# Appendix I Meteorological Model Performance

# TABLE OF CONTENTS

**I. INTRODUCTION ...................................**

**................................................... ..............................................1** 

**II. 12 KM MM5 PERFORMANCE IN NORTH CAROLINA .......**

**................................................... .........1** 

**III. MM5 MODEL PERFORMANCE AT GREENSBORO, NC ......**

**................................................... ......7** 

**IV. UPPER AIR MODEL PERFORMANCE ...................**

**................................................... .......................8** 

**V. SUMMARY........................................**

**................................................... ...............................................12** 

# LIST OF FIGURES

**Figure I-1: Monthly plots of modeled 1.5 meter t emperature, bias and absolute error................**  **..............2**

**Figure I-2: Monthly plots of modeled 1.5 meter m ixing ratio, bias and absolute error...............**  **..............2**

**Figure I-3: Monthly plots of modeled 1.5 meter r elative humidity, bias and absolute error ..........**  **...........3**

**Figure I-4: Monthly plots of modeled cloud cover age, bias and absolute error. ......................**  **.................4**

**Figure I-5: Monthly plots of modeled wind direct ion, bias and absolute error. ......................**  **..................4**

**Figure I-6: Monthly plots of modeled wind speed, bias and absolute error...........................**  **....................5**

**Figure I-7: Monthly plots of modeled wind speed wi th calm observations omitted, bias and absolute** 

**error..............................................**

**................................................... ...................................................**  **...6**

**Figure I-8: Monthly plots of modeled wind speed with modeled wind speed below 1.5 m/s omitted, bias** 

**and absolute error.................................**

**................................................... ..............................................6** 

**Figure I-9: Modeled data compared to surface obse rvations at the Greensboro, NC ASOS site (KGSO)** 

**for two weeks typical of winter conditions.........**

**................................................... ...............................7** 

**Figure I-10: Modeled data compared to surface obse rvations at the Greensboro, NC ASOS site (KGSO)** 

**for two weeks typical of summer conditions. ........**

**................................................... ............................8** 

**Figure I-11(a).....................................**

**................................................... ...................................................**  **...10**

**Figure I-11(b).....................................**

**................................................... ...................................................**  **...10**

**Figure I-11(c).....................................**

**................................................... ...................................................**  **...11**

**Figure I-11: The Charlotte, NC (CHANC) profiler wi nds co-plotted with the 12-km MM5 winds for (a)** 

**12-23 UTC on January 17, 2002, (b) 00-11 UTC on Jan uary 19, 2002, and 00-11 UTC on January** 

**20, 2002...........................................**

**................................................... .................................................11** 

**Figure I-12(a).....................................**

**................................................... ...................................................**  **...11**

**Figure I-12(b).....................................**

**................................................... ...................................................**  **...12**

**Figure I-12: The Charlotte, NC (CHANC) profiler wi nds co-plotted with the 12-km MM5 winds for (a)** 

**00-11 UTC on November 10, 2002, and (b) 12-23 UTC o n November 17, 2002 ..............................12** 

# 1 METEOROLOGICAL MODEL PERFORMANCE

I. INTRODUCTION

**The VISTAS (Visibility Improvement State and Triba l Association of the Southeast) MM5**  **meteorological model performed quite well at the 12 km grid resolution. In a majority of cases, the m**  **odel statistics fell within the expected ranges of error**  **. In reviewing all available data, SCDHEC agrees w ith**  **VISTAS/ASIP and NCDAQ’s conclusions that the VISTAS MM5 results for the 2002 modeled core**  **ozone season will produce credible inputs for CMAQ modeling intended as the basis for the Metrolina** 

**Area 8-hour ozone attainment demonstration.**

**The attainment demonstration for the Charlotte-Gas tonia-Rock Hill, NC-SC 8-hour ozone**  **nonattainment area (referred to as the Metrolina ar ea) used the meteorological modeling from the**  **VISTAS regional haze modeling. VISTAS is run by th e ten Southeast states: Alabama, Florida, Georgia,**  **Kentucky, Mississippi, North Carolina, South Caroli na, Tennessee, Virginia, and West Virginia. The**  **meteorological model used for this project was the Pennsylvania State University/National Center for**  **Atmospheric Research Mesoscale Meteorological Model (MM5).** 

