeling domain. The overall 

June-July 2006 mixing ratio bias (Mean) is 0.18 g/kg averaged over 4 km domain. As with the 

36 km and 12 km results for Colorado, the mixing ratio changed from a June positive bias of 

0.86 g/kg to a July negative bias of -0.45 g/kg. All mixing ratio bias was well within the 

acceptability benchmark of ±1.0 g/kg. 

Mixing ratio error results are presented in Table 3-10 for the 36 km domain. The mean error for 

the June-July 2006 data set was 1.33 g/kg for the whole 36 km domain (ALL). The range of 

Mean errors was from a low of 0.94 g/kg in Maine to a high of 1.83 g/kg in New Mexico. The 

model shows a mean error throughout the year in each state and RPO that is within the guideline 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-4

benchmark value of 2.0 g/kg. A comparison of the values of mean error for each state and RPO 

over both June and July show little difference. 

Mixing ratio error results are presented in Table 3-11 for the 12 km domain. The mean error for 

the June-July 2006 data set for the 12 km domain was 1.51 g/kg. The 12 km grid domain 

modeling shows mean mixing ratio errors that are generally within the guideline value of 2.0 

g/kg. For New Mexico, the June 12 km value was 2.13 g/kg. The monthly values of mean error 

are highest for July 2006 MM5 results except for New Mexico. 

Mixing ratio error results are presented in Table 3-12 for the 4 km domain. The mean mixing 

ratio error is 1.64 g/kg for the 4 km modeling domain. The mixing ratio errors for June and July 

2006 were similar and were 1.60 to 1.68 g/kg, respectively. These errors while appearing to 

degrade from the 36 km to the 12 km to the 4 km domains actually were about the same when 

considering the performance in Colorado ranging from 1.59 to 1.70 to 1.68 over the various 

domains of the MM5 model degraded somewhat over the from the 36 km The model shows that 

all mixing ratio error values were within the acceptability benchmark of 2.0 g/kg. 

3.1.3 Wind Index of Agreement 

Comparisons between the June-July 2006 36 km, 12 km, and 4 km domain MM5 modeling of 

winds and those of the NOAA Forecast Systems Lab (FSL) MADIS surface observations were 

made using the Wind Index of Agreement (IA). Recall that the benckmark is a Wind Speed 

Index of Agreement equal to 0.6. Values below that benckmark are generally poor agreement 

and values above that benchmark are better with an IA of 1.0 being the best. Note also that the 

Index of Agreement metric is sensitive to the number of monitors being used in the calculation, 

with more monitors tending to give higher Index of Agreement scores. 

The Wind IAs for the 36 km domain are presented in Table 3-13. The domain-wide June-July 

2006 averaged Wind IA is 0.89 for the 36 km domain. No significant monthly differences were 

noted between June and July in any one state or RPO. For all states and RPOs except New 

Hampshire (0.44), Vermont (0.56), Connecticut (0.56), and Delaware (0.51), the Wind IA fell in 

the guideline (0.6) to best (1.0) range of comparison. For the Western states the Wind IA ranged 

from 0.75 to 0.81 for each state and the WRAP RPO was 0.88. 

The Wind IAs for the 12 km modeling domain are presented in Table 3-14. The June-July 2006 

average Wind IA is 0.88 for the 12 km domain. For all states and months in the 12 km domain, 

the Wind IA fell in the guideline (0.6) to best (1.0) range of comparison. Specifically for the 12 

km states the Wind IA ranged from 0.75 to 0.81 showing very good wind agreement for each 

state. 

The Wind IAs for the 4 km modeling domain are presented in Table 3-15. The June-July 2006 

average Wind IA is 0.83 for the 4 km domain. The wind IA for each month was about the same 

at 0.83 and 0.84, respectively. 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-5

3.1.4 Spatial Mean Temperature and Mixing Ratio 

This section presents spatial mean time series plots on a monthly basis for both temperature and 

mixing ratio for the 4 km modeling domain. The “observed” (shown by a “*” in the figures) 

spatial mean temperature or mixing ratio was computed for each hour by averaging all valid 

observed station data within the modeling domain (30-40 stations). The “model” estimated 

spatial mean (solid red line in the figures) was computed for each hour by averaging the model 

estimates at all station locations that reported valid data for that hour. These 4 km domain-wide 

hourly averages for observed and modeled temperature and mixing ratio data were then plotted 

versus time to demonstrate the comparison of the two sets of data and allow a qualitative 

evaluation of the MM5 data. These straightforward plots were useful for discerning overall 

trends in model performance and provide a convenient tool to quickly identify if the MM5 

Model is tending to over or underestimate modeled fields. 

Figures 3-2 and 3-3 present the spatial mean temperatures by month within the 4 km modeling 

domain. Review of these two June and July 2006 mean spatial temperature profiles indicates 

that the MM5-generated temperature fields capture the synoptic and diurnal trends of 

temperature across the domain quite well. This is shown by noting the general agreement in the 

patterns of temperature for the modeled and observed values as a function of time. Also shown 

in these patterns is the general good agreement of the MM5 model in following the diurnal 

pattern of the temperatures. The greatest differences in temperatures are noted where the MM5 

data underpredict the high peak temperatures and overpredict the low peak temperatures. The 

model versus observed temperatures are generally within a few degrees of the observed values. 

Figures 3-4 through 3-5 present the spatial mean mixing ratios over the 4 km modeling domain. 

