Atmospheric Environment, 2000, 34, 5067-5078
PowerPoint Presentation of the paper:
http://capita.wustl.edu/CAPITA/CapitaReports/GlobVisIGAC/ContinentalAerosolExtinction/
Distribution of continental surface aerosol extinction based on
surface visual range data
Rudolf B. Husar*1, Janja D. Husar1 and Laurent Martin1
Center for Air Pollution Impact and Trend Analysis (CAPITA)
Washington University, St. Louis, MO 63130-4899, USA
Abstract
The global continental haze pattern was evaluated based on daily average visibility data at 7000
surface weather stations over five years, 1994-98. The data processing consisted of three broad
categories of filters: (1) validity of individual data points, (2) filters based on statistics for specific
stations, and (3) filters based on spatial analysis. The data are presented as the aerosol extinction
coefficient (Bext or haze) at the surface, seasonally aggregated over five years. The data reveal that the
continental haze is concentrated over distinct aerosol regions of the world. The haziest regions of Asia
are the Indian subcontinent, eastern China, and Indochina where the 75th percentile seasonal Bext
exceeds 0.4 km-1. In Africa the highest year around extinction coefficient >0.4 km-1 is found over
Mauritania, Mali and Niger. During December, January, February, the savanna region of sub-Saharan
Africa shows similar values. The haziest region of South America is over Bolivia, adjacent to the
Andes mountain range, with a peak during August-November (0.4-0.6 km-1). In North America and
Europe there are isolated haze pockets, such as the San Joaquin Valley in California and the Po River
Valley in the northern Italy. In many regions of the world the size, shape, and intensity of hazy pockets
is determined by the topographic barriers. A major qualification of this work is that the haze maps are
based on daily average visibility which emphasizes humid regions with hygroscopic aerosols (nighttime peak Bext) and de-emphasizes arid, dusty regions with daytime maximum extinction. Regional
haze episodes over several continental aerosol regions are illustrated by daily truecolor rendering of the
reflectance data from the SeaWiFS satellite.
Keyword: haze; visibility; aerosol; light extinction; scattering efficiency
1. Introduction
Atmospheric aerosols are major carriers in the biogeochemical cycle of sulfur, nitrogen, and trace
metals, as well as crustal elements. As the substances carried by particles pass through air, land and
water, they cause many effects, including changes in climate and weather, fertilization of the oceans
and land, acidification of lakes and health effects to humans. Unfortunately, the quantification of the
linkage between aerosols and these effects is severely hampered by the lack of consistent global scale
aerosol data sets. Recently, satellite remote sensing allowed the construction of aerosol maps over the
1
*Corresponding author. Tel +1-314-935-6099; fax +1-314-935-66145. E-mail address: rhusar@me.wustl.edu.
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oceans (e.g. Durkee et al., 1991; Husar et al., 1997; Deuze et al., 1999; Wang et al., 2000). There are
several successful efforts to derive short-term and regional aerosol optical thickness over the land
(Ferrare et al., 1990; Veefkind et al., 1998) but climatological global aerosol maps over continents are
currently not available. A very promising technique of aerosol detection over land is reported by the
POLDER research group (Deuze et al., 2000). The semi-quantitative absorbing aerosol index derived
from the TOMS ozone sensor also provides useful information about the spatial and temporal pattern of
dust and smoke events over the ocean as well as over land (Herman et al., 1997). This paper presents
the global pattern of seasonal horizontal extinction coefficient over the land, based on routine visibility
observations at more than 7000 synoptic weather stations.
2. Data source and processing methodology
2.1. Global Summary of the Day (SOD) database
This work uses the Global Summary of Day (SOD) database distributed by the National Climatic
Data Center (NCDC). The SOD data are derived from the data exchanged under the World
Meteorological Organization (WMO) World Weather Watch Program according to WMO Resolution
40 (Cg-XII) (WMO, 1996). More than 8000 stations' data are typically included each month. Data are
accessible through NCDC web server (NCDC, 1998).
The SOD data contain 18 surface meteorological parameters that are derived from the synoptic
hourly observations: mean temperature, mean dew point, mean sea level pressure, mean station
pressure, daily mean visibility, mean wind speed, maximum sustained wind speed, maximum wind
gust, maximum temperature, minimum temperature, precipitation amount, snow depth. The flags are
also included for the occurrence of fog, rain or drizzle, snow or ice pellets, hail, thunder, tornado/funnel
cloud. For the calculation of daily mean values it is required that at least four valid hourly readings are
available.
