Episodic Dust Events along Utah’s Wasatch Front

W. JAMES STEENBURGH AND JEFFREY D. MASSEY

Department of Atmospheric Sciences, University of Utah, Salt Lake City, UT

THOMAS H. PAINTER

Jet Propulsion Laboratory, Pasadena, CA

In preparation for submittal to

Journal of Applied Meteorology and Climatology

Draft of Tuesday, May 16, 2023

Corresponding author address: Dr. W. James Steenburgh, Department of Atmospheric Sciences, University of Utah, 135 South 1460 East Room 819, Salt Lake City, UT, 84112. E-mail: jim.steenburgh@utah.edu

Abstract

Episodic dust events cause hazardous air quality along Utah’s Wasatch Front and dust

loading of the snowpack in the adjacent Wasatch Mountains. This paper presents a climatology

of episodic Wasatch Front dust events based on surface-weather observations from the Salt Lake

City International Airport (KSLC), GOES satellite imagery, and the North American Regional

Reanalysis. Dust events at KSLC, defined as any day with at least one report of a dust storm,

blowing dust, and/or dust in suspension (i.e., dust haze) with a visibility of 10 km (6 mi) or less,

occur an average of 4.3 days per water year (WY, Oct–Sep), with considerable interannual

variability from 1930–2010. The monthly frequency of dust-events is bimodal with primary and

secondary maxima in Apr and Sep, respectively. Dust reports are most common in the late

afternoon and evening.

An analysis of the 33 most recent (2001–2010 WY) events at KSLC indicates that 16

were associated with a cold front or baroclinic trough, 11 with airmass convection and related

outflow, 4 with persistent southwest flow ahead of a stationary trough or cyclone over Nevada,

and 2 with other synoptic patterns. GOES satellite imagery and backtrajectories from these 33

events, as well as 61 additional events from the surrounding region, illustrate that emissions

sources are mostly concentrated in the deserts of southern Utah and western Nevada, including

the Sevier dry lake bed, Escalente Desert, and Carson Sink. Efforts to reduce dust emissions in

these regions may help mitigate the frequency and severity of hazardous air-quality episodes

along the Wasatch Front and dust loading of the snowpack in the adjacent Wasatch Mountains.

2

1. Introduction

Dust storms impact air quality (Gebhart et al. 2001; Pope et al. 1996), precipitation

distribution (Goudie & Middleton, 2001), soil erosion (Gillette 1988; Zobeck 1989), the global

radiation budget (Ramanathan 2001), and regional climate (Nicholson 2000, Goudie &

Middleton 2001). Recent research regarding regional hydrologic and climatic change produced

by dust-radiative forcing of the mountain snowpack of western North America and other regions

of the world has initiated a newfound interest in dust research. (Hansen and Nazarenko 2004;

Painter et al. 2007; Painter et al. 2010). For example, observations from Colorado’s San Juan

Mountains indicate that dust loading increases the snowpack’s absorption of solar radiation, thus

decreasing the duration of snow cover by several weeks (Painter et al. 2007). Modeling studies

further suggest that dust-radiative forcing results in an earlier runoff with less annual volume in

the upper Colorado River Basin (Painter et al. 2010).

Synoptic and mesoscale weather systems are the primary drivers of global dust emissions

and transport. Mesoscale convective systems that propagate eastward from Africa over the

Atlantic Ocean produce half of the dust emissions from the Sahara Desert, the world’s largest

Aeolian dust source (Swap et al. 1996; Goudie & Middleton 2001). Dust plumes generated by

these systems travel for several days in the large-scale easterly flow (Carlson 1979), with human

health and ecological impacts across the tropical Atlantic and Caribbean Sea (Goudie &

Middleton 2001; Prospero & Lamb 2003). In northeast Asia, strong winds in the post-cold-

frontal environment of Mongolian Cyclones drive much of the dust emissions (Yasunori and

Masao 2002; Shoa, Wang, 2003; Qian et al., 2001). The highest frequency of Asian dust storms

occurs over the Taklimakan and Gobi Deserts of northern China where dust is observed 200 d yr-

1 (Qian et al., 2001). Fine dust from these regions can be transported to the United States,

3

producing aerosol concentrations above National Ambient Air Quality Standards (Husar et al.

2001; Jaffe et al., 1999; Fairlie et al., 2007)

The Great Basin, Colorado Plateau, and Mojave and Sonoran Deserts produce most of the

dust emissions in North America (Tanaka and Chiba 2006; see Fig. 1 for geographic and

topographic locations). Most land surfaces in these deserts are naturally resistant to wind erosion

due to the presence of physical, biological, and other crusts (Gillette 1980). However, these

crusts are easily disturbed leading to increased dust emissions, in some cases long after the initial

disturbance (e.g., Belnap et al. 2009). Based on alpine lake sediments collected over the interior

western United States, Neff et al. (2008) found that dust loading increased 500% during the 19 th

century, a likely consequence of land-surface disturbance by livestock grazing, plowing of

dryland argricultural soils, and other activities.

Several studies suggest that the synoptic and mesoscale weather systems that generate

dust emissions and transport over western North America vary geographically and seasonally. In

a dust climatology for the contiguous United States, Orgill and Sehmel (1976) proposed several

including convective systems, warm and cold fronts, cyclones, diurnal winds, and specifically for

the western United States, downslope (their katabatic) winds generated by flow-mountain

interactions. They identified a spring maximum in the frequency of suspended dust for the

contiguous United States as a whole, which they attributed to cyclonic and convective storm

activity, but found that several locations in the Pacific and Rocky Mountain regions have a fall

maximum. However, they made no effort to quantify the importance of the differing synoptic

and mesoscale systems. In Arizona, Brazel and Nickling (1986, 1987) found that fronts,

thunderstorms, cutoff lows, and tropical disturbances (i.e., decaying tropical depressions and

cyclones originating over the eastern Pacific Ocean) are the primary drivers of dust emissions.

4

The frequency of dust emissions from fronts is highest from late Fall–Spring, thunderstorms in

the summer, and cutoff lows from May–June and Sep–Nov. Dust emissions produced by

tropical disturbances are infrequent, but are likely confined to Jun–Oct when tropical cyclone

remnants move across the southwest United States (Ritchie et al. 2011). For dust events in

nearby California and southern Nevada, Changery (1983) and Brazel and Nickling (1987) also

established linkages with frontal passages and cyclone activity, respectively. In addition to

synoptic and mesoscale systems, these studies also cite the importance of land-surface conditions

(e.g. soil moisture, vegetation) for the seasonality and spatial distribution of dust events.