Review of the mean spatial mixing ratio profiles for June and July 2006 indicate the MM5-

generated mixing ratio fields capture the synoptic trends as well as the diurnal patterns across the 

domain quite well. This is shown in the figures by noting the general agreement in the patterns 

of mixing ratio as a function of time over each month. Although this general trend was estimated 

well by the MM5 data, some underestimation and overestimation was noted in some periods of 

time. More overestimates were made by the model in June (Figure 3-4) when mixing ratios were 

lower (of the two months) and more underestimates in July 2006 (Figure 3-5) when the mixing 

ratios were higher. 

3.1.5 Spatial and Temporal Mean Wind Speed Index of Agreement, Wind Speed and 

Wind Direction 

This section presents spatial mean time series plots on a monthly basis for the Wind Speed Index 

of Agreement (IA), wind speed, and wind direction. The model estimated spatial wind speed IA 

was computed for each hour by averaging the model estimates at all station locations that 

reported valid data for that hour and comparing those to observed data. The IA provides a 

measure of the quantitative comparability. The mean wind speeds were computed using the 

calculated vector averaged hourly domain-wide observed and modeled data. The “observed” 

spatial vector averaged wind speed was computed for each hour by averaging all valid observed 

station wind speed data within the modeling domain (30-40 stations). The “model” estimated 

spatial wind speed was computed for each hour by averaging the model estimates at all station 

locations that reported valid data for that hour. The mean wind direction was calculated from the 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-6

hourly domain-wide averaged observed versus modeled data similar to the wind speeds. These 

domain-wide hourly averages of wind speed IA, vector wind speed, and mean wind direction for 

observed and modeled data were then plotted versus time to demonstrate the comparison of the 

two sets of data. This allowed a qualitative evaluation of the MM5 data performance as 

compared to the average observed data. These straightforward plots were useful for discerning 

overall trends in model performance and provide a convenient tool to quickly identify if the 

MM5 Model is tending to over or underestimate modeled fields. 

Figures 3-6 and 3-7 provide the spatial mean of the Wind Speed Index of Agreement as a 

function of time over the 4 km domain for June and July 2006 simulations. In both plots the IA 

is generally greater than the minimum guideline benchmark of 0.6 with a few exceptions in midJune and mid to late July. The diurnal pattern indicates that MM5 performs best during the 

daylight hours where the IA is highest and poorest in the nighttime hours when wind speeds are 

lower. 

 

Figure 3-8 provides the spatial mean profiles of the wind directions for modeled and observed 

data as a function of time over the 4 km domain for the June 2006 simulations. Review of the 

June wind direction plots indicate the spatially averaged MM5 generated wind direction fields 

capture the synoptic trends of wind direction across the domain quite well. This is shown by 

noting the general agreement in the patterns of wind direction between the observed and modeled 

data as a function of time. Also shown in these patterns is the general good agreement of the 

MM5 model in following the diurnal pattern of wind direction for each day. The agreement 

between the observations and modeled wind directions were best when winds were persistent, 

e.g., June 13-15 where modeled and observed values were within about 5-10o

 of each other. On 

days when diurnal variations were significant the MM5 wind direction averages tend to miss 

some of the daily wind shifts by 50-90o

 but still follow the general pattern of change over several 

days to weeks. 

Figure 3-9 provides the spatial mean profiles of the wind speeds for modeled and observed data 

as a function of time over the 4 km domain for the June 2006 simulations. Review of the June 

wind speed plots indicate the spatially averaged MM5 generated wind speeds fields capture the 

synoptic trends of wind direction across the domain quite well. This is shown by noting the 

general agreement in the patterns of wind speed between the observed and modeled data as a 

function of time. Also shown in these patterns is the general good agreement of the MM5 model 

in following the diurnal pattern of wind speed for each day. Where wind speeds are lowest the 

model tends to overpredict the speeds compared to observed values. The MM5 model did 

particularly well in calculating the high values on June 15. 

Figures 3-10 and 3-11 provide the spatial mean profiles of the wind directions and wind speeds 

for modeled and observed data as a function of time over the 4 km domain for the July 2006 

simulations. Review of the July wind direction and wind speed plots indicate the spatially 

averaged MM5 generated wind direction fields capture the synoptic and diurnal trends across the 

domain quite well. Other comparisons are similar to those for June noted above. 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-7

3.2 Qualitative Monthly Precipitation Analysis 

This section presents qualitative comparisons of MM5 estimated precipitation with the CPC 

retrospective analysis data. When comparing the CPC and MM5-generated precipitation data, 

note should be taken that the CPC analysis covers only the Continental U.S. and does not extend 

offshore or into Canada or Mexico. The MM5 fields, on the other hand, cover the entire 36 km 

domain. Also note that the CPC analysis is based on a 0.25 x 0.25 degree (~40 x 40 km) grid 

and the MM5 is based on a comparable grid of 36 x 36 km and much finer grids of 12 x 12 km, 

and 4 x 4 km. Neither the 40km or 36 km grid spacing capture small precipitation features 

effectively, while both the 12 km and 4 km grid spacing will capture and display such features. 

Total precipitation comparisons for June and July 2006 over the 36 km domain are presented in 

Figures 3-12 through 3-15. For each month, the first plot presents the CPC analysis data (e.g., 

Figure 3-12) and the second plot represents the MM5 total precipitation (e.g., Figure 3-13). 