2.2. Surface aerosol extinction coefficient from visibility observations
The primary goal of the data preparation was to derive a local aerosol extinction coefficient, Bext, as
an index of surface aerosol concentration. Bext is derived from the surface visual range observations.
The visual range, or visibility, is the maximum distance at which an observer can discern the outline of
an object against a horizon sky. The observational procedures are specified in the guidelines issued by
the World Meteorological Organization (WMO, 1996a). Most visibility observations are made by
human observers in airport towers observing visual targets at known distance such as large buildings
and hills.
According the Koschmieder (1926) theory, the visual range of an object viewed against the horizon
sky, VR [km], is inversely proportional to the horizontal extinction coefficient, Bext [km-1],
Bext=K/VR. The Koschmieder constant, K, depends on the contrast threshold sensitivity (2-5%) of the
human eye as well as on the inherent contrast of the visible objects against the horizon sky (Middleton,
1952). The limitations in visual range estimates include the observers’ visual acuity, the number,
configuration, and physical and optical properties of the visible targets. The observer’s subjectivity
imposes a random component on the observed signal. The lower contrast of real targets compared to
black objects imposes a systematic underestimate of visual range. In addition, visibility is reported in
quantized units, depending on the availability of visible targets, i.e. an observation of 10 miles means
that the visual range is greater than 10 miles. Thus, the reported visual range is always an
underestimate of the actual visual range compared to ideal black target conditions.
In this report, we have taken K=1.9 in accordance with the data of Griffing (1980) which is about
half of the standard value of 3.92. The factor of two reduction of the Koschmieder constant
incorporates the fact that real visual targets are not black, they are frequently too small in angular size,
and are located only at quantized distances away from the observer. All non-ideal conditions tend to
reduce the apparent visual range and increase the value of the Koschmieder constant.
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In the absence of particles, the visual range of a Rayleigh atmosphere would be over 200 km, due to
scattering by air molecules (Bext=0.005 km-1 at 0.55 m wavelength). In fact, under those conditions,
the visibility of most distant objects near the surface would be limited by the curvature of the earth.
The visual range in the boundary-layer atmosphere is reduced mainly by the presence of aerosol
particles (dust, smoke, and haze) and hydrometeors. Hydrometeors are large droplets or crystals of
water (>5m) and they occur as rain, fog, clouds, and snow.
The major goal of the visibility data processing is to determine the magnitude of the haze by
eliminating the influence of naturally occurring hydrometeors, such as rain, snow, and fog. This is
accomplished by the application of a rather elaborate set of filtering algorithms described below. The
resulting weather-filtered extinction coefficient is referred to as Bext (km-1). In what follows, Bext will
be used interchangeably with the words haze and haziness.
2.3. Data processing
The global SOD data undergo extensive automated quality control by the Air Weather Service
(AWS), and over 400 algorithms are applied automatically to correctly 'decode' the synoptic data, and
to eliminate many of the random and systematic errors found in the original data. The details of the
algorithms are unknown to us. However, an evaluation of the SOD data revealed that many visibility
data points remained in the SOD data that were unsuitable for the present analysis. For this reason,
additional filters were developed for this work, consisting of three broad categories of filters: (1)
validity of individual data points, (2) filters based on statistics for specific stations, and (3) filters based
on spatial analysis of the data.
2.3.1. Single data point filters.
A missing Bext value in the SOD database arises when less than 4 valid hourly observations are
recorded for a day. In addition, observations were eliminated when either the temperature, dew point or
the precipitation data were not available. These variables are used in the weather filter and their
absence would prevent the identification of weather related obstructions to vision.
The weather filter eliminated visibility records when the obstruction to vision could be attributed to
weather, i.e. hydrometeors associated meteorological phenomena. Records that contain flags for rain,
fog, or precipitation >0.25 cm throughout the day were eliminated. Furthermore, the daily record when
the difference between temperature and dew point was <2.2 C were also eliminated. This temperature
spread corresponds to about 90% relative humidity. It is to be recalled that, both temperature and dew
point are daily averages reported in the SOD database. Finally, an “ice fog” and “blowing snow” filter
was applied that eliminated extreme cold and windy conditions (temperature <-29 C and wind speed
>16 km/hr). The latter filter was applied to eliminate low visibility conditions that occur frequently at
monitoring sites above the Arctic Circle and do not affect any observations at mid and low latitudes.
