TSD-1a



## Meteorological Modeling using Penn State/NC AR 5 t h



## Generation Mesoscale Model (MM5)

Bureau of

Air Qualit y Anal ysis a nd Research

Division o f Air Reso urces

Ne w York State Depart me nt o f Environ me ntal Con servation

Alba ny , NY 12233

February 1, 2006

1Meteorologi cal Modeling using Penn State/N CAR 5 th Generation Mesoscale Model

(MM5)

Version 3.6 of MM5 w as used to generate annual 2002 meteoro log y for the OTC

mode ling w ork. Prof. Dalin Zhang of the U niversit y of Mar yl and performed the MM5

simul ations in consultation with N YS DEC staff. The model w as applied in Lamber t

conform al m ap projection and utilized M PP Ver sion developed for clusters. The two-way

nested domain consisted of coarse (36km) and fine (12km) mesh corresponding to

149x129 and 175x175 grids, re spective l y, in this application (see Figure 1).

The Lamb ert projection used in this work followed the Regional Planning Organization

(RPO) national doma in setup with the center at (40 o N , 97 o W) and parallels at 33 o N and

45 o N. Map pro

jection para met ers in reference to the projection center point are as

follows: S outhwest corner for the 36 km grid is at (-2664km, -2304km) and the northeast

corner at (2664km, 2304km). In the case of the 12km grid, the southwe st corner is at

(252km, -900km) and the northeast corner at (2340km, 1188km). In the vertical direction,

the terrain following σ -coordinate sy ste m was u sed with the pressure at each σ -level

deter min ed from a reference state that is estima ted using the hy drost ati c equation from a

given sea-level pressure and te mpera ture with a standard lapse rate. There are 30

unevenl y spaced σ levels, giving 29 vertical la y ers, with higher resolution within the

planetar y boundary la ye r (PBL). The σ levels are:

1.0000, 0.9974, 0.9940, 0.8980, 0.9820, 0.9720, 0.9590, 0.9430, 0.9230, 0.8990,

0.8710, 0.8390, 0.8030, 0.7630, 0.7180, 0.6680, 0.6180, 0.5680, 0.5180, 0.4680,

0.3680, 0.3180, 0.2680, 0.2180, 0.1680, 0.1230, 0.0800, 0.0400, 0.0000

The surface la ye r was set at about 10m, the level at w hich surface winds were t yp ic al l y

observed, and the mode l top w as set at 50hPa with a radiative top boundary condition.

The tim e steps for the 36km and 12km domains were 75 and 25 s econds, respective l y.

The import ant mod el ph ys ics options u sed for this M M5 simul ation include:

• Kain- F ritsch (1993) convective s che me for both 36- and 12-km doma ins

• Explici t moistur e scheme (without the mix ed phase) containing progno stic

equations for cloud water (ice) and rainwater (snow) ( Dudhia 1989; Zhang 1989)

• Modified version of the Blackadar planetar y boundar y lay er ( PBL) scheme

(Zhang and Anthes 1982; Zhang and Zheng 2004)

• Simp le radiativ e cooling scheme ( Grell et al. 1994)

• Multi- la ye r s oil mode l to predict land surface tempera tures using the s urface

energ y budget equation ( Dudhia 1996)

Note that the Blackadar

PBL schem e has been modified in order to correct the phase s hift

of surface wind s peed and te mperatur e diurnal c yc le

, following a stud y that compar ed

five different PBL schemes: the Ga yn o- Seam an TKE s che me (Shafran et al. 2000), Burk2Thompson (1989), Blackadar (Zhang and A nthes 1982), M RF (Hong and Pan 1996), and

Mellor- Yamada- Ja

jic (Mellor and Yamad a 1974; Jajic 1990, 1994). The details of the

stud y can be found at Zhang and Zheng (2004).

Nudgin g Proces ses

The MM5 p ro vides op tio ns for n ud gi ng ob servati ons for each d omain d uri ng t he mo del

inte gratio n proce ss (Stauff er a nd Seaman, 1 99 0; S tauf fe r et al . 19 91 ). The Eta a nalyses of

up per- air wi nd s, temperature a nd water- v ap or mixi ng rati o as well a s their a ssociate d surface

fields were u sed for nu dg in g every 6 h ou rs, a nd the Eta s urface wi nd fields b len ded with

surface win d o bservati on s were use d t o nu dg e every 3 ho urs. While on ly the surface win ds

were n ud ge d, t heir influences c oul d e xten d int o t he PBL a s well (see Sta uf fe r et al. 19 91).