Given that the CPC analysis data are considered to be the standard for precipitation, MM5 

provides a reasonable representation of the spatial distribution of precipitation over the 

contiguous U.S. for June and July of 2006. The poorest agreement is in the southwest U.S. for 

both months where the MM5 precipitation estimates are much greater across Nevada, Colorado, 

Utah, Wyoming, Arizona, and New Mexico. In June MM5 precipitation is heavier along the 

south east coast than CPC and in Montana and New Mexico. The July MM5 pattern is similar to 

CPC but the MM5 results are much higher in the Southeast U.S. and in the terrain induced high 

intensity precipitation over New Mexico. The MM5 model treats more specifically the terrain 

which leads to the potential differences in the MM5 results in the Rockies in the summertime. 

Total precipitation comparisons for June and July 2006 over the 12 km domain are presented in 

Figures 3-16 through 3-19. As with the 36 km simulations, the MM5 data provide a more 

refined treatment of terrain-induced precipitation and therefore in the mountainous Southwest 

U.S. more widespread precipitation is calculated. In both the June and July 2006 periods the 

MM5 results are higher in magnitude and spatial extent of the precipitation. The refinement of 

the 12 km grid size is obvious when comparing the CPC precipitation to that of the MM5 

simulations as the MM5 graphics appear to have much finer detail. 

Total precipitation comparisons for June and July 2006 over the 4 km domain are presented in 

Figures 3-20 through 3-21. Within the spatial limitations of the CPC analysis data, MM5 does a 

reasonably good job representing the general spatial coverage of the precipitation shown in the 

CPC data. The MM5 plots show much more precipitation over the central Colorado Rockies in 

both months than CPC data. Much higher and widespread precipitation was estimated by MM5 

in June. The July simulations did well in finding the rainshadow over central Colorado along the 

western edge of the front range but gave much higher precipitation over western Colorado. 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-8

Table 3-1. Temperature Bias (K) for June and July 2006 MM5 by Month and by State and 

Region in the 36 km Domain. 

Region June '06 July '06 Mean 

AL 0.25 -0.04 0.11

ALL -0.08 -0.15 -0.12

AR 0.42 0.18 0.30

AZ -0.67 -0.72 -0.70

CA -2.02 -2.25 -2.13

CENRAP 0.19 0.04 0.11

CO -1.17 -0.82 -1.00

CT 0.17 0.25 0.21

DE 0.17 0.28 0.22

FL -0.19 -0.05 -0.12

GA 0.21 0.01 0.11

IA 0.48 0.44 0.46

ID -0.37 -0.05 -0.21

IL 0.57 0.48 0.52

IN 0.49 0.42 0.45

KS 0.10 0.07 0.09

KY 0.48 0.31 0.39

LA 0.37 0.38 0.38

MA 0.02 0.11 0.06

MANE_VU 0.03 0.10 0.06

MD 0.00 0.01 0.00

ME 0.06 0.06 0.06

MI 0.17 0.19 0.18

MN 0.32 0.12 0.22

MO 0.22 0.06 0.14

MS 0.46 0.21 0.34

MT -0.54 -0.64 -0.59

MW 0.48 0.40 0.44

NC 0.31 0.08 0.19

ND 0.37 0.51 0.44

NE 0.09 0.10 0.09

NH 0.46 0.66 0.56

NJ 0.00 0.16 0.08

NM -0.72 -0.56 -0.64

NV -0.95 -1.11 -1.03

NY -0.25 -0.24 -0.25

OH 0.43 0.35 0.39

OK 0.34 0.03 0.19

OR -1.13 -1.03 -1.08

PA 0.16 0.23 0.19

RI -0.03 -0.12 -0.07

SC 0.29 0.19 0.24

SD 0.22 0.20 0.21

TN 0.48 0.36 0.42

TX -0.11 -0.32 -0.22

UT -0.17 -0.79 -0.48

VA -0.11 -0.05 -0.08

VISTAS 0.16 0.07 0.11

VT 0.01 0.03 0.02

WA -0.52 -0.40 -0.46

WI 0.82 0.62 0.72

WRAP -1.02 -1.02 -1.02

WV 0.33 0.36 0.35

WY -1.47 -1.38 -1.42
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-9

Table 3-2. Temperature Bias (K) for June and July 2006 MM5 by Month and by State in the 12 

km Domain.

Region June '06 July '06 Mean 

ALL 0.02 -0.04 -0.01

AZ -0.41 -0.43 -0.42

CO -0.60 -0.20 -0.40

ID 0.13 0.31 0.22

NM -0.47 -0.27 -0.37

NV -0.67 -0.78 -0.73

UT 0.40 -0.09 0.16

WY -0.52 -0.43 -0.47

Table 3-3. Temperature Bias (K) for June and July 2006 MM5 in the 4 km Domain. 

Region June '06 July '06 Mean 

ALL -0.42 0.01 -0.20

Table 3-4. Temperature Error (K) for June and July 2006 MM5 by Month and by State and 

Region in the 36 km Domain. 

