The e ff ect of atmospheric aerosol particles and clouds on Net Ecosystem Exchange in Amazonia

Introduction Conclusions References


Introduction
Clouds and aerosols influence both the surface energy balance and hydrological cycle through the modification of incoming solar radiation flux and precipitation (Benner and Curry, 1998;Gu et al., 1999Gu et al., , 2001)).Consequently, clouds and aerosols exert direct influence on terrestrial ecosystems and are, therefore, expected to modify CO 2 exchanges in the biosphere-atmosphere interface.Over the past 20 yr, field observations over many regions, have shown that the highest rates of carbon uptake in forest ecosystems often occur on slightly cloudy rather than sunny days (Gu et al., 1999;Law et al., 2002;Yamasoe et al., 2006;Oliveira et al., 2007;Jing et al., 2010).Other studies have found that for a given level of irradiance, cloudy days, compared to clear days, generally have higher absolute values of Net Ecosystem Exchange (NEE) (Baldocchi, 1997;Goulden et al., 1997;Gu et al., 1999;Doughty et al., 2010) due to the increase in diffuse radiation, except for highly overcast conditions.Several mechanisms have been proposed to explain these observations including: increases in diffuse radiation (Gu et al., 1999;Yamasoe et al., 2006;Oliveira et al., 2007;Mercado et al., 2009;Jing et al., 2010;Zhang et al., 2010), reduced respiration of sunlit leaves (Baldocchi, 1997;Miller et al., 2004;von Randow et al., 2004), reduction in water vapor pressure difference (VPD) and, finally, modifications in stomatal dynamics associated with ambient light fluctuations.Although these observations have been limited to flux tower measurements (i.e., a few point measures), it is expected that an increase in carbon uptake under increasing cloudiness and atmospheric aerosol load has implications for regional and global climate (Abakumova et al., 1996;Gu et al., 1999).This is of particular interest for regions where the percentage of cloud cover and vegetated areas have increased recently (Keeling et al., 1996;Myneni et al., 1997;Gu et al., 1999Gu et al., , 2003)).
Long-term studies coordinated by the LBA experiment (The Large Scale Biosphere-Atmosphere Experiment in Amazonia) have shown that total annual emissions of CO 2 derived from land use change are between 150 and 200 megatons of C per year (Houghton et al., 2000).On the other hand, studies of forest inventories (Phillips et al., Figures Back Close Full 1998) indicate that intact Amazonian forest may represent a sink of carbon at rates ranging from 0.5 up to a high value of 7 t C ha −1 annually (Araújo et al., 2002;Ometto et al., 2005;Malhi, 2010Malhi, , 2012)).Although there is a significant uncertainty regarding the role of the Amazon as a sink or as a source of carbon to the atmosphere (Keller et al., 1996), due to the balance between deforestation and biomass burning emissions vs. enhanced carbon uptake, recent numbers indicate a kind of balance in uptake/emissions.In Amazonia, biomass burning is the main driver of changes in atmospheric composition, accounting for a significant increase in the concentration of gases and particles in the dry season (Artaxo et al., 2002(Artaxo et al., , 2009;;Davidson et al., 2012).This translates into a large anthropogenic impact on the local energy balance, and brings important environmental consequences for the entire Amazon ecosystem (Artaxo et al., 1998;Schafer et al., 2002;Procopio et al., 2004;Sena et al., 2013).In the dry season, where biomass burning emissions are widespread, the reduction in the ground-based flux of photosynthetic active radiation (PAR) can reach values of the order of 70 % (Eck et al., 2003;Procopio et al., 2004), strongly impacting Amazon rainforest primary production (Artaxo et al., 2013).This augmented aerosol loading boosts the fraction of diffuse radiation in the atmosphere, which, in turn, increases the penetration of solar radiation into the forest canopy.The vegetation uses diffuse radiation more efficiently for photosynthesis, which increases forest carbon uptake; a fact that partly balances the effects of reducing direct radiation flux.Most of the Amazon, even outside the region of the so-called "arc of deforestation" experiences the effects of biomass burning emissions to some extent, with the resulting modification in the ecosystem functioning (Oliveira et al., 2007;Doughty et al., 2010;Artaxo et al., 2013).Atmospheric aerosol lifetime is of the order of days to weeks and thus long-range transport of aerosol particles implies that biomass burning may impact the radiation budget of areas thousands of kilometers away (Seinfeld and Pandis, 2006;Martin et al., 2010b).More knowledge is needed with respect to the impacts that clouds and aerosols have on carbon absorbed by the Amazon forest annually, especially in regions of the Central Amazon, which suffer smaller impacts from biomass burning emissions.Introduction