None of these studies, however, have specifically examined the Wasatch Front of

northern Utah, where episodic dust events produce hazardous air quality in the Salt Lake City

metropolitan area and contribute to dust loading of the snowpack in the nearby Wasatch

Mountains (Fig. 2). From 2002–2010, wind-blown dust events contributed to 13 exceedances of

the National Ambient Air Quality Standard for PM2.5 or PM10 in Utah (T. Cruickshank, Utah

Division of Air Quality, Personal Communication). Dust loading in the Wasatch Mountains

affects a snowpack that serves as the primary water resource for approximately 400,000 people

and enables a $1.2 billion winter sports industry, known internationally for the “Greatest Snow

on Earth” (Salt Lake City Department of Public Utilities 1999; Steenburgh and Alcott 2008; Salt

Lake Tribune 2011).

This paperHere we examines the climatological characteristics and emissions sources

during Wasatch Front dust events. We find that Wasatch Front dust-events occur throughout the

historical (1930–2010 water year) record, with considerable interannual variability. Events are

driven primarily by strong winds associated with cold fronts or airmass convection, with the

deserts and dry lake beds of southern Utah, as well as the Carson Sink of Nevada, serving as

5

primary regional emission sources. Dust emission mitigation efforts in these regions may reduce

the frequency and severity of related hazardous air quality events along the Wasatch Front and

dust loading of the Wasatch Mountain snowpack.

2. Data and methods

a. Long-term climatology

Our long-term dust-event climatology derives from hourly surface weather observations

from the Salt Lake City International Airport (KSLC), which we obtained from the Global

Integrated Surface Hourly Database (DS-3505) at the National Climatic Data Center (NCDC).

KSLC is located in the Salt Lake Valley just west of downtown Salt Lake City and the Wasatch

Mountains (Fig. 1) and provides the longest quasi-continuous record of hourly weather

observations in northern Utah. The analysis covers the 1930–2010 water years (Oct–Sep) when

97.9% of all possible hourly observations are available.

The hourly weather observations included in DS-3505 derive from multiple sources, with

decoding and processing occurring at either operational weather centers or the Federal Climate

Complex in Asheville, NC (NCDC 2001, 2008). Studies of dust events frequently use similar

datasets (e.g., Nickling and Brazel 1984; Brazel and Nickling 1986; Brazel and Nickling 1987;

Brazel 1989; Hall 1981; Orgill and Sehmel 1976; Changery 1983; Weihong 2002; Kurosaki and

Masao 2002; Shao et al. 2003; Song et al. 2007; Shao and Wang 2003). Nevertheless, while

hourly weather observations are useful for examining the general climatological and

meteorological characteristics of dust events, they do not quantify dust concentrations, making

the identification and classification of dust somewhat subjective. Inconsistencies arise from

observer biases, changes in instrumentation, reporting guidelines, and processing algorithms.

6

These inconsistencies result in the misreporting of some events (e.g., dust erroneously reported

as haze) and preclude confident assessment and interpretation of long-term trends and variability.

Consistent with World Meteorological Organization (WMO) guidelines (WMO 2009),

the present weather record in DS-3505 includes 11 dust categories (Table 1). During the study

period, there were 916 blowing dust (category 7), 178 dust-in-suspension (category 6), 7 dust

storm (categories 9, 30–32, and 98) and one dust or sand whirl report (category 8) at KSLC.

There were no severe dust storm reports (categories 33–35). Amongst the blowing dust, dust-in-

suspension, and dust storm reports, there were 69 with a visibility > 6 statute miles (10 km), the

threshold currently used by the WMO and national weather agencies for reporting blowing dust

or dust-in-suspension (Shao et al. 2003; Federal Meteorological Handbook, 2005). Since these

events are weak, or may be erroneous, they were removed from the analysis. This includes all

but one of the 7 dust storm reports. The dust or sand whirl report was also removed since we are

interested in widespread events rather than localized dust whirl(s) (a.k.a. dust devils). The

resulting long-term dust-event climatology is based on the remaining 1033 reports. A dust day is

any day (MST) with at least one such dust report.

b. Characteristics of recent dust events

The analysis of the synoptic, meteorological, and land-surface conditions contributing to

Wasatch Front dust events concentrates on events at KSLC during most recent ten-year period

(2001–2010). This enables the use of modern satellite and reanalysis data, and limits the number

of events, making the synoptic analysis of each event tractable.

Resources used to synoptically classify dust events, composite events, and prepare case

studies includes the North American Regional Reanalysis (NARR), GOES satellite imagery, Salt

7

Lake City (KMTX) radar imagery, and hourly KSLC surface weather observations and remarks

from DS-3505. The NARR is a 32-km, 45-layer reanalysis for North America based on the

National Centers for Environmental Predication (NCEP) Eta model and data assimilation system

(Mesinger et al. 2006). Compared to the ERA-Interim and NCEP-NCAR reanalysis, the NARR

better resolves the complex terrain of the Intermountain West, but still has a poor representation

of the basin and range topography over Nevada (see Jeglum et al. 2010). We obtained the

NARR data from the National Oceanic and Atmospheric Administration (NOAA) Operational

Model Archive Distribution System (NOMADS) at the National Climatic Data Center web site

(http://nomads.ncdc.noaa.gov/#narr_datasets), the level-II KMTX radar data from NCDC

(website: http://www.ncdc.noaa.gov/nexradinv/, and the GOES data from the NOAA

Comprehensive Large Array-Data Stewardship System (CLASS,

http://www.class.ncdc.noaa.gov).

c. Dust emission sources

We identify dust emission sources during this most recent 10-year period using a dust-

retrieval algorithm applied to GOES satellite data. Because the algorithm only works in cloud-

free areas and many dust events occur in conjunction with cloud cover, we expand the number of

events to include those identified in: (1) DS-3505 reports from stations in the surrounding region

with at least 5 years of hourly data (Fig. 1), (2) the authors’ personal notes, and (3) Utah

Avalanche Center annual reports. This analysis is thus not specific to KSLC, but does identify

emissions sources that contribute to dust events in the region.

Our dust-retrieval algorithm follows that described by Zhoa et al. (2010) for MODIS.