Region June '06 July '06 Mean 

AL 1.49 1.51 1.50

ALL 1.53 1.54 1.53

AR 1.21 1.30 1.25

AZ 2.11 2.14 2.13

CA 2.94 3.16 3.05

CENRAP 1.29 1.27 1.28

CO 2.79 2.54 2.66

CT 1.19 1.20 1.20

DE 0.85 0.83 0.84

FL 1.55 1.42 1.48

GA 1.35 1.34 1.35

IA 1.26 1.19 1.23

ID 1.90 2.39 2.14

IL 1.20 1.19 1.20

IN 1.12 0.99 1.06

KS 1.20 1.14 1.17

KY 1.09 0.99 1.04

LA 1.65 1.45 1.55

MA 1.19 1.12 1.15

MANE_VU 1.22 1.23 1.23

MD 1.28 1.30 1.29

ME 1.07 1.12 1.10

MI 1.50 1.41 1.45

MN 1.35 1.40 1.38

MO 1.14 1.12 1.13

MS 1.31 1.21 1.26

MT 1.72 2.13 1.93

MW 1.34 1.30 1.32

NC 1.30 1.23 1.26

ND 1.21 1.39 1.30

NE 1.30 1.29 1.29

NH 1.74 1.92 1.83

NJ 1.14 1.14 1.14

NM 1.93 1.73 1.83

NV 2.32 2.55 2.43

NY 1.28 1.27 1.27
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-10

Region June '06 July '06 Mean 

OH 1.17 1.14 1.15

OK 1.27 1.30 1.28

OR 1.96 2.19 2.08

PA 1.12 1.08 1.10

RI 1.20 1.28 1.24

SC 1.11 1.04 1.08

SD 1.47 1.54 1.50

TN 1.25 1.30 1.27

TX 1.23 1.18 1.20

UT 2.22 2.43 2.33

VA 1.31 1.23 1.27

VISTAS 1.35 1.29 1.32

VT 1.31 1.36 1.34

WA 1.60 1.81 1.70

WI 1.45 1.49 1.47

WRAP 2.23 2.37 2.30

WV 1.35 1.28 1.32

WY 2.38 2.55 2.47

Table 3-5. Temperature Error (K) for June and July 2006 MM5 by Month and by State in the 12 

km Domain.

Region June '06 July '06 Mean 

ALL 1.41 1.43 1.42

AZ 1.65 1.57 1.61

CO 2.19 1.92 2.06

ID 1.54 2.00 1.77

NM 1.69 1.48 1.59

NV 1.95 2.14 2.05

UT 1.86 1.93 1.89

WY 1.76 1.92 1.84

Table 3-6. Temperature Error (K) for June and July 2006 MM5. 

Region June '06 July '06 Mean 

ALL 1.93 1.64 1.78

Table 3-7. Mixing Ratio Bias (g/kg) for June and July 2006 MM5 by Month and by State and 

Region in the 36 km Domain.

Region June '06 July '06 Mean 

AL 0.54 0.64 0.59

ALL 0.15 0.05 0.10

AR -0.23 0.04 -0.09

AZ 1.06 0.26 0.66

CA -0.01 -0.02 -0.01

CENRAP 0.07 0.18 0.13

CO 0.39 -0.94 -0.28

CT 0.23 -0.18 0.02

DE 0.13 -0.36 -0.12

FL 0.70 0.17 0.44

GA 0.38 0.25 0.31

IA -0.31 -0.38 -0.34

ID -0.76 -0.66 -0.71

IL -0.24 -0.31 -0.28

IN -0.40 -0.39 -0.39
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-11

Region June '06 July '06 Mean 

KS 0.24 0.25 0.25

KY 0.14 -0.42 -0.14

LA 0.63 0.57 0.60

MA 0.35 0.14 0.25

MANE_VU 0.38 0.02 0.20

MD 0.39 -0.13 0.13

ME 0.37 0.01 0.19

MI -0.12 0.00 -0.06

MN -0.36 0.01 -0.18

MO -0.04 0.00 -0.02

MS 0.40 0.50 0.45

MT -0.42 0.45 0.02

MW -0.17 -0.11 -0.14

NC 0.50 0.04 0.27

ND -0.05 0.40 0.17

NE 0.34 0.17 0.25

NH 0.44 0.03 0.23

NJ 0.41 -0.02 0.19

NM 1.32 0.04 0.68

NV 0.20 0.03 0.12

NY 0.33 0.06 0.20

OH -0.05 -0.11 -0.08

OK -0.40 0.03 -0.19

OR -0.22 0.24 0.01

PA 0.52 0.07 0.29

RI 0.13 -0.01 0.06

SC 0.55 0.09 0.32

SD 0.47 0.61 0.54

TN 0.13 -0.13 0.00

TX 0.57 0.54 0.56

UT -0.38 -0.18 -0.28

VA 0.10 -0.51 -0.20

VISTAS 0.43 0.05 0.24

VT 0.41 -0.10 0.16

WA -0.34 0.09 -0.13

WI -0.16 0.08 -0.04

WRAP 0.10 -0.01 0.05

WV 0.48 -0.16 0.16

WY -0.13 0.18 0.03

Table 3-8. Mixing Ratio Bias (g/kg) for June and July 2006 MM5 by Month and by State and 

Region in the 12 km Domain.

Region June '06 July '06 Mean 

ALL 0.11 0.06 0.09

AZ 1.01 0.15 0.58

CO 0.53 -0.93 -0.20

ID -0.54 -0.43 -0.49

NM 1.37 0.02 0.69

NV 0.18 0.00 0.09

UT -0.36 -0.27 -0.31

WY 0.01 0.31 0.16
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-12

Table 3-9. Mixing Ratio Bias (g/kg) for June and July 2006.

Region June '06 July '06 Mean 

ALL 0.81 -0.45 0.18

Table 3-10. Mixing Ratio Error (g/kg) for June and July 2006 MM5 by Month and by State and 

Region in the 36 km Domain. 