Conclusions References
Tables Figures

Back Close
Full CO 2 flux monitoring has been limited essentially to 13 flux towers distributed over 5.5 million km 2 and operated by the LBA experiment.Given this observational density and length of record (∼ 10 yr), it has not been possible to draw conclusions about clouds and aerosols impacts on the carbon cycle for Amazonia.Moreover, the limited number of sun-photometers for continuous monitoring of aerosol optical depth at these flux tower sites, especially in the central Amazon, has greatly hampered a broader and more precise mapping of the relationship between biomass burning aerosols and the net balance of carbon in the Amazonian forest.A few previous studies have shown a significant relationship between fluxes and aerosols in Amazon, but these were made from relatively short data time series and are representative of only two regions of the Amazon: Rondonia-RO and Santarem-PA (Yamasoe et al., 2006;Oliveira et al., 2007;Doughty et al., 2010).
In the present study, the influence of clouds and aerosol particles emitted by biomass burning on the NEE for two sites in Amazonia was analyzed.Furthermore, the net effect of the increase in diffuse radiation fraction and the reduction of the total solar flux on carbon fluxes were analyzed.This analysis was carried out using long-term LBA meteorological and eddy-correlation flux data, in addition to Aerosol Optical Depth (AOD) measurements from MODIS (Moderate Resolution Imaging Spectroradiometer).Moreover, our study implies that the use of remotely sensed AOD can be expanded into forested regions where there are no solar photometry AERONET (Aerosol Robotic Network) sites, thus enabling a broader mapping of the net exchange of carbon between the forest canopy and the atmosphere.

Site descriptions
Two LBA flux tower sites were chosen for this study, both having long-term measurements of carbon flux, aerosol optical depth, radiation and vertical profiles of CO 2 , tem-Introduction

Conclusions References
Tables Figures

Back Close
Full perature and relative humidity within the canopy.Separated by approximately 1000 km, each site experiences a different precipitation regime and nearby land-use activities.
The Forest Reserve of Jaru -RBJ is a protected area located in southeastern Rondonia and is strongly affected every year by biomass burning emissions (Andreae et al., 2004;Oliveira et al., 2007;Silva Dias et al., 2002).Previous studies have shown strong seasonality and carbon assimilation, around −18 and −8 kg C ha −1 day −1 during on the wet and dry season, respectively (von Randow et al., 2004).At this site, this study analyzed approximately 4 yr of measurements of carbon flux and associated meteorological variables (March 1999to November 2002).The second LBA site (Cuieiras Forest Reserve), located in Central Amazonia 60 km northwest of Manaus, was chosen as representative of an intact, well-preserved forest site with little disturbance or deforestation in recent decades.In the Cuieiras Reserve, the seasonal variations in net carbon uptake by the ecosystem are small (de Araujo et al., 2002Araujo et al., , 2010)).At this site, this work has analyzed a long time series (∼ 10 yr) of carbon flux and meteorological variables, between June 1999 and December 2009.Figure 1 shows the locations of the two sites used in this study.

Cuieiras Biological Reserve (K34)
The second sampling site is the so-called K34 LBA tower flux, located in the central Amazon's Cuieiras Biological Reserve (2 • 36 32.67 S, 6 • 12 33.48W).The K34 tower has been widely utilized for over 10 yr for a range of meteorological studies, inluding energy and trace gases fluxes (de Araujo et al., 2002Araujo et al., , 2010) ) and even tropospheric variables such as precipitable water vapor (Adams et al., 2011).The study area is densely forested with typical canopy height of 30 m with significant variation (20-45 m) throughout the Reserve.Topography is complex containing a sequence of plateaus, hills and lowlands.The topography of this site, which has a maximum altitude of 120 m, is distributed between 31 % plateau, 26 % slope and 43 % valley (Rennó et al., 2008) concentrations between the soil and atmosphere were obtained using a closed path infrared gas analyzer.The fluxes of H 2 O and CO 2 were performed through the eddy covariance system similar to that described by Moncrieff et al. (1997).The system is comprised of a sonic anemometer (∼ 10.4 Hz), and an infrared gas analyzer.Fluxes, means and variances were averaged every 30 min, with data processed using Alteddy (version 3.1) based on Aubinet et al. (2000).Table 1 contains a detailed list of the sensors employed.The instrumentation and data acquisition systems are similar at both study sites.However, the procedures for data collection, calibration of sensors, and other operational issues do differ to a small extent between the two sites.The data collection heights can be seen in Table 1 as well as canopy heights for both sites.

Measurements of Aerosol Optical Depth
Remotely sensed aerosol optical depth measurements at 550 nm are taken from two sources, the MODIS instrument on Aqua and Terra platform (MODIS Atmosphere Prod-Introduction

Conclusions References
Tables Figures

Back Close
Full ucts, MOD/MYD-04L2) and from the solar radiometer network AERONET (Aerosol Robotic Network).The CIMEL CE 318-A radiometers have detectors capable of performing direct solar radiation as well as almucantar measurements (Holben et al., 1998).Direct solar measurements have a field of view of 1.2

Methods
In this section, a description of the procedures employed to observe aerosol and clouds effects on net radiation fluxes is provided.Firstly, the variables used to estimate the cloudiness are presented.In meteorological observations, the cloudiness is usually measured in tenths or eighths of sky covered.However, in the present study, the word "cloud" will be used to refer to the presence, quality or quantity of clouds in the sky.
A method to identify clear-sky conditions was also developed.The procedures used Introduction

Conclusions References
Tables Figures

Back Close
Full to evaluate cloud/aerosol influence on NEE including the environmental factors that possibly contribute to changes in the carbon flux are also described.

