Dust aerosols affect human life, ecosystems, atmospheric chemistry and climate in various aspects. Some studies have revealed intensified dust activity in the western US during the past decades despite the weaker dust activity in non-US regions. It is important to extend the historical dust records, to better understand their temporal changes, and to use such information to improve the daily dust forecasting skill as well as the projection of future dust activity under the changing climate. This study develops dust records in Arizona in 2005–2013 using multiple observation data sets, including in situ measurements at the surface Air Quality System (AQS) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites, and level 2 deep blue aerosol product by the Moderate Resolution Imaging Spectroradiometer. The diurnal and inter-annual variability of identified dust events are shown related to observed weather patterns (e.g., wind and soil moisture) and surface conditions (e.g., land cover type and vegetation conditions), suggesting a potential for use of satellite soil moisture and land products to help interpret and predict dust activity. Backtrajectories computed using NOAA's Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model indicate that the Sonoran and Chihuahuan deserts are important dust source regions during identified dust events in Phoenix, Arizona. Finally, we assess the impact of a recent strong dust event on western US air quality, using various observational and modeling data sets, during a period with a stratospheric ozone intrusion event. The capability of the current US National Air Quality Forecasting Capability (NAQFC) Community Multi-scale Air Quality (CMAQ) modeling system to represent the magnitude and the temporal variability of aerosol concentrations is evaluated for this event. Directions for integrating observations to further improve dust emission modeling in CMAQ are also suggested.
Dust aerosols, generated by anthropogenic or natural sources, present strong spatial and temporal variability (Ginoux et al., 2001, 2010, 2012a, b; Carslaw et al., 2010; Prospero et al., 2002; Zender et al., 2004) and affect human life, ecosystems, atmospheric chemistry and climate in many aspects. Degraded visibility during dusty periods prevents normal outdoor activities and transportation, and dust activity may be associated with a number of human diseases such as “valley fever”, “haboob lung syndrome” and certain eye diseases (Sprigg et al., 2014; Goudie, 2013; Panikkath et al., 2013; Liu et al., 2009a; Morain et al., 2010). Dust neutralizes acid rain (Hedin and Likens, 1996) and interacts with terrestrial and ocean ecosystems (Gassó et al., 2010; Chen et al., 2013; Yu et al., 2015; Reynolds et al., 2001, 2006). Also, dust absorbs sunlight, reduces the planetary albedo over bright surfaces such as snow, ice and deserts, and modifies cloud properties and precipitation (Zhao et al., 2012; Creamean et al., 2013, 2015). The deposition of dust on snow and ice can accelerate their melting and affect regional climate (e.g., Carslaw et al., 2010; Painter et al., 2007). In addition, mineral dust aerosols affect atmospheric chemistry through surface adsorption and reactions (Dentener et al., 1996; Grassian, 2001; Underwood et al., 2001; Fairlie et al., 2010).
North America contributes to a small proportion of the world's total dust
emissions, ranging from < 0.1 to
Surface and satellite observations have been used to study dust trends and variability, as well as for model evaluation (e.g., Tong et al., 2012; Appel et al., 2013; Torres et al., 2002; Ginoux and Torres, 2003; Draxler et al., 2010; Vukovic et al., 2014; Mahler et al., 2006; Raman and Arellano, 2013; Morain et al., 2010). Surface observations used in many of these studies are sparsely and/or infrequently sampled, and there is delay for obtaining some of these data sets which prevents timely updates on the observed dust records. The capability of satellite aerosol optical depth products to capture the dust events depends on various factors such as sensor characteristics, cloud conditions, surface reflectance and dust mineralogy (e.g., Baddock et al., 2009). There is still a lack of comprehensively developed observational dust records with broad spatial coverage up to the very recent years, and accurately simulating dust aerosols is challenging. Therefore, it is important to extend the temporal changes of observed dust activity to recent years using diverse observations. These various observations can assist in evaluating the chemical transport model skills especially during dust events. Furthermore, better understanding the linkages between the temporal changes of dust observations and the observed surface/weather conditions can be beneficial for advancing the dust emission modeling skills via improving the meteorology and dust source input data, as well as for projecting future dust activity under the changing climate.
Data used in this study
Several studies found that dust events can be accompanied by stratospheric intrusions in multiple regions of the world (e.g., Pan and Randel, 2006; Yasunari et al., 2007; Yasunari and Yamazaki, 2009; Reddy and Pierce, 2012). Recently, substantial attention has been called on the influences of stratospheric ozone intrusions on western US surface/near-surface ozone variability (e.g., Lin et al., 2012; Langford et al., 2014). Observations and modeling tools are useful for identifying the periods when dust events are associated with stratospheric intrusions, as well as to assess the impact of elevated surface/near-surface ozone and PM (particulate matter) concentrations on public health and the environment during such events.