First, we substitute the GOES 10.7 μm channel for the MODIS 11.02 μm channel. Then the two

8

reflectance condition thresholds used to identify the presence of clouds from the

MODIS .47, .64, and .86 μm channels are replaced by a single threshold (.35) that uses the only

visible channel on GOES. Finally, the maximum threshold for the brightness temperature

difference between the 3.9 and 11 μm (11 and 12 μm) bands was changed from -.5 ºC to 0 ºC (25

ºC to 10 ºC). These adjustments enable the identification of visible dust over Utah using GOES

data, although uncertainties arise near cloud edges, when the sun angle is low, or when the dust

concentrations are low or near the surface. The algorithm is applied every 15 min during the

daylight hours (1400–0200 UTC), with plume origin and orientation identified subjectively.

3. Results

a. Long-term climatology

Dust events at KSLC occur throughout the historical record, with an average of 4.3 per

water year (Fig. 3)1. Considerable interannual variability exists, with no events reported in seven

years (1941, 1957, 1981, 1999, 2000, 2001, 2007) and a maximum of 15 in 1934. No effort was

made to quantify or assess long-term trends or interdecadal variability given the subjective

nature of the reports and changes in observers, observing methods, and instrumentation during

the study period.

Based on current weather observing practices (Shao and Wang 2003; Glossary of

Meteorology 2000), the minimum visibility when dust is reported on 95.40%, 2.59%, and 2.01%

of the dust days meets the criteria for blowing dust (>5/8 statute miles1 km), a dust storm

(0.5/165 km -– 1 km5/8 statute miles), or a severe dust storm (<0.5 km5/16 statute miles),

respectively (Fig. 4). The observed visibility meets these criteria in 98.04%, 1.20%, and 0.76%

1 All years in this paper are water years (Oct–Sep).

9

of all dust reports. Therefore, only a small fraction of the dust events and observations meet dust

storm or severe dust storm criteria.

To integrate the effects of event severity, frequency, and duration into an estimate of the

annual near-surface dust flux, we first estimate the dust concentration, C (µg/m3), for each dust

report following eq. 9.81 of Shao (2008, p. 334):

C = 2802.29VIS-0.84) VIS < 3.5 km

C = exp(-0.11VIS + 7.62)) VIS ≥ 3.5 km

where VIS is the visibility. Multiplying by the wind speed and integrating across all observation

intervals yields an estimated mean annual near-surface dust flux of 399.4 g/m2, with a maximum

of 2810.2 g/m2 in 1935 (Fig. 5). Because it integrates event severity, frequency, and duration,

the annual near-surface dust flux provides a somewhat different perspective from the annual

number of dust days (Fig. 3). For example, 1934 featured the most dust days, but the greatest

near-surface dust flux occurred in 1935. In 2010, there were only 2 dust days, but also a

pronounced decadal-scale maximum in near-surface dust flux.

The monthly distributions of dust days (Fig. 6) and estimated dust flux (Fig. 7) are

bimodal, with primary and secondary peaks in Apr and Sep, respectively. The dust flux is

distinctly lower in the summer compared to the dust-day frequency, suggesting summer dust

events are characterized by shorter or weaker events. The local maximum in dust flux during Jan

is rather surprising, but careful examination of the data revealed a particularly strong two-day

event in January of 1943 that contributed to 83% of the Jan monthly mean. From Mar–May, the

climatologicalwhich usually encompasses the maximum snowpack snow water equivalent

maximum and beginning of the Spring runoff, the mean three-month dust flux is 237 g/m2, or

59XX% of the annual flux.

10

Similar bimodal or modal distributions with a spring dust maximum have been identified

in the Taklimakan desert of China, southern Great Plains of the United States, Mexico City, and

the Canadian Prairies (Yasunori and Masao 2002; Stout 2001; Jauregui 1989; Wheaton and

Chakravarti 1990). The spring peak appears to be the result of erodible land-surfaces and

enhanced upper level support for surface wind events from the migration of the polar jet stream

over these areas (Lee, 1995)?? In fact, At KSLC, the bimodal distribution at KSLC is very

similar to that of Intermountain cold fronts and cyclones, which are strongest and most frequent

in the spring (e.g., Shafer and Steenburgh 2008; Jeglum et al. 2010). These features produce

persistently strong winds capable of generating dust emissions and transport during favorable

land-surface conditions. Interestingly fact, dust was reported at KSLC within 24 h of the passage

oduringf 12 of the 25 strongest cold fronts identified by Schafer and Steenburgh (2008).

The mean wind speed during dust reports at KSLC is 11.6 m s-1 with a standard deviation

of 4.0 m s-1, slightly higher than the 8.5 m s-1 and 9.29 m s-1 found by Holcombe et al. (1996) for

Yuma, AZ and Blythe, CA, respectively. Therefore, and for convenience, we use 10 ms -1 as an

estimated threshold velocity for dust emissions and transport. At KSLC winds ≥10 m s -1 are

most common in Mar and Apr, with a relatively even distribution the rest of the year (Fig. 9).

This Mar and Apr maximum resembles the springtime peak in dust days and flux, but the lack of

a fall secondary maximum and winter minimum suggests that the secondary peak in other

factorsdust days and flux may be related to seasonal changes to vegetation, soil conditions, and

soil moisture (Neff et al., 2008, Belnap et al., 2009, Gillette, 1999) are also important

contributors to dust flux quantity and dust day frequency.

Dust reports exhibit a strong diurnal cycle and are most common in the late afternoon and

evening hours (Fig. 10), as observed in other regions (Jauregui 1989; Mbouro et al. 1997). The

11

frequency of winds ≥10 m s-1 is about three times higher in the afternoon than morning (Fig. 11),

which is consistent with the development of the daytime convective boundary layer. The peak

for winds ≥10 m s-1 occurs at 1400 MST, roughly four hours earlier than the peak in dust reports;

a likely consequence of the time needed for dust to travel from its source to KSLC.

