Atmospheric Effects on Insolation In The Brazilian Amazon: Observed Modification of Solar 
Radiation by Clouds and Smoke and Derived Single Scattering Albedo of Fire Aerosols 
J.S. Schafer1, B.N. Holben2, T.F. Eck3, M.A. Yamasoe4, P. Artaxo4 
1 Science Systems and Applications, Inc. (SSAI), Lanham, MD 20706 
2NASA/GSFC, Biospheric Sciences Branch, Code 923, Greenbelt, MD 20771 
3University of Maryland-Baltimore County, Goddard Earth Sciences and Technology Center 
4Departamento de Fsica Aplicada, Instituto de Fsica da Universidade de So Paulo 
Rua do Mato, Travessa R, 187, So Paulo - SP - Brazil CEP 05508-900 
ABSTRACT: Five aerosol and solar flux monitoring sites were 
established in Brazil for the Large Scale Biosphere-Atmosphere 
Experiment in Amaznia (LBA) project. The first two sites were 
developed in the states of Rondonia and Mato Grosso in January 
1999, while the others were initiated in September 1999 in 
Amazonas, Para and near Brasilia (later re-located to Acre). 
Daily insolation (PAR and total solar) for 1999 and nine months 
of 2000 was determined from flux measurements and the daily 
fraction of theoretical cloud-free, background-aerosol insolation, 
B(day), was evaluated for each site. Observed daily shortfall 
(MJoules . m-2 . Day -1) of PAR insolation due to clouds and 
aerosols (relative to modeled values for background-aerosol), and 
the instantaneous reductions of PAR irradiance due to high AOT 
smoke events are presented for 1999 at Alta Floresta. The ratio of 
PAR flux to total solar flux (PAR fraction) was examined for all 
atmospheric conditions during 1999, and the observed dependence 
of this parameter on column water vapor and smoke AOT was 
quantified. No significant relationship with cloud amount (as 
quantified) was found. 
Instantaneous PAR irradiance measurements and concurrent, 
cloud-cleared aerosol data from collocated CIMEL 
sunphotometers were used with a radiative transfer model to 
investigate the optical properties of smoke aerosols during the 
burning season. In particular, the single scattering albedo was 
evaluated in the PAR spectral range for AOT440nm values ranging 
from 0.8 to 3.0. These estimates were compared with the 
operational retrievals of the same parameter from algorithms 
developed by AERONET for CIMEL sunphotometer radiance 
measurements. 
1. INTRODUCTION 
The limited number of aerosol and solar flux 
monitoring networks and the relative scarcity of operational 
sites in many large regions of the world creates a significant 
source of uncertainty in attempts to fully understand the 
global dynamics of earth-atmosphere interactions. The 
prevalence of these gaps in regional measurements 
complicates the task of effectively modeling the processes 
that drive our present climate, let alone forecasting 
accurately the future consequences of human activities. A 
network of five aerosol and flux monitoring sites was 
developed in Amaznia for this study as a part of the Large 
Scale Biosphere-Atmosphere Experiment in Amaznia 
(LBA) project to assist with filling in some of these data 
gaps by characterizing the aerosol and solar radiation 
climatology of one of the world's most vital ecosystems. 
The products of long-term environmental monitoring efforts 
such as these have applicability to improving satellite remote 
sensing of the earth, forest ecology and agricultural research, 
human health studies and, most prominently, global climate 
modeling projects. 
Atmospheric aerosols modify climate by direct 
absorption and scattering of solar energy and by secondary 
means when fine mode aerosols act as auxiliary cloud 
condensation nuclei (CCN), thereby decreasing average 
cloud droplet size and enhancing planetary albedo [Charlson 
and Heintzenberg, 1995; Charlson, 1997; Facchini et al., 
1999]. Additionally, absorbing aerosols may also modify 
climate by the semi-direct effect [Hansen et al., 1997] 
wherein heating of the aerosol layer reduces cloud cover by 
increasing atmospheric stability or by evaporating clouds 
[Ackerman et al., 2000]. Highly absorbing smoke aerosols, 
such as are regularly produced in great quantity during the 
annual biomass-burning season in Amaznia, have an effect 
on the regional radiation budget and climate dramatically 
larger than that observed in even the most polluted of urban 
environments. Climate model designers understandably 
desire better quantification of the absorption properties 
(single scattering albedo) of tropical aerosols in the visible 
1
spectrum [Toon, 1995] as well as their seasonal and interannual 
variability. Also, the importance of establishing 
"background" aerosol optical thickness (AOT) levels for 
pristine environments (e.g. the wet season, rural Amazonian 
aerosol), characterizing strong regional sources (e.g., 
Amazonian fire centers) sufficiently for modeling purposes 
[Schwartz et al., 1995], and better understanding the 
observed correlation of heavy aerosol loadings (pollution or 
biomass burning) with precipitation tendencies [Rosenfeld, 
1999, 2000] are widely recognized. Many of these issues 
are being explored by the NASA-funded aerosol monitoring 
network (AERONET) whose broad reach (75+ 
sunphotometers worldwide) is continually extending the 
global record of aerosol optical properties [Holben et al., 
1998; Holben et al., 2000]. The five CIMEL 
sunphotometers used in this study are a subset of this 
network. 
The disparity in southern Amaznia between the 
wet season and dry (biomass-burning) season aerosol 
regimes is profound. The measurements of Holben et al. 
[1996] have shown that daily average aerosol optical 
thicknesses (AOT) increase by greater than an order of 
magnitude in southern Amaznia between the wet and dry 
season. Predictably, these elevated atmospheric levels of 
smoke aerosol produce substantial reductions in both 
photosynthetically active radiation (PAR) [Eck et al., 1998] 
and total global radiation. This raises many questions about 
how such prolonged periods of diminished insolation (PAR, 
in particular), might impact the development of plant life 
routinely subjected to these conditions. The spectral region 
designated as the PAR band (400-700nm) is of special 
interest as this parameter is the primary determinant of 
photosynthetic rates, and thus, of biomass accumulation 
[Monteith and Elston, 1993]. While the effect of reduced 
PAR intensity is highly species-dependent, it is known that 
many crops, when growing at or near their potential rate, are 
fully utilizing all available solar energy, and thus may suffer 
diminished productivity if sunlight levels were appreciably 
lower [Lawlor, 1995]. The persistent smoke-haze from the 
1997 Indonesian fires was observed to suppress 
photosynthesis in three tree species due to high AOT values 
and the associated increase in atmospheric pollutant levels 
(Davies and Unam, 1999). Further, it is believed that local 
forest productivity models in humid zones at least, are 
commonly more sensitive to solar radiation inputs than to 
any other climate drivers (Aber and Freuder, 2000). Making 
a similar assessment in southern Amaznia is complicated 
by the tendency of plants in sub-equatorial, seasonallyhumid 
tropics to exhibit growth that is water-limited during 
parts of the driest months (Monteith and Elston, 1993), an 
effect that might supersede PAR deprivation effects. Of 
course, an initial step in any effort to determine the 
biological consequences of large PAR reductions over a long 
duration is to quantify the seasonal shortfall of diurnal 
insolation in this important spectral band that results from 
biomass-burning practices that consistently subject 
2 
thousands of kilometers of land to a thick pall of persistent 
smoke-haze conditions. Eck et al. [1998] estimated that high 
smoke aerosol loadings in southern Amaznia during 
August-September caused reductions in PAR irradiance of 
25-40% with an assumption that cloud amount was not 
changed by the presence of aerosols. 