This study develops decadal dust records in the state of Arizona using multiple in situ and satellite observation data sets, and relates the diurnal and inter-annual variability of observed dust activity to the observed surface conditions (e.g., land cover type and vegetation conditions) and weather patterns (e.g., wind and soil moisture; Sects. 3.1–3.3). We also analyze observations and model simulations during a recent strong dust event in the western US accompanied by a stratospheric ozone intrusion. The modeling analyses include the US National Air Quality Forecasting Capability (NAQFC) 12 km Community Multi-scale Air Quality (CMAQ) regional model base and sensitivity simulations (Sect. 3.4). In the analyses, we discuss the usefulness and limitations of different observations for identifying potential exceptional events and for model evaluation. We also suggest future directions of integrating observations into regional dust emission modeling in the western US for further improvement of the air quality forecasts.
Three data sets were analyzed to interpret the observed inter-annual variability of the drought conditions from 2005 to 2013 in Arizona, an important dust source and receptor region in the western US. They are the normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on the NASA Aqua satellite, a European soil moisture data set that merged both passive and active satellite sensor data, and the Palmer drought severity index (PDSI).
NDVI is the most commonly used vegetation index, calculated using the
reflected visible and near-infrared light by vegetation (Scheftic et al.,
2014; Brown et al., 2006). Smaller NDVI values refer to less vegetated
areas, which may have a high potential of emitting dust (D. Kim et al., 2013;
Vukovic et al., 2014). NDVI has been used for monitoring land cover changes
and indicating drought (Tucker and Choudhury, 1987; Karnieli et al., 2010;
Wan et al., 2004), and it has been found to be correlated with
meteorologically based drought indexes such as the standardized precipitation
index (Ji and Peters, 2003). In this study we used the monthly mean 1 km
MODIS NDVI product Collection 5, which temporally aggregated the 16-day 1 km
MODIS NDVI using a weighted average. Following the users' guide instructions
(
Soil moisture has also been used for drought monitoring and several studies
have found that satellite and modeled soil moisture is related to dust
outbreaks in Asian countries (Liu et al., 2004; Y. Kim et al., 2013; Kim
and Choi, 2015). This study used a multi-sensor satellite soil moisture
product from the European Space Agency (ESA) within the soil moisture
Climate Change Initiative (CCI) project that merged all available passive and
active products and preserved the original dynamics of these remote sensing
observations. The data are produced daily on a 0.25
Monthly PDSI data, calculated from temperature and precipitation (Palmer,
1965; Alley, 1984), are widely used for identifying long-term and abnormal
moisture deficiency or excess. Studies have found that PDSI is moderately or
significantly correlated (
The dust productive areas depend on surface conditions such as land cover
types and vegetation conditions, and therefore are temporally variable.
Several studies specified dynamic dust source regions using either or both
satellite land cover types and NDVI products (e.g., Vukovic et al., 2014;
Yin et al., 2007; D. Kim et al., 2013). In this study, to explore the
inter-annual variability of dust sources in the western US and its
influences on the dust activity, we specified the dust sources following the
methods in Vukovic et al. (2014). First, for each year during 2005–2013, we
located open shrubland, cropland, and barren areas where dust can
potentially be emitted from, according to the annual-mean MODIS land cover
type product Collection 5.1 (MCD12Q1, 500 m resolution in tile grid; Friedl et
al., 2010) and its 17-category International Geosphere Biosphere Programme
(IGBP) land cover classification scheme (defined at:
– Barren (category 16): 100 % dust source (independent from NDVI).