The frequency distribution of wind directions during dust events is bimodal, with peaks at

southerly and north-northwesterly (Fig. 12). About 50% of the time, the wind is from the south-

southwest through south-southeast and about 28% of the time the wind is northwesterly through

northerly. Dust flux is also greatest for winds from the south (Fig. 13). About 60% of dust flux

is transported in south-southwest through south-southeast flow and about 23% in northwest

through northerly flow meaning higher dust concentrations are transported in southerly flow

compared to northerly flow.

b. Recent (2001-2010) events

Sub-setting our long term climatology into a recent climatology enabled the use of

modern reanalysis, satellite, and radar data to characterize and classify dust events. The monthly

frequency distribution of the 33 dust days during 2001-2010 resembles our long-term

climatology except for a disproportionately high number of summer events (Fig. 14). The

primary peak is still centered around Apr, but a secondary peak occurs in Jul, which is two

months ahead of the Sep secondary maximum in the long-term climatology. Therefore,

summertime dust events may be over-representative in our recent climatology. .2001 and 2007

water years do not have any reported dust days and 2009 has a maximum of 7 days, but there is

no observable recent trend in the annual number of dust days (Figure 13). Since

12

Recent dust events were divided into four groups depending on their primary

meteorological mechanism for dust emission and transport: (1) mesoscale airmass convection,

(2) cold fronts or baroclinic troughs, (3) stationary baroclinic troughs, and (4) other synoptic

mechanisms. A list of all the recent events and their respective typing is presented in Table 2.

The 11 (33%) events forced by airmass convection were identified by a thunderstorm,

thunderstorm in the vicinity, or squall comment within an hour of the dust observation in the DS-

3505 reports, or by nearby convection on satellite and radar without strong 700 hPa baroclinicity.

These events tended to be shortlived, have erratic surface wind speeds and directions, and have a

similar airmass before and after the event. 16 (48%) events were forced by cold fronts or

baroclinic troughs and four (18%) were forced by upstream stationary baroclinic troughs. Cold

front or baroclinic trough events have a surface cold front passage within 24 hours of the dust

observation, a distinct frontal band on visible satellite, and evidence of a mobile baroclinic

trough or intermountain cyclone on NARR 700 hPa temperature, and 850 hPa height fields.

Stationary baroclinic trough events are identified similarly, but their axis of dilatation never

passes KSLC within 24 hours of a dust report. Previous studies differentiated between

mesoscale convection and synoptic scale systems in the production of dust emission (Changery,

1983; Brazel and Nickling, 1987; Orgill and Sehmel 1976), but have not, to the best of our

knowledge, differentiated between stationary and transient baroclinic troughs or cold fronts. Out

of the 16 cold front or baroclinic trough events, four (25%) reported dust in the prefrontal

environment, 16 (100%) during frontal passage, and two (13%) in the postfrontal environment,

where prefrontal and postfrontal describe the conditions three hours before and after surface

frontal passage, respectively. September 16, 2003 and March 13, 2005 were the two (6%) events

forced by other synoptic patterns. The surface front on September 16, 2003 that formed

13

downstream of KSLC and the equatorward travelling arctic front on March 13, 2005 forced dust,

but are atypical. Table 2 lists the August 30, 2009 event as questionable because after an initial

dust observation all other observations with low visibility had smoke comments, and smoke

plumes are visible on satellite images over the area. This event is still included in all analyses

since the dust observation cannot be disproven.

Other classifications schemes in the literature are Brazel and Nickling’s (1986) five

synoptic types for Arizona dust storm generation: (1) pre-frontal, (2) post-frontal, (3)

thunderstorm/convective, (4) tropical disturbance, (5) upper level/cut-off low. Henx and

Woiceshyn (1980) created a hierarchy of weather-duststorm systems for the southern and central

Great Plains and their classifications were (1) dust devils, (2) Haboob, (3) Severe Mountain Dust

Storm, (4) Frontal, (5) Cyclogenic. The cyclogenic category was further broken down into (a)

low level jet, (b) upper level jet, (c) surface storm circulation, and (d) Severe mountain

downslope windstorm. Our categories are only specific to recent KSLC dust days.

Dust events are most often associated with upper level troughing upstream of KSLC

coupled with a low level pressure minimum. A NARR composite of the dynamic tropopause

(Fig. 15), created using analyses that were within an hour of the dust onset times, shows a mean

trough to the west and an embedded southwesterly jet over Utah. Unfortunately, NARR data

only extends to 100 hPa so all levels of the two potential vorticity unit (PVU) dynamic

tropopause > 100 hPa are forced to 100 hPa. The 700 hPa temperature and wind analysis (Fig.

16) shows a tight baroclinic zone over Nevada being advected by ageostrophic westerly flow

towards Utah and strong southwest geostrophic flow further downstream. Area averaged NARR

700 hPa winds over western Utah indicate wind speeds associated with dust events are

considerably higher (Fig. 17a) and skewed southwesterly (Fig. 18a) compared to climatology.

14

Climatological variables were averaged from 37N to 41N and 112W to 114W, roughly

corresponding to western Utah south of KSLC, and were computed for each of NARR’s eight

synoptic time steps (00Z, 03Z, 06Z, etc.). The 850 hPa height composite (Fig. 19) shows a mean

surface trough near the location of the 700 hPa baroclinic zone providing evidence that

baroclinic troughs are a dominant mechanism for dust emission. The height of the planetary

boundary layer is also much higher than climatology during dust events (Figure 20a) allowing

strong winds aloft to be better realized at the surface. Shafer and Steenburgh (2008) found PBL

heights significantly higher in prefrontal environments than postfrontal suggesting KSLC dust

events are more likely to be initiated in the prefrontal environments.

Interestingly, soil moisture during dust events does not vary significantly from

climatology (Figure 21a). Past studies suggest soil moisture has a capillary effect on soil grains,

which increases the friction velocity of the soil making it less erodible (Saleh and Fryrear 1995;

Bisal and Hsieh 1966; Chepil and Woodruff, 1963; McKenna-Neuman and Nickling, 1989).

However, Gillette (1999) observed wind erosion 10-30 minutes after a soaking rain because the

eroding layer needs only to be a millimeter thick and strong winds can dry a layer that thin very

quickly. The NARR soil moisture content is calculated from the soil surface down to 200 cm so

it may be an inappropriate proxy for surface dryness.