Evidently, the fog flag is somewhat ambiguous in the SOD database. Sometimes it refers to high
humidity, fog situation, in other circumstances the fog flag is applied when the visibility is less than a
few miles, regardless of the humidity. “Dry fog” (<75% RH) often occurs in tropical regions such as
Indonesia when smoke from biomass burning obscure the vision. When the temperature-dew point
difference exceeded 4 C (RH<75%), the fog flag was overridden and the visibility observations were
retained.
The intent of the spike filter was to eliminate observations that constitute a large one-day drop of
visibility (spike in extinction). Such short-term spikes in extinction coefficient are attributed to
meteorological obstructions to vision that did not get eliminated by the previous filters. A spike is
defined when the extinction coefficient on a given day is three times higher than the previous and next
day. This filter does not eliminate sudden but persistent changes in extinction.
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2.3.2. Statistical filters.
The statistical properties of a station accumulated over longer periods of time allow the
identification of unsuitable stations. The minimum number of valid observations per 3-month season
was set to be 10, i.e. stations having less than 10 valid data points were not accepted.
A major filter is the threshold filter. The significance of this filter arises from the fact that at many
remote locations all the good visibilities are reported as >12 km or >20 km. Hence, there is a threshold
visual range above which the visibility is not resolved. Stations that have visibility threshold <12 km
(Bext<0.16 km-1) were eliminated.
There are some monitoring sites where the visibility is reported to be low and constant from one day
to another, for example at 6 km. These stations were judged to be unacceptable because they do not
reflect the normal day-to-day fluctuations of aerosol induced horizontal extinction coefficients. An
indication of a time invariant extinction coefficient is when all the percentile values are identical over a
season. The temporal variability filter eliminated a station when the ratio of 75th and 50th percentile was
less than 1.07 or if the ratio of the 90th to 75th percentile was less than 1.1.
2.3.3. Spatial filters.
Additional 29 stations out of 9731 total were removed manually from the data set. These stations
were identified subjectively as “outliers” because they differed greatly from their surrounding stations.
Those stations were spatial “spikes” on geographic maps. Once an outlier station was identified the
daily time series over the four-year period was visually examined. All 29 stations have exhibited
anomalous behavior, including sudden but persistent jumps of extinction coefficient, or high and
changing threshold value. It is conceivable that some of the anomalous pattern was the result of actual
aerosol concentration peaks. However, these were considered less relevant to the present global
analysis.
2.4. Spatial distribution of qualified stations
The above-described filters have eliminated 2611 stations from the data set and the remaining 7120
valid visibility stations were used for the following global continental haze pattern analysis. The global
distribution of remaining visibility-monitoring sites is shown in Figure 1. The spatial coverage is
highest in Europe, former Soviet Union, China and US, where the meteorological stations are about
100-300 km apart. Throughout much of the remaining continents, the average station distance is on the
order of 200-400 km. The visibility monitoring data have low spatial coverage over northern Canada,
northern Siberia, western China, as well as over the central portions of South America, Africa, and
Australia. The low station density in the Sahara region and over northern Brazil and south Peru also
constitute a major limitation of the surface synoptic data set.
For some countries data are not available due to restrictions or communication problems. Most
notably, data are missing from large African countries, Nigeria, Zambia, Angola, Somalia, and
Botswana, as well as from Liberia and Sierra Leone. The data loss from Zambia, Angola, and Nigeria is
particularly unfortunate since these areas include major sources of biomass burning areas. In Asia, data
are missing from Iraq and Afghanistan.
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Figure 1. Visibility measurement station location density.
2.5. Statistical measure of Bext at each station
In this climatological analysis, the aerosol extinction coefficient was aggregated for four seasons.
For each season, e.g. December, January and February, the data were further aggregated over five years
between 1994-98. Due to inherent limitations of the data set (visibility threshold) the aggregation was
performed using non-parametric statistics (percentiles) rather than averaging. The specific parameter
that is plotted for the haze maps is the 75th percentile of the extinction coefficient. While this is
unconventional, it constitutes the safest approach in that it does not require any extrapolation or other
adjustments to the data. More conventional statistical measures, e.g. the mean, can be estimated as
follows: from previous research, e.g. Husar et al., (1979), the extinction coefficient is roughly log
normally distributed with the typical logarithmic standard deviation ranging between 1.6 and 3.4. For a
distribution with g=2.5, the 50th percentile is 0.5 times the 75th percentile, and the mean is 0.76 times
the 75th percentile.