Region June '06 July '06 Mean 

AL 1.52 1.55 1.53

ALL 1.25 1.41 1.33

AR 1.28 1.62 1.45

AZ 1.54 1.74 1.64

CA 1.09 1.34 1.22

CENRAP 1.37 1.50 1.43

CO 1.40 1.77 1.59

CT 0.91 1.24 1.08

DE 0.97 1.47 1.22

FL 1.52 1.36 1.44

GA 1.65 1.77 1.71

IA 1.31 1.61 1.46

ID 1.31 1.49 1.40

IL 1.20 1.50 1.35

IN 1.28 1.34 1.31

KS 1.36 1.46 1.41

KY 1.25 1.44 1.35

LA 1.59 1.50 1.55

MA 0.85 1.10 0.98

MANE_VU 0.95 1.20 1.08

MD 1.01 1.39 1.20

ME 0.90 0.99 0.94

MI 0.96 1.13 1.04

MN 1.16 1.38 1.27

MO 1.16 1.29 1.22

MS 1.56 1.58 1.57

MT 1.12 1.30 1.21

MW 1.08 1.29 1.18

NC 1.36 1.53 1.44

ND 1.12 1.38 1.25

NE 1.35 1.35 1.35

NH 0.94 1.08 1.01

NJ 1.08 1.44 1.26

NM 1.99 1.66 1.83

NV 1.01 1.42 1.21

NY 0.90 1.13 1.01

OH 1.08 1.22 1.15

OK 1.49 1.62 1.56

OR 0.93 1.13 1.03

PA 1.04 1.30 1.17

RI 0.93 1.22 1.08

SC 1.40 1.37 1.38

SD 1.18 1.36 1.27

TN 1.26 1.36 1.31

TX 1.53 1.58 1.56

UT 1.31 1.55 1.43

VA 1.18 1.66 1.42

VISTAS 1.40 1.51 1.45

VT 0.96 1.07 1.01
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-13

Region June '06 July '06 Mean 

WA 0.90 1.03 0.96

WI 1.02 1.28 1.15

WRAP 1.21 1.40 1.31

WV 1.08 1.20 1.14

WY 1.20 1.27 1.24

Table 3-11. Mixing Ratio Error (g/kg) for June and July 2006 MM5 by Month and by State and 

Region in the 12 km Domain.

Region June '06 July '06 Mean 

ALL 1.42 1.61 1.51

AZ 1.59 1.90 1.75

CO 1.55 1.85 1.70

ID 1.29 1.51 1.40

NM 2.13 1.85 1.99

NV 1.06 1.60 1.33

UT 1.40 1.73 1.57

WY 1.30 1.41 1.36

Table 3-12. Mixing Ratio Error (g/kg) for June and July 2006.

Region June '06 July '06 Mean 

ALL 1.60 1.68 1.64

Table 3-13. Wind Index of Agreement for June and July 2006 MM5 by Month and by State and 

Region in the 36 km Domain.

Region June '06 July '06 Mean 

AL 0.72 0.73 0.73

ALL 0.90 0.88 0.89

AR 0.70 0.70 0.70

AZ 0.75 0.75 0.75

CA 0.80 0.78 0.79

CENRAP 0.87 0.87 0.87

CO 0.80 0.80 0.80

CT 0.56 0.57 0.56

DE 0.50 0.52 0.51

FL 0.79 0.79 0.79

GA 0.68 0.69 0.69

IA 0.74 0.71 0.73

ID 0.79 0.78 0.78

IL 0.72 0.74 0.73

IN 0.65 0.68 0.66

KS 0.78 0.76 0.77

KY 0.65 0.62 0.63

LA 0.67 0.68 0.68

MA 0.71 0.69 0.70

MANE_VU 0.76 0.74 0.75

MD 0.67 0.63 0.65

ME 0.66 0.63 0.64

MI 0.69 0.70 0.69

MN 0.79 0.81 0.80

MO 0.75 0.73 0.74

MS 0.69 0.71 0.70

MT 0.81 0.81 0.81

MW 0.77 0.78 0.77
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-14

Region June '06 July '06 Mean 

NC 0.69 0.66 0.68

ND 0.78 0.81 0.79

NE 0.81 0.81 0.81

NH 0.46 0.43 0.44

NJ 0.64 0.61 0.63

NM 0.79 0.79 0.79

NV 0.80 0.75 0.77

NY 0.76 0.76 0.76

OH 0.69 0.69 0.69

OK 0.75 0.71 0.73

OR 0.76 0.78 0.77

PA 0.69 0.68 0.69

RI 0.77 0.75 0.76

SC 0.72 0.72 0.72

SD 0.82 0.83 0.82

TN 0.66 0.64 0.65

TX 0.82 0.79 0.81

UT 0.78 0.74 0.76

VA 0.71 0.68 0.69

VISTAS 0.82 0.81 0.81

VT 0.56 0.55 0.56

WA 0.81 0.83 0.82

WI 0.67 0.67 0.67

WRAP 0.88 0.88 0.88

WV 0.61 0.58 0.60

WY 0.80 0.81 0.81

Table 3-14. Wind Index of Agreement for June and July 2006 MM5 by Month and by State and 

Region in the 12 km Domain.