Cold fronts or baroclinic troughs and airmass convection events have drastically different

700 hPa wind speeds. The 700 hPa speed for cold fronts or baroclinic trough at the onset of dust

events is centered around 15m/s (Figure 17b), which occurs only 4% of the time climatologically

and airmass convection events are only skewed slightly towards higher values than climatology

(Figure 17c). Wind directions are only in the southwest quadrant of the compass for cold front or

baroclinic trough events (Figure 18b), whereas airmass convection events have some northerly

15

trajectories (Figure 18c). Planetary boundary layers are larger than climatology for both groups

(Figures 20b and 20c), but soil moisture does not appear to be any different from climatology

(Figures 21b and 21c).

c. Dust emission sources and transport

Additional dust days were added to our recent dust day climatology in an effort to locate

as many source regions as possible. Hourly dust observations have been reported in accordance

with our 10 km visibility and present weather (e.g. no dust whirls) constraints at four different

stations across the Intermountain West (IMW) since 2001 (33 at KSLC, 30 at Delta, UT, 18 at

Pocatello, ID, 6 at Elko, NV for 87 total, but 79 individual events due to overlap). The dust days

from these stations were further supplemented with personal observations of dust along the

Wasatch Front, and from Utah Avalanche Center annual reports, bringing the total number of

dust days to 94. The characteristics of these events are consistent with the long-term climatology

of KSLC in terms of annual, monthly, and diurnal distribution (not shown). Our GOES satellite

dust retrieval algorithm is applied to all 94 dust days in an effort to locate all visible dust plumes

originating in the IMW. For the 94 dust days, 120 independent plumes were identified during 47

(50%) dust days. The remaining 47 (50%) dust days may not have had any observable plumes

because clouds blocked the dust from the satellite detection, the dust occurred at night or during

a low sun angle, or the dust concentration was too weak for the detection algorithm to pick it up.

Airmass convection events and frontal passages with two or fewer dust observations were the

most common types of dust events without any visible plumes.

GOES data indicates the low topographical ancient depositional environments (e.g.,

ancient lake beds) in southwest Utah and Western Nevada are the primary dust plume emission

16

sources for the IMW. Figure 22 shows the approximate plume origins are mostly clustered in

certain lowland regions, most notably the Sevier Desert, Milford Flat area, Escalente Desert, and

West Desert in southwest Utah and the Carson Sink in Nevada. Gillette (1999) calls small areas

of frequent dust production “hot spots”, which are depositional environments in transitional arid

regions that have had their biological and physical crust disturbed. The aforementioned areas

receive heavy recreation and agricultural use so the crusts in these areas are likely disturbed.

The plumes are mostly oriented from the SSW and SW, indicating that the plumes are mainly

transported in southwesterly flow. Only 8.3% of the plumes had a southerly component and they

all originated in Nevada. The length of the plume lines only represents the length of the plume at

one particular time step and the lines are not related to plume strength or to the distance the

plume traveled. 40 (33%) plumes occurred on Delta, UT dust days, 29 (24%) on KSLC dust

days, 10 (8%) on personal notes and UAC annual report dust days, 9 (8%) on Pocatello, ID dust

days, 6 (5%) on Elko dust days, and 26 (22%) on dust days reported at multiple stations.

Interestingly, many observed plumes are not oriented towards their respective station, and days

with visible plumes have an average of 2.55 plumes, meaning there are multiple dust sources

throughout the IMW on any given dust day. Not all of the dust we observed on satellite started

as a point source. There are 11 cases when large areas of dust showed up on the satellite with no

clear origin and then were transported with the flow. The majority of these cases occurred over

western Nevada and moved southeast during the day, but a couple of these cases also occurred

over central Utah, and one over the Snake River Plain of Idaho.

It is important to note that the postfrontal environment of an intermountain cold front is

usually cloudy, which blocks satellite detection of dust plumes. In an effort to avoid a bias

towards southwest transport we computed backtrajectories for all KSLC dust events since 2004.

17

Using the web version of the Hybrid Single-Particle Lagrangian Integrated Trajectory

(HYSPLIT) model (Draxler and Rolph, 2011; Rolph, 2011), we computed 6 hr backtrajectories

ending at 1000 m above KSLC using 40km Eta Data Assimilation System (EDAS) data.

Previous studies have used lagrangian transport models to trace atmospheric aerosols back to

their source (Haller et al., 2011; Gebhart et al., 2001), but they have employed different

durations, ending heights, and used ensembles. The 25 KSLC backtrajectories computed since

2004 reveal the majority of dust comes from the south-southwest and southwest (Fig. 23) making

the starting locations found from GOES imagery a good proxy for the primary emission sources.

Only the airmass convection event on July 26, 2006 and the arctic frontal passage on March 13,

2005 have backtrajectories starting north of KSLC. The airmass convection event did not have a

visible dust plume, but the arctic front did have a diffuse area of dust show up over the Snake

River Plain in Idaho and move south towards KSLC. Since this was a diffuse area and not a

plume it was not recorded on the plume plot (Fig. 22). The rest of the events all point towards

source regions identified by GOES imagery.

d. Case Studies

a. 5/10/2004

May 10, 2004 exhibits a common baroclinic trough induced dust event. Initially, a

baroclinic zone forms over western Nevada downstream of a landfalling Pacific trough. At 15 Z

a weak surface trough forms and 700 hPa winds reach 25 m/s in the prefrontal environment

(Figure 24a). The frontal band is seen clearly over northwestern Nevada on visible satellite, but

dust is not detected (Figure 25a), and winds are only 4.9 m/s from the south at KSLC. By 18Z

the trough has become better organized and has shifted to the east (Figure 24b) and satellite

18

imagery shows a similar shift to the frontal band and the initiation of dust near the frontal

boundary in Nevada and over western Utah (Figure 25b). At 21Z the baroclinic zone nears

northern Utah and 850 hPa heights continue to fall indicting a deepening intermountain cyclone

(Figure 24c). The frontal band is now more organized and further east with pre and post frontal

dust visible over Nevada, and a very distinct prefrontal dust plume originating from the

Escalente Desert and Milford area and extending to near the Utah/Idaho border (Figure 25c).

Winds at KSLC during this time are at 16.5 m/s from the south-southeast, but dust is not yet

reported. The surface trough nears KSLC at 00Z on May 11, 2004 with apparent deformation

frontogenesis (Figure 24d) and the prefrontal dust plume reached KSLC and extended well into

Idaho (Figure 25d). Visibilites at KSLC dropped to 8 km at 23Z with a haze comment and dust

was reported at 0Z with winds at 15.6 m/s from the south. By 1Z the wind shifted to the north-

northwest, the temperature dropped nearly 13 degrees celcius signaling frontal passage, but

visibility remained at 8 km with dust observed.

c. 10/17/2004

The event on 0ctober 17, 2004 is a stationary trough example that produced one

observation of dust at 05Z and dropped visibilities to 10 km. At 18Z on the 16 th, a zonal

baroclinic zone set up over the Pacific Northwest (Figure 26a) out ahead of an approaching

trough. Six hours later, at 0Z on the 17 th, a weak surface trough formed over central Nevada and