The terrestrial remote-sensing community also 
stands to benefit substantially from extensive ground-based 
monitoring of both aerosols and solar radiation. Knowledge 
of AOT values representative of remote, "background" 
levels is needed for atmospheric corrections of satellite 
imagery, and provides higher confidence in retrieved 
vegetative indices (e.g., NDVI). Improved parameterization 
of biomass burning aerosols is essential for satellite-driven 
surface radiation models which are known to currently 
overestimate shortwave (SW) irradiance by poorly 
accounting for highly-absorbing smoke aerosols. Large 
discrepancies between measured and modeled SW irradiance 
of 20-40 W/m2 [Wild, 1999] and 40-80 W/m2 [Konzelman 
et al., 1996] have been documented in connection with 
prevalent savanna fires in Africa, while model 
overestimations of incoming solar radiation up to 44% are 
reported for regions of the Brazilian Amazon and Cerrado 
affected by biomass burning [Pereira et al., 1999]. 
Similarly, quantification of the PAR fraction (ratio of global 
PAR insolation to total solar insolation) and its variability 
due to fluctuations of precipitable water and AOT allows for 
estimation of surface PAR flux from existing and future 
datasets (satellite-derived or surface measurements) of 
global shortwave radiation. 
Finally, numerous health-related issues are 
associated with the effects of elevated aerosol levels due to 
annual biomass burning in Amaznia. These include 
concerns that vectors for diseases such as malaria will have 
increased active periods due to sunlight reduction (Mims et 
al., 1997), general questions about the effect of prolonged 
exposure to smoke (and associated tropospheric ozone) on 
respiratory functions, and concern that the acidity of 
rainwater will be increased by rainout of fire-generated 
aerosols, though this acidity enhancement effect has not 
been observed in recent studies of regions influenced by 
transported smoke from Indonesian fires (Radojevik and 
Tan, 2000; Balasubramanian and Begum, 1999). 
In this paper we present the data and analysis of 
AOT, PAR and total solar fluxes for several LBA / 
AERONET sites in southern and central Amaznia for 1999 
and nine months in 2000. In particular, the analysis focuses 
on the effects of water vapor, clouds and aerosols on flux 
and additionally on the retrieval of aerosol absorption 
information from synthesis of the simultaneous AOT and 
flux data. 
2. INSTRUMENTATION AND SITE DESCRIPTIONS 
Five aerosol particle and solar flux monitoring sites 
were established in Brazil for the LBA project (Figure 1).
The first two sites were developed in the states of Rondonia 
(Abracos Hill) and Mato Grosso (Alta Floresta) in January 
1999, while the others were initiated in September 1999 in 
Amazonas (Balbina), Par (Belterra) and near Brasilia. The 
Brasilia site was re-located to Rio Branco, Acre, in July 
2000. 
Each site is comprised of a CIMEL sunphotometer 
and two flux sensors--a Skye-Probetech SKE 510 PAR 
(photosynthetically-active radiation) Energy sensor (spectral 
range: 400-700 nm) and a Kipp and Zonen CM-21 
pyranometer (305-2800 nm) for measuring the total solar 
spectrum. The flux sensors record the instantaneous 
irradiance at 1-minute intervals. The automatic 
sunphotometers (model CE-318A) were manufactured by 
CIMEL Electronique and their properties are discussed at 
length in Holben et al. [1998]. Each is equipped with narrow 
bandpass filters in the visible and near infrared with center 
wavelengths at 340, 380, 440, 500, 670, 870, 940, and 1020 
nm. The filters are ion-assisted deposition interference filters 
with bandpass (FWHM) of 2 nm for the 340 nm channel, 4 
nm for the 380 nm channel and 10 nm for all other channels. 
The CIMEL sunphotometer provides aerosol optical 
thickness (AOT) at each of these wavelengths, except for the 
940 channel which is used to derive total column water 
vapor. In addition to the direct solar irradiance 
measurements that are made with a field of view of 1.2, 
these instruments measure the sky radiance in four spectral 
bands (440, 670, 870, and 1020 nm) along the solar principal 
plane (i.e., at constant azimuth angle, with varied view 
zenith angles) up to 9 times a day and along the solar 
almucantar (i.e., at constant solar zenith angle, with varied 
view azimuth angles) up to 6 times a day. A 
preprogrammed sequence of measurements is taken by these 
instruments starting at an air mass of 7 in the morning and 
ending at an air mass of 7 in the evening. During the large 
air mass periods direct sun measurements are made at 0.25 
air mass intervals, while at smaller air masses the interval 
between measurements is typically 15 minutes. The 
almucantar measurements are taken at 0.5 intervals near the 
Sun (within 6), and increase from 2 to 10 intervals away 
from the solar position. It is these sky radiance 
measurements that are used to retrieve additional column 
aerosol properties including volume size distribution, phase 
function, real and imaginary component of refractive index, 
effective radius and single scattering albedo that are 
routinely computed with the AERONET inversion 
algorithms [Dubovik and King, 2000b]. 
Calibration of field sunphotometers is achieved by 
a transfer of calibration from reference instruments that are 
calibrated every 2-3 months by the Langley plot technique at 
Mauna Loa Observatory, Hawaii. The total uncertainty in 
AOT retrievals for field instruments has been estimated at 
0.01-0.02, with the uncertainty increasing with shorter 
wavelengths [Eck et al., 1998]. 
Calibration of the PAR sensors was accomplished 
by using in-situ comparisons to a radiative transfer model on 
3 
selected optimal days. The 6S [Vermote et al, 1997] model 
we employed is based on the successive order of scattering 
method. Field days used were of minimal aerosol-loading 
(AOT500nm < 0.1) under cloud-free conditions. Such aerosol 
levels are sufficiently low to render an exact knowledge of 
the absorption properties unimportant for computing clearsky 
insolation. The factory calibration was not used as the 
manufacturer (Skye Probetech) states an accuracy of 5% 
(generally < 3%) and we desired a higher confidence in the 
PAR irradiance. The difference between factory calibration 
factor and model-derived factor for the five sites ranged 
from 0-5%, and thus was within the accuracy stated by the 
manufacturer. 
Due to additional complicating factors, 
such as water vapor influence, thermal equilibrium issues, 
and also, because of the greater degree of accuracy (2%) 
provided by the manufacturer (Kipp and Zonen), the factory 
calibrations were used for the pyranometers. 
3. ANALYSIS 
Daily integrated insolation (PAR and total solar) for 
1999 was determined with instantaneous 1-minute sampling 
interval flux measurements for the 5 LBA sites. In this 
paper, the term insolation (PAR or total solar) will indicate 
the quantity of solar energy arriving at the surface in a given 
time interval (e.g., MJoules . m-2 . day -1), while irradiance 
will be reserved for the rate of solar energy per unit time and 
area (e.g., Watts . m-2) We also evaluated the fraction of 
theoretical cloud-free, background-aerosol insolation, B(day), 
for each day at all sites based on modeled daily integrated 
values using the 6S radiative transfer model. 
fB(day) = 
INSOLATIONday ; : [AOTx SSAx] 
INSOLATIONday SSA 9 0 5 : [AOT= = 0 0 . ; . 7] 
The fluxes for background aerosol conditions were estimated 
using an aerosol optical thickness (AOT500nm) of 0.05, 
column water vapor of 2.0 cm and an imaginary component 
of refractive index of 0.003. The annual cycle of PAR and 
total solar daily insolation for background aerosol conditions 
were modeled with the 6S radiative transfer model. Then, 
the ratio of each daily-integrated measurement to the 
predicted cloudless sky, background value for the date and 
site of interest was evaluated. Comparison of observed 
values of daily insolation on optimal, cloud-free, low-aerosol 
days with the modeled values for the clean atmosphere 
conditions show an agreement of 1-2%, and provides 
confidence in the calibration of the instruments. 