– Cropland and cropland/native vegetation (categories 12 and 14): if
NDVI
– Open shrubland (category 7): if NDVI
Both remote sensing and in situ aerosol observations were used to explore
the dust aerosol distributions in Arizona. We first demonstrate the
large-scale spatial distributions of aerosols using satellite aerosol
products and discuss their diurnal (e.g., late morning vs. early afternoon
times) and inter-annual variability link to the weather and surface
conditions. We mainly focus on spring and summer time periods when dust
activity is generally strong in Arizona, as found by Ginoux et al. (2012a)
for the 2003–2009 period. In situ observations at Arizona surface monitoring
sites were then analyzed, focusing on their temporal variability in the
populated Phoenix urban area (i.e., with a population of
We extracted scenes dominated by dust aerosols from the MODIS level 2 deep
blue aerosol product Collection 6 (Hsu et al., 2013) during 2005–2013. This
product includes the values of AOD and single scattering albedo (SSA) at 412, 470, 550, and 670 nm, as well as the Ångström exponent between 412 and
470 nm. It is recommended for identifying both dust sources and plumes at
high spatial resolution (e.g., Baddock et al., 2009). The Collection 6 deep
blue data were created using the enhanced deep blue algorithm (from the previous
Collection 5.1), with improved surface reflectance determination, aerosol
model selection, and cloud screening schemes. Also, the deep blue data from
Terra MODIS have been extended beyond 2007 using suitable calibration
corrections (Hsu et al., 2013). Compared with the Aerosol Robotic Network
(AERONET) AOD data, the Collection 6 deep blue AOD data from Aqua MODIS show
a
The very good (quality assurance flag
Most IMPROVE surface sites are located in rural regions, many of which are
in the national parks to measure background pollution levels. Here, we
analyzed the temporal variability of observed particulate matter mass PM10
(i.e., < 10
In general the US Environmental Protection Agency (EPA) AQS sites are
designed to monitor air quality in populated urban or suburban areas. In
this study the AQS hourly PM10 and PM2.5 data from 2005 to September 2013 and
the AirNow from September to December 2013 at the Phoenix JLG supersite (co-located with the
IMPROVE PHOE1 site, AQS site no. 040139997) were analyzed to study the
temporal variability of dust events on hourly temporal resolution. In the
case study on the dusty year of December 2006–November 2007, AQS trace gas
measurements (i.e., carbon monoxide, CO, and oxides of nitrogen, NO
The achieved NOAA Hazard Mapping System (HMS) text product narratively
describes the observed smoke and dust events based on images of multiple
satellites. It qualitatively indicates the dust's locations and the intensity,
which in this study supports the analysis during a recent strong event we
selected for the case study in Sect. 3.4. We also used the dust score data
from the Atmospheric Infrared Sensor (AIRS) instrument on board the Aqua
satellite to qualitatively represent the presence of atmospheric dust during
this recent event. The Aqua satellite has ascending overpass times in the
early afternoon (
As atmospheric dust concentrations depend on the wind fields (e.g., Kavouras
et al., 2007; Ravi et al., 2011; Csavina et al., 2014), we used the observed
hourly surface wind speed and direction in December 2006–November 2007 at the Phoenix
Encanto site (33.4792
Backward air mass trajectories were computed to locate the sources of dust aerosols observed at the Phoenix JLG site during the identified dust events in December 2006–November 2007. These trajectories were calculated using NOAA's Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, version 4 (Draxler and Rolph, 2015; Stein et al., 2015). The accuracy of the trajectories depends on the resolution of the wind data (Draxler and Hess, 1998), and we calculated these trajectories based on the 3-hourly North America Regional Reanalysis (NARR) data (Mesinger et al., 2006) on 32 km horizontal resolution and nine vertical levels below 800 hPa. NARR is the finest meteorology HYSPLIT can currently run with for studying this year, as the horizontally finer (12 km) North American Mesoscale Forecast System (NAM; Janjic, 2003; Janjic et al., 2004) wind fields are only available for HYSPLIT calculations for the time after May 2007. These trajectories were initiated at 500 m above Phoenix's ground level at identified dust periods and were computed for 24 h. The HYSPLIT-indicated air mass origins during the Phoenix dust events will be discussed together with the MODIS land cover product (details in Sect. 2.2).
Inter-annual variability of drought indicators in dust seasons:
The US NAQFC 12 km CMAQ (Byun and Schere, 2006; Chai et al., 2013; Pan et
al., 2014) model simulations were used to depict the PM distributions during
a recent strong dust event in the western US that was accompanied by a
stratospheric ozone intrusion. Dust emissions for NAQFC's CMAQ simulations
were calculated by the FENGSHA dust emission model based on a modified Owen's
equation, which is a function of wind speed, soil moisture, soil texture and
erodible land use types (Tong et al., 2015). Both the FENGSHA and CMAQ model
calculations were driven by meteorological fields from the NAM model, which
is known to usually have positive biases in temperature, moisture, and wind
speed in the continental US (e.g., McQueen et al., 2015a, b). The CMAQ base
simulation was evaluated against surface observations at the AirNow and
IMPROVE sites, and we focused on PM2.5 concentrations as it is one of the
standard NAQFC products. To quantify the impact of western US dust emissions
on PM2.5 concentrations during this event, an additional sensitivity
simulation was conducted in which no dust emissions were included. NAQFC
CMAQ lateral chemical boundary conditions were downscaled from a monthly mean
output from a global GEOS-Chem simulation of year 2006
(
The level 3 daytime ozone and carbon monoxide (CO) profiles (AIRX3STD
version 6, gridded in 1
MODIS-derived dust sources over the western US (from the MODIS tile grid horizontal 8/vertical 5, defined in Fig. S1) and in the southwestern US (lower, defined as the region within the box in Fig. 1a), during the dust seasons in 2005–2013. The absolute source areas for three types of land cover are shown in the left column, and the contributions (%) from individual land cover types to the total source areas are shown in the right column.