The continental Bext data are plotted as global contour maps using standard inverse distance squared
weighing of stations. If there were no stations within 500 km, contour area was left blank (white).
2.6. Spectral reflectance data from the SeaWiFS satellite
Spectral reflectance data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) sensor
(McClain et al., 1998) allow rich pictorial illustration of the haze over the continents. The raw (Level
1A) Local Area Coverage (LAC), 1 km resolution SeaWiFS data were downloaded from the SeaWiFS
Program (McClain et al., 1998) and processed at Washington University. Some of the images were
obtained from the SeaWiFS website. The processing included removal the scattering by air molecules
using a Rayleigh correction procedure developed by (Vermote and Tanre, 1992) and transformation of
the pixel radiance values into spectral reflectance. The spectral reflectance (fraction of radiation
reflected) represent the combined reflectance from the land, water clouds and the ambient aerosol. The
reflectance data are rendered as truecolor images using the 0.412m (blue), 0.55m (green), and
0.67m (red) channels. The resulting images are shown in Figure 2.
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Figure 2. (a) Hazy regions of Southeast Asia from the SeaWiFS satellite data on December 28 and 29, 1999. The
spectral reflectance data were rendered as a truecolor digital image by combining the blue (0.412 m), green (0.55
m), and red (0.67 m) channels. The scattering by air molecules was removed. Bluish haze covers northern
India and eastern China. The stripes in the image arise from combining two days of data from the low-flying
polar orbiting satellite. (b) Haze aerosol over central South America shown by the SeaWiFS satellite data on
September 5 and 6, 1999. The stripes in the image arise from combining two days of data from the low-flying
polar orbiting satellite. (c) Haze aerosol over the Po River Valley on January 27, 1998. (d) Haze aerosol over the
San Joaquin Valley on December 25, 1997.
3. Spatial distribution of extinction coefficient by region
The global haze patterns are presented in four seasonal maps of extinction coefficient (Figure 3
a,b,c,d). The three-month seasons are centered in January, April, July, and October. The nature of the
aerosol pattern over several of the hazy regions are further illustrated with SeaWiFS satellite data for
specific days (Figure 2).
The main feature of the extinction coefficient maps is that aerosol pockets with high light extinction
are scattered over all continents. The extinction coefficient data (Figure 3) show that within each
continent there is at least factor of 5-10 variation in seasonal average aerosol extinction. It is also
evident that the haziness in the various pockets is highly seasonal, but with varying seasonal pattern.
The months of the peak extinction coefficient, the duration of the peak, as well as the seasonal
amplitude varies strongly from region to region.
In the following analysis the aerosol pattern for each of the continental regions is examined in more
detail. The evaluation consists of spatial pattern analysis, including extinction levels and gradients, and
identification of peak seasons. Attention is also given to the relationship between haze aerosol and
topography since many of the aerosol pockets are confined by mountain ranges.
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Figure 3a. Global extinction coefficient for December, January, February; b. June, July, August; c. Global extinction
coefficient for March, April, May; d. September, October, November.
3.1. Haze over Asia
The ground level extinction coefficient over Asia exhibits extreme variations between the pristine
clean air over the Tibet Plateau and the haziest global region in the low-lying valleys of the Indian
subcontinent, China, and Indochina (Figure 3). The region of most intense surface haze is found just
south of the Himalayas stretching from Northern Pakistan through India to Northern Bangladesh
(Figure 2a). The highest seasonal extinction coefficient in that region is recorded during December,
January, and February (DJF), while the lowest values occur in September, October, and November
(SON). Throughout the year the 75th percentile Bext exceedes 0.5 km-1, which corresponds to <4 km
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visibility. There is a strong gradient of extinction coefficient at the Himalayas mountain range. The
high elevation sites have much lower extinction coefficients, indicating that these sites are generally
above the shallow haze layer that covers the northern region of the Indian subcontinent. The specific
causes of the Indian haze are not known, but it geographically coincides with the highest regional
population density in the world.
Another hazy region exists over the low-lying valleys of northern Thailand and Laos. The peak
extinction levels in excess of 0.5 km-1 occur between December and May. Between June and
November the extinction level is <0.25 km-1. Closer inspection of the spatial pattern reveals that the
hazy regions of Indochina are also confined to the low-lying valleys, while higher elevation mountain
sites are above the haze layers throughout the year.