**The sections that follow summarize the meteorologi cal model performance for North Carolina on the**  **12 kilometer (km) grid domain. York County, SC, as part of the Metrolina Area, is included in the mod**  **el performance data as an extended part of the North C**  **arolina review, since it contains the only part of SC**  **for which this document applies. SCDHEC has evalua ted the balance of this work and agrees with its**  **conclusions in their entirety.**

**The overall VISTAS meteorological model developmen t and model performance was documented**  **by the VISTAS contractor Baron Advanced Meteorologi cal Systems, LLC, and is attached to this**  **Appendix.**

II. 12 KM MM5 PERFORMANCE IN NORTH CAROLINA

**In general, the MM5 performance for North Carolina (including York County, SC) was very similar**  **to the performance for the entire VISTAS modeling d omain. The temperature bias was near zero in May,**  **June, and August. July had a slight negative bias near –0.25 Kelvin (K), and September had a negative**  **bias of –0.1 K. The absolute temperature error hov ered around 1.5 K from May-September. Figure I-1**  **displays the overall temperature, temperature bias and absolute error for North Carolina and the VISTA**  **S modeling domain.** 

# 2

Figure I-1: Monthly plots of modeled 1.5 meter tem perature, bias and absolute error.

**The mixing ratio bias in North Carolina was closer to neutral as compared to the entire VISTAS**  **domain. The mixing ratio bias in North Carolina wa s near 0 gram/kilogram (g/kg) in May through July,**  **then fell to –0.2 g/kg in August and to -0.6 g/kg i n September. The absolute error was only slightly**  **higher in North Carolina than in the entire VISTAS domain, peaking at 1.8 g/kg in July. Figure I-2**  **displays the overall mixing ratio, mixing ratio bia s and absolute error for North Carolina and the VIS**  **TAS modeling domain.** 

Figure I-2: Monthly plots of modeled 1.5 meter mix ing ratio, bias and absolute error.

1.5m Temperature

275 280 285 290 295 300JanFebMarAprMayJunJulAugSepOctNovDec

MonthTemperature (K)

NC

VISTAS 

### 1.5m Temperature Bias

-1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2JanFebMarAprMayJunJulAugSepOctNovDec

MonthTemperature (K)

NC

VISTAS



### 1.5m Temperature (K) Absolute Error

0 0.5 1 1.5 2 2.5JanFebMarAprMayJunJulAugSepOctNovDec

MonthAbs Error (K)

NC

VISTAS



### Mixing Ratio Q

v

4 6 8 10 12 14 16JanFebMarAprMayJunJulAugSepOctNovDec

Monthg/kg NC

VISTAS 

### Mixing Ratio Q

v 

### Bias

-0.8 -0.6 -0.4 -0.2 0 0.2 0.4JanFebMarAprMayJunJulAugSepOctNovDec

Monthg/kg NC

VISTAS



### Mixing Ratio Q

v 

### Absolute Error

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2JanFebMarAprMayJunJulAugSepOctNovDec

MonthAbs Error (g/kg)

NC

VISTAS

# 3

**The relative humidity bias in North Carolina was a bout 0.5% higher when compared to the entire**  **VISTAS domain. The relative humidity bias in North Carolina generally hovered around ± 3%. The**  **absolute error was slightly higher in North Carolin a than the entire VISTAS domain, holding steady**  **around 10% during the ozone season. Figure I-3 dis plays the overall relative humidity, relative humid**  **ity**

**bias and absolute error for North Carolina and the VISTAS modeling domain.** 

Figure I-3: Monthly plots of modeled 1.5 meter rel ative humidity, bias and absolute error

**The cloud coverage bias in North Carolina was 2 – 3% higher compared to the entire VISTAS**  **domain. The cloud coverage bias peaked near 10% in July, with all other months with a bias less than**  **5%. The absolute error was generally 1 – 2% lower than the entire VISTAS domain, peaking at 31% in**  **September. Figure I-4 displays the overall cloud c overage, cloud coverage bias and absolute error for**  **North Carolina and the VISTAS modeling domain.** Relative Humidity