Evaluating this received fraction of cloud-free, low 
AOT insolation, allows for a direct comparison of the 
relative reductions of incident solar flux at each site due to 
cloud and aerosol effects without regard for latitudedependent 
discrepancies (solar zenith angle). A linear 
interpolation algorithm was implemented to account for gaps 
in the 1-minute sampled flux data, based on average pre- and 
post gap observations. The errors associated with such
interpolation were also examined by applying the algorithm 
to artificially introduced data gaps for days when the flux 
record was complete. Days of all sky conditions were used, 
including clear sky, partial cloud cover and overcast days. 
For cloudless conditions, the anticipated errors resulting 
from small to moderate data gaps (1-2 hours) were of 
negligible effect on the computed daily totals, while even for 
days with highly variable clouds the error for a 1 hour gap is 
expected to average less than 2% and not exceed 5%. For 
cloudy and variably cloudy conditions these errors should be 
random (unbiased) and thus average out on a multi-day time 
scale. In addition, the data record reflects only days where 
the interpolated insolation comprised less than 10% of the 
total daily value. 
500nm 

3.1 Annual Insolation Trends 
The seasonal trend of the B(day) weekly averages 
for total solar insolation (pyranometer) is quite similar at 
both Alta Floresta and Abracos Hill during 1999 (Figure 2a). 
The initial months show daily reductions that reflect the 
prevalent cloud cover associated with the wet season, 
reaching a minimum of 0.45-0.50 in February. A steady 
increase in the fraction of expected insolation accompanies 
the transition to the dry season approaching a maximum 
weekly average of 0.95, before the biomass burning 
commences. These high B(day) levels are the combined 
result of minimal cloud cover and low, background aerosol 
conditions (average AOT500nm: 0.065). The rapid decline of 
the B(day) values that subsequently begins is due exclusively 
to the highly elevated smoke aerosol loadings resulting from 
burning activity. It is noteworthy that the reductions in this 
3-4 week interval (circled in the plot) are comparable to 
those observed in the March-May interval of the wet season 
due to persistent, broken cloud cover. At Alta Floresta, one 
week during this period of heavy smoke (average AOT 
=1.7) experienced a prolonged reduction of daily integrated 
PAR insolation of approximately 35% that corresponds to a 
typical daily shortfall of 3-4 MJ . m-2 in relation to 
background aerosol conditions (Figure 2b). Single day 
reductions can exceed even these levels (Figure 3) as on 
Sept. 4, 1999 at Alta Floresta (AOT500nm ~ 2.1). 
The sites at Balbina and Belterra were installed in 
September of 1999 and a comparison of the first complete 
year of data (Sept. 1999 - Sept. 2000) with the same interval 
at Alta Floresta reveals some differences (Figure 4). Balbina 
and Belterra are proximal to the equator (1.9 S and 2.6 S, 
respectively) and experience more persistent cloud cover and 
a less intense dry season than either Alta Floresta (9.9 S) or 
Abracos Hill (10.8 S) which are further south. No 
differences are apparent in the wetter months (January- 
March), with all sites exhibiting an average B(day) of 0.55 to 
0.6. As would be expected, a pronounced difference occurs 
in the dry season (pre-burning) period (June-July) when the 
B(day) at the southern Amazonian sites increases to a typical 
value of 0.85-0.9. The equatorial sites as well see an 
4 
increase in fraction of expected background insolation 
during this phase, but the effect is muted (B(day) average: 
0.65) due to the perseverance of tropical convection. The 
measured daily insolation reductions for 2000 at Alta 
Floresta and Abracos Hill track closely the pattern observed 
at these sites in 1999, with corresponding weekly average 
B(day) from the 2 years generally agreeing within 10% at a 
given site. However, the burning season in 2000 was 
delayed and subdued by an unusually wet pre-burning phase, 
and this presumably created a divergence between the two 
years. Unfortunately, transmitter problems at both sites 
limited the initial months of pre-burning/burning season data 
in 2000, making difficult the direct examination of this 
difference. 
Annual median values of B(day) in 1999 were 0.74 
for Alta Floresta and 0.68 for Abracos Hill. By comparison, 
the first complete year at the equatorial sites (September 
1999 - September 2000) produced values that were not 
greatly different, with both Balbina and Belterra recording 
annual medians of 0.68, while Alta Floresta was 0.73 for the 
same interval. The median B(day) at Alta Floresta was 
greater despite experiencing much higher daily average 
AOTs during the dry seasons (AOT440nm > 1.8) than at 
Balbina or Belterra, where the daily average AOT440nm never 
exceeded 0.8. The most obvious distinction between the 
southern Amazonian and equatorial sites is in the incidence 
of cloud-free or minimally cloudy days. Whereas 28% of 
the days at Alta Floresta had a B(day) value greater than 0.9 
during this year interval, the percentage of days surpassing 
this threshold was only 8% and 12% at Belterra and Balbina, 
respectively. 
3.2 PAR Fraction 
The ratio of PAR irradiance to total irradiance was 
examined for all atmospheric conditions. This ratio is 
sensitive to column water vapor, clouds and AOT. As water 
vapor is minimally absorbing in the PAR spectral interval, 
the result of increasing atmospheric water vapor is an 
increase in the PAR fraction, independent of other factors. 
Conversely, the dramatic rise in quantity of sub-micron 
radius emission particles during biomass burning episodes 
diminishes the transmitted PAR irradiance more strongly 
than the irradiance measured by the pyranometer since the 
resultant aerosol optical depth is much higher at the shorter 
(visible) wavelengths to which the PAR sensor is sensitive. 
Thus, increases in AOT due to smoke are always associated 
with a decrease in PAR fraction. The seasonal trend of day 
PAR fraction is shown for Alta Floresta in 1999 (Figure 5). 
For these purposes, the PAR fraction was simply computed 
as the ratio of the daily-integrated values of PAR to total 
flux. This ratio method was used because it is intrinsically 
weighted more heavily during the higher solar zenith angles 
when the irradiance levels are greater. Taking the daily 
average of all the simultaneous pairs of PAR and 
pyranometer observations would have weighted each
measurement ratio equally, even for low sun conditions that 
contribute negligibly to the daily insolation, and might also 
be influenced by the difference in response time of the two 
sensors. For the stated accuracy of the measured daily 
insolation (< 3% for PAR, 2% for total solar insolation), the 
fractional uncertainty in the computed PAR fraction would 
be approximately 5%. This indicates that the absolute 
uncertainty would vary from 0.02 to 0.025 over the observed 
range of PAR fractions. 