Time series of surface PM data at AQS and IMPROVE sites in
Phoenix. These observations are shown in their original temporal resolution
in
We first review the spatial and inter-annual variability of the drought
conditions during 2005–2013 in Arizona, in the dusty seasons (i.e., spring
and summer, from March to August), based on satellite NDVI (Fig. 1a) and
soil moisture (Fig. 1b) products. These observations show that
southwestern and south central Arizona, a region close to the Sonoran
Desert, is overall drier, with less greenness, than the rest of the state.
Most of these dry regions fall into two NOAA climate divisions (i.e.,
south central including the Maricopa and Pinal counties and southwest including the La Paz and Yuma counties). The mean PDSI values in
spring and summer in these two climate divisions were calculated (Fig. 1c), indicating moderate to severe dry conditions under warm weather in
these regions in the past decade, except for 2005 (extremely wet), 2008 (near
neutral), and 2010 (moderately wet). The PDSI values were then correlated with
the anomalies of satellite NDVI and soil moisture, defined as the ratio of
the annual mean value over the multi-year mean value. In general, Fig. 1c
shows that the PDSI-indicated drought conditions are consistent with those
based on the satellite NDVI and soil moisture products: i.e., with
correlation coefficients (
Gridded MODIS DOD maps are shown in Fig. 2a, b for each year's dusty season
during 2005–2013 and they were related to the satellite-based weather and
vegetation conditions (Fig. 1c). To exclude the locations occasionally
affected by long-range transported dust aerosols, data are shown only for the
grids in which DOD data are available on
The correlations between dust activity and drought conditions can be partially attributed to the dependency of dust source regions as well as the threshold wind velocity (i.e., the minimum wind velocity required to initiate soil erosion; Ravi et al., 2011, and the references therein) on the surface conditions in the western US. Figure 3 shows the MODIS-derived annual-mean dust source regions during the dusty season in 2005–2013 over several land use types (maps of the dust sources from three land use types are shown for selected wet and dry years in Fig. S1 in the Supplement). In most years, barren contributed the most (> 50 %) and cropland contributed the least (< 5 %) to the dust source regions, qualitatively consistent with the findings by Ginoux et al. (2012a) and Nordstrom and Hotta (2004). In general, larger dust source regions are found in drier years, with the strongest inter-annual variability from the open shrubland category. As an important nonerodible roughness element, the variable vegetation also modified the threshold wind velocity for the soil erosion. These findings suggest that dust emission modeling can be improved by using satellite land products, instead of those based on static land data. Similar land products of smaller footprints from newer satellite instruments, such as those from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument launched in 2011, can also be considered. In addition, soil moisture affects dust activity by modifying the threshold wind velocity, dependent on the soil type. Therefore, dust emission modeling can also benefit from careful evaluation and improvement of the soil moisture inputs using surface and satellite soil moisture measurements.
We then analyze the long-term surface PM measurements at the AQS and IMPROVE
monitoring sites in the Phoenix area. The time series of PM10 from
AQS/AirNow and IMPROVE sites in Phoenix are shown in Fig. 4a during
2005–2013 in their original temporal resolution. It is shown that the 24 h
mean IMPROVE PM10 data missed the extreme values (e.g., > 150
We take the dry and dusty year of December 2006–November 2007 (Fig. 4b) as an
example to introduce a novel approach of identifying dust events using
hourly observations. We first calculated the seasonal averages of PM10 and
wind speed in Phoenix based on the AQS PM10 and AZMET wind speed
observations. It is shown that in this year dominant westerly and easterly
winds in spring and summer carried much PM10 to Phoenix (Fig. S2),
whereas most PM10 in autumn and winter came from the north and east.
Hourly mean wind speed is highly correlated with the hourly maximum wind
speed (
The identified high dust periods were validated using the hourly AQS trace
gas observations. Figure S5 includes the scatterplots of AQS CO and NO
Evaluation of NAQFC CMAQ PM2.5 predictions during a recent dust storm event on 11 May 2014.