Region June '06 July '06 Mean 

ALL 0.89 0.88 0.88

AZ 0.75 0.76 0.75

CO 0.81 0.82 0.81

ID 0.80 0.78 0.79

NM 0.78 0.80 0.79

NV 0.77 0.74 0.75

UT 0.75 0.74 0.75

WY 0.80 0.81 0.81

Table 3-15. Wind Index of Agreement for June and July 2006. 

Region June '06 July '06 Mean 

ALL 0.83 0.84 0.83
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-15

Figure 3-1. Regional Planning Organization (RPO) Boundaries. 

Figure 3-2: Spatial Mean Temperature (Deg. C) for June 2006 within the 4 km Domain. 
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-16

Figure 3-3. Spatial Mean Temperature (Deg. C) for July 2006 within the 4 km Domain. 

Figure 3-4. Spatial Mean Mixing Ratio (g/kg) for June 2006 within the 4 km Domain.
F:\Denver_O3_2008\Reports\Preliminary_MM5\draft#1\MM5_Eval_DENSIP_Feb25_2008.doc 3-17

.

Figure 3-5. Spatial Mean Mixing Ratio (g/kg) for July 2006 within the 4 km Domain.

Figure 3-6. Spatial Mean Index of Agreement for June 2006 within the 4 km Domain. 
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.

Figure 3-7. Spatial Mean Index of Agreement for July 2006 within the 4 km Domain 

Figure 3-8. Spatial Mean Wind Direction (deg.) for June 2006 within the 4 km Domain. 
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Figure 3-9. Vector Mean Wind Speed (m/s) for June 2006 within the 4 km Domain.

Figure 3-10. Spatial Mean Wind Direction (deg.) for July 2006 within the 4 km Domain. 
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Figure 3-11. Vector Mean Wind Speed (m/s) for July 2006 within the 4 km Domain. 

Figure 3-12. CPC Analyzed Precipitation for June 2006 over the 36 km Domain.
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Figure 3-13. MM5 Estimated Precipitation for June 2006 over the 36 km Domain. 

Figure 3-14. CPC Analyzed Precipitation for July 2006 over the 36 km Domain. 
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Figure 3-15. MM5 Estimated Precipitation for July 2006 over the 36 km Domain. 

Figure 3-16. CPC Analyzed Precipitation for June 2006 over the 12 km Domain. 
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Figure 3-17. MM5 Estimated Precipitation for June 2006 over the 12 km Domain. 

Figure 3-18. CPC Analyzed Precipitation for July 2006 over the 12 km Domain. 
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Figure 3-19. MM5 Estimated Precipitation for July 2006 over the 12 km Domain.

Figure 3-20. CPC Analyzed Precipitation for June 2006 over the 4 km Domain. 
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Figure 3-21. MM5 Estimated Precipitation for June 2006 over the 4 km Domain. 

Figure 3-22. CPC Analyzed Precipitation for July 2006 over the 4 km Domain.
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Figure 3-23. MM5 Estimated Precipitation for July 2006 over the 4 km Domain. 
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4 Upper-Air Meteorological Analysis 

To compare the performance of the model aloft, radiosonde comparison plots were prepared 

using the “Raobplot” program developed by Matthew Johnson of the Iowa DNR. Radiosonde 

data were selected from the Denver upper air site. Radiosonde plots were prepared for each day 

during June and July of 2006 (when Denver experienced its worst ozone episodes). For 

presentation and specific comparison purposes, plots are presented herein in a time step of 36 

hours during the episodic period of July 20-30, 2006 starting with 00Z on July 21, 2006. Thus, 

there are four 00Z soundings on July 20, 23, 26, and 29 and four 12Z soundings on July 21, 24, 

27, and 30. No regard to synoptic-scale weather patterns was considered in interpreting these 

comparisons. 

Figures 4-1 through 4-8 present the Skew T- log p soundings from observations (dark line) and 

MM5 simulations (red line) for every 36 hours during the episodic period of July 20-30, 2006. 

Thus, the first figure, Figure 4-1 represents the sounding taken at 00Z on July 20 in Denver 

(which translates to 1700 hours or 5:00 PM local time disregarding daylight savings time on July 

19). As can be seen, both the temperature and moisture profiles match reasonably well with the 

greatest disparities at the lower levels and at the 200mb height. Comparisons are best above the 

550-600 mb height away from influences of the earth’s surface. The magnitude of the winds is 

in reasonable agreement throughout the soundings but the wind directions agree best above about 

400mb. Surface wind directions in the first 850 to 600mb levels are more north northeasterly 

from the MM5 sounding than the northwesterly observations. 

Figure 4-2 presents a morning sounding for Denver, that is, the 12Z sounding (0500 or 5:00 AM 

local time) on July 21. As can be seen both the temperature and moisture soundings overall are 

reproduced well by the MM5 simulations. The MM5 lower level temperature sounding does not 

account for the depth of the inversion layer as well as the observations and underestimates the 

amount of moisture at the surface layers. Winds throughout the sounding generally agree very 

well both in magnitude and direction. 

Figure 4-3 represents the sounding taken at 00Z (1700 hours or 5:00 PM local time) on July 23 in 

Denver. As can be seen, both the temperature and moisture profiles match reasonably well with 

very little disagreement. The observed moisture profile tends to have more variation than the 

MM5 sounding and is lower in the upper atmosphere. The magnitude of the winds is in 

reasonable agreement throughout the soundings as are the wind directions except in the 700-

500mb level where MM5 data are more north northeasterly than the north northwesterly 

observations. 