700 hPa southwesterly winds intensified downstream (Figure 26b). Unlike the May 10th event,

the baroclinic zone remained weak over Nevada and the upper level potential vorticity support is

much less (not shown). One hour after the dust observation, at 6Z, a surface trough is well

established and strong southwesterly winds are evident over Utah. Isotherms are oriented

19

meridionally over western Nevada, but the gradient is weak (Figure 26c). During this time

KSLC has winds at 12.1 m/s from 160 degrees and visibility at 13 km. Unfortunately the sun

had already set so satellite imagery could not resolve any dust plumes. Six hours later, at 12Z,

the surface trough and baroclinic zone over Nevada remained fairly stationary and weakened, but

a new surface trough formed over western Idaho (Figure 26d). This feature eventually

strengthens downstream of KSLC so KSLC never experiences a frontal passage. All the while a

longwave upper level trough with its PV support sits off the west of coast of the United States

preventing transient cold-frontal trough event from happening.

b. 5/19/2006

The 11 airmass convection events over the recent period of record are characterized by

very similar parameters. All of these events occurred between the middle of May and the middle

of September in a monsoonal surge scenario. May 19 th, 2006 is the earliest in the year of these

events, but still demonstrates the typical setup. Figure 27 shows the surface convective available

potential energy (CAPE), 700 hPa winds, and the atmospheric column precipitable water (PW).

Both the CAPE and PW have a local maximum over KSLC. Although CAPE values around 400

J/kg, and PW values around 20 mm are not that impressive compared to other regions in the

United States, it is substantial enough for convection in Utah. As mentioned earlier, one of the

distinguishing factors between airmass convection dust events and synoptic dust events is the

700 hPa wind speed, which is much lower for airmass convection. These low wind speeds mean

even with the 700 hPa winds mixing down to the surface they would still be insufficient in

entraining dust. Strong winds must originate in smaller mesoscale processes within convection.

At 23Z on May 19th, 2006 winds at KSLC are only 4.5 m/s from the south and this is the

20

strongest they have been all day. Then, at 23:07 winds go to 24.1 m/s and gust to 27.7 m/s and

dust is reported along with a squall at or within sight of the station comment. Radar imagery just

two minutes before reveals a convective cell very close to the station with returns greater than 60

dBZs (Figure 28). By 01Z on the 20th winds are back down to 4 m/s since the storm is fully

passed.

4. Conclusions

Dust events at KSLC occurred throughout the historical record, with considerable interannual

variability. The vast majority of these events have visibilities above dust storm or severe dust

storm criteria and blowing dust is the most common observer comment. Dust events have a

bimodal monthly distribution with a primary peak in the spring and a secondary peak in the fall.

Climatological winds have a local maximum during the spring months as well, but are fairly

consistent for the remainder of the year demonstrating that winds alone cannot explain the dust

day monthly frequency. Annual and monthly dust flux calculations offer a different perspective

than the frequency distributions, but results are very similar with the exception of a more

dramatic local minimum during the summer in the monthly dust flux distribution. This

difference is from shorter and less intense airmass convection events primarily occurring in the

summer. A third of all recent events at KSLC are forced by mesoscale airmass convection and

the rest are synoptically forced. Almost three quarters of synoptically forced events are

baroclinic troughs or cold fronts and 25% reported dust in the prefrontal environment, 100%

during frontal passage, and two (13%) in the postfrontal environment. The other synoptically

forced events are associated with stationary baroclinic zones upstream of KSLC that produce

21

persistently strong southwesterly winds and events with atypical synoptically forced mechanisms

suchas arctic fronts and downstream frontal development.

NARR analysis suggests upper level troughing upstream of KSLC coupled with strong

anomalous southwest 700 hPa winds and a low level pressure minimum are commonly

associated with KSLC dust events. These composites are skewed towards the synoptic events

since airmass convection events have 700 hPa wind speeds and directions closer to climatology.

Planetary boundary layer heights are higher than climatology for all dust events. Surprisingly,

soil moisture in the NARR analysis does not appear to effect dust emission.

GOES data and HYSPLIT back trajectories indicate the ancient depositional

environments (e.g., ancient lake beds) in southwest Utah and Western Nevada are the primary

dust emission sources for the Intermountain West. Specifically Sevier Desert, Carson Sink,

Escalente Desert, and the Milford Flat area are common emitters. These areas experience high

agricultural and recreational use, which are dust disturbing practices that lead to increased dust

emission. Mitigating crust disturbing practices in these areas will help decrease dust flux over

the IMW, which will improve air quality and decrease dust loading in the mountain snowpack

5. Acknowledgments

6. References

Belnap, J., R. L. Reynolds, M. C. Reheis, S. L. Phillips, F. E. Urban, H. L. Goldstein, 2009:

Sediment losses and gains across a gradient of livestock grazing and plant invasion in a

cool, semi-arid grassland, Colorado Plateau, USA, Aeolian Research, 1, 27-43

22

Bisal, F. and J. Hsieh (1966) Influence of soil moisture on erodibility of soil by wind. Soil Sci.,

102, 143–14

Carlson, T.N., 1979. Atmospheric turbidity in Saharan dust outbreaks as determined by analyses

of satellite brightness data. Monthly Weather Review 107, 322–33

Chepil and Woodruff, N.P. 1963. The physics of Wind Erosion and its Controls. Advances in

Agronomy; Vol. 15, pg. 211-302

Christopher, A. S., T. A. Jones. 2010. Satellite and surface-based remote sensing of Saharan dust

aerosols. Remote Sensing of Environment 114, 1002-1007

Draxler, R.R. and Rolph, G.D., 2011. HYSPLIT (HYbrid Single-Particle Lagrangian Integrated

Trajectory) Model access via NOAA ARL READY Website

(http://ready.arl.noaa.gov/HYSPLIT.php). NOAA Air Resources Laboratory, Silver

Spring, MD.

Fairlie T. D., D. J. Jacob, R. J. Park, 2007, The impact of transpacific transport of mineral dust in

the United States. Atmospheric Environment 41, 1251-1266

Federal Meteorological Handbook ,FMH, 2005 September. Surface Weather Observations and

Reports. Retreived from: http://www.ofcm.gov/fmh-1/fmh1.htm

Gebhart, K.A., Kreidenweis, S.M. and Malm, W.C. 200. Back Trajectory Analyses of fine

particulate matter measured at Big Bend National Park in the historical database and the

1996 scoping study. The Science of the Total Environment; Vol. 276, no. 1-3, pp. 185-

204

Gillette, D. A., 1999: A Qualitative geophysical explanation for hot spot dust emitting source

regions. Contr. Atmos. Phys., 72,1,67-77

23

Gillette, D. A., 1988: Threshold Friction Velocities for Dust Production for Agricultural Soils.