The plot of daily average PAR fraction values for 
1999 depicts a relatively consistent ratio for the wet season 
(January-March), though a small decline is apparent as the 
Amazonian dry season develops toward the end of the preburning 
interval (approaching day 205). This minor effect is 
likely a product of the diminishing column water vapor 
(from 5 cm to 2.5 cm). The initiation of the burning season 
produces dramatic decreases in PAR fraction, occasionally 
producing substantially lower ratios during the days of 
highest smoke AOT. The combination of these 2 factors 
effect a pronounced minimum in the August-September 
interval with daily PAR fractions as low as 0.39, or 0.08 less 
than the average for the middle of the wet season. During 
the pre-burning phase (median daily AOT500nm: 0.08), the 
average daily PAR fraction was 0.465  0.005, while the 
same parameter averaged 0.44  0.02 for days within the 
burning phase (median daily AOT500nm: 0.95). For 
comparison, the seasonal PAR fraction values when 
calculated as the average of all instantaneous flux 
measurement pairs from the year (solar zenith < 40) were 
essentially the same as those found using ratios of daily 
integrals (pre-burning: 0.467; burning: 0.448). The lower 
observed column water vapor during the peak burning 
interval (pre-burning phase median: 4.82cm; burning phase 
median: 3.48cm) accounts for some of the difference in daily 
PAR fraction, but the major cause is the elevated smoke 
aerosol levels. Note that the day-to-day variability of the 
PAR fraction is much greater during the burning phase as 
well (range of daily values: 0.39-0.48) than in the preburning 
interval (range: 0.45-0.48), as the smoke levels 
fluctuate from day to day. The average PAR fraction stated 
here for the pre-burning phase is in general agreement with 
observed values from previous studies [Blackburn and 
Proctor, 1983; Rao 1984; Papaioannou et al.,1996; Zhang et 
al., 2000], though differences in techniques and assumptions 
(spectral definition of PAR spectrum; day vs. hourly ratios; 
different sensor types) and climatic variations (column water 
vapor; aerosol type and optical depth) make these 
observations less commensurable. 
3.2.1 PAR Fraction and Clouds 
Since these daily integral PAR fractions are based 
on full days of observations, they reflect various sky 
conditions from overcast to fully clear. The influence of 
clouds on PAR fraction is seen to be minor relative to that of 
water vapor and to AOT changes in particular, generally 
modifying the ratio by less than 1 percent in the annual plot. 
5 
This is in contrast to simulations of cloud optical depth on 
PAR ratio [Pinker and Laszlo, 1991] which predicted a 
substantial increase in PAR fraction for cloudy conditions. 
The record of scientific literature based on empirical results 
is of varied opinion on this matter. Several studies have 
suggested a moderate or large increase in PAR fraction 
under cloudy conditions [Blackburn and Proctor, 1983; 
Rodskjer, 1983; Rao, 1984], while other studies indicate 
small or negligible increases of 2 percent or less [Suckling et 
al., 1975; Papaioannou et al., 1993, 1996]. 
Rao et al. [1984] found a significant increase in 
PAR fraction only for sky conditions with fractional cloud 
cover > 0.85, while the observations acquired in conditions 
between 0.15 and 0.85 fractional coverage showed 
negligible difference from the 'clear' category (0.447 vs. 
0.443). Various studies used different parameters to 
designate cloudy conditions (fractional cloud cover, 
sunshine duration), and the influence of water vapor or 
atmospheric aerosol variability on the derived PAR fraction 
averages was not typically quantified. Often, year or multiyear 
averages of PAR fraction are presented without 
addressing sufficiently the implications of annual variations 
in these atmospheric parameters (water vapor, AOT). 
Consider a climate regime similar to that of the Brazilian 
sites: During the wet season, column water vapor levels 
routinely surpass 5.5 cm, while this parameter in the dry 
season is commonly only 2.5 cm. If one examined yearly 
averages of PAR fraction only, then the average for the 
'cloudy' cases would be based on data disproportionately 
sampled from the wet season because the dry season has 
much less frequent cloud development. In this scenario, the 
effect of these higher wet season water vapor amounts alone 
could be falsely interpreted as an increase of PAR fraction 
values by clouds. 
To further investigate the effect of clouds on daily 
PAR fractions at the Abracos Hill site, the calculated B(day) 
values were employed as an approximate indicator of cloud 
amount, as this parameter reflects the combined effect of 
cloud fraction and cloud optical thickness. The relationship 
between daily PAR fraction and B(day) values was examined 
for all days prior to the burning phase (February-June 1999). 
Since AOT was low (< 0.1 at 500nm) for all the days 
considered, the dominant influence on daily PAR insolation 
was clouds. While the B(day) parameter does not provide 
information about the spatial distribution of the clouds 
(fractional coverage), it is obvious that the minimum B(day) 
values (as low as 0.2) designate days when received PAR 
was substantially diminished by optically-thick clouds. 
Similarly, the numerous days with B(day) near 1.0 were 
certainly days of little or no cloud cover. Even so, there is 
no significant trend (R2: 0.04) of daily PAR fraction with 
B(day). This is true as well when these same data are 
grouped into bins of equivalent column water vapor 
amounts. Frouin and Pinker [1995] found a similar lack of 
correlation between surface-measured daily PAR fraction
and fractional cloud cover, although they attributed this to 
the use of daily-integrated fluxes, stating, "at this time scale 
the PAR fraction variability is small". 
In order to explore the possibility that computing 
the PAR fraction as the ratio of daily-integrated PAR and 
total solar flux masked the effect of clouds, the 
instantaneous PAR fraction was plotted for three narrow (5 
or 10 degree) solar zenith angle bins for flux measurement 
pairs over the same pre-burning interval at Alta Floresta in 
1999. The solar zenith angle ranges used were 0-10, 20-25 
and 35-40, and the number of days included in each bin was 
dependant on the seasonal changes in solar geometry. The 
smallest solar zenith bin had a range of 10 degrees to 
increase the quantity of qualifying observations. The 0-10 
degree bin represented averages from February-March 1999 
at Alta Floresta, the 20-25 degree bin covered February- 
April, and the 30-35 degree bin spanned the full pre-burning 
(February-June) interval. The number of measurement pairs 
in each selected solar zenith bin, ranged from 3092 (SZ: 0- 
10) up to 7914 (SZ: 35-40). 
For each qualifying 1-minute, instantaneous PAR 
measurement, the ratio of the measured flux to the 
theoretical, clear-sky flux for background aerosol conditions 
at the relevant solar zenith angle (6S modeled data) was 
determined, B(ins). The PAR fractions were then plotted 
versus the corresponding B(ins) values. The results for the 
35-40 degree solar zenith range are shown in Figure 6a. In 
this case, since 1-minute flux pairs were being used, the 
B(ins) parameter was more difficult to interpret as a measure 
of cloud magnitude. Large B(ins) near 1.0 may demonstrate 
either cloud-free conditions or enhanced PAR irradiances 
during broken cloud cover due to reflections from verticallydeveloped 
cloud edges. This is a common effect and B(ins) 
often reach 1.2 or more. Still, the observed low B(ins) 
values, some lower than 0.1, clearly result from surface PAR 
fluxes that are strongly reduced by cloud. Despite this, there 
is no trend evident for any of the three solar zenith angle 
groups, and the linear correlation coefficients for all 3 
groups are insignificant (SZ: 0-10 R2= 0.003; SZ: 20-25 R2= 
0.005; SZ: 35-40 R2= 0.0002). The 35-40 degree plot is 
most relevant in this regard since it includes data from the 
wet season as well as numerous observations during the 
early dry, pre-burning season (ie., sunny days). Even so, the 
median PAR fraction for all cases occurring in the cloudiest 
conditions (B(ins): 0.0 to 0.1) was 0.464 which is negligibly 
different from the median value for the 0.9 to 1.0 B(ins) range 
(0.466), with the only apparent effects of clouds on PAR 
fraction being greater variability in this parameter. This 
greater variability is likely due to instrumental response 
differences evident for 1-minute comparisons because the 
response time of the PAR sensor (10 ns) is much shorter 
than that of the pyranometer (< 5s). This effect will average 
out for a full day of instantaneous PAR fraction 
measurements, and is negligible for daily PAR fractions 
3.2.2 PAR Fraction and Water Vapor 
6 
computed as the ratio of daily integrated values of PAR to 
total insolation. 
