Time-space distribution of the impact of initial and ...
Episodic Dust Events along Utah’s Wasatch FrontW. James Steenburgh AND Jeffrey D. MasseyDepartment of Atmospheric Sciences, University of Utah, Salt Lake City, UTThomas H. PainterJet Propulsion Laboratory, Pasadena, CAIn preparation for submittal toJournal of Applied Meteorology and ClimatologyDraft of TIME \@ "dddd, MMMM dd, yyyy" Tuesday, October 11, 2011Corresponding 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.eduAbstractEpisodic 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. 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, 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 19th 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. 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 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 methodsa. Long-term climatologyOur 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. 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 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 (), the level-II KMTX radar data from NCDC (website: , and the GOES data from the NOAA Comprehensive Large Array-Data Stewardship System (CLASS, ). 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 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 ?C to 0 ?C (25 ?C to 10 ?C). 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. ResultsLong-term climatologyDust events at KSLC occur throughout the historical record, with an average of 4.3 per water year (Fig. 3). 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% 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 (?g/m3), for each dust report following eq. 9.81 of Shao (2008, p. 334):C = 2802.29VIS-0.84) VIS < 3.5 kmC = exp(-0.11VIS + 7.62))VIS ≥ 3.5 kmwhere 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. 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 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). SinceRecent 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 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. 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 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).Dust emission sources and transportAdditional 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 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. 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. Case Studiesa. 5/10/2004May 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 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. 10/17/2004The 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 16th, 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 17th, 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 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. 5/19/2006The 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 19th, 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 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. ConclusionsDust 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 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 snowpack5. Acknowledgments6. ReferencesBelnap, 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, 27-43Bisal, F. and J. Hsieh (1966) In?uence of soil moisture on erodibility of soil by wind. Soil Sci., 102, 143–14Carlson, T.N., 1979. Atmospheric turbidity in Saharan dust outbreaks as determined by analyses of satellite brightness data. Monthly Weather Review 107, 322–33Chepil and Woodruff, N.P. 1963. The physics of Wind Erosion and its Controls. Advances in Agronomy; Vol. 15, pg. 211-302Christopher, A. S., T. A. Jones. 2010. Satellite and surface-based remote sensing of Saharan dust aerosols. Remote Sensing of Environment 114, 1002-1007Draxler, R.R. and Rolph, G.D.,?2011. HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) Model access via NOAA ARL READY Website (). 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: , 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. 185-204Gillette, D. A., 1999: A Qualitative geophysical explanation for hot spot dust emitting source regions. Contr. Atmos. Phys., 72,1,67-77Gillette, D. A., 1988: Threshold Friction Velocities for Dust Production for Agricultural Soils. Journal of Geophysical Research, 93, D10, 12,645-12,662Gillette, 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. 9003-9016Gorrell, M., 2011, Aug 22: Big Fourth of July weekend boosts Utah resorts. The Salt Lake Tribune. Retrieved from , A. S., and N. J. Middleton, 2001: Saharan dust storms: nature and consequences. Earth-Science Reviews, 56, 197-204Hansen, 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. 26:1147–115Holcombe, 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), 18317–1833Jaffe, D., et al., 1999. Transport of Asian air pollution to North America. Geophysical Research Letters 26 (6), 711–714Mbouro, 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(1997)036%3C0868:TDASCO%3E2.0.CO;2Mc 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, 79-96Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87, 343–360Morales, 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: , 2008: Data documentation for data set 3505 (DSI-3505) Integrated Surface Data. [Available from ].