Journal of Geophysical Research, 93, D10, 12,645-12,662

Gillette, D.A., Adams, J., Endo, A., and Smith, D. 1980. Threshold Velocities for Input of Soil

Particulates into the Air by Desert Soils. Journal of Geophysical Research; Vol 87, no.

C11, pp. 9003-9016

Gorrell, M., 2011, Aug 22: Big Fourth of July weekend boosts Utah resorts. The Salt Lake

Tribune. Retrieved from http://www.sltrib.com

Goudie, A. S., and N. J. Middleton, 2001: Saharan dust storms: nature and consequences. Earth-

Science Reviews, 56, 197-204

Hansen, J., and L. Nazarenko, 2004: Soot climate forcing via snow and ice albedos. Proc. Natl.

Acad. Sci. U. S. A., 101, 423-428.

Helgren, D.M., and J.M. Prospero. 1987. Wind velocities associated with dust deflation events in

the western Sahara. J. Clim. Appl. Meteorol. 26:1147–115

Holcombe, T. L., Ley, T. and Gillette, D.A. 1996. Effects of Prior Precipitation and Source Area

Characteristics on Threshold Wind Velocities for Blowing Dust Episodes, Sonoran

Desert 1948 – 78. Journal of Applied Meteorology; vol. 36, no. 9, pp. 1160-1175.

Husar, R.B., et al., 2001. Asian dust events of April 1998. Journal of Geophysical Research 106

(D16), 18317–1833

Jaffe, D., et al., 1999. Transport of Asian air pollution to North America. Geophysical Research

Letters 26 (6), 711–714

Mbouro, G., Bertrand J., and S. Nicholson, 1997: The Diurmal and Seasonal Cycles if Wind-

Borne Dust Over Africa North of the Equator. J. Appl. Meteor., 36, 868–882

24

http://journals.ametsoc.org/doi/full/10.1175/1520-0450(1997)036%3C0868:TDASCO

%3E2.0.CO;2

Mc Kenna-Neuman C. and Nickling W.G., 1989: A theoretical and wind tunnel investigation of

the effect of capillary water on the entrainment of sediment by wind. Canadian Journal

of Soil Science. Vol 69, 79-96

Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor.

Soc., 87, 343–360

Morales, C., 1979. The use of Meteorological Observations for Studies of the Mobilization,

Transport and Deposition of Saharan Soil Dust. In Saharan Dust. John Wiley and Sons

Ltd. Pp. 119-131.

Nakata, J.K., Wilshire, H.G. and Barnes, G.G. 1979. Origin of Mojave Desert dust plumes

photographed from space. Geology; Vol. 4, pp. 644-648.

NCDC, 2001: http://www1.ncdc.noaa.gov/pub/data/inventories/ish-tech-report.pdf

NCDC, 2008: Data documentation for data set 3505 (DSI-3505) Integrated Surface Data.

[Available from

http://www1.ncdc.noaa.gov/pub/data/documentlibrary/tddoc/td3505.pdf].

Neff, J. C., and Coauthors, 2008: Increasing eolian dust deposition in the western United States

linked to human activity. Nature Geosci., 1, 189-195.

Nicholson, S. (2000) Land surface processes and Sahel climate. Rev. Geophys., 38, 117–13

Painter, T. H., J. S. Deems, J. Belnap, A. F. Hamlet, C. C. Landry, and B. Udall, 2010: Response

of Colorado River runoff to dust radiative forcing in snow. Proc. Natl. Acad. Sci. U. S.

A., NEED FINAL VOLUME AND PAGES.

25

Painter, T. H., and Coauthors, 2007: Impact of disturbed desert soils on duration of mountain

snow cover. Geophys. Res. Lett., 34, L12502, doi:10.1029/2007GL030284.

Pope, C.A., Jr, Bates, D.V. and Raizenne, M.E. (1996) Health effects of particulate air pollution:

time for reassessment?. Env. Health Perspect., 103, 472–48

Prospero, J. M. 2003. African Droughts and Dust Transport to the Caribbean: Climate Change

Implications. Science 302, 1024

Qian, Weihong, Lingshen Quan, Shaoyin Shi, 2002: Variations of the dust storm in china and its

climatic control. J. Climate, 15, 1216–1229

Ramanathan, V., Crutzen, P.J., Kiehl, J.T. and Rosenfeld, D. (2001) Aerosols, climate, and the

hydrological cycle. Science, 294, 2119–2124

Reid, J. S., Kinney, J. E., Westphal, D. L, Holben, B. N., Welton, E. J., Tsay, S. -C., et al.

(2003). Analysis of measurements of Saharan dust by airborne and ground-based remote

sensing methods during the Puerto Rico Dust Experiment (PRIDE). Journal of

Geophysical Research, 108(D19), 8586. doi:10.1029/2002JD002493.

Rolph, G.D., 2011. Real-time Environmental Applications and Display sYstem (READY).

Website (http://ready.arl.noaa.gov). NOAA Air Resources Laboratory, Silver Spring,

MD.

Saleh, A. and Fryrear, D.W. (1995) Threshold wind velocities of wet soils as affected by wind

blown sand. Soil Sci., 160, 304–309

Salt Lake City Department of Public Utilities, 1999: Salt Lake City Watershed Management

Plan. Bear West Consulting Team, 129 pp. [Available from

www.slcgov.com/utilities/PDF%20Files/slcwatershedmgtplan.pdf].

26

Shao, Y., and J. Wang, 2003: A climatology of northeast Asian dust events. Meteor. Zeitschrift,

12, 187-196.

Schwartz J, Norris G, Larson T, Sheppard L, Claiborne C, Koenig J. 1999. Episodes of high

coarse particle concentrations are not associated with increased mortality. Environ Health

Perspect.107:339–34

Steenburgh, W. J., and T. I. Alcott, 2009: Secrets of the "Greatest Snow on Earth". Bull. Amer.

Meteor. Soc., 89, 1285-1293.

Swap, R., Ulanski, S., Cobbett, M., Garstang, M., 1996. Temporal and spatial characteristics of

Saharan dust outbreaks. Journal of Geophysical Research 101 D2 , 4205–4220

Tanaka, T. Y., and M. Chiba, 2006: A numerical study of the contributions of dust source

regions to the global dust budget. Glob. Planet. Change, 52, 88-104.