Independent IMPROVE and satellite observations can also assist in validating
these identified dust events. IMPROVE observations were only available on
We classified PM mass by wind direction observed at the Phoenix AZMET site,
which indicates the dominant westerly/southwesterly winds at the Phoenix
high dust times. Furthermore, based on the NARR meteorology, HYSPLIT air mass
trajectories were originated from 500 m above the ground level (a.g.l.) of
Phoenix at the identified dust periods to locate the origins of Phoenix
dust episodes and indicate the regional transport patterns. The endpoints of
these HYSPLIT backtrajectories are overlaid on the MODIS land
classification map (Fig. 5b), showing that most of the transported dust
particles were at the shrublands or deserts (primarily Sonoran, also
Chihuahuan) 0–12 h before arriving in urban Phoenix areas below
Multiple satellites identified a recent dust event (10–11 May 2014) in the
western US: as described by NOAA's HMS text product
(
The modeled PM2.5 was evaluated mainly for the Maricopa and Pima counties in
Arizona where both IMPROVE and AirNow observations were available during
this event. Time series of observed and modeled PM2.5 are shown in Fig. 6c and d. AirNow
observations indicate daily maxima to be over 100
This dust event was accompanied by a stratospheric ozone intrusion, as shown from a RAQMS model simulation that assimilated ozone columns from the Ozone Monitoring Instrument and ozone profiles from the Microwave Limb Sounder, as well as the AIRS satellite products (Figs. 7, S6). Descending dry air containing rich ozone enhanced the surface ozone concentrations in eastern Arizona and New Mexico at late morning and early afternoon times, when dust was strongly impacting the same locations. Observed surface ozone at the Petrified Forest National Park in eastern Arizona (AQS/AirNow site no. 040170119) at this time exceeded 65 ppbv. However, the current NAQFC CMAQ modeling system is unable to capture the exceptionally high ozone during stratospheric intrusion episodes, as the CMAQ lateral boundary conditions were downscaled from the monthly mean GEOS-Chem simulation in 2006 and no upper boundary conditions were used.
We developed dust records in Arizona for 2005–2013 using multiple observation data sets, including the MODIS level 2 deep blue aerosol product and in situ measurements at the surface AQS and IMPROVE sites in Phoenix. Both satellite and surface aerosol observations were anticorrelated with three drought indicators (i.e., NDVI, soil moisture, and PDSI). Dust events were stronger and more frequent in the afternoon times than in the morning due to stronger winds and drier soil; in addition, the Sonoran and Chihuahuan deserts were important dust source regions during the identified dust events in Phoenix. These findings suggest a potential for use of satellite soil moisture and land products to interpret and predict dust activity. We also emphasized the importance of using hourly observations for the better representation of dust events, and we expect that the hourly geostationary satellite observations will in future complement the current surface PM and meteorological observations, especially considering their broader spatial coverage. Continued development of products from the polar-orbiting satellites is also important in that they can provide higher-spatial-resolution observations from each swath due to their lower orbit level. Future efforts should also be devoted to better characterizing and attributing the observed dust, by integrating additional satellite measurements (such as ammonia as shown in Ginoux et al., 2012b) and in situ measurements of trace gases and aerosol compositions.
In a case study, we evaluated the capability of the current NAQFC CMAQ modeling system to capture the magnitude of aerosol concentrations and their temporal variability during a recent dust event. Sensitivity simulations from this modeling system assessed the impact of this dust event on western US air quality, and showed that dust contributed to > 70 % of the total PM2.5 in Arizona, on average. Satellite weather and land products are currently being integrated into dust emission modeling for future improvement of NAQFC's PM forecasting skill. Finally, we showed that this recent dust event was accompanied by a stratospheric ozone intrusion, and we emphasized the importance of representing both PM and ozone well under such conditions.
This study was supported in part by a NASA ROSES grant (NNX13AO45G). We thank Janae Csavina and William Sprigg for their constructive comments on an earlier version of the manuscript. We thank the useful information from the NASA Air Quality Applied Science Teams, SMAP early adaptor working teams, and the NAQFC and HYSPLIT groups at NOAA ARL. We also acknowledge the open access to the surface and satellite observations used (the sources of data are included in the main text). The views, opinions, and findings contained in this paper are those of the author(s) and should not be construed as an official National Oceanic and Atmospheric Administration or U.S. Government position, policy, or decision. Edited by: A. Sorooshian