Figure 4-4 presents a morning sounding for Denver, that is, the 12Z sounding (0500 or 5:00 AM 

local time) on July 24. As can be seen both the temperature and moisture soundings overall are 

reproduced well by the MM5 simulations. The MM5 lower level temperature sounding creates a 

more significant temperature inversion layer than the observations but matches the observations 

quite well above that. MM5 data are slightly less than the observations for moisture at the 

surface. Winds throughout the sounding generally agree very well both in magnitude and 

direction except for the surface where the MM5 wind directions from the northwest vary from 

the observed west directions. 
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Figure 4-5 represents the sounding taken at 00Z (1700 hours or 5:00 PM local time) on July 26 in 

Denver. As can be seen, both the temperature and moisture profiles match reasonably well with 

very little disagreement. The observed moisture profile tends to have more variation than the 

MM5 sounding and is lower in the upper atmosphere. The MM5 temperature sounding misses 

the shallow inversion layer detected in the observations. The magnitude of the winds is in 

reasonable agreement throughout the soundings as are the wind directions except in the 750-

700mb level where the observations are from the east southeast and the MM5 winds are more 

north northwesterly. 

Figure 4-6 presents a morning sounding for Denver, that is, the 12Z sounding (0500 or 5:00 AM 

local time) on July 27. As can be seen both the temperature sounding overall is reproduced well 

by the MM5 simulations. The MM5 moisture sounding tends to underpredict the moisture 

throughout most of the sounding. The MM5 lower level temperature sounding creates a stronger 

temperature inversion layer than the observations but matches the observations quite well above 

that. Winds throughout the sounding generally agree very well both in magnitude and direction 

with a few exceptions at selected sounding levels (~610 and 350mb). 

Figure 4-7 represents the sounding taken at 00Z (1700 hours or 5:00 PM local time) on July 29 in 

Denver. As can be seen, both the temperature and moisture profiles match reasonably well with 

very little disagreement. Both the observed and MM5 moisture profiles have variation 

throughout the sounding with them alternating as to which one is higher and lower. The MM5 

temperature sounding misses the shallow superadiabatic condition at the surface but matches the 

remainder of the sounding very well. The magnitude of the winds is in reasonable agreement 

throughout the soundings as are the wind directions except in the surface to 700mb level where 

the observations are from the southeast and the MM5 winds are from the south and south 

southeast. 

Figure 4-8 presents a morning sounding for Denver, that is, the 12Z sounding (0500 or 5:00 AM 

local time) on July 30. As can be seen both the temperature sounding overall is reproduced well 

by the MM5 simulations. Even the strong inversion layer at the surface is reproduced well by 

the MM5 data. Within this same layer, however, the MM5 moisture sounding is at odds with the 

observations up to where the inversion layer ceases. Much disparity between the MM5 and 

observed moisture data takes place from the surface up to about 500mb. Winds throughout the 

sounding generally agree very well both in magnitude and direction with the exception of the 

400-300mb level where the observations are from the south at 400 mb and from the north at 

300mb while the MM5 simulation generally has them from the west over this layer. 
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Figure 4-1. Radiosonde Sounding Comparison at Denver on 0Z 20 July 2006. 

Figure 4-2. Radiosonde Sounding Comparison at Denver on 12Z 21 July 2006. 
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Figure 4-3. Radiosonde Sounding Comparison at Denver on 0Z 23 July 2006. 

Figure 4-4. Radiosonde Sounding Comparison at Denver on 12Z 24 July 2006. 
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Figure 4-5. Radiosonde Sounding Comparison at Denver on 0Z 26 July 2006. 

Figure 4-6. Radiosonde Sounding Comparison at Denver on 12Z 27 July 2006. 
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Figure 4-7. Radiosonde Sounding Comparison at Denver on 0Z 29 July 2006. 

Figure 4-8. Radiosonde Sounding Comparison at Denver on 12Z 30 July 2006.
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5 Comparison with Other MM5 Simulations 

This section presents a comparison of this June-July 2006 4 km MM5 simulation with other 4 km 

annual meteorological simulations that have been completed recently by the ENVIRON/Alpine 

Team. Tables 5-1 through 5-5 present these comparisons on the basis of the temperature bias and 

error, the mixing ratio bias and error, and the wind index of agreement. 

5.1 Comparison to Other 4 km Simulations 

Comparisons between the RAQC June-July 2006 MM5 simulation for Colorado and other 4 km 

simulations were conducted. All available MM5 simulations over roughly the same domain at a 

4 km grid resolution using the same vertical grid definitions as the 4 km grid simulations are 

compared. The three New Mexico Environment Department (NMED) MM5 simulations for 

2003, 2004, and 2005 (McNally and Schewe, 2006 and Schewe and McNally, 2006) were 

generated for the use in modeling studies centered over the Four Corners area. The CDPHE 

2003 (McNally and Schewe, 2007) simulation was conducted over a 4 km domain that was 

somewhat larger than the State of Colorado. Thus, the spatial coverage of the simulations were 

somewhat different. The CDPHE 2003 and the NMED 2003-2005 simulations were annual 

simulations, but for comparison, only June and July simulations were conducted and are 

presented in this report. The analysis of these simulations was performed using the Alpine 

Geophysics, MAPS analysis package (McNally and Tesche, 1994). 