Base d on UMD’s pri or experie nce in n umerical ex periments, t he followin g n ud gi ng

coeff icients h ave been use d:

• Up per- air win d fields: 5. 0E-4s -1 for Domain 1 (3 6km), an d 2 . 5E-4 s -1 for Domain 2

(12 km);

• Up per- air temperature fields: 1. 0E- 5 s -1 for bo th D omains;

• Surface win ds: 5 . 0 s -1 E-4s -1 for Domai n 1, an d 2. 5E-4s -1 for Domai n 2; an d

• Surface temperature an d moist ure: no t n ud ged du e to in stability c onsi deratio n.

AS SESSMENT

This as sessment covers the period of May through Septe mber 2002.

National Weather Service (NW S) and C ASTNet data – S urf ace te mp erature, Win d

Speed, and Hu mi dity

NWS (TDL) and C ASTNet ( w ww.epa.gov/castnet / )surface measure me nts of

te mpera ture, wind speed, and humidi t y (note there were no humidit y measure me nts for

CASTNet) were used to compare with the M M5 outputs. The evaluation wa s perform ed

with METSTAT program developed by Environ Corporation

( ww w.ca mx.com

/f iles/ me tst at.15feb05. tar.gz. .When comp aring to NW S data, the

METSTAT interpolates the first la ye r MM5 (at 10m height) te mpera ture and humidit y

data to a height of 2m, the level that correspond s to the NWS measure me nt of these

para meters. H owever, no such interpola tion w as made for wind speed and direction. In

the case of CASTNet surface measure me nts, no such changes were needed as CASTNet

data were reported at a height of 10m. In this analy si s, no exclusion wa s m ade for cal m

conditions. The reported calm wind s (zero wind speed measured) were treated as is in

this evaluation effort. The METSTAT calculat ed standard statistical measures –

average, bias, error and index of agreemen t between the measured and predicted

para meters.

Figure 2 display s the te mpera ture and wind s peed compar ison of M M5 and me asured

data from NWS and CASTNet networks for August 2002. M M5 perform ance for both in

magn itude and diurnal tim ing, te mpera ture can be considered to be quite good for both

NWS and CASTNet data, while M M5 underpredicted NW S and overpredicted CASTNet

3da yt i me wind s peed, respectivel y

. It should be pointed out that there are differences in

how the meteoro logica l inform ation is collected and reported by the two networks as well

as in M M5. The CASTNet m easurem en ts are based on hourl y averaged wind s peed while

NWS reports 2min average at 10m in before the hour, whereas MM5 predictions are

reflect ive of the last ti me- step of the hour of computa tion. Interestingl y

, M M5 appears to

track quite well the nightti me min im um wind s peed for both networks. In the case of

humid it y (not sho wn), MM5 tracks the NW S observed humidit y trend well, but MM5

missed the observed semi- diurnal cy cl es. Comparisons for the five months including bias

and root mean s quare error from both NW S and C ASTNet are availabl e on request from

NY SDEC.

The above assessment

is based on domain- wide averages to provide an overall respon se

of the model over the five months. A nother way of as sessing the model is to exam ine the

degree of correlation between the measuredand predicted paramet ers. Figure 3 displa ys

such a co mparison for te mpera ture and wind s peed for the NWS hourly data covering the

period of May through Septe mber 2002. For the NW S data, the correlations are in the

range from 0.7 to 0.8 for wind speed, above 0.96 for te mperatur e, and in the range of 0.8

to 0.9 for humidit

y

. CA STNet data (not sho wn) also exhibit simil ar correlation. These

correlat ions indicate that MM5 simulat ion has captured both the diurnal and s yn optic

scale variations. Detailed plots of this comp arison are available on request from

NY SDEC.

V erti cal Profiler – Winds

The Wind-Profiler

network me asurem en ts along the U. S . East Coast ( ww w.mad isfsl.org/cap) were used to evaluate the vertical profiles from M M5. There are twelve

wind-profiler

me asurem ent stations from w hich data were availabl e for compar ison. For

convenience of compar ison, the wind-profiler me asurem ents w ere interpolated to the

MM5 vertical levels. The approach u sed was simple interpolat ion between two ad jacent

wind-profiler

la ye rs to the M M5 vertical level, and was lim ited to that reported by the

profiler me asurem ent. The focus of the compar ison wa s to as sess if MM5 w as able to

capture the measured vertical structure, and for this we u sed the observed Low Level Jet

(LLJ) as an indicator. The compar ison wa s perform ed for June, July and August 2002. In

general it is found that M M5 captures the profiler measured

vertica l wind field structure

reasonabl y well. Figure 4 displa ys an exa mple of the MM5 and wind profilercompar ison

for the Augu st 2002 episode at Richmond, V A and Concord, NH. M M5 predicted weaker

LLJ wind s comp ared to those based on the wind-profiler measurem en ts. The detailed

plots of this compar ison are availab le on request from NY SDEC.