Calculation of net ecosystem CO 2 exchange
At both sites, NEE is obtained from turbulent flux measurements by means of the eddy covariance technique taking into account the storage term (de Araújo et al., 2010;von Randow et al., 2004).Micrometeorological sensors distributed vertically along the tower are essential for the NEE calculations (Richardson and Hollinger, 2005), using continuous measurements of the CO 2 profile between soil and top of the tower.Under these conditions, NEE can be approximated by: Where Fc is called "CO 2 turbulent flow", calculated by the eddy correlation system above the treetops; Stg (the storage term) is the CO 2 concentration (non-turbulent term), measured in a vertical profile at discrete levels z i of ∆z i thickness, from the soil surface to the point of eddy correlation measurements around 53 m and 63 m on the K34 and RBJ towers, respectively (Finnigan, 2006;Loescher et al., 2006;Dolman et al., 2008).At RBJ, procedures for calculating the NEE were made following von Randow et al. (2004).At K34, vertical profiles of CO 2 concentrations were calculated following Albinet et al. ( 2001) and de Araujo et al. (2010).
Where P a is the atmospheric pressure (N m −2 ), R is the molar gas constant (N mmol −1 K −1 ), T a is the air temperature (K), c is the [CO 2 ] (µmol mol −1 ), t is the time (s) and z is the maximum height (m) between the ground and the canopy (Finnigan, 2006;Loescher et al., 2006).Introduction

Conclusions References
Tables Figures

Back Close
Full Figure 2 shows the diurnal cycle of NEE during the wet and dry season at both sites.The diurnal cycle of NEE is typical for tropical forests, with the magnitudes and peak hours of carbon absorption (Table 2) consistent with previous observations in other areas of the Brazilian Amazon forest (de Araujo et al., 2010;Hutyra et al., 2008;von Randow et al., 2004;Vourlitis et al., 2011).NEE is negative during daytime when photosynthesis is larger than respiration.During nighttime, CO 2 fluxes are predominantly positive and CO 2 is released into the atmosphere (respiration greater than photosynthesis).Differences in respiration values between the two locations are associated with both the intrinsic physiological characteristics of both ecosystems as well as issues associated with the topographic complexity in the Manaus K34 area (von Randow et al., 2004;Tota et al., 2008;de Araujo et al., 2010;Mahrt, 2010).It was also possible to observe over the dry season that the maximum carbon absorption (negative values) does not occur at local solar noon, but often around 10:00 LT, at both sites.On the other hand, during the wet season, the maximum negative values of NEE were observed around 11:00-12:00 LT.This indicates a possible connection between biotic and physical factors with a possible ecophysiological response of vegetation to higher availability of incoming radiation in the dry period (da Rocha et al., 2004(da Rocha et al., , 2009;;de Araujo et al., 2010).Large variability in CO 2 fluxes during the first hours of the day, with larger standard deviations compared to nighttime values were observed (Fig. 2).This is due to early morning turbulence at the canopy level and the breakup of the nocturnal boundary layer and the beginning of the daytime boundary layer (Betts and Dias, 2010).

Procedure for the quantification of aerosol and clouds effects on NEE
Since no direct observations of cloud cover were made at K34 or RBJ, measurements of global solar radiation at the surface to assess the presence or absence of clouds were used (Gu et al., 1999;Oliveira et al., 2007;Zhang et al., 2010;Bai et al., 2012).
The critical step in this approach is to identify what is a "clear-sky" day in order to establish a basis for comparison with cloudy or partly cloudy days.In the present study, the words "cloud" or "cloudiness" was used to refer to the presence, without regard for Introduction

Conclusions References
Tables Figures

Back Close
Full quality or quantity, of clouds in the sky (Gu et al., 1999).The concept of relative irradiance, f , was used to determine the reduction of incident solar irradiance due to clouds and/or aerosols and associate this with the changes in NEE, which also changes with temperature and relative humidity variations.In this study, the quantity f was calculated following Oliveira et al. (2007): Where S (W m −2 ) is the total incident solar radiation measured on the surface at a given time (with or without the presence of aerosols and clouds) and S 0 (W m −2 ), the expected total incident solar irradiance at the surface in a cloudless atmosphere with an aerosol optical depth of 0.10 at 550 nm.Previous studies in Amazonia have shown that the background AOD, due to atmospheric natural conditions is about 0.1 at 550 nm (Holben et al., 1996;Guyon et al., 2003).There are few models assessed in the literature for the calculation of S 0 (Ricchiazzi et al., 1998;Duchon and O'Malley, 1999).In this study, we chose to employ an algorithm for clear-sky irradiance that would include the intrinsic characteristics of local conditions in the Amazon.S 0 and f were calculated employing the methodology of Gu et al. (1999), which establishes a set of criteria to find clear-sky days.These criteria are based on the concept of clearness index, kt, which is discussed in detail in the next section.In this study, kt was used to find S 0 and thus determine f .To observe only the aerosol effect on the solar irradiance flux (computed from f ), and consequently on the NEE measurements, the aerosol effect has to be isolated from the cloud effect.Radiation measurements were classified as affected only by aerosols if they were performed under cloudless conditions, that is, under clear-sky conditions (Oliveira et al., 2007).The MODIS sensor has a reasonable algorithm to exclude cloud contamination of the AOD measurements (King et al., 1999(King et al., , 2003;;Remer et al., 2005).Introduction