An additional plot (Figure 6b) characterizes the 
prevalent enhancements of surface irradiance above 
expected clear sky values at Alta Floresta due to reflection 
from edges of vertically developed clouds. A histogram of 
calculated B(ins) values for all qualifying PAR irradiance 
data from four 5 degree solar zenith ranges (0-5, 5-10, 20-25 
and 35-40) was generated with the Alta Floresta 
measurements to demonstrate the fractional contribution 
from observations in every B(ins) bin. The great number of 
enhanced observations is a prominent feature for every solar 
zenith range, indicating that at least for the tropical 
convective regime, conditions that produce such elevated 
surface flux events are persistent and that the resulting 
increases in PAR flux are often substantial. As mentioned 
above, these data reflect a range of days from 1999 that 
increases with solar zenith angle so that while the 0-5 range 
only includes data from February, the data presented for the 
35-40 zenith bin extends to observations through June. This 
inclusion of pre-burning dry season data is reflected in the 
distinct 0.95-1.0 B(ins) spike for the 35-40 plot which results 
from the contribution of many cloud-free observations in 
June. Even so, all four zenith intervals have a significant 
fraction of enhanced observations with a PAR irradiance 
increase of 10% or more observed for 19% of the 
measurements in the 0-5 zenith range, and 24% of the 
measurements in the 35-40 zenith range. The clear sky PAR 
flux used to determine B(ins) values were calculated based on 
assumed background aerosol conditions, which is in good 
agreement with the actual aerosol optical thickness values 
measured over this interval (AOT500nm: 0.06  0.02). 
A pair of selected days demonstrates the minimal 
effect of clouds on the PAR fraction. We considered two 
dates which had comparable column water vapor amounts 
(diurnal range: 3.7-4.3 cm), and very low daily average 
AOT500nm (0.07 for both). Of these, May 22nd was a 
completely cloud-free day, while the cloud conditions on 
May 19th transitioned from heavily overcast to broken 
cumulus, yet both demonstrated a PAR fraction of 0.46-0.47 
(Figure 7). 
The effect of water vapor on PAR fraction was 
quantified at Alta Floresta for all low aerosol days 
(AOT500nm < 0.1). Observed AOTs on these days were 
sufficiently low to have a negligible influence on PAR 
fraction variability. Daily PAR fraction was computed as 
above and plotted versus daily average water vapor. (Figure 
8a) In addition, instantaneous measurements (based on the 1- 
minute flux sensor observations) of this parameter were 
plotted against simultaneous (within  1 minute) water vapor 
measurements from the collocated CIMEL sunphotometer 
(Figure 8b). The solar zenith range was small for the 
instantaneous observations included here (SZ: 35  5) to
minimize variability due to changing solar geometry. These 
instantaneous irradiance ratios were matched only to water 
vapor retrievals drawn from a sunphotometer database of 
cloud-screened CIMEL observations (Smirnov et al., 2000), 
although this screening algorithm only ensures that the sky 
near the solar position is free of clouds. Despite the 
difference in methods, the two derived relationships are very 
similar. The modeled (6S model) PAR fraction for an 
assumed AOT500nm of 0.1 is also shown on this plot and 
agrees with the observed trend within the uncertainties of the 
flux measurements. A dependence of the form A ln(x) + B 
was suggested by the model (where x is column water vapor 
amount in cm) and a best-fit trendline of this type indicates 
the reduction in PAR fraction due to a 1 cm increase in 
precipitable water ranges from 1% to 0.5%, with the effect 
diminishing for higher values of column water vapor. 
3.2.3 PAR Fraction and Smoke Aerosol 
To examine the substantial reduction in PAR 
fraction due to smoke aerosol, measurements made 
exclusively during smoke events were considered. 
Observations acquired during the season of burning activity 
which exhibited an Angstrom wavelength exponent greater 
than 1.0 and an AOT500nm of greater than 0.5, determined 
with simultaneous, cloud-screened AOT retrievals from the 
CIMEL, were considered to be associated with a smoke 
event. The associated precipitable water amounts were 
between 3 and 4 cm, typical of the dry season, and a limited 
range of solar zenith angles (35  5) was allowed. For the 
qualifying measurements, the instantaneous PAR fraction 
was plotted versus the associated AOT determined from the 
CIMEL sunphotometer (Figure 9). The resulting regression 
indicates a significant reduction in PAR fraction (0.028) for 
an increase in AOT500nm of 1.0. The correlation of PAR 
fraction with smoke AOT is very strong (0.94) and indicates 
a PAR fraction of 0.39 for an AOT500nm of 2.5 which is 
markedly lower than average, wet season PAR fraction 
measurements (0.47). 
While the influence of smoke AOT fluctuation on 
the PAR fraction is much more dramatic than that of 
precipitable water changes, this is due in part to the wider 
range of values of this parameter, and its greater temporal 
variability. Whereas column water may range annually 
from 2cm to 6cm, a factor of 3 change, the AOT observed in 
the wet season commonly differs by factor of 50 from that 
measured at the height of burning. Even within the burning 
season the smoke AOT may fluctuate by a factor of 5 or 
more within a few days, and this is evident in the variability 
in the PAR fraction during this period. 
3.3 PAR Attenuation by Smoke Aerosols 
Clearly, based on examining the PAR fraction, flux 
in the PAR spectral region is diminished by smoke 
disproportionately relative to the total solar spectrum. It is 
of interest, then, to quantify this reduction of PAR irradiance 
by biomass burning in absolute energy units. In the same 
7 
manner as for the instantaneous PAR fraction plots, PAR 
sensor measurements were matched to simultaneous, cloudscreened 
CIMEL observations for a limited range of solar 
zenith angles (25-35). For each matched observation, the 
PAR irradiance expected for background aerosol conditions 
(background aerosol: AOT500nm: 0.05) was determined with 
the 6S radiative model. To minimize any effect of water 
vapor variability, the PAR was modeled using the observed 
(CIMEL-derived) column water vapor to compute each 
expected clear sky flux, though the range of precipitable 
water was quite small during the burning season. For 
consistency, the radiative transfer code used to model these 
fluxes was the same one used for the in situ PAR sensor 
under low AOT conditions. 
The observed PAR irradiances were then subtracted 
from the modeled values to estimate the reduction in PAR 
(W m-2) due to smoke aerosol. This procedure was applied 
to three Amazonian sites (1999- Alta Floresta and Abracos 
Hill; 1998- Concepcion) during their respective burning 
seasons (Figure 10a). The observed PAR reductions were 
quite similar at all locations, indicating an approximate loss 
of 86 W m-2 at an aerosol optical thickness of 1.0 (500nm). 