A unique region of elevated surface extinction coefficient is found over Indonesia and Malaysia.
During SON of 1994-98, the 75th percentile had the highest seasonal value in the world. Six stations in
the region had seasonal value in excess of 1 km-1, which correspond to visual range of about 2 km.
According the weather records, the extreme haze levels in the region are attributable to smoke due to
major forest fires that occur mainly during SON season and less frequently during March, April, May
(MAM) and SON, most notably during the 1997 fire season.
Within China the highest extinction coefficients are recorded in the Sichuan Basin in south-central
China. During December-May the extinction levels exceed 0.4 km-1 (5 km visual range). This circular
500 km wide basin is completely surrounded by mountain ranges, where the extinction coefficient is
below 0.1 km-1. The intense cold season haze is probably attributable to anthropogenic emissions and
poor ventilation in the confined basin.
Another confined basin of elevated extinction coefficient, is found over the Xinjiang Autonomous
Region in northwestern China. The highest seasonal values (>0.3 km-1) are found during March
through August. This arid region is dominated by frequent springtime dust storms. The spatial pattern
of the surface extinction coefficients indicates that climatologically the dust events are confined to the
Tarim Basin, while the adjacent monitoring sites in the surrounding mountains are outside the dust
layer.
The coastal zone of Eastern China stretching from Northern China to Vietnam is covered by diffuse
haze with moderate extinction coefficients between 0.25 km-1 in winter and 0.2 km-1 in the summer.
This region of the China-Korea seaboard is mostly flat and is bounded to the west by mountains.
Throughout the region elevated extinction levels are recorded, mostly in areas of high population
density.
3.2. Haze over Africa
Africa has several hazy regions, Sahara being the most prominent (Figure 3). Seasonally the highest
extinction coefficient over Sahara is recorded during Jun, July, and August (JJA), with 75th percentile
extinction coefficient in excess of 0.4 km-1 over Mauritania, Mali, and Niger. Unfortunately, the details
of the spatial pattern in this important aerosol region cannot be established since large portions of the
Sahara Desert are void of monitoring sites. However, the data indicate a clear decline of extinction
coefficients toward the Mediterran and toward the East Africa. Seasonally, the extinction coefficient
over Sahara is highest during spring and summer and lowest in the fall. In this region the weather
records indicate the cause of the obstruction to vision to be windblown dust.
Another haze region is located just south of Sahara in the sub-Saharan Sahel region that stretches
from Senegal to Sudan. The magnitude of the extinction coefficient shows a sharp peak during DJF
with average values exceeding 0.4-0.6 km-1. In the summer season, JJA, the regional average haze is
<0.2 km-1. The data coverage of this region is rather complete with the exception of Nigeria. It
indicates a rather uniform distribution of wintertime haziness throughout the sub-Saharan Sahel region.
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The region is free from major topographic features such that aerosol dispersion is unhindered by
topography.
3.3. Haze South America
The spatial pattern of extinction coefficient over most of South America is between 0.1-0.2 km-1
throughout the year (Figure 3) except over the more hazy central South America covering western
Brazil and Bolivia (Figure 2b). The surface haze is highest during September, October, November
(0.4-0.6 km-1) and declines to 0.2 km-1 throughout the rest of the year. The Andes mountain range to
the west presents a sharp boundary to the haze. Toward north, east, and south there is a gradual decay
of haze. Unfortunately, the spatial pattern of haze in South America can not be fully assessed because
of poor spatial coverage over much of Amazon basin. There is no evidence of local hot spots where the
extinction level is significantly higher than its neighborhood.
Data form adjacent stations at different elevations can reveal the vertical gradient of aerosol. For
example, four monitoring sites in Bolivia are located within a radius of 150 km on the eastern slopes of
the Andes at elevations 792 m (Camiri), 1998 m (Vallegrande), 2903 m, (Sucre), and 3934 m (Potosi).
The basin floor just east of the Andes is at about 500 m. The daily extinction coefficient for the four
monitoring sites between August and November 1995 is plotted in Figure 4. At the low elevation
monitoring sites (Camiri and Vallegrande), the hazy period is recorded between August 15 and October
1, while for the remainder of the year the extinction coefficient is about 0.1 km -1 or less. These
monitoring sites also show similar day to day variations indicating that they are exposed to the same
hazy air masses. Figure 4 indicates that the Camiri and the Vallegrande sites are located within the
thick haze layer, while the site at 2903 m is exposed to haze only occasionally. The Potosi site at 3934
m is not exposed to haze at all, indicating that the top of the Andes extrude from the central South
American haze into the haze free troposphere. The average extinction coefficient calculated for the
period August 20-September 20, 1995 for the four stations is plotted as a vertical profile in Figure 4b.