Conclusions References
Tables Figures

Back Close
Full

The definition of the clearness index
The relative irradiance, f , provides an estimation of changes in cloudiness and AOD as a result of changes in measured solar radiation fluxes.However, the concept requires that S 0 be available.When clear-sky irradiance is not available, sky conditions can be described in terms of the "clearness index", kt, defined as the ratio of solar radiation received at the surface to the solar irradiance at the top of the atmosphere (TOA).For a given solar elevation angle, small kt values indicate an increase in the cloud coverage and/or aerosol loading, while higher values indicate more clear sky conditions (Gu et al., 1999;Zhang et al., 2010;Bai et al., 2012).Mathematically, the clearness index can be expressed by: kt = S/S e ( 4a) Where S is the ground-based total solar irradiance actually measured at the surface, while S e is the TOA solar irradiance, where S sc (∼ 1367 W m −2 ) is the solar constant, and td the Julian Day.For the calculation of sin β the following equation is used: Where (β) is the solar elevation angle and (φ), (δ) and (ω) are, respectively, the latitude, the declination of the Sun (in degrees) and the hour angle.An interesting characteristic of this definition is that it is possible establish a clearness index for clear skies (i.e., cloud free and AOD ∼ 0.10).Under these conditions, it is possible to denominate a clear-sky clearness index, kt * , and Eq. ( 4a) can be rewritten as: Therefore, the ratio between kt and kt * provides the relative irradiance f ; see Eq. ( 3).
The physical concepts of kt and kt * indicate an alternate way to determine f to a good approximation.

Defining clear skies conditions
To quantify the specific influence of clouds on NEE, firstly, the NEE behavior on days with minimal cloud cover was determined using the method of separation of clear days from Gu et al. (1999).This provides a basis for the comparison of NEE behavior for "clear-sky days" vs. aerosol and/or cloudy days.The "clear-sky" days were defined based on a 4 h period, evaluated for two temporal intervals: between 08:00 a.m. to 12:00 p.m. and from 12:00 p.m. to 04:00 p.m., local time (averages were made of the irradiances over each 4 h period).These periods were used because of the timing of the close overpass of the Aqua and Terra satellites over Amazonia.To ascertain the accuracy of our cloudiness estimates with an independent data set, time-averaged GOES10 channel 4 brightness temperature was used over the same two 4 h periods for the pixel (4 km × 4 km) containing the K34 and RBJ sites.Brightness temperatures less than 280 K were assumed to result from cloudiness for that particular pixel.The clear days selected by the method of Gu (1999) were compared with the clear sky days from satellite observations (GOES10) and it was found that about 70 % of the number of clear days selected by GOES10 were also selected by the method of Gu (1999).Two patterns for clear mornings and afternoons were assumed (Gu et al., 1999;Zhang et al., 2010;Bai et al., 2012): (1) kt should increase smoothly with the solar zenith angle -cos(z) and ( 2) the relationship between clear-sky kt and cos(z) must form an envelope in the "lumped" scatterplot of kt against cos(z).The following steps and procedures were employed to find kt * : First, value of kt were plotted against time of the day.Only the mornings and afternoons that showed small variations in kt were selected.The solar zenith angle cos(z) from the "clear-sky days" were ploted on the same graph.The kt values which were outside the two patterns set out above were excluded from our database.Finally, the values of kt found during the mornings and Introduction

Conclusions References
Tables Figures

Back Close
Full afternoons clear-sky selected were plotted with the solar zenith angle again to check if the clear-sky days selected met the two criteria set out above.The degree of dependence between kt * (clear-sky clearness index) and cos(z) was used to assess whether the mornings and clear afternoons were accurately selected.This relationship can be expressed as follows: Where kt 0 is the clear-sky clearness index from the regression curves (Fig. 3a and b); z is the solar zenith angle calculated Gates (1980); a 1 , a 2 , a 3 and a 4 are the regression coefficients specific to the selected clear mornings and afternoons, calibrated to local conditions of the tropical forest at K34 and RBJ, respectively.The clear-sky irradiance (S 0 ) was also determined, obtained similarly to Eq. ( 7).The coefficients kt 0 and S 0 are fixed as showed in Table 3. Figure 3 show asymmetries between the period of morning and afternoon light at both sites.The values of kt * selected during afternoons are slightly higher when compared with the indexes of selected mornings, especially for low angles (less than cos −1 0.45).Similar results were obtained by Gu et al. (1999) and Zhang et al. (2010).For a given solar zenith angle, decreases in the clearness index generally indicate an increase in the depth of the clouds, with the exception for situations in which the clouds are not distributed uniformly across the sky; i.e., when there is a cloud gap effect (Gu et al., 1999;Oliveira et al., 2007).

Determination of NEE on clear-sky days
In this study, the influence of aerosols and clouds on carbon uptake is analyzed mainly in terms of variations in NEE and environmental factors through their impact on f .The observed NEE on clear days was used also as a basis of comparison for cloudy days and/or days with high aerosol loading.Equation ( 1 way of the following relationship (Gu et al., 1999;Oliveira et al., 2007;Bai et al., 2012): Where NEE(z) is a measure of NEE under a given condition sky throughout the day and NEE csky is the NEE calculated under sky conditions with low aerosol loading in the atmosphere and minimal cloud cover (f ≈ 1.0, AOD ∼ 0.10).
To eliminate the interference of sun elevation angle on the variation of NEE% or NEE on the relative irradiance parameter f , data grouped at intervals of solar zenithal angle between 10-20 and 20-35 were initially analyzed.Zenith angles of 5 • intervals proved too small to develop a robust statistical analysis (Gu et al., 1999).Values above 50 • or around 0 • (solar angle very near the horizontal and vertical plane, respectively) were in general too heavily contaminated by clouds.Therefore, a 10 to 35 • elevation angle was chosen to be optimal for measuring the ecosystem response to changes in cloudiness and AOD rather than the effect of variations in solar zenith angles.The results shown in Fig. 4a and b show the solar zenith angle interval for which carbon fluxes experiences the greatest variation.The statistical parameters R 2 and p value (Fig. 4a and b) are satisfactory in view of the measurement sample size; For K34 > 59 000 points, and for RBJ > 26 000 values.The coefficient of determination R 2 is relatively low, but the level of statistically significant p values in all cases are smaller than 0.001, indicating a high degree of relationship between the NEE and solar zenithal angle.The obtained coefficients of NEE (clear-sky) are listed in Table 4.These coefficients are consistent with those of the Tapajos National Forest in Amazonia, reported by Oliveira et al. (2007), but are quite different from those obtained in other ecosystems, such as temperate deciduous forests, mixed forests and pine forest, found in southern Canada and Northwest China, respectively (Gu et al., 1999;Zhang et al., 2010).
The relationship between NEE and some variables that directly interferes with the uptake of carbon by forests, such as: total PAR, diffuse PAR, air temperature, canopy temperature and VPD were also studied.This discussion about methods used to calcu-Introduction