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, 117–13Painter, 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.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, 472–48Prospero, J. M. 2003. African Droughts and Dust Transport to the Caribbean: Climate Change Implications. Science 302, 1024Qian, Weihong, Lingshen Quan, Shaoyin Shi, 2002: Variations of the dust storm in china and its climatic control.?J. Climate,?15, 1216–1229Ramanathan, V., Crutzen, P.J., Kiehl, J.T. and Rosenfeld, D. (2001) Aerosols, climate, and the hydrological cycle. Science, 294, 2119–2124Reid, 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 (). 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, 304–309Salt Lake City Department of Public Utilities, 1999: Salt Lake City Watershed Management Plan. Bear West Consulting Team, 129 pp. [Available from utilities/PDF%20Files/slcwatershedmgtplan.pdf].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.107:339–34Steenburgh, 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 , 4205–4220Tanaka, 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:10.1029/2002JD003273WMO, 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, 245-252Zhoa, T., S. Ackerman, W. Guo, 2010: Dust and smoke detection for multi-channel imagers. Remote Sensing, 2, 2347-2368Zobeck, T.M., Fryrear, D.W. and Pettit, R.D. (1989) Management effects on wind-eroded sediment and plant nutrients. J. Soil Water Cons., 44, 160–16Figure CaptionsTopography and geography of the study region. 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. 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.Same as Fig. 2 except for KSLC.Dust layer climatology derived from UAC reports. (a) Number of events by year. (b) Number of events by month.Satelite (dust product), MesoWest, and manual surface analysis during selected events. (a) 2002 Tax Day storm, (b-?) other events. Maybe pick four. Camera images from selected events, especially the nasty 5 April (date?) 2010 event with the haboob.Meteograms for (a) Delta and (b) KSLC during the 10-12 April 2010 event.PM2.5 or PM10 for sites in the Salt Lake Valley during the 10-12 April 2010 event.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.CategoryFull DescriptionAbbreviated DescriptionReports06Widespread dust in suspension in the air, not raised by wind at or near the station at the time of observationDust in suspension178 (155)07Dust 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 seenBlowing dust905 (867)08Well 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 sandstormDust whirl(s)1 (0)09Duststorm or sandstorm within sight at the time of observation, or at the station during the preceding hourDuststorm2(1)30Slight or moderate duststorm or sandstorm has decreased during the preceding hourDuststorm1 (0)31Slight or moderate duststorm or sandstorm no appreciable change during the preceding hourDuststorm1 (0)32Slight or moderate duststorm or sandstorm has begun or has increased during the preceding hourDuststorm1 (0)33Severe duststorm or sandstorm has decreased during the preceding hourDuststorm0 (0)34Severe duststorm or sandstorm no appreciable change during the preceding hourDuststorm0 (0)35Severe duststorm or sandstorm has begun or has increased during the preceding hourDuststorm0 (0)98Thunderstorm combined with duststorm or sandstorm at time of observation, thunderstorm at time of observationDuststorm2 (0)Table 2DateAirmass ConvectionPersistent SW FlowTransient troughOtherNotes3/23/2002PrefrontalFrontalXPostfrontal4/15/2002PrefrontalFrontalXPostfrontal6/1/2002XPrefrontalFrontalPostfrontal9/16/2002XPrefrontalFrontalPostfrontal2/1/2003PrefrontalFrontalXPostfrontal4/1/2003XPrefrontalFrontalPostfrontal4/2/2003PrefrontalXFrontalXPostfrontal9/16/2003PrefrontalXTrough forms to the southFrontalPostfrontal4/28/2004PrefrontalFrontalXPostfrontal5/10/2004PrefrontalFrontalXPostfrontal7/9/2004XPrefrontalFrontalPostfrontal10/17/2004XPrefrontalFrontalPostfrontal3/13/2005PrefrontalXArctic frontFrontalPostfrontal4/13/2005PrefrontalFrontalXPostfrontal5/16/2005PrefrontalFrontalXPostfrontal7/22/2005XPrefrontalFrontalPostfrontal7/30/2005XPrefrontalFrontalPostfrontal5/19/2006XPrefrontalFrontalPostfrontal7/19/2006XPrefrontalFrontalPostfrontal7/26/2006XPrefrontalFrontalPostfrontal4/29/2008PrefrontalFrontalXPostfrontal5/20/2008PrefrontalFrontalXPostfrontalX7/27/2008XPrefrontalFrontalPostfrontal8/31/2008PrefrontalStationary trough at firstFrontalXPostfrontal3/4/2009PrefrontalStationary trough at firstFrontalXPostfrontal3/21/2009XPrefrontalFrontalPostfrontal6/30/2009XPrefrontalFrontalPostfrontal8/5/2009XPrefrontalFrontalPostfrontal8/6/2009PrefrontalXFrontalXPostfrontal8/30/2009XPrefrontalMany Smoke ObsFrontalPostfrontal9/30/2009PrefrontalFrontalXPostfrontal3/30/2010PrefrontalXFrontalXPostfrontalX4/27/2010PrefrontalXFrontalXPostfrontal ................
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