Tanré, D., Haywood, J., Pelon, J., Léon, J. F., Chatenet, B., Formenti, P., et al. (2003).

Measurement and modeling of the Saharan dust radiative impact: Overview of the

Saharan Dust Experiment (SHADE). Journal of Geophysical Research, 108(D18), 8574.

doi:10.1029/2002JD003273

WMO, 2009: Manual on Codes. See WMO (2009b) in my directory. We'll need to do full

reference eventually.

Yasunori, K., and M. Masao, 2002: Seaonsla and Regional Characteristics of Dust Event in the

Taklimakan Desert. Journal of Arid Land Studies, 11-4, 245-252

Zhoa, T., S. Ackerman, W. Guo, 2010: Dust and smoke detection for multi-channel imagers.

Remote Sensing, 2, 2347-2368

27

Zobeck, T.M., Fryrear, D.W. and Pettit, R.D. (1989) Management effects on wind-eroded

sediment and plant nutrients. J. Soil Water Cons., 44, 160–16

Figure Captions

Fig. 1. Topography and geography of the study region.

Fig. 2. Examples of dust layering in the late-season Wasatch Mountain snowpack. (a) Ben

Lomond Peak (XXXX m), April 2005. (b) Alta 2009, (b) Alta 2010.

[Fig. 3.] Blowing dust climatology at Delta, UT. (a) Blowing dust reports by year. (b) Blowing

dust reports by month. (c) Blowing dust reports by time of day (may need to normalize

by report frequency given Delta’s frequent lack of reporting). (d) Wind roses of all

blowing dust events. (e) Wind roses of blowing dust events with visby less than 1 mile.

[Fig. 4.] Same as Fig. 2 except for KSLC.

[Fig. 5.] Dust layer climatology derived from UAC reports. (a) Number of events by year. (b)

Number of events by month.

[Fig. 6.] Satelite (dust product), MesoWest, and manual surface analysis during selected events.

(a) 2002 Tax Day storm, (b-?) other events. Maybe pick four.

[Fig. 7.] Camera images from selected events, especially the nasty 5 April (date?) 2010 event

with the haboob.

[Fig. 8.] Meteograms for (a) Delta and (b) KSLC during the 10-12 April 2010 event.

[Fig. 9.] PM2.5 or PM10 for sites in the Salt Lake Valley during the 10-12 April 2010 event.

28

Table 1: DS-3505 dust-related present-weather categories, including full and abbreviated (i.e.,

used in the text) descriptions and the number of total and used reports at Salt Lake City.

Category Full Description Abbreviated Description Reports06 Widespread dust in suspension in the air, not raised by wind at or near

the station at the time of observationDust in suspension 178 (155)

07 Dust or sand raised by wind at or near the station at the time of observation, but no well-developed dust whirl(s) or sand whirl(s), and

no duststorm or sandstorm seen

Blowing dust 905 (867)

08 Well developed dust whirl(s) or sand whirl(s) seen at or near the station during the preceding hour or at the time of observation, but no

duststorm or sandstorm

Dust whirl(s) 1 (0)

09 Duststorm or sandstorm within sight at the time of observation, or at the station during the preceding hour

Duststorm 2(1)

30 Slight or moderate duststorm or sandstorm has decreased during the preceding hour

Duststorm 1 (0)

31 Slight or moderate duststorm or sandstorm no appreciable change during the preceding hour

Duststorm 1 (0)

32 Slight or moderate duststorm or sandstorm has begun or has increased during the preceding hour

Duststorm 1 (0)

33 Severe duststorm or sandstorm has decreased during the preceding hour

Duststorm 0 (0)

34 Severe duststorm or sandstorm no appreciable change during the preceding hour

Duststorm 0 (0)

35 Severe duststorm or sandstorm has begun or has increased during the preceding hour

Duststorm 0 (0)

98 Thunderstorm combined with duststorm or sandstorm at time of observation, thunderstorm at time of observation

Duststorm 2 (0)

29

Table 2

DateAirmass

ConvectionPersistent SW

Flow Transient trough Other Notes

3/23/2002Prefrontal

Frontal XPostfrontal

4/15/2002Prefrontal

Frontal XPostfrontal

6/1/2002 XPrefrontal

FrontalPostfrontal

9/16/2002 XPrefrontal

FrontalPostfrontal

2/1/2003Prefrontal

Frontal XPostfrontal

4/1/2003 XPrefrontal

FrontalPostfrontal

4/2/2003Prefrontal X

Frontal XPostfrontal

9/16/2003Prefrontal

XTrough forms to the

southFrontalPostfrontal

4/28/2004Prefrontal

Frontal XPostfrontal

5/10/2004Prefrontal

Frontal XPostfrontal

7/9/2004 XPrefrontal

FrontalPostfrontal

10/17/2004 XPrefrontal

FrontalPostfrontal

3/13/2005Prefrontal

XArctic front

FrontalPostfrontalPrefrontal

30

4/13/2005 Frontal XPostfrontal

5/16/2005Prefrontal

Frontal XPostfrontal

7/22/2005 XPrefrontal

FrontalPostfrontal

7/30/2005 XPrefrontal

FrontalPostfrontal

5/19/2006 XPrefrontal

FrontalPostfrontal

7/19/2006 XPrefrontal

FrontalPostfrontal

7/26/2006 XPrefrontal

FrontalPostfrontal

4/29/2008Prefrontal

Frontal XPostfrontal

5/20/2008Prefrontal

Frontal XPostfrontal X

7/27/2008 XPrefrontal

FrontalPostfrontal

8/31/2008Prefrontal Stationary trough at

firstFrontal XPostfrontal

3/4/2009Prefrontal Stationary trough at

firstFrontal XPostfrontal

3/21/2009 XPrefrontal

FrontalPostfrontal

6/30/2009 XPrefrontal

FrontalPostfrontal

8/5/2009 XPrefrontal

FrontalPostfrontal

8/6/2009Prefrontal X

Frontal XPostfrontal

8/30/2009 XPrefrontal

Many Smoke ObsFrontal

31

Postfrontal

9/30/2009Prefrontal

Frontal XPostfrontal

3/30/2010Prefrontal X

Frontal XPostfrontal X

4/27/2010Prefrontal X

Frontal XPostfrontal

32