50 55 60 65 70 75 80 85JanFebMarAprMayJunJulAugSepOctNovDec

Month% NC

VISTAS 

### Relative Humidity Bias

-6 -4 -2 0 2 4 6JanFebMarAprMayJunJulAugSepOctNovDec

Month% NC

VISTAS



### Relative Humidity Absolute Error

0 2 4 6 8 10 12 14JanFebMarAprMayJunJulAugSepOctNovDecAbs Error (%)

NC

VISTAS

# 4 Figure I-4: Monthly plots of modeled cloud coverag e, bias and absolute error.

**Wind direction was the most erratic of the measure ments. The direction bias in North Carolina was**  **more pronounced, being more negative May through Ju ly, and more positive in August and September.** 

**The absolute error was close to the entire VISTAS d omain, peaking at 35 degrees in July when the**  **lightest winds are experienced. Figure I-5 display s the overall wind direction, wind direction bias a**  **nd**

**absolute error for North Carolina and the VISTAS mo deling domain.** 

Figure I-5: Monthly plots of modeled wind directio n, bias and absolute error.

Cloud Coverage

0 10 20 30 40 50 60 70JanFebMarAprMayJunJulAugSepOctNovDec

Month% NC

VISTAS 

### Cloud Coverage Bias

-5 0 5 10 15JanFebMarAprMayJunJulAugSepOctNovDec

Month% NC

VISTAS



### Cloud Cover (%) Absolute Error

0 5 10 15 20 25 30 35JanFebMarAprMayJunJulAugSepOctNovDecAbs Error (%)

NC

VISTAS



### Wind Direction

0 60 120 180 240 300 360JanFebMarAprMayJunJulAugSepOctNovDec

MonthDegrees

NC

VISTAS 

### Wind Direction Bias

-80 -60 -40 -20 0 20 40 60 80 100JanFebMarAprMayJunJulAugSepOctNovDec

MonthDegrees

NC

VISTAS



### Wind Direction Absolute Error

0 5 10 15 20 25 30 35 40JanFebMarAprMayJunJulAugSepOctNovDec

MonthDegrees
NC

VISTAS

# 5

**The wind speed bias in North Carolina was 0.3 to 0 .4 meter/second (m/s) higher than wind speeds**  **across the entire VISTAS domain. When considering all wind measurements, the wind speed was 0.8 to**  **1.0 m/s too strong. The absolute error is near 1.2 m/s, just above the entire VISTAS domain. When**  **omitting calm observations, the bias falls to 0.2 t o 0.5 m/s. The absolute error is near 1.2 m/s, ver**  **y close to the entire VISTAS domain. When omitting modeled**  **wind speeds below the threshold of the anemometer (<1.5 m/s), the bias is 0.5 to 0.8 m/s.**  **The absolute error is near 1.3 m/s, just above the entire**  **VISTAS domain. Figure I-6 displays the overall win d speed, wind speed bias and absolute error for**  **North Carolina and the VISTAS modeling domain. Fig ure I-7 displays the wind speed when the calm** 

**observations are omitted as well as the bias and ab solute error. Figure I-8 displays the wind speed w**  **ith modeled wind speeds below 1.5 m/s omitted.** 

Figure I-6: Monthly plots of modeled wind speed, b ias and absolute error.

Wind Speed

1 1.5 2 2.5 3 3.5 4JanFebMarAprMayJunJulAugSepOctNovDec

Monthm/s NC

VISTAS 

### Wind Speed Bias

0 0.2 0.4 0.6 0.8 1 1.2JanFebMarAprMayJunJulAugSepOctNovDec

Monthm/s NC

VISTAS



### Wind Speed Absolute Error

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8JanFebMarAprMayJunJulAugSepOctNovDecAbs Error (m/s)

NC

VISTAS

# 6

Figure I-7: Monthly plots of modeled wind speed wi th calm observations omitted, bias and

absolute error.

Figure I-8: Monthly plots of modeled wind speed wi th modeled wind speed below 1.5 m/s omitted,

bias and absolute error.