The vertical profile obtained in this manner corresponds to an aerosol scale height of 2600 m above sea
level (ASL).
The vertical distribution of the aerosol layer in the same region of South America was captured by
space-borne lidar measurements (Winker et al., 1996) on September 13, 1994, orbit 55. The lidar data
clearly depict a rather homogeneous haze layer extending from the basin floor to about 3000 m ASL,
which is comparable to the scale height derived from the average extinction coefficient at the four
vertically separated monitoring sites. It is remarkable that the aerosol layer is uniform over the entire
1000 km long vertical cross section along the spacecraft pass. It also clearly illustrates that the Andes
constitute a strong barrier to the dispersion of the South American smoke layers.
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Figure 4. (a) Daily extinction coefficient for four stations at different elevations in Bolivia. (b) Vertical profile of
average extinction coefficient. (c) Aerosol vertical cross section measured by the space-borne LITE sensor.
3.4. Haze over North America
Compared to other continents, North America (Figure 3) has low levels of haziness throughout the
year. Only Australia has lower levels of extinction coefficients. Increased haze is found in Central
America from Guatemala to southern Mexico during the spring season, March, April, May. High
elevation sites above 1500 m show low or moderate extinction coefficients.
Some haziness is observed over most of the eastern US. The extinction coefficient in the region is
relatively moderate (0.1-0.2 km-1). It is interesting that during all seasons, the haze is spatially uniform
over the 2000 km size area. This includes the major metropolitan areas of the Washington-Boston
corridor, as well as the industrial Ohio River Valley. Seasonally, the JJA period has the highest haze
values (0.25 km-1), while the transition seasons have the lowest levels. Throughout eastern US and
southeastern Canada the terrain is relatively flat, and the surface based haze layers cover the entire
territory. Possible exception is the crest of the Appalachian Mountains (above 1500 m) which extrudes
from the haze during the cold season.
Haze is also evident in California throughout the San Joaquin Valley (Figure 2c), and in the Los
Angeles basin. The monitoring sites in the Sierra Mountains show low extinction coefficient (<0.1 km1
) indicating that the haze layers in these air basins are confined to the low lying areas, while the
mountains extrude from the boundary layer haze. These are relatively small pockets of haze compared
to the hazy regions of Asia, Africa and South America that extend over several thousand kilometers.
3.5. Haze over Europe
Europe is geographically a small continent but it exhibits extreme variations in haziness. The
highest levels of haziness are found in the Po River Valley in northern Italy (Figure 5, Figure 2d).
Throughout the year the extinction coefficients there exceed 0.2 km-1. The haze peak is at 0.35 km-1
during the cold season and 0.25 km-1 in the warm season. The Po River Valley is confined by the Alps
and the prevailing winds tend to accumulate the haze in the basin.
Data form adjacent stations at different elevations also reveal the vertical gradient of haze aerosol.
For example, four monitoring sites in and above the Po RiverValley are located on the southern slopes
of the Alps at elevations 103 m (Milano), 237 m (Bergamo), 1322 m, (Bisbano Mountain), and 1638 m
(San Bernardino). The basin floor south of the Alps is at about 200 m. The monitoring sites at 103 m
and 237 m are evidently located within the thick haze layer, while the site at 1322 m is exposed to less
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intense haze. The San Bernardino monitoring site at 1638 m is not exposed to haze, indicating that the
top of the Alps are above the Po River Valley haze. The average extinction coefficient calculated for
the period November 1995-March 1996 for the four stations is plotted as a vertical profile in Figure 5b.
The corresponding aerosol scale height is about 1000 m ASL or 800 m above the basin floor.
Figure 5. Daily extinction coefficient for four stations at different elevations in Po River Valley, Italy. (b) Vertical
profile of average extinction coefficient.
The remaining part of Europe including the Iberian Peninsula and the British Isles show moderate
levels of haziness. Seasonally, the highest levels of haziness throughout Europe are observed during the
cold months, October-March. The gradient of haze is relatively mild and declines toward Scandinavia,
and toward southern Europe. Pockets of haze can also be found over the Pannonia and lower Danube
basins.