Conclusions References
Tables Figures

Back Close
Full late total PAR downward radiation, diffuse PAR and canopy temperature are discussed in Sects.2.3.6 and 2.3.7.

Methods to derive total and diffuse PAR
Unfortunately, measurements of diffuse PAR, were not available at either K34 or RBJ.Therefore, to determine the diffuse component of total PAR, we followed the methods derived by Spitters et al. (1986) and Reindl et al. (1990) which have been widely used in the literature (Gu et al., 1999;Jing et al., 2010;Zhang et al., 2010;Bai et al., 2012).
The calculation is performed deriving the diffuse PAR radiation PARf from the following formulation (Spitters, 1986): Where PAR f is the diffuse PAR radiation (µmol photon m −2 s −1 ) and q = (S f /S e )/kt; S f denotes the total diffuse radiation (visible plus near infrared) received on a horizontal plane at the Earth's surface (W m −2 ).The fraction of diffuse PAR was defined as the ratio between PAR f and total PAR (PARt).To express the light use efficiency (LUE) of vegetation and the fraction of diffuse PAR (D f ), respectively, the NEE and PAR f values were normalized by PARt as follows (Jing et al., 2010):

Canopy top temperature
As there are no direct measurements of skin temperature of the canopy at either study sites, we used the data sets of pyrgeometers operated around 15-20 m high inside the canopy on both sites (Table 1) to measure the emission of long wave radiation from the Figures

Results and discussions
This section presents and discusses the main results of this study.The first task was to validate MODIS AOD estimations with the AOD measurements from the AERONET sun-photometer network.Following this, the radiative effects of aerosols and clouds on the CO 2 fluxes for both sites was analyzed.Measurements of NEE, PARt, PAR f , AOD, relative humidity, air temperature and surface temperature of the forest canopy are further analyzed as a function of the relative irradiance parameter (f ), during the biomass burning season at both sites.

MODIS AOD validation for the Central and Southwestern Amazon
The estimates of the MODIS AOD allowed to observe the atmospheric aerosol loadings from two geographic regions with very different characteristics.One region less impacted by anthropogenic activities (Manaus and Balbina), Central Amazon (Fig. 5a), and the other, heavily impacted by biomass burning smoke, represented by the site RBJ in Rondonia (Fig. 5c).Balbina (coordinates 1 Full for the Amazon), but increased significantly during the dry season with the long-range transport of biomass burning aerosol emissions.During the dry season, daily average AOD reached high values at RBJ (greater than 3.5) and at K34 (around 1.5) (Fig. 5a  and c).These high atmospheric aerosol loadings from biomass burning cover very large areas of South America, and have impacts far from their source regions (Artaxo et al., 1998(Artaxo et al., , 2002;;Procopio et al., 2004;Martin et al., 2010a, b;Davidson et al., 2012).Figure 5b and d shows that for both sites used in this study, MODIS and AERONET AOD agrees quite well, with values of R 2 that are statistically significant at the 95 % confidence level.In general, MODIS values tend to overestimate the AOD measurements at the two sites at 550 nm.The systematic errors (Mean Absolute Error -MAE) of the estimates with MODIS, show values around 5-10 % higher than AERONET measurements, are considered acceptable (Chu et al., 2002).The largest errors occur for AOD values greater than 1.0, where in some cases the MODIS values are higher than AERONET measurements by up to a factor of 2 (Fig. 5d).The regression analysis presented in Fig. 5b and d show that MODIS can be used to derive AOD, taking AERONET values as a reference.New validations could be implemented in future studies with the new MODIS high resolution 3 km aerosol product (Remer et al., 2013).