**Overall, excess wind speeds, increased relative hu midity, and cloud cover likely lead to under**  **prediction of the daily maximum peak ozone concentr ation, which will be discussed in the air quality**  **model performance (Appendix J).** Wind Speed - no calm

1 1.5 2 2.5 3 3.5 4 4.5JanFebMarAprMayJunJulAugSepOctNovDec

Monthm/s NC

VISTAS 

### Wind Speed - no calm Bias

-0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6JanFebMarAprMayJunJulAugSepOctNovDec

Monthm/s NC

VISTAS



### Wind Speed - no calm Absolute Error

0 0.2 0.4 0.6 0.8 1 1.2 1.4JanFebMarAprMayJunJulAugSepOctNovDecAbs Error (ms/)

NC

VISTAS



### Wind Speed - 'minicalm'

1 1.5 2 2.5 3 3.5 4JanFebMarAprMayJunJulAugSepOctNovDec

Monthm/s NC

VISTAS 

### Wind Speed - 'minicalm' Bias

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9JanFebMarAprMayJunJulAugSepOctNovDec

Monthm/s NC

VISTAS



### Wind Speed - 'minicalm' Absolute Error

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6JanFebMarAprMayJunJulAugSepOctNovDecAbs Error (m/s)

NC

VISTAS

# 7

III. MM5 MODEL PERFORMANCE AT GREENSBORO, NC

**An additional way to evaluate model performance is to compare the various parameters to surface**  **observations for a site-specific evaluation. This methodology, when results are statistically sound,**  **should provide a good surrogate for model performance in a**  **reas containing similar climatology to the evaluate d**  **station. (In this case, the Greensboro site is use d as a surrogate due to its similarity to the Metro**  **lina Area). Figures I-9 and I-10 show a time-series mod**  **el and observed meteorological data for the Greensboro, North Carolina Automated Surface Observ**  **ing System (ASOS) site (KGSO). The time series include modeled surface values for temperature, mix**  **ing ratio, wind speed, wind direction, relative humidity, cloud cover, and precipitation (blue dash**  **ed lines). The model-predicted values are compared to**  **actual observations from the Greensboro site (solid black lines). Figure I-9 depicts two different wi**  **nter weeks (January 15-21 and November 12-18, 2002), whi**  **le Figure I-10 depicts two summer weeks (July 20-26 and August 19-25, 2002). It is important to**  **look at both summer and winter events, as the forci ng**  **mechanisms for synoptic features can differ from se ason to season.** 

Figure I-9: Modeled data compared to surface obser vations at the Greensboro, NC ASOS site

(KGSO) for two weeks typical of winter conditions.

# 8

Figure I-10: Modeled data compared to surface obse rvations at the Greensboro, NC ASOS site

(KGSO) for two weeks typical of summer conditions.

**Generally the time series reflect what was seen on the monthly plots. Overall, the plots reflect goo**  **d model performance for 2002 when compared to modelin**  **g standards. Wind direction was close to observed values and switched at the appropriate tim**  **e (when frontal boundaries passed through the area)**

**. Wind speeds were captured well by the model during**  **the daylight hours, but were often too strong at night.** 

**Model performance was better at capturing the wint ertime diurnal temperature trends than the**  **summertime trends. For the summer temperatures, th e model was generally too cool with the afternoon**  **high temperatures. The mixing ratio was close to o bservations in the winter, but, again, the model wa**  **s more variable in the summertime. The diurnal trend**  **s in relative humidity were reasonably well capture d,**  **though the diurnal ranges were less in the model th an with observations.** 

IV. UPPER AIR MODEL PERFORMANCE

**To further quantify model performance, upper air d ata from the model was compared to data from**  **the Charlotte, North Carolina radar profiler. A rad ar profiler is an instrument designed to accurately** 

# 9

**measure various meteorological variables from the s urface up through the first couple of thousand mete**  **rs of the atmosphere (commonly known as the “Planetary**  **Boundary” or “Mixed” Layer). The profiler, similar in function to weather radar, sends pulses**  **of electromagnetic radiation up into the atmosphere**