Cloud C over – Satellite cloud im age

Cloud informat ion derived from satelli te i mage data

( ww w.at mos.um d.edu/~srb/gc ip/webgc ip.htm ) were used to asses s the M M5 prediction

of cloud cover. The 0.5 o by 0.5 o resolution of the satelli te data were interpola ted into the

12km M M5 grid for comp arison. The M M5 total cloud fraction was estima ted b y MCIP

based on the MM 5’s low cloud, middle cloud and high cloud predictions. In general,

4MM5 captured the satelli te cloud pattern well but underesti mat es the satelli te cloud

fraction (see Figure 5 as an examp le). Part of problem ma y due to the coarse resolution of

the satellite cloud data. The detailed plots of this comp arison are available on request

from N YS DEC or at the following U RL

Precipitat ion co mp arison

The monthl y total observed precipit ation data w ere constructed from 1/8-degree dail y precipit ation anal ys is data ( http://d ata. eol.ucar. edu/cod iac/dss/id=21.093 produced b y

Cli mat e Prediction Center, based on 7,000-8,000 hourl y/ 6- hourl y gauge reports and

radar). The MM5 monthl y total precipita tion was estim ated from the M M5 predicted

convective and non-convective rainfall and s um me d up for each month. In general, M M5

captured the observed spatial patterns in Ma y and September, but no so well for June,

July and A ugust (See Figure 6), perhaps reflective of the s um me rti me convectiv e rain

activi ties not captured by M M5. Detailed plots of this comp arison are available on

request from NY SDEC.

Cal m Con ditions

Cal m conditions are defined as observed wind s peed of zero knots and wind direction as

0 o . It w ould be useful to assess ho w MM5 performs under observed cal m conditions,

because of potential pollutant buildup that could occur under such conditions. Table 1

lists the summ ar y of the percentage of calm condition at each hour for the August 2002

from the NWS data within the 12km doma in. It is apparent from the Table that the cal m

conditions occurprimari l y during the night and earl y morning hour s, from 23Z (7 p.m.

EDT) to 15Z (11 a.m. EDT) with a peak at 10Z (6 a.m. EDT). To assess M M5

perform ance, the observed and M M5 predicted wind speeds were divided into calm and

non-cal m according to observed wind speed. Figure 7 display s s uch a compar ison of the

MM5 predicted wind speed to the observed wind speed under the cal m and non-calm

conditions for the month of August 2002. For the “calm ” group, the average wind s peed

for MM5 varies from 1 m /s during the night and early morn ing hours and over 1.5 m/s

during the da y. MM5 is over-predicting during observed cal m wind conditions. There

are local mini ma every 3 hours, due to the surface observed wind speed nudging in MM5.

In contrast under the non-calm conditions, MM 5 underpredicts b y about 0.5 m/s for all

hours with noticeab le local m axim um happening at the nudging hours. The M M5

nudging proces s would pull predictions toward the measureddata, w hile the

underpredict ion of MM 5 for the non-calm conditions ma y due to the adopted P BL

schem e in this simulat ion.

Su m m ar y

In this study

, we performed an as sessment of the MM5 simulat ion to real-world data,

both at the s urface level as well as in the vertical. While there are no specific

reco mm ended procedures identifi ed for this a ssessment, similar approaches have been

used elsewhere (Dolwick 2005, Baker 2004, and John son 2004). Tradition all y

, the NWS

surface measure me nts are u sed for such a comparison. Since NWS data had been used

5through nudging processes in developing the M M5 simul ation, the comp arisons s hould

not be far removedfrom each other. In this study

, we extended the evaluation b y using

CASTNet me asurem ents that w ere not used in the M M5 simul ations. Thus co mparison

with C ASTNet data provides for an independent assessment and s hould comple me nt the

comp arison with NWS data. We also compared the MM5 results with the wind profiler

data and cloud data derived from satellit e imag es to diagnose if the M M5 simula tion is

y ie ld ing the right

ty pe of d yn am ic s in the vertical. The anal y ses sho ws that in general, the

perform ance of the MM5 is reasonable both at the surface and in the vertical, thereb y providing confidence in the use of these data in the CMA Q simu lations.