The influence of aerosols and clouds on PAR radiation and relative irradiance
In the present study, the impact of aerosols from biomass burning emissions on the radiation budget is assessed in terms of incident solar irradiance represented by the relative irradiance parameter f , PARt and PAR f .The behavior of the relative irradiance f as a function of AOD, under minimal cloud effects is shown in Fig. 6a and 6b for K34 and RBJ respectively.In spite of the relatively large scattering, it is possible to observe a linear relationship, with relative irradiance reduced by 25 % for AOD values close to 0.5 at the K34 site.The linear relationship between f and AOD is significant statistically with p values < 0.01 with a R 2 , ∼ 0.22 (K34) and ∼ 0.37 (RBJ).At cos(z) values for z between 10 and 35 • , a reduction in the value of f on the order of 20 % was observed Introduction

Conclusions References
Tables Figures

Back Close
Full when the AOD varied from 0.10 to 0.70 at the site of K34 (Fig. 6c) and approximately 25 % when the AOD varies from 0.10 to 2.5 in the forest area of RBJ. Figure 6c and d shows the calculated fraction of diffuse radiation as a function of AOD.The calculation shows an increase of about 25 % in diffuse radiation as AOD increases from 0.2 to 0.60 (K34) and from 0.10 to 2.2 (RBJ).These results are particularly important because diffuse PAR penetrates more efficiently in the canopy and contributes to an increase in carbon uptake (Doughty et al., 2010).The joint analyses of Fig. 6 with the results shown in Sect.3.5 helps to understand how the increase in AOD and PAR f affect carbon uptake by the forest.
The Fig. 7a and b show that for f ranging from 0.80 to 1.2, the PARt is reduced by approximately 30-35 % at both sites K34 and RBJ.This behavior was observed both during the biomass burning season and the wet season.Oliveira et al. (2007) showed similar decreases (∼ 20 %) when f varied from 1.0 to 0.80.These figures also show a strong reduction in PARt when the cloud cover changes from a "clear sky" conditions (f > 1.0, AOD ∼ 0.10) to completely overcast by clouds and aerosols (f < 1.0, AOD 0.10).Although the PARt decreases almost linearly with the relative irradiance (Fig. 7a  and b), the relationship between the diffuse PAR radiation and f is not linear (Fig. 7c  and d).In this case, the PAR f increases ∼ 500 µmol m −2 s −1 when the relative irradiance f decreases from 1.2 to 0.75.This corresponds to a 50 % increase in PAR (diffuse) during biomass burning season due to scattering by aerosols and clouds.In the RBJ, these changes are mainly due to the dense aerosol layer observed during the biomass burning season.

The effect of PAR (diffuse) radiation on the light use efficiency (LUE) through forest
In Sects.3.1 and 3.2, strong AOD seasonality was observed, with important effects in the atmospheric radiation balance, in particular, PAR radiation.In this section, the effect of these changes on the efficiency of radiation used by forests (LUE) was evaluated Introduction

Conclusions References
Tables Figures

Back Close
Full and the values of radiation efficiency use for which this efficiency is maximum were identified.Figure 8a and b shows NEE as a function of total PAR observed during clear-sky days and high aerosol loading/cloudy days during the dry season for both K34 and RBJ.The assimilation of carbon gradually increases with increasing total downward PAR (PARt) radiation reaching its maximum saturation at around 1800-2000 µmol m −2 s for both sites (Fig. 8a and b).Additionally, it was observed that for the same level of irradiance at the surface (e.g., between 0-1800 µmol m −2 s −1 ) the forest tends to absorb more carbon (more negative NEE) under high aerosol loading/cloudy atmospheric conditions (Fig. 8a and b).These results show that the fraction of diffuse solar radiation affects NEE at both sites in Amazonia.Figure 8c and d shows the NEE normalized by the total PAR flux plotted against the diffuse fraction of PAR radiation.It is possible to analyze vegetation LUE analyzing the ratio of NEE/PAR-total (Jing et al., 2010).This relationship represents the photosynthetic efficiency, which is related to the ability of the canopy to convert solar energy into biomass.At both sites, it is possible to observe that LUE is low (∼ 1-2 %), requiring large amounts of energy for photosynthesis.Furthermore, peaks of up to 4 % (K34) and 6 % (RBJ) in photosynthetic efficiency were observed in cases where the diffuse fraction reaches values around 1, during situations when the sky is obscured by clouds and aerosols (f < 1.0, AOD > 0.10).A gradual increase in LUE was observed (Fig. 8c     and d) with increasing PAR (diffused) for irradiance values around 0.80, falling sharply after this value until the maximum fraction PAR f which is 1.0.These results are similar to those obtained in the semiarid region of northeastern China (Jing et al., 2010).the combined effect of clouds and aerosols.It is possible to observe at both sites that NEE has an inflection point at around f ∼ 0.8.In other words, the maximum CO 2 fixation does not occur on a clear day (f ∼ 1.0 and AOD < 0.10), but on days with either small cloud cover and/or moderate aerosol loading which increases the diffuse fraction of solar radiation.This effect was observed at both sites, during the dry season when there is a large loading of aerosols in the atmosphere and low cloud cover, and during the wet season, which experiences minimal aerosol content and frequent cloud cover (Figs. 5, 10b and 10c).However, this enhancement in NEE appears to occur from f values from 1.0 to ∼ 0.8.For further reduction in the radiation field, the enhanced diffuse radiation does not compensate for the reduced total flux of solar radiation and the photosynthesis process is severally reduced (Fig. 9a and 9b).In short, diffuse radiation (PAR f ) increases the rate of photosynthesis only until a certain level of aerosol loading.A similar effect was also observed by Gu et al. (1999) and Doughty et al. (2010).