**, interpreting the return echoes into useable informa**  **tion, especially wind speed and direction. The Charlotte profiler is owned and operated by the Sta**  **te of North Carolina.**

**Profilers yield results at a much finer vertical a nd temporal resolution than do standard rawinsondes**  **(balloons with attached meteorological equipment us ed to take upper air readings). The profiler data**  **are not used to nudge or correct MM5 modeling results,**  **and in fact, cannot effectively be used in that capacity without additional quality control to remo**  **ve or correct erroneous data. Since the model resu lts**  **will not be artificially biased toward the profiler data because of nudging, and, since the profiler h**  **as a high data resolution, it makes an excellent source**  **of data to judge model performance. Figure I-11 sh ows**  **a series of profiler plots from the Charlotte, Nort h Carolina profiler.** 

**Figures I-11 and I-12 compare model predicted wind s (purple wind barbs) with profiler-derived**  **winds (black wind barbs) over the lowest 2,500 mete rs of the atmosphere. Each plot contains 12 hours o**  **f data, with the hour of the observation labeled near**  **the plot bottom and with the hours increasing from left**  **to right. The wind barbs follow the meteorological standard, with a full barb representing a 10-knot**  **(kt) wind, a half barb representing a 5-kt wind, and a f**  **ull flag representing a 50-kt wind.**

**Figure I-11(a) is from the period of 12 to 23 Coor dinated Universal Time (UTC) on January 17,**  **2002, and depicts the typical wind flow pattern pri or to frontal passage. Figure I-11(b) is 00-11 UTC**  **on January 19, 2002, and shows the disruption to the w**  **inds field as a cold front passes through the area, with**  **Figure I-11(c) (00-11 UTC on January 20, 2002) illu strating the northerly flow typically seen after fr**  **ont passage in the region. The model captures the wind**  **direction fairly well through out the atmosphere. The**  **model winds do become disjointed from the observati ons in the mid levels during the early hours of the**  **frontal passage on the 19th [Figure I-11(b)].**

**Figure I-12(a) represents the time period from 00 UTC to 11 UTC on November 10, 2002, and**  **shows the modeling capturing uniform flow throughou t the atmosphere. Figure I-12(b) is from seven**  **days later (12-23 UTC on November 17, 2002) and dem onstrates the model capturing the disturbance of**  **the uniform flow in the upper levels.**

**Overall, these Charlotte, North Carolina profiler plots show typical performance, in that the model**  **generally matches the profiler winds albeit not per fectly. Upper level winds are captured very well,**  **as are the wind shifts associated with frontal passages.**  **In the subset of days presented here, the model win ds are**  **approximately within 20 degrees of the profiler obs erved winds and typically are much closer.**  **Unfortunately, it is difficult to know if this slig ht wind direction bias indicates a model flaw or an**  **issue with the profiler data being representative. It is**  **likely that there are physical mechanisms in the r eal**  **world of which the model is unaware, which in this case are not being compensated for via nudging.** 

# 10 Figure I-11(a)

Figure I-11(b)

# 11 Figure I-11(c)

Figure I-11: The Charlotte, NC (CHANC) profiler wi nds are co-plotted with the 12-km MM5 winds for (a) 12-23 UTC on January 17, 2002, (b) 00 -11 UTC on January 19, 2002, and 00-11 UTC on January 20, 2002.

Figure I-12(a)

# 12 Figure I-12(b)

Figure I-12: The Charlotte, NC (CHANC) profiler wi nds are co-plotted with the 12-km MM5 winds for (a) 00-11 UTC on November 10, 2002, and ( b) 12-23 UTC on November 17, 2002

V. SUMMARY

**In general, the VISTAS MM5 meteorological model pe rformed quite well at the 12 km grid**  **resolution. In a majority of cases, the model stat istics fell within the expected ranges of error. I**  **n reviewing all available data, SCDHEC agrees with VI**  **STAS and NCDAQ’s conclusions that the VISTAS MM5 results will produce credible inputs for CMAQ m**  **odeling intended as the basis for the Metrolina**

**Area 8-hour ozone attainment demonstration.**