The efficiency (regression slope of PAR reduction vs. AOT) 
of smoke attenuation was also comparable, ranging from - 
53. W m-2 to -62 W m-2 for a unit change of AOT500nm. For 
comparison, the average reduction in PAR irradiance at the 
same site in the peak wet season interval February-April 
(SZ: 20-25) was -122 W m-2 for observations under all sky 
conditions. Given that the median AOT500nm during the 
interval of heaviest smoke is near 1.0, the typical reductions 
in PAR irradiance resulting from biomass burning are seen 
to be about 70% of the average reductions due to clouds 
during the middle of the wet season. 
These rates of PAR reduction by smoke are in good 
agreement with modeled PAR reductions (Figure 10b) using 
CIMEL-derived smoke volume size distributions selected by 
AOT. The best agreement with the observed data, in terms 
of PAR attenuation rate by smoke aerosol is for the cases 
with an input SSA equal to 0.95 and 0.90, which predict a 
PAR attenuation rate of -55.0 W m-2 and -65.0 W m-2 
respectively for a unit change in AOT500nm.These are 
reasonable single scattering albedos for the smoke of this 
region and generally compare well with CIMEL retrievals of 
this parameter from the same period (detailed in the Single 
Scattering Albedo Section below). Figure 10c displays the 
same data as in Figure 10a, with the reduction of PAR 
expressed as a fraction of modeled PAR flux for background 
conditions. 
3.4 Single Scattering Albedo Estimation 
For CIMEL observations that were evaluated to be 
cloud-free by the AERONET cloud-screening algorithm, 
concurrent aerosol data from collocated CIMELs were used 
to investigate the optical properties of smoke aerosols. PAR 
flux data (1-minute sampling interval measurements) were 
matched with CIMEL observations acquired within  2
440nm 
minutes. The CIMEL-derived atmospheric parameters of 
AOT, Angstrom wavelength exponent, and column water 
vapor were then associated with the nearly simultaneous 
PAR measurements and the data were filtered to reject cases 
with solar zenith angle greater than 40 degrees, AOT 
less than 0.8 and wavelength exponent less than 1.0. The 
Angstrom wavelength exponent was computed as a linear 
regression of ln(AOT) vs ln(wavelength) for the 
wavelengths (440,500,675 and 870 nm). This procedure was 
applied to the burning season data at Alta Floresta and 
Abracos Hill (1999) and Concepcion, Bolivia (1998). The 
final matched data sets of PAR and corresponding CIMEL 
measurements contained 48 observations for Alta Floresta 
(from 14 different days), 60 at Abracos Hill, and 183 at 
Concepcion. 
These data were used as input to the 6S model 
using the observed atmospheric properties during each flux 
measurement as well as the appropriate solar zenith angle 
and day of year. The aerosol size distribution was also an 
input parameter and was based on an average of distributions 
derived from the set of optimal CIMEL retrievals during 
year of 1999 at Abracos Hill, Brazil (Figure 11). The size 
distributions were grouped into 15 bins according to AOT 
value, and the appropriate size distribution was 
automatically utilized in 6S based on the given AOT. Based 
on each set of observed properties, the expected flux was 
modeled for a range of imaginary refractive indices (ni) 
0.000 to 0.061, to determine the trend of PAR flux for 
increasingly absorbing aerosols. These refractive indices 
represent a range of single scattering albedo (SSA) of 
approximately 0.75 to 1.0. A trendline was fitted to the 
resultant modeled fluxes and assumed SSA, and then the 
measured PAR flux was used to interpolate the theoretical 
SSA for each observation. The SSA estimates acquired are 
assumed to effectively represent the absorption properties at 
approximately 550nm, which is the central wavelength of 
the PAR sensor response curve (400-700nm). 
The basic principles of this technique are identical 
to those employed by Eck et al. in similar studies in Brazil 
and Africa (Eck et al., 1998, 2000), though the 
implementation has been modified. 
The single scattering albedos retrieved using the 
PAR measurements were generally similar at the 3 sites, 
perhaps due to the common nature of the biomass source 
(forest) and the prevalent wind patterns of the season that 
routinely transports smoke great distances in a westerly 
direction along the site transect. Since many of the retrieved 
SSA are often derived from a single day, statistics for daily 
average values were also compiled. The number of days 
with at least one SSA estimate was 17 at Alta Floresta, 9 at 
Abracos Hill, and 16 at Concepcion. Based on these daily 
averages, the median SSA for the sites were between 0.89- 
0.91 with a standard deviation of 0.03 or less. Considering 
all the individual retrievals, the estimates of SSA at all 
locations ranged from a minimum of 0.86-0.87 to a 
those that met the above criteria. 
differences. These include: 
transfer model used for this procedure. 
which the flux sensors are sensitive. 
conditions. 
to an underestimation of the irradiance. 
8 
maximum of 0.93-0.96 (Table 1). The typical standard 
deviation of SSA for an individual day was less than 0.01. 
The CIMEL sunphotometer radiance measurements 
are also operationally processed with a new inversion code 
(Dubovik et al., 1998, 2000a; Dubovik and King, 2000) to 
produce estimates of SSA at four wavelengths (440nm, 
500nm, 670nm and 870nm). The radiance inversion 
technique is most accurate when AOT440nm is greater than 
0.4, solar zenith angle is larger than 45, and the skyradiance 
fitting error is less than 5%. Therefore, CIMELderived 
SSA products used in this study were restricted to 
SSA estimates derived from the PAR flux method were 
found to consistently provide values lower than the sky 
radiance by an average of 0.03 (Figure 12). This discrepancy 
is within the expected uncertainty of the methods, estimated 
at 0.03 for both the sky radiance method and the PAR flux 
method. A number of known factors could produce 
  Non-simultaneity of observations: PAR-derived 
retrievals were all acquired for solar zenith angle < 
40 while those derived from sky radiance 
measurements were all restricted to solar zenith angle 
> 45 
  Absolute calibration of sensors: PAR accuracy ( 
3%); sky radiance accuracy (5%). The importance of 
absolute PAR calibrations is diminished by 
calibrating the sensors versus the same radiative 
  Non-uniformity of smoke: When variable smoke 
plumes are present, the AOT observed by the CIMEL 
may not be representative of the full sky conditions to 
  Cloud contamination: The cloud-screening algorithm 
applied to the CIMEL measurements only ensures a 
cloud-free circumsolar region. PAR measurements 
associated with these observations may potentially be 
affected by peripheral clouds. This is less of a 
problem than it could be given the general 
suppression of clouds during heavy burning 
  Cosine errors: Although the PAR measurements were 
restricted to solar zenith < 40 (where cosine errors 
are minimal), as AOT increases, the incident 
hemispherical flux upon the sensor becomes more 
isotropic. This, in turn, increases the relative 
contribution of flux at low incidence angles that are 
characterized by poor cosine response, and may lead 
The last of these points may be the most plausible for 
the possible negative bias to the SSA estimates derived from 
PAR measurements. If the flux is underestimated, it creates 
an appearance of additional absorption that is manifested as
a lower SSA. Contrary to this hypothesis, however, no trend 
with AOT is evident in the discrepancy between the sky 
radiance and flux method. In fact, the correlation between 
the derived products of the two methods is quite strong, both 
for daily average SSA values and for retrievals that are 
relatively coincident in time. While the different solar 
geometry restrictions preclude simultaneous retrievals of the 
two methods, the Concepcion site had 15 cases when each 
type of retrieval was acquired within a 1.5 hour span. For 
this set of data, the correlation coefficient was 0.95, 
indicating that the two techniques were similarly responsive 
to the absorption properties of the aerosol (Figure 13). Even 
for the comparison of daily average SSA estimates there was 
strong correlation (0.76), although the retrievals by each 
technique may have been obtained many hours apart. 