The net uptake of CO 2 due to aerosols and clouds
Through the use of Eqs. ( 1) and ( 8) it is possible to calculate the ratio of NEE (%) and the relative irradiance (f ) for various intervals of zenithal angle.This procedure was adopted to minimize the effects of solar elevation throughout the day on NEE.
For each SZA interval analyzed, the average NEE (%) for the clearness index f in bins equal to 0.1 (Fig. 9a, b) were calculated separately.At K34, an average increase of approximately 20 % in carbon uptake was observed relative to clear-sky (NEEcsky) conditions when the clearness index f is reduced from 1.1 to 0.8 (Fig. 9c).For this range of variation in f , AOD increases from 0.10 to 0.60 (Fig. 6a) and produces significant reductions in total PAR radiation flux (PARt), of approximately 50 % and, concomitantly, an increase of up to 25 % in PAR f (Fig. 7c).At RBJ, the relative increase of NEE (%) was about 30 % when f varies from 1.1 to 0.80 (Fig. 9d).In the latter case, considering these same variations in f , the aerosol loading in the atmosphere increases AOD from 0.10 to 2.5 (Fig. 6b) producing reductions of up to 50 % of PAR and an increase of 25 % in PAR f (Fig. 7d).The increase in carbon uptake in the presence of aerosols Introduction

Conclusions References
Tables Figures

Back Close
Full and clouds becomes smaller and similar in both sites, for solar zenithal angles < 20 • (Fig. 9c and d).Near zenith, solar radiation is less scattered by particles suspended in the atmosphere due to decreased path length, mitigating the diffuse radiation effects on the photosynthetic process.
The results from Fig. 9 shows that the photosynthetic efficiency of the forest is relatively larger on days with the atmosphere loaded with small amounts of aerosol particles and/or low cloud cover.The effect is clearly nonlinear, reaching a point where NEE begins to decrease.The value of this behavior varies for each solar zenith angle range.
For measurements between 10-20 • , a reduction in solar irradiance of up to 30 % does not inhibit CO 2 uptake in the forest canopy.For measurements taken for solar zenith angle between 20-35 • , a 40 % reduction in irradiance does not show effects on CO 2 uptake.This result is important since much of the Amazon area is often impacted by the presence of aerosols in small amounts (low AOD) similar to those observed for Manaus.The increases in CO 2 uptake are significant and could have major impacts on the Amazon forest carbon budget.Peak CO 2 uptake is often observed for f values near 0.80, a value typically encountered in dense forest ecosystems (Gu et al., 1999;Yamasoe et al., 2006;Oliveira et al., 2007;Doughty et al., 2010) but quite different from what is found in grasslands and other temperate forested regions (Niyogi, 2004;Jing et al., 2010;Zhang et al., 2010).

The relationship between the current patterns of aerosols and clouds and carbon uptake
Figure 10 shows the percentage distribution of the kt (clearness index) throughout the year at K34 (1999K34 ( -2009K34 ( ) and RBJ (1999K34 ( -2002) ) sites.The percentage of cloud cover (not shown), as well as the distributions of kt (Fig. 10a and b) are similar for both sites, but differ from wet and dry seasons, as expected.Using brightness temperature from GOES10, 60 % of the time during the rainy season, both K34 and RBJ experienced some degree of cloud cover.This percentage, decreases during the dry season (August through October) reaching a minimum of 20 % at RBJ and 30 % at K34 in Introduction

Conclusions References
Tables Figures

Back Close
Full September.The frequency distribution of kt (Fig. 10a and b), is compatible with the observations of cloud cover observed using GOES10 analysis (around 60-70 %).The analysis of kt frequency distributions (Fig. 10a and b), indicates that current patterns of cloudiness do not yet exceed the maximum limit for which the forests of K34 and RBJ sites reach the maximum amounts of carbon uptake.The peak kt distribution at both sites is near 0.75 (Fig. 10b), which is smaller than the values of f for which the NEE reaches its maximum negative value during the burning season (kt ∼ 0.57).This is the limit at which the cloudiness and/or aerosol load result in the maximum carbon uptake at RBJ and K34 (Fig. 10c).Larger quantities of aerosols and clouds in the region could cause these forests to absorb even greater amounts of carbon throughout the day, considering the combined effect of NEE enhancement by aerosols and clouds.The distribution patterns of the frequency occurrence of kt found throughout the years in both forest sites (Fig. 10) are similar to those found by Oliveira et al. (2007) in the Tapajos National Forest, in Santarem and Rondonia also in RBJ.These results are also consistent with calculations from Gu et al. (1999) in temperate forests of Canada, where kt values are centered at 0.75 and the maximum negative NEE is at about 0.55-0.60.

Effects of temperature and VPD on CO 2 uptake
Figure 11 shows the direct influence that clouds and aerosols have on some of the major environmental factors that also affect the photosynthetic activity of plants.The attenuation of incident solar irradiance due to the presence of aerosols and clouds, cause significant reductions in air temperature near the canopy forest and also in the vapor pressure deficit (VPD) associated with relative humidity (Fig. 11).At the K34 site, the combined effect of aerosols and clouds (in this case, more aerosols than clouds) produced, respectively, a cooling of 1.5 and 2.5 • C in air temperature of the canopy when f ranged from 1.2 to 0.80 (Fig. 11a and c).At RBJ, considering the same variations in f , a cooling of 3-4 • C was observed (Fig. 11b and d).These values are on the relatively high side, but are similar to results found by Davidi et al. (2009).Another Introduction

Conclusions References
Tables Figures

Back Close
Full factor that can increase canopy photosynthesis is the general trend of decreasing vapor pressure deficit on cloudy or smoke-filled skies (Min andWang, 2005, 2008;Bai, et al., 2012).Figure 11e and f shows the relationship between the VPD and irradiance on f (again, between solar zenithal angle 10-35 • ).For Freedman et al. (1998), increasing relative humidity due to cloud/aerosol-induced cooling (Altaratz et al., 2008), can increase photosynthesis since this increase naturally induces the opening of the stomata of the leaves (Collatz et al., 1991).At both sites, the reduction in f produced an increase in VPD of up to 15 % during the dry season.The reductions observed in the vapor pressure deficit associated with reductions in air temperature in the forest canopy can also be contributing to an increase in NEE.