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Do lw ic k, P. 2 00 5:

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7Table 1 Measured cal m and non-calm occurrences over the modeling domain

during A ugust 2002 based on NWS data

Ho ur #No nCal m #C alm #T ot al % Calm

00Z 18 20 9 39 24 22 13 3 1 7. 7

01Z 16 53 1 60 26 22 55 7 2 6. 7

02Z 15 60 4 69 29 22 53 3 3 0. 8

03Z 14 98 3 72 45 22 22 8 3 2. 6

04Z 14 30 9 75 40 21 84 9 3 4. 5

0 5z 14 07 3 77 35 21 80 8 3 5. 5

06Z 13 93 4 79 49 21 88 3 3 6. 3

07Z 13 79 2 80 40 21 83 2 3 6. 8

08Z 13 54 2 82 73 21 81 5 3 7. 9

09Z 13 54 2 83 85 21 92 7 3 8. 2

10Z 13 70 8 85 91 22 29 9 3 8. 5

11Z 14 13 9 86 93 22 83 2 3 8. 1

12Z 15 29 7 76 90 22 98 7 3 3. 5

13Z 17 33 6 51 92 22 52 8 23

14Z 18 52 2 34 39 21 96 1 1 5. 7

15Z 18 75 5 26 17 21 37 2 1 2. 2

16Z 19 16 9 20 15 21 18 4 9. 5

17Z 19 55 5 16 17 21 17 2 7. 6

18Z 19 98 2 14 30 21 41 2 6. 7

19Z 20 14 9 13 89 21 53 8 6. 4

20Z 20 56 5 12 88 21 85 3 5. 9

21Z 20 51 8 13 83 21 90 1 6. 3

22Z 20 67 2 15 56 22 22 8 7

23Z 20 23 1 22 92 22 52 3 1 0. 2

8Figure 1: OTC M M5 mode ling domain with areal extent

of 12km and 36km grids

9Figure 2: Temp erature and Wind s peed compar isons for August 2002. In each case the

upper panel corresponds to comparison between MM 5 and NW S data and the lower

panel between M M5 and CASTNet data.

10

O b s e r ve d / P re d i c t e d T e m p e ra t u re

2 7 5 2 8 0 2 8 5 2 9 0 2 9 5 3 0 0 3 0 58/18/28/38/48/58/68/78/88/98/108/118/128/138/148/158/168/178/188/198/208/218/228/238/248/258/268/278/288/298/308/31K O b s T e m p Pr d T e m p

O b s e r ve d / P re d i c t e d T e m p e ra t u re

2 7 5 2 8 0 2 8 5 2 9 0 2 9 5 3 0 0 3 0 58/18/28/38/48/58/68/78/88/98/108/118/128/138/148/158/168/178/188/198/208/218/228/238/248/258/268/278/288/298/308/31K O b s T e m p Pr d T e m p

O b s e r ve d / P re d i ct e d W i n d s p e e d

1 2 3 4 5 6 78/18/28/38/48/58/68/78/88/98/108/118/128/138/148/158/168/178/188/198/208/218/228/238/248/258/268/278/288/298/308/31m/s O b s W n d S p d Pr

d W n d S p d

O b s e r v e d / P r e d i ct e d W i n d s p e e d

1 2 3 4 5 6 78/18/28/38/48/58/68/78/88/98/108/118/128/138/148/158/168/178/188/198/208/218/228/238/248/258/268/278/288/298/308/31m/s O b s W n d S p d Pr

d W n d S p dFigure 3a: Spatial correlation esti mat es between MM5 and NWS data for wind s peed

from May to Septemb er 2002

11Figure 3b: Spatial distribution of correlation coefficients for Te mpera ture between

MM5 and NWS data from May to Septemb er 2002.

12Rich mond, VA

Concord, N H

Figure 4: M M5 and Wind profiler compar ison for Augu st 6 to 17, 2002 at Rich mond, VA

and Concord, N H. The upper and lower panes at each station are for MM5 and profiler,

respectivel y

. The abcissa represents da y and the ordinate the height (m).

13Figure 5: M M5 and Satellite cloud im ages for Augu st 14, 2002 at 0700 EST

14Figure 6: M M5 predicted and measured precipitat ion over the domain for the mon th of

August 2002

150 0

. 5 1 1

. 5 2 2

. 5 3 3

. 5 4 4

. 5

0 0 Z 0 3 Z 0 6 Z 0 9 Z 1 2 Z 1 5 Z 1 8 Z 2 1 Z

T I M EWINDSPEED(m/s)

T D L A v g N C

M M 5 A v g N C

M M 5 A v g C

Figure 7: Comparison of averaged wind s peed between MM5 and observed under cal m

(C) and non-calm ( NC) conditions.

16