The same benchmarks as described in Section 3 were used in this comparison. Recall the 

purpose of these benchmarks was not to give a passing or failing grade to any one particular 

meteorological model application, but rather to put its results into the context of other models 

and meteorological data sets. The benchmarks include bias and error in temperature and mixing 

ratio as well the Wind Speed Index of Agreement (IA) between the models and data bases. As a 

reference the performance benchmarks are repeated here: 

• Temperature bias: <±0.5 K 

• Temperature error: <2.0 K 

• Mixing ratio bias: <±1.0 g/kg 

• Mixing ratio error: <2.0 g/kg 

• Wind Speed Index of Agreement (IA): 0.0 = worst, 0.6=acceptable, 1.0 = best 

Temperature bias for both this study and the three years of NMED data is presented in Table 5-1. 

This RAQC 2006 MM5 application was within the range of the temperature bias benchmark of 

<±0.5 K with a -0.21 K average over both months and individual month biases of -0.42 and 0.01. 

When comparing the RAQC 2006 performance to other study simulations, this RAQC 2006 

simulation performed as well or better than the others both on a monthly basis as well as an 

average basis. 

Temperature error is presented in Table 5-2. For this RAQC 2006 application of MM5 the 

temperature error of 1.79 K was within the guideline temperature error of 2.0 K. All other 

simulations were higher than the guideline range by a degree or more. 
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Mixing ratio bias over the 4 km simulation domain for the RAQC 2006 MM5 data set is 

presented in Table 5-3. The domain-wide bias for this RAQC 2006 MM5 simulation was 0.18 

g/kg which is within the acceptability benchmark of ±1.0 g/kg. While this mean value of the 

RAQC 2006 data appears to be better than other simulations, closer review indicates this may be 

an artifact of the average of the June and July monthly values. The June mixing ratio bias was 

0.81 and the July bias was -0.45. Both values are still within the benchmark. Performance by 

other simulations were similar and generally within the benchmark but were all on the positive 

side of the bias. 

Mixing ratio error over the 4 km simulation domain is presented in Table 5-4 The domain-wide 

error for this RAQC 2006 MM5 simulation was 1.64 g/kg which is less than the benchmark of 

2.0 g/kg. The mixing ratio bias was within the range of the acceptability benchmark for both 

months and compared well in both magnitude and variability to other data sets. 

Wind speed index of agreement (IA) is presented in Table 5-5. The domain-wide IA for the 

RAQC 2006 simulation was 0.84 which is above the minimally guideline value of 0.6 and 

tending toward the best agreement level of 1.0. This RAQC 2006 data was comparable to all 

other data sets. 

Table 5-1. Temperature Bias (K) For June and July 4 km MM5 Simulations. 

Region Jun Jul Mean 

RAQC 2006 -0.42 0.01 -0.21

CDPHE 2003 0.73 -0.25 0.24

NMED 2003 0.49 -0.11 0.19

NMED 2004 0.87 0.97 0.92

NMED 2005 0.94 0.58 0.76

Table 5-2. Temperature Error (K) for June and July 4 km MM5 Simulations. 

Region Jun Jul Mean 

RAQC 2006 1.93 1.64 1.79

CDPHE 2003 3.07 3.82 3.45

NMED 2003 3.36 3.70 3.53

NMED 2004 3.51 3.28 3.40

NMED 2005 3.51 3.71 3.61

Table 5-3. Mixing Ratio Bias (g/kg) for June and July 4 km MM5 Simulations. 

Region Jun Jul Mean 

RAQC 2006 0.81 -0.45 0.18

CDPHE 2003 0.30 1.71 1.01

NMED 2003 0.51 1.24 0.88

NMED 2004 0.72 0.62 0.67

NMED 2005 0.52 1.37 0.95
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Table 5-4. Mixing Ratio Error (g/kg) for June and July 4 km MM5 Simulations. 

Region Jun Jul Mean 

RAQC 2006 1.60 1.68 1.64

CDPHE 2003 1.36 2.25 1.81

NMED 2003 1.37 1.88 1.63

NMED 2004 1.50 1.73 1.62

NMED 2005 1.49 1.91 1.70

Table 5-5. Wind Index of Agreement for June and July 4 km MM5 Simulation. 

Region Jun Jul Mean 

RAQC 2006 0.83 0.84 0.84

CDPHE 2003 0.83 0.83 0.83

NMED 2003 0.80 0.80 0.80

NMED 2004 0.81 0.81 0.81

NMED 2005 0.80 0.80 0.80
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6 References 

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Validation Tests and Simulation of an Atlantic Cyclone and Cold Front", Mon. Wea.

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Emery, C. et al., 2001. “Enhanced Meteorological Modeling and Performance Evaluation for 

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Grell, G. A., J. Dudhia, and D. R. Stauffer, 1994. "A Description of the Fifth Generation Penn 

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Regional Air Partnership, prepared by ENVIRON International Corporation and 

University of California at Riverside. 

McNally, D. E., and G. J. Schewe, 2006. “Evaluation of 36/12/4 km MM5 for Calendar Year 

2003”, “Evaluation of 36/12/4 km MM5 for Calendar Year 2004”, “Evaluation of 36/12/4 

km MM5 for Calendar Year 2005”, prepared for the New Mexico Environment 

Department, prepared by Alpine Geophysics, LLC, Arvada, CO. 

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McNally, D. E., and T. W. Tesche, 1994. "MAPS2.3 User's Guide", Alpine Geophysics, LLC, 

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Schewe, G. J., and D.E. McNally, 2006, “Evaluation of 36/12/4 km MM5 for Calendar Year 

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