4. CONCLUSION 
This study has focused on characterizing the 
substantial influence of clouds and aerosols on the solar 
energy reaching the ground on a year-round basis. The 
effects of smoke aerosol alone during the heaviest months of 
biomass burning have been observed to produce reductions 
in insolation comparable to those resulting from persistent 
cloud cover in the latter phase of the wet season. 
Instantaneous reductions of PAR irradiance from the values 
expected for background (pre-burning) aerosol conditions 
are shown to average 86 W/m2 for smoke aerosol optical 
depths of 1.0, with reductions of ~55 W/m2 indicated for a 
unit change of AOT. Since smoke aerosol optical depths 
routinely average greater than 1.0 for several months of the 
year, the implications for vegetation productivity warrant 
further investigation. 
Modification of the spectral signal of incoming 
solar radiation during smoke intervals was examined as 
manifested in changes to the PAR fraction. Smoke aerosol 
was found to be the prominent factor causing variability in 
this parameter, at times lowering the ratio by more than 0.1 
from typical, pre-burning values, indicating a 
disproportionate reduction of PAR relative to the full solar 
spectrum. This has consequences for researchers who may 
estimate PAR or total solar insolation by applying an fixed 
PAR fraction assumption to predict one flux from the other. 
For a common approximation of PAR as comprising 50% of 
the total solar signal, this could produce errors of 10% or 
more in derived flux during long periods within the dry 
season. 
The effect of water vapor upon PAR fraction was 
also found to have a definite, albeit minor influence which 
should not be ignored. Notably, the modification of this 
ratio by the presence of clouds was not observed to be 
significant based on the indicators of cloud presence used in 
this study. However, the clouds were observed to produce 
frequent, often large increases in the irradiance 
measurements above expected clear sky values. The PAR 
flux data for a five month period at one site revealed that 
enhancements of PAR irradiance of 10% or greater occurred 
9 
in 24% of the measurements due to reflections from 
vertically developed cloud edges. 
The single scattering albedo (SSA) of dry season 
smoke aerosol was also estimated using PAR irradiance 
measurements and the 6S radiative transfer code, as well as 
with CIMEL sunphotometer sky radiance inversions. 
Comparison of the two techniques at 3 sites revealed a 
discrepancy with SSA values determined from PAR fluxes 
(daily average SSA: 0.89-0.91) uniformly lower than those 
derived from the CIMEL sunphotometer (0.93), although the 
correlation of the two methods was quite strong (R2: 0.89). 
ACKNOWLEDGEMENTS We thank the site managers 
responsible for maintaining the instrumentation suites and ensuring 
continuous, high quality data sets. These colleagues include 
Edilson Bernardino de Andrade (Alta Floresta), Rosivaldo Lelis da 
Silva and Fabricio Berton Zanchi (Abracos Hill), Evan Everton 
(Belterra) and Sr. Zairon (Balbina). 
P. Artaxo acknowledges financial support from FAPESP 
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Single Scatter Albedo Estimates (~550nm) from PAR 
and Sunphotometer Measurements at 3 sites (dry season) 
Abracos Hill 
1999 
From PAR: 
Median (day average) 
St Dev (day average) 
Mininum (all points) 
Maximum (all points) 
From Cimel: 
Median (day average) 
St Dev (day average) 
Alta Floresta 
1999 
0.91 
0.02 
0.87 
0.95 
0.93 
0.02 
0.90 
0.03 
0.87 
0.96 
0.93 
0.01 
Concepcion 
1998 
0.89 
0.03 
0.86 
0.93 
0.93 
0.02
FIGURE CAPTIONS 
Figure 1: Site map of LBA (Alta Floresta, Abracos Hill, Balbina, Belterra, Rio Branco) 
and AERONET (Concepcion) aerosol and flux monitoring sites. 
Figure 2: a) Record of the ratio of measured to modeled daily (pyranometer) insolation. 
The modeled insolation is for assumed cloud-free, background-aerosol conditions. Data 
are weekly averages of daily ratios at Alta Floresta and Abracos Hill in 1999. b) 
Computed shortfall in daily PAR insolation relative to that expected for cloud-free, 
background-aerosol conditions. Data are weekly averages of daily values (1999). c) 
Modeled daily PAR insolation for Alta Floresta for cloud-free, background-aerosol 
conditions. 
Figure 3: a) Measured PAR irradiance on September 4th, 1999 at Alta Floresta exhibiting 
flux reduction by heavy smoke. Also shown, PAR irradiance modeled for cloud-free, 
background-aerosol conditions, and modeled for actual observed smoke AOT values. b) 
Computed fraction of modeled irradiance for background-aerosol conditions and 
observed instantaneous PAR fraction (ratio of PAR irradiance to pyranometer irradiance 
with 1-minute values). 
Figure 4: Record of the ratio of measured to modeled daily (pyranometer) insolation at 3 
LBA sites from September 1999 to September 2000.
Figure 5: a) Daily PAR fraction for Alta Floresta (1999) computed as the ratio of daily 
PAR insolation to daily total (pyranometer) insolation. b) Daily average aerosol optical 
depth (AOT440nm) c) Daily average precipitable water vapor (cm). 
Figure 6: a) Instantanous PAR fraction (1 minute values) versus observed fraction of 
modeled PAR irradiance for cloud-free background-aerosol conditions (measured PAR / 
modeled PAR (background)). Data represent all observations with solar zenith range 
between 35 and 40 degrees during the period Feb-Jun 1999 at Alta Floresta. b) Histogram 
of relative incidence of fraction of background (B(ins)) values (measured PAR irradiance / 
modeled PAR (background)) for four different solar zenith angle ranges from Alta 
Floresta during the pre-burning season in 1999. 
Figure 7: a) Measured PAR irradiance on May 19th and May 22nd at Alta Floresta in 
1999. b) Computed instantaneous PAR fraction for the same days based on 1-minute 
measurement pairs. 
Figure 8: a) Daily PAR fraction versus daily average precipitable water (cm) for days of 
low aerosol optical depth (day average AOT500nm < 0.1) at Alta Floresta in 1999. b) 
Instantaneous PAR fraction (AOT500nm < 0.1) versus simultaneous precipitable water 
vapor measurements. Modeled PAR fraction dependence on column water vapor is also 
shown for an assumed AOT500nm of 0.1.
Figure 9: Instantaneous PAR fraction versus simultaneous CIMEL sunphotometerderived 
AOT measurements. 
Figure 10: Computed PAR irradiance reductions from modeled PAR irradiance values for 
assumed cloud-free, background-aerosol conditions at 3 sites during 1998 (Concepcion) 
and 1999 (Alta Floresta, Abracos Hill) biomass burning intervals b) 6S-modeled 
reductions in PAR irradiance for smoke aerosol with 3 different assumed single scattering 
albedo (SSA) values c) Same as a) with the reductions expressed as fractional values. 
Figure 11: Aerosol volume size distributions averaged by AOT range for use in 
irradiance modeling procedures. Averages are based on the full record of volume size 
distribution retrievals derived from CIMEL radiance measurements at Abracos Hill in 
1999. 
Figure 12: a) Single scattering albedo (SSA) estimates based on PAR flux measurements 
and CIMEL sky radiance inversions at Alta Floresta in 1999. Qualifying data are 
restricted to those satisfying AOT, solar zenith and retrieval error constraints described in 
the text b) Same as a) for Abracos Hill data from 1999 c) Same as a) for Concepcion 
data from 1998. 