4. Limitations and qualification of the haze maps
In order to aid the further use of the above-presented global continental haze maps, several
qualifying statements are given below. The first qualification pertains to the role of daily averaging in
the SOD database. The Summary of the Day (SOD) database consists of one record of meteorological
observations per day. For most meteorological parameters the summary parameter is a daily average
calculated from the hourly or 3-hourly observations, provided that there were at least four hourly data
per day available. Most importantly, the visibility is arithmetically averaged throughout the day. Both
temperature and dewpoint are also given as daily average values. On the other hand, the 6 reported
weather flags (fog, rain, snow, hail, thunder, tornado) indicate the occurrence of these weather events
during any part of the day. At most geographic locations there is a strong diurnal cycle of visual range,
as well as of relative humidity, and the relationship between the two is highly non-linear. Replacing the
full diurnal cycle of meteorological parameters with a single daily value causes significant loss of
information about the diurnal cycle, that is relevant to the interpretation of the global visibility data.
The consequences of the daily averaging are illustrated for different regions of the world. For
example, in Milan Italy (Figure 6) during the wintertime in wet and humid conditions the visual range
decreases from 10-20 km during the day, to <2 km during the night and early morning hours. The
resulting daily average visibility reported in SOD is 6.2 km, which is less than half of the daytime
visibility values. An opposite diurnal cycle is found at Nouakchott, Mauritania on the Atlantic coast of
Mauritania, where the reported visibility is high (10 km) throughout the night, but declines throughout
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the day to 3.5 km, due to wind blown dust. The resulting daily average visibility reported in SOD is
also 6.2 km. In these extreme examples, for identical daily average SOD visibility, the noon visibility
(or extinction coefficient) may differ by a factor of three.
Figure 6. Diurnal visibility pattern for Milan, Italy and Nouakchott, Mauritania. The two stations have the same
daily average visibility, but distinctly different diurnal cycle.
In regions dominated by daytime dust such as Sahara, Arabia, and western China, the SOD derived
extinction maps will underestimate the noon extinction coefficient. On the other hand, in humid regions
dominated by hygroscopic aerosols that grow at night the SOD-derived extinction coefficient will
overestimate the noon extinction coefficient. It is conceivable the high SOD-derived extinction values
for India and Indochina are partly due to this nighttime amplification effect. It is to be noted that the
above discussed diurnal representatives is a problem shared by all monitoring data that have a single
daily value, e.g. polar orbiting satellites. However, at this time it is unclear whether the metric based on
noon observations is superior to the daily average reported here.
Another disadvantage of averaging visibility throughout the day arises from the existence of
visibility thresholds. For example, at Nouakchott the maximum reported visibility is 10 km, while in
reality the nighttime visibility could have been 20 km or higher, as illustrated schematically in Figure 6.
Accordingly, the true daily average visibility could have been 8-10 km compared to the reported 6.2
km. Regrettably, hourly data such as used in the illustration Figure 6, are only available to a 1500
station subset of the global synoptic database. The detailed exploration and analysis of the hourly
global visibility data is currently in progress.
It is tempting to overlay the satellite-derived oceanic aerosol maps and the complimentary
continental haze maps reported here. However, the global continental haze maps derived from daily
average visibility are not directly comparable to the existing satellite derived oceanic aerosol maps
(Husar et al., 1997; Deuze et al., 1999; Wang et al., 2000) for several reasons. First, the visibility data
provide the surface extinction coefficient, while the satellite-derived data represent vertical integrals.
The surface extinction coefficient could only be compared to the satellite aerosol optical depth if the
daily aerosol scale height was known throughout the continents. In Figures 4 and 5 it is illustrated that
the aerosol scale height may vary by at least a factor of three (1-3 km) depending on the region and
season. The actual spatial distribution of the aerosol scale height is not known. The second limitation
in comparing the satellite and visibility data is due to the above discussed incompatibility of the
sampling and averaging times. Finally, the visibility data are collected on both cloudy and cloudless
12
sky conditions, while the satellite detectors only provide backscattering aerosol data over cloud-free
areas.