Conclusions
Aerosol optical depth derived by MODIS has been shown to be satisfactory for two different sites in the Amazon, after comparisons with AERONET AOD.This allows the expansion of studies of aerosol effects on the Amazonian ecosystem to other areas of the Amazon, where no AERONET measurements exist.Given the long time series of micrometeorological measurements at the K34 and RBJ sites, it was possible to assess the reduction in solar irradiance due to the presence of clouds and aerosols emitted by biomass burning.The clear-sky irradiance algorithm developed was able to satisfactorily quantity the reduction in surface radiation flux, taking into account an atmosphere free of clouds and with minimal aerosol loading.Thus, the changes in incident solar radiation and CO 2 flux (NEE) could be attributed to the combined effect of clouds and aerosol.In Central Amazonia (K34 site), the net carbon flux (NEE) increased by 20 % when the optical depth ranged from 0.10 to 0.65.At the RBJ site, a stronger effect was observed, with an increase of 29 % on the NEE observed when AOD varied between 0.1 and 2. Aerosols from biomass burning produced up to a 50 % reduction in the amount of total incident solar radiation and also an increase of up to 25 % in the fraction of diffuse solar radiation, which is utilized more efficiently by the Introduction

Conclusions References
Tables Figures

Back Close
Full forest photosynthesis process.The results show higher photosynthetic efficiency in situations where the atmosphere is lightly loaded with particles and/or clouds.A more efficient use of the diffuse solar radiation can be pointed to as the main source of increased CO 2 flux in the forest areas of the sites studied.In addition, in view of the increased cloudiness and aerosol loading, significant variations were observed in other meteorological variables, such as temperature and vapor pressure deficit (VPD).The variations of these quantities may also influence carbon uptake.
The increase in VPD associated with decreased air temperature due to aerosols and clouds may be causing reductions in the rate of respiration of forest and hence an increase in NEE, during biomass burning aerosols exposure.Many physiological and environmental factors also are involved in the dynamics and control of carbon fluxes in the Amazon, thereby attributing and separating the different effects on CO 2 fluxes difficult.
The increase in NEE due to the increased amount of aerosols and clouds constitute an effect of considerable relevance due to the importance of carbon cycling in Amazonia.A regional study of this effect, based on vegetation maps, remote sensing estimates, assimilated meteorological data and environmental modeling, will help to better understand how climate and ecosystem functioning in Amazonia are affected by natural and anthropogenic environmental factors.Introduction

Conclusions References
Tables Figures

Back Close
Full  Full  Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 05 00 S and 61 • 55 00 W) is densely forested and located approximately 100 km north of the urban area of Ji-Parana, Rondonia, Brazil.It consists of approximately 268 000 ha of primary forest at an altitude ranging between 100 and 150 m a.s.l. with typical canopy height of 30-35 m.Although the forest reserve is protected by Brazilian Environmental Protection Agency (IBAMA), in recent years it has suffered from forest fires and deforestation relatively close to the sampling site (von Randow et al., 2004).The different geological substrates and diverse rainfall patterns at this site promote numerous vegetation types and five phyto-ecological formations, namely: Open Tropical Rain Forest, Rain Forest, Vegetation Transition or Contact, Cerrado and Alluvial Pioneer Formations.Average annual rainfall ranges from 1400-2600 mm yr −1 with the dry season (rainfall < 60 mm per month) extending from Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) and NEE (clear-sky) were used to calculate the percentage effect of aerosols and clouds on the carbon flux (%NEE) by Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | surface (L ↑) (W m −2 ).The Eq. (11) was derived from the Stefan-Boltzmann equation and used to calculate the temperature of the canopy (T c ) of the K34 and RBJ sites K34.Dougthy et al. (2010) used similar procedures to estimate the canopy temperature (skin temperature) in FLONA-Tapajos (Santarem-PA).
Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Figure
Figure 9a and b shows the relationship between NEE and relative irradiance f for the experimental forest sites K34 and RBJ.In Fig. 9c and 9d the changes in net carbon absorbed by these forests (Relative Change of NEE, NEE %) due to aerosols (green dots) and clouds (black dots) can be observed.These analyses were performed with 28839 Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Figure 9 .
Figure 9. Variability of NEE with the relative irradiance f for the K34 /Manaus (R 2 = 0.32) and RBJ/Ji-Parana (R 2 = 0.12) sites for solar zenith angle interval (z) between 10° and 35° (a) and (b).Relative change of NEE (%NEE) as a function of the relative irradiance f, averaged for all solar zenithal angle intervals (z), from 10° to 55° (c) and (d).Note that this plot includes clouds and aerosol effects.

Table 1 .
List of measurements, instruments and measurement heights for the automatic weather station and eddy correlation instrumentation installed on the K34/Manaus-AM and RBJ/Ji-Paraná LBA towers.