Figure 13: a) Correlation of single scattering albedo (SSA) estimates derived with PAR 
flux measurements and CIMEL sky radiance inversions. Data compared are estimates 
based on observations acquired within the same 1.5 hour interval.
Table 1: Statistics of single scattering albedo (SSA) estimates from PAR flux 
measurements and CIMEL sky radiance inversions for 3 sites. Statistics are based on 
daily averages of SSA estimates evaluated for Concepcion (1998), Alta Floresta (1999), 
and Abracos Hill (1999).
1 
Alta Floresta 
0.9 Abracos Hill 
0.8 
0.7 
0.6 
0.5 Predominately 
Smoke 
0.4 
a) 
0.3 
25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345 365 
0 
Alta Floresta 
Abracos Hill 
b) 
-1 
-2 
-3 
-4 
-5 
-6 
-7 
-8 
-9 
25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345 365 
14 
13 
12 
11 
10 
c) 
9 
25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345 365 
Julian Day (1999) 
Fraction of Background MJ. m-2 Day-1 MJ . m^-2 . Day^-1
500 
a) 
450 
400 
350 
300 
250 
200 
150 
100 
50
0 
12 11 
0.70 
b) 
0.65 
0.60 
0.55 
0.50 
0.45 
0.40 
0.35 
11 
W/m2 
6S (clean) 
6s (smoke) 
PAR 
Alta Floresta Sept 4th, 1999 
Average AOT (500nm): 2.2 
21 20 19 18 17 16 15 14 13 
TIME (GMT) 
Fraction of Background 
PAR Fraction 
21 19 17 15 13 
TIME (GMT)
1 
0.9 
0.8 
0.7 
0.6 
0.5 
Alta Floresta 
0.4 Balbina 
Belterra 
2000 1999 
0.3 
75 100 125 150 175 200 225 250 275 265 290 315 340 365 25 50 
Julian Day 
Fraction of Background
0.50 
0.48 
0.46 
0.44 
0.42 
0.40 
a) 
0.38
25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345 365 
3.0 
b) 
2.5 
2.0 
1.5 
1.0 
0.5 
0.0 
25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345 365 
6
5
4
3
2 
c) 
1 
25 45 65 85 105 125 145 165 185 205 225 245 265 285 305 325 345 365 
Julian Day (1999) 
Daily PAR Fraction Precipitable Water (cm) AOT440 nm
% of Observations Instantaneous PAR Fraction 
0.52 
0.51 
0.50 
0.49 
0.48 
0.47 
0.46 
0.45 
0.44 
0.43 
a) 
0.42 
0.2 0 
0.18 
0.16 
0.10 
0.08 
0.06 
0.04 
0.02 
0.00 
b) 
0.00 
b) 
0.10 
0.20 
0.14 
0.12 
0-5 
0.30 
0.40 
0.50 
0.60 
Alta Floresta Feb-June 1999 SZ: 35-40 
0.70 
0.80 
0.90 
1.00 
N=7914 
1.10 
1.20 
R2 = 0.0002 
1.30 
1.40 
1.4 1.2 1 0.8 0.6 0.4 
Instantaneous Fraction of Background PAR Irradiance 
5-10 
20-25 
35-40 
FOBins (PAR)
600 
19-May 500 
22-May 
400 
300 
200 
100 
a) 
0 
14 13 
0.49 
19-May 0.48 
22-May 
0.47 
0.46 
b) 
0.45 
14 13 
Instantaneous PAR Fraction PAR (W / m^2) 
16 15 
TIME (UTC) 
16 15 
TIME (UTC) 
18 17 
18 17
0.5 
a) 
0.49 
0.48 
0.47 
0.46 
0.45 
y = 0.0186Ln(x) + 0.4376 
0.44 
R2 = 0.6301 
0.43 
0.42 
6 5.5 5 4.5 3.5 3 2.5 2 4 
Daily Average Column Water Vapor (cm) 
0.50 
b) 
0.49 
Solar Zenith: 35 +/- 5 
0.48 y = 0.0197Ln(x) + 0.4372 
R2 = 0.6995 
0.47 
0.46 
0.45 
Modeled (AOT550nm= 0.1; SZ=30) 
0.44 
y = 0.0179Ln(x) + 0.4295 
0.43 
0.42 
6 5.5 5 4.5 3.5 3 2.5 2 4 
Simultaneous Column Water Vapor (cm) 
Daily PAR Fraction Instantaneous PAR Fraction
0.46 
0.45 
0.44 
0.43 
0.42 
0.41 
0.40 
0.39 
0 
Instantaneous PAR Fraction 
Solar Zenith: 35 +/- 5 
Water Vapor: 3-4 cm 
0.5 
a) 
y = -0.0276x + 0.463 
R2 = 0.9399 
2.5 2 1.5 1 
AOT 500 nm
-60 
y = -30.199 - 53.165x R2= 0.57991 a) 
y = -21.346 - 61.451x R2= 0.95414 
-80 
y = -36.646 - 55.585x R2= 0.83295 
-100 
-120 
-140 
-160 
-180 Abracos Hill 
Alta Floresta 
Concepcion 
-200
0.5 3 2.5 1.5 1 2 
AOT
500nm 
PAR Irradiance Shortfall (W / m2)
0 
b) 
-50 
-100 
-150 
-200 
-250
0.5 
Modeled PAR Irradiance Shortfall (W/m2) 
SSA: 1.0 
SSA: 0.95 
SSA: 0.90 
y = -4.2798 - 40.576x R2= 0.99907 
y = -12.322 - 55.099x R2= 0.99709 
y = -22.049 - 64.958x R2= 0.99335 
3 2.5 1 2 1.5 
AOT
500nm
0.85 
y = 0.93479 - 0.1358x R2= 0.612 c) 
y = 0.94923 - 0.15041x R2= 0.94057 
0.80 
y = 0.91059 - 0.13554x R2= 0.82846 
0.75 
0.70 
0.65 
0.60 
0.55 Abracos Hill 
Alta Floresta 
Concepcion 
0.50
0.5 3 2.5 1.5 1 2 
AOT 
500nm 
Fraction of Background PAR Irradiance
0.35 
0.30 
0.25 
0.20 
0.15 
0.10 
0.05 
0.00
0.01 
dV / d(ln r) [um^3 / um^2] 
AOT 440nm 
< 0.1 
0.2-0.3 
0.4-0.5 
0.6-0.8 
1.0-1.2 
1.5-2.0 
>2.5 
100 10 0.1 1 
Radius (micrometer, um)
1.00 
a) 
0.95 
0.90 
0.85 
From PAR 
From CIMEL 
0.80
210 310 290 270 250 230 
Julian Day 
SSA
1.00 
b) 
0.95 
0.90 
0.85 
From PAR 
From CIMEL 
0.80
250 290 280 260 270 
Julian Day 
SSA
1.00 
c) 
0.95 
0.90 
0.85 
From PAR 
From CIMEL 
0.80
220 300 280 240 260 
Julian Day 
SSA
1.00 
y = 0.17569 + 0.85229x R2= 0.89325 
0.98 
0.96 
0.94 
0.92 
CIMEL 
0.90
0.87 0.95 0.94 0.93 0.92 0.91 0.90 0.89 0.88 
PAR SSA Retrievals 
CIMEL SSA Retrievals