The extinction coefficient derived from visual range observations can be related to the concentration
of fine particles, thus the above haze maps may serve as rough estimates of particle mass
concentrations. For dry conditions, i.e. relative humidity below 60%, the extinction to mass relationship
depends on characteristic particle size and to some extent the particle refractive index. A review of the
extensive literature on the light extinction per unit particle mass (mass extinction efficiency) yields the
relatively coherent relationship as shown in Table 1. The lowest mass extinction efficiency of 0.5-0.8
m2/g is associated with windblown dust since dust particles are 1-5 m in diameter and they do not
scatter light efficiently. Smoke from open fires is reported to have mass extinction efficiency in the 3-5
m2/g range. Evidently, haze particles scatter most efficiently at 4-6 m2/g. These efficiency factors
allow the estimation of aerosol mass concentration from the measured extinction coefficient. For
example in India under winter hazy conditions (Bext = 0.5 km-1, mass extinction efficiency = 4 m2/g)
the approximate aerosol concentration would be 125g/m3. For similar surface extinction in the dusty
West African desert (0.7 m2/g) the estimated aerosol concentration would be 700 g/m3.
Table 1. Extinction efficiency per unit particle mass for different locations and aerosol types.
Location
Remarks
m2/g
References
Tenerife
dust
0.5
Maring et al., 1999
DUST
Barbados
dust
0.8
Li et al., 1996
Seoul, Korea
dust
0.8
Chung and Yoon, 1996
AVERAGE
0.7
SMOKE
HAZE
Australia
South America
South America
Porto Velho, Brazil
Ciuba, Brasil
Ciuba, Brasil
Maraba, Brasil
AVERAGE
fire
fire
fire
Abbeyville, LA
Luray, VA
Lewes, DE
Lewes, DE
Lenox, MA
K-Puszta
AVERAGE
summer
summer
summer
winter
summer
summer
local
aged
4.2
2.9
3.0
3.9
3.1
4.1
3.2
3.5
Eccelston et al., 1974
Reid and Hobbs, 1998
Kaufman et al., 1998
Reid et al., 1998
Reid et al., 1998
Reid et al., 1998
Reid et al., 1998
3.9
5.0
4.8
3.7
5.8
6.0
4.9
NAPAP, 1990
NAPAP, 1990
NAPAP, 1990
NAPAP, 1990
NAPAP, 1990
Meszaros et al., 1998
Haze, smoke and to some extent dust particles are hygroscopic, i.e. they absorb an increasing
amount of water with increasing relative humidity. The role of the hygroscopicity is most pronounced
during the rainy cold seasons when the relative humidity is high and over regions where the haze is
composed of hygroscopic sulfates, nitrates, and condensed organic substances, rather than lesshygroscopic soil dust. While the role of humidity in surface extinction is extremely important, a
detailed evaluation of the role of hygroscopicity is beyond the scope of this report.
The global haze maps presented above were derived from daily average visibility data. Other diurnal
Bext metric, such as taking the noon data only, may differ from the presented results by up to a factor
13
or two. Since it is not clear what is the most relevant diurnal metric, and recognizing the inherent
limitations of human visual range estimates, it is recommended that the presented maps are used as
semi quantitative measures (within a factor of two) of the global surface aerosol extinction pattern.
Nevertheless, the 7000 station data are meaningful to delineate the spatial extent and the seasonal
variation of atmospheric haze over the continents.
4.1. Future work
Full quantification of the global four dimensional (x, y, z, t) aerosol pattern will require combined
instrumental measurement from remote sensing satellites and from surface measurements.
Unfortunately, routine quantitative techniques for the retrieval of a full set of aerosol properties over
land from satellites are not yet available, though it is an area of active research (King et al., 1999).
Even when such techniques will be developed and used operationally, visibility data will complement
the satellite observations and surface based aerosol optical thickness measurements (e.g. AERONET,
Holben et al., 1998) since it represents the horizontal extinction coefficient at the surface, while the
other sensors respond to the vertical integral. Also, visibility data are available throughout the day and
night, including conditions when clouds obscure the underlying aerosol layers from the satellite
detectors. Proper fusion of satellite data, surface visibility and sun photometer data and augmented by
occasional particle size distribution, morphology and chemical composition characterization could yield
a comprehensive global estimate of the global aerosol pattern and properties. Without such
comprehensive global aerosol data fusion, evaluating the role of aerosols in climate and in the biogeochemical cycling of materials will remain highly uncertain.
Acknowledgments
The assistance of Drs. Bret A. Schichtel and Stefan R. Falke are gratefully acknowledged. This
research has been funded in part by the United States Environmental Protection Agency (EPA) through
CX-825834 (OAR-OAQPS). Mention of trade names or commercial products does not constitute
endorsement or